From 542d9542008a932a6de27babd21c02c9cf7cd48c Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Thu, 11 May 2023 08:30:16 +0200
Subject: [PATCH 001/238] Fix missing model monitoring in XGB train script

---
 .../tensorflow/prediction/pipeline.py         | 16 +++++----
 .../training/assets/train_tf_model.py         | 13 ++++---
 .../pipelines/tensorflow/training/pipeline.py |  1 +
 .../pipelines/xgboost/prediction/pipeline.py  | 16 +++++----
 .../training/assets/train_xgb_model.py        | 35 ++++++++++++++-----
 .../pipelines/xgboost/training/pipeline.py    |  1 +
 6 files changed, 57 insertions(+), 25 deletions(-)

diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index 5121aea3..b011b0c1 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -108,12 +108,16 @@ def tensorflow_pipeline(
     ).set_display_name("Ingest data")
 
     # lookup champion model
-    champion_model = lookup_model(
-        model_name=model_name,
-        project_location=project_location,
-        project_id=project_id,
-        fail_on_model_not_found=True,
-    ).set_display_name("Look up champion model")
+    champion_model = (
+        lookup_model(
+            model_name=model_name,
+            project_location=project_location,
+            project_id=project_id,
+            fail_on_model_not_found=True,
+        )
+        .set_display_name("Look up champion model")
+        .set_caching_options(False)
+    )
 
     # batch predict from BigQuery to BigQuery
     bigquery_source_input_uri = f"bq://{project_id}.{dataset_id}.{ingested_table}"
diff --git a/pipelines/src/pipelines/tensorflow/training/assets/train_tf_model.py b/pipelines/src/pipelines/tensorflow/training/assets/train_tf_model.py
index c89a7880..5d164ae7 100644
--- a/pipelines/src/pipelines/tensorflow/training/assets/train_tf_model.py
+++ b/pipelines/src/pipelines/tensorflow/training/assets/train_tf_model.py
@@ -219,6 +219,9 @@ def _get_temp_dir(dirpath, task_id):
 parser.add_argument("--hparams", default={}, type=json.loads)
 args = parser.parse_args()
 
+if args.model.startswith("gs://"):
+    args.model = Path("/gcs/" + args.model[5:])
+
 # merge dictionaries by overwriting default_model_params if provided in model_params
 hparams = {**DEFAULT_HPARAMS, **args.hparams}
 logging.info(f"Using model hyper-parameters: {hparams}")
@@ -261,9 +264,9 @@ def _get_temp_dir(dirpath, task_id):
     logging.info("not chief node, exiting now")
     sys.exit()
 
-os.makedirs(args.model, exist_ok=True)
 logging.info(f"Save model to: {args.model}")
-tf_model.save(args.model, save_format="tf")
+args.model.mkdir(parents=True)
+tf_model.save(str(args.model), save_format="tf")
 
 logging.info(f"Save metrics to: {args.metrics}")
 eval_metrics = dict(zip(tf_model.metrics_names, tf_model.evaluate(test_ds)))
@@ -281,11 +284,13 @@ def _get_temp_dir(dirpath, task_id):
     json.dump(metrics, fp)
 
 # Persist URIs of training file(s) for model monitoring in batch predictions
-path = Path(args.model) / TRAINING_DATASET_INFO
+# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
+# for the expected schema.
+path = args.model / TRAINING_DATASET_INFO
 training_dataset_for_monitoring = {
     "gcsSource": {"uris": [args.train_data]},
     "dataFormat": "csv",
-    "targetField": hparams["label"],
+    "targetField": label,
 }
 logging.info(f"Save training dataset info for model monitoring: {path}")
 logging.info(f"Training dataset: {training_dataset_for_monitoring}")
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index cb99e091..2767d210 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -215,6 +215,7 @@ def tensorflow_pipeline(
             fail_on_model_not_found=False,
         )
         .set_display_name("Lookup past model")
+        .set_caching_options(False)
         .outputs["model_resource_name"]
     )
 
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index 0bd1ec91..ed474eb8 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -102,12 +102,16 @@ def xgboost_pipeline(
     ).set_display_name("Ingest data")
 
     # lookup champion model
-    champion_model = lookup_model(
-        model_name=model_name,
-        project_location=project_location,
-        project_id=project_id,
-        fail_on_model_not_found=True,
-    ).set_display_name("Look up champion model")
+    champion_model = (
+        lookup_model(
+            model_name=model_name,
+            project_location=project_location,
+            project_id=project_id,
+            fail_on_model_not_found=True,
+        )
+        .set_display_name("Look up champion model")
+        .set_caching_options(False)
+    )
 
     # batch predict from BigQuery to BigQuery
     bigquery_source_input_uri = f"bq://{project_id}.{dataset_id}.{ingested_table}"
diff --git a/pipelines/src/pipelines/xgboost/training/assets/train_xgb_model.py b/pipelines/src/pipelines/xgboost/training/assets/train_xgb_model.py
index 31d95247..71cc65b5 100644
--- a/pipelines/src/pipelines/xgboost/training/assets/train_xgb_model.py
+++ b/pipelines/src/pipelines/xgboost/training/assets/train_xgb_model.py
@@ -1,4 +1,6 @@
 import argparse
+from pathlib import Path
+
 import joblib
 import json
 import os
@@ -14,7 +16,9 @@
 
 logging.basicConfig(level=logging.DEBUG)
 
-
+# used for monitoring during prediction time
+TRAINING_DATASET_INFO = "training_dataset.json"
+# numeric/categorical features in Chicago trips dataset to be preprocessed
 NUM_COLS = ["dayofweek", "hourofday", "trip_distance", "trip_miles", "trip_seconds"]
 ORD_COLS = ["company"]
 OHE_COLS = ["payment_type"]
@@ -39,6 +43,9 @@ def indices_in_list(elements: list, base_list: list) -> list:
 parser.add_argument("--hparams", default={}, type=json.loads)
 args = parser.parse_args()
 
+if args.model.startswith("gs://"):
+    args.model = Path("/gcs/" + args.model[5:])
+
 logging.info("Read csv files into dataframes")
 df_train = pd.read_csv(args.train_data)
 df_valid = pd.read_csv(args.valid_data)
@@ -111,15 +118,25 @@ def indices_in_list(elements: list, base_list: list) -> list:
     "rootMeanSquaredLogError": np.sqrt(metrics.mean_squared_log_error(y_test, y_pred)),
 }
 
-try:
-    model_path = args.model.replace("gs://", "/gcs/")
-    logging.info(f"Save model to: {model_path}")
-    os.makedirs(model_path, exist_ok=True)
-    joblib.dump(pipeline, model_path + "model.joblib")
-except Exception as e:
-    print(e)
-    raise e
+logging.info(f"Save model to: {args.model}")
+args.model.mkdir(parents=True)
+joblib.dump(pipeline, str(args.model / "model.joblib"))
 
 logging.info(f"Metrics: {metrics}")
 with open(args.metrics, "w") as fp:
     json.dump(metrics, fp)
+
+# Persist URIs of training file(s) for model monitoring in batch predictions
+# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
+# for the expected schema.
+path = args.model / TRAINING_DATASET_INFO
+training_dataset_for_monitoring = {
+    "gcsSource": {"uris": [args.train_data]},
+    "dataFormat": "csv",
+    "targetField": label,
+}
+logging.info(f"Training dataset info: {training_dataset_for_monitoring}")
+
+with open(path, "w") as fp:
+    logging.info(f"Save training dataset info for model monitoring: {path}")
+    json.dump(training_dataset_for_monitoring, fp)
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 1db2023c..27cb47ed 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -212,6 +212,7 @@ def xgboost_pipeline(
             fail_on_model_not_found=False,
         )
         .set_display_name("Lookup past model")
+        .set_caching_options(False)
         .outputs["model_resource_name"]
     )
 

From 22f6dcd3c863764356e2e801f97c0bc05876deff Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Fri, 12 May 2023 14:52:56 +0200
Subject: [PATCH 002/238] feat: enable multiquery, update queries and pipelines

---
 .../bigquery_components/bq_query_to_table.py  | 20 +--------
 .../tensorflow/prediction/pipeline.py         | 30 +++++++------
 .../tensorflow/prediction/queries/ingest.sql  | 13 +++++-
 .../pipelines/tensorflow/training/pipeline.py | 45 +++++++------------
 .../tensorflow/training/queries/ingest.sql    | 29 ++++++++----
 .../tensorflow/training/queries/sample.sql    | 24 +++-------
 .../pipelines/xgboost/prediction/pipeline.py  | 30 ++++++++-----
 .../xgboost/prediction/queries/ingest.sql     |  9 ++++
 .../pipelines/xgboost/training/pipeline.py    | 44 +++++++-----------
 .../xgboost/training/queries/ingest.sql       | 27 +++++++----
 .../xgboost/training/queries/sample.sql       | 12 +++--
 11 files changed, 145 insertions(+), 138 deletions(-)

diff --git a/components/bigquery-components/src/bigquery_components/bq_query_to_table.py b/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
index 9530bd92..4b6afc29 100644
--- a/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
+++ b/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
@@ -22,25 +22,15 @@
 def bq_query_to_table(
     query: str,
     bq_client_project_id: str,
-    destination_project_id: str,
-    dataset_id: str = None,
-    table_id: str = None,
     dataset_location: str = "EU",
-    query_job_config: dict = None,
 ) -> None:
     """
     Run query & create a new BigQuery table
     Args:
         query (str): SQL query to execute, results are saved in a BigQuery table
         bq_client_project_id (str): project id that will be used by the bq client
-        destination_project_id (str): project id where BQ table will be created
-        dataset_id (str): dataset id where BQ table will be created
-        table_id (str): table name (without project id and dataset id)
         dataset_location (str): bq dataset location
-        query_job_config (dict): dict containing optional parameters
         required by the bq query operation. No need to specify destination param
-        See available parameters here
-        https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.job.QueryJobConfig.html
     Returns:
         None
     """
@@ -50,13 +40,7 @@ def bq_query_to_table(
 
     logging.getLogger().setLevel(logging.INFO)
 
-    if (dataset_id is not None) and (table_id is not None):
-        dest_table_ref = f"{destination_project_id}.{dataset_id}.{table_id}"
-    else:
-        dest_table_ref = None
-    if query_job_config is None:
-        query_job_config = {}
-    job_config = bigquery.QueryJobConfig(destination=dest_table_ref, **query_job_config)
+    job_config = bigquery.QueryJobConfig()
 
     bq_client = bigquery.client.Client(
         project=bq_client_project_id, location=dataset_location
@@ -65,7 +49,7 @@ def bq_query_to_table(
 
     try:
         result = query_job.result()
-        logging.info(f"BQ table {dest_table_ref} created")
+        logging.info(f"BQ Job finished")
     except GoogleCloudError as e:
         logging.error(e)
         logging.error(query_job.error_result)
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index b011b0c1..3a9fdb02 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import os
 import pathlib
 
@@ -29,9 +28,10 @@ def tensorflow_pipeline(
     project_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
     model_name: str = "simple_tensorflow",
-    dataset_id: str = "preprocessing",
+    preprocessing_dataset_id: str = "preprocessing",
     dataset_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_dataset_id: str = "chicago_taxi_trips",
+    prediction_dataset_id: str = "prediction",
     timestamp: str = "2022-12-01 00:00:00",
     batch_prediction_machine_type: str = "n1-standard-4",
     batch_prediction_min_replicas: int = 3,
@@ -49,13 +49,14 @@ def tensorflow_pipeline(
     Args:
         project_id (str): project id of the Google Cloud project
         project_location (str): location of the Google Cloud project
-        pipeline_files_gcs_path (str): GCS path where the pipeline files are located
         ingestion_project_id (str): project id containing the source bigquery data
             for ingestion. This can be the same as `project_id` if the source data is
             in the same project where the ML pipeline is executed.
         model_name (str): name of model
-        model_label (str): label of model
-        dataset_id (str): id of BQ dataset used to store all staging data & predictions
+         preprocessing_dataset_id (str): id of BQ dataset used to
+            store all staging data .
+        prediction_dataset_id (str): id of BQ dataset used to
+            store all predictions.
         dataset_location (str): location of dataset
         ingestion_dataset_id (str): dataset id of ingestion data
         timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
@@ -91,6 +92,10 @@ def tensorflow_pipeline(
         queries_folder / "ingest.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
+        prediction_dataset=f"{ingestion_project_id}.{prediction_dataset_id}",
+        preprocessing_dataset=f"{ingestion_project_id}.{preprocessing_dataset_id}",
+        ingested_table=ingested_table,
+        dataset_region=project_location,
         filter_column=time_column,
         filter_start_value=timestamp,
     )
@@ -98,14 +103,11 @@ def tensorflow_pipeline(
     # data ingestion and preprocessing operations
     kwargs = dict(
         bq_client_project_id=project_id,
-        destination_project_id=project_id,
-        dataset_id=dataset_id,
         dataset_location=dataset_location,
-        query_job_config=json.dumps(dict(write_disposition="WRITE_TRUNCATE")),
     )
-    ingest = bq_query_to_table(
-        query=ingest_query, table_id=ingested_table, **kwargs
-    ).set_display_name("Ingest data")
+    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
+        "Ingest data"
+    )
 
     # lookup champion model
     champion_model = (
@@ -120,8 +122,10 @@ def tensorflow_pipeline(
     )
 
     # batch predict from BigQuery to BigQuery
-    bigquery_source_input_uri = f"bq://{project_id}.{dataset_id}.{ingested_table}"
-    bigquery_destination_output_uri = f"bq://{project_id}.{dataset_id}"
+    bigquery_source_input_uri = (
+        f"bq://{project_id}.{preprocessing_dataset_id}.{ingested_table}"
+    )
+    bigquery_destination_output_uri = f"bq://{project_id}.{prediction_dataset_id}"
     instance_config = {"instanceType": "object"}
 
     # predict data
diff --git a/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
index e01a7c57..5a44d671 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
@@ -14,8 +14,16 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
+CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
+  OPTIONS (
+    description = 'Prediction Dataset',
+    location = "{{ dataset_region }}");
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
 with filter_start_values as (
-    SELECT 
+    SELECT
     IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
@@ -43,7 +51,7 @@ SELECT
     trip_miles,
     CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
                WHEN trip_seconds <= 0 then m.avg_trip_seconds
-               ELSE trip_seconds 
+               ELSE trip_seconds
                END AS FLOAT64) AS trip_seconds,
     payment_type,
     company,
@@ -54,3 +62,4 @@ WHERE
                 "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
+    );
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 2767d210..56aea64c 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import os
 import pathlib
 
@@ -101,6 +100,9 @@ def tensorflow_pipeline(
         queries_folder / "ingest.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        ingested_table=ingested_table,
+        dataset_region=project_location,
         filter_column=time_column,
         target_column=label_column_name,
         filter_start_value=timestamp,
@@ -109,6 +111,8 @@ def tensorflow_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=train_table,
         num_lots=10,
         lots=tuple(range(8)),
     )
@@ -116,6 +120,8 @@ def tensorflow_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=valid_table,
         num_lots=10,
         lots="(8)",
     )
@@ -123,51 +129,34 @@ def tensorflow_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=test_table,
         num_lots=10,
         lots="(9)",
     )
-    data_cleaning_query = generate_query(
-        queries_folder / "engineer_features.sql",
-        source_dataset=dataset_id,
-        source_table=train_table,
-    )
 
     # data ingestion and preprocessing operations
 
-    kwargs = dict(
-        bq_client_project_id=project_id,
-        destination_project_id=project_id,
-        dataset_id=dataset_id,
-        dataset_location=dataset_location,
-        query_job_config=json.dumps(dict(write_disposition="WRITE_TRUNCATE")),
+    kwargs = dict(bq_client_project_id=project_id, dataset_location=dataset_location)
+    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
+        "Ingest data"
     )
-    ingest = bq_query_to_table(
-        query=ingest_query, table_id=ingested_table, **kwargs
-    ).set_display_name("Ingest data")
 
-    # exporting data to GCS from BQ
     split_train_data = (
-        bq_query_to_table(query=split_train_query, table_id=train_table, **kwargs)
+        bq_query_to_table(query=split_train_query, **kwargs)
         .after(ingest)
         .set_display_name("Split train data")
     )
     split_valid_data = (
-        bq_query_to_table(query=split_valid_query, table_id=valid_table, **kwargs)
+        bq_query_to_table(query=split_valid_query, **kwargs)
         .after(ingest)
         .set_display_name("Split validation data")
     )
     split_test_data = (
-        bq_query_to_table(query=split_test_query, table_id=test_table, **kwargs)
+        bq_query_to_table(query=split_test_query, **kwargs)
         .after(ingest)
         .set_display_name("Split test data")
     )
-    data_cleaning = (
-        bq_query_to_table(
-            query=data_cleaning_query, table_id=preprocessed_table, **kwargs
-        )
-        .after(split_train_data)
-        .set_display_name("Clean data")
-    )
 
     # data extraction to gcs
 
@@ -176,10 +165,10 @@ def tensorflow_pipeline(
             bq_client_project_id=project_id,
             source_project_id=project_id,
             dataset_id=dataset_id,
-            table_name=preprocessed_table,
+            table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(data_cleaning)
+        .after(split_train_data)
         .set_display_name("Extract train data to storage")
     ).outputs["dataset"]
     valid_dataset = (
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
index de9459fc..7f9f3b0b 100644
--- a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
@@ -14,26 +14,36 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
-with filter_start_values as (
-    SELECT 
-    IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
+
+CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
+  OPTIONS (
+    description = 'Preprocessing Dataset',
+    location = "{{ dataset_region }}");
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
+WITH filter_start_values AS (
+SELECT
+	IF("{{ filter_start_value }}" = '',
+	CURRENT_DATETIME(),
+	CAST("{{ filter_start_value }}" AS DATETIME)) AS filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
-,filtered_data as (
+,filtered_data AS (
     SELECT
     *
     FROM `{{ source_dataset }}.{{ source_table }}`, filter_start_values
     WHERE
          DATE({{ filter_column }}) BETWEEN
-         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value as DATETIME)), INTERVAL 3 MONTH) AND
+         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value AS DATETIME)), INTERVAL 3 MONTH) AND
          DATE_SUB(DATE(filter_start_value), INTERVAL 2 MONTH)
 )
 -- Use the average trip_seconds as a replacement for NULL or 0 values
-,mean_time as (
+,mean_time AS (
     SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
     FROM filtered_data
 )
-
 SELECT
     CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
     CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
@@ -43,15 +53,16 @@ SELECT
     trip_miles,
     CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
                WHEN trip_seconds <= 0 then m.avg_trip_seconds
-               ELSE trip_seconds 
+               ELSE trip_seconds
                END AS FLOAT64) AS trip_seconds,
     payment_type,
     company,
     (fare + tips + tolls + extras) AS `{{ target_column }}`,
-FROM filtered_data as t, mean_time as m
+FROM filtered_data AS t, mean_time AS m
 WHERE
     trip_miles > 0 AND fare > 0 AND fare < 1500
     {% for field in ["fare", "trip_start_timestamp", "pickup_longitude",
                 "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
+);
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/sample.sql b/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
index bf47bbf6..be8458be 100644
--- a/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
+++ b/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
@@ -1,20 +1,10 @@
--- Copyright 2022 Google LLC
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ target_table }}`;
 
--- Licensed under the Apache License, Version 2.0 (the "License");
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
-SELECT *
+CREATE TABLE `{{ preprocessing_dataset }}.{{ target_table }}` AS (
+SELECT
+	*
 FROM
- `{{ source_dataset }}.{{ source_table }}` AS t
+	`{{ source_dataset }}.{{ source_table }}` AS t
 WHERE
-    MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-        {{ num_lots }}) IN {{ lots }}
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	{{ num_lots }}) IN {{ lots }});
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index ed474eb8..0c4504ec 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import os
 import pathlib
 
@@ -29,9 +28,10 @@ def xgboost_pipeline(
     project_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
     model_name: str = "simple_xgboost",
-    dataset_id: str = "preprocessing",
+    preprocessing_dataset_id: str = "preprocessing",
     dataset_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_dataset_id: str = "chicago_taxi_trips",
+    prediction_dataset_id: str = "prediction",
     timestamp: str = "2022-12-01 00:00:00",
     batch_prediction_machine_type: str = "n1-standard-4",
     batch_prediction_min_replicas: int = 3,
@@ -50,14 +50,17 @@ def xgboost_pipeline(
             for ingestion. This can be the same as `project_id` if the source data is
             in the same project where the ML pipeline is executed.
         model_name (str): name of model
-        dataset_id (str): id of BQ dataset used to store all staging data & predictions
+        preprocessing_dataset_id (str): id of BQ dataset used to
+            store all staging data .
+        prediction_dataset_id (str): id of BQ dataset used to
+            store all predictions.
         dataset_location (str): location of dataset
         ingestion_dataset_id (str): dataset id of ingestion data
         timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
             (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
             If any time part is missing, it will be regarded as zero.
         batch_prediction_machine_type (str): Machine type to be used for Vertex Batch
-            Prediction. Example machine_types - n1-standard-4, n1-standard-16 etc
+            Prediction. Example machine_types - n1-standard-4, n1-standard-16 etc.
         batch_prediction_min_replicas (int): Minimum no of machines to distribute the
             Vertex Batch Prediction job for horizontal scalability
         batch_prediction_max_replicas (int): Maximum no of machines to distribute the
@@ -85,6 +88,10 @@ def xgboost_pipeline(
         queries_folder / "ingest.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
+        prediction_dataset=f"{ingestion_project_id}.{prediction_dataset_id}",
+        preprocessing_dataset=f"{ingestion_project_id}.{preprocessing_dataset_id}",
+        ingested_table=ingested_table,
+        dataset_region=project_location,
         filter_column=time_column,
         filter_start_value=timestamp,
     )
@@ -92,14 +99,11 @@ def xgboost_pipeline(
     # data ingestion and preprocessing operations
     kwargs = dict(
         bq_client_project_id=project_id,
-        destination_project_id=project_id,
-        dataset_id=dataset_id,
         dataset_location=dataset_location,
-        query_job_config=json.dumps(dict(write_disposition="WRITE_TRUNCATE")),
     )
-    ingest = bq_query_to_table(
-        query=ingest_query, table_id=ingested_table, **kwargs
-    ).set_display_name("Ingest data")
+    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
+        "Ingest data"
+    )
 
     # lookup champion model
     champion_model = (
@@ -114,8 +118,10 @@ def xgboost_pipeline(
     )
 
     # batch predict from BigQuery to BigQuery
-    bigquery_source_input_uri = f"bq://{project_id}.{dataset_id}.{ingested_table}"
-    bigquery_destination_output_uri = f"bq://{project_id}.{dataset_id}"
+    bigquery_source_input_uri = (
+        f"bq://{project_id}.{preprocessing_dataset_id}.{ingested_table}"
+    )
+    bigquery_destination_output_uri = f"bq://{project_id}.{prediction_dataset_id}"
 
     batch_prediction = (
         model_batch_predict(
diff --git a/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql b/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
index e01a7c57..bf8fe57a 100644
--- a/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
@@ -14,6 +14,14 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
+CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
+  OPTIONS (
+    description = 'Prediction Dataset',
+    location = "{{ dataset_region }}");
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
 with filter_start_values as (
     SELECT 
     IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
@@ -54,3 +62,4 @@ WHERE
                 "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
+    );
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 27cb47ed..6c9ad9d9 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import os
 import pathlib
 
@@ -99,6 +98,9 @@ def xgboost_pipeline(
         queries_folder / "ingest.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        ingested_table=ingested_table,
+        dataset_region=project_location,
         filter_column=time_column,
         target_column=label_column_name,
         filter_start_value=timestamp,
@@ -107,6 +109,8 @@ def xgboost_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=train_table,
         num_lots=10,
         lots=tuple(range(8)),
     )
@@ -114,57 +118,43 @@ def xgboost_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=valid_table,
         num_lots=10,
         lots="(8)",
     )
-    data_cleaning_query = generate_query(
-        queries_folder / "engineer_features.sql",
-        source_dataset=dataset_id,
-        source_table=train_table,
-    )
     split_test_query = generate_query(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=test_table,
         num_lots=10,
         lots="(9)",
     )
 
     # data ingestion and preprocessing operations
 
-    kwargs = dict(
-        bq_client_project_id=project_id,
-        destination_project_id=project_id,
-        dataset_id=dataset_id,
-        dataset_location=dataset_location,
-        query_job_config=json.dumps(dict(write_disposition="WRITE_TRUNCATE")),
+    kwargs = dict(bq_client_project_id=project_id, dataset_location=dataset_location)
+    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
+        "Ingest data"
     )
-    ingest = bq_query_to_table(
-        query=ingest_query, table_id=ingested_table, **kwargs
-    ).set_display_name("Ingest data")
 
     split_train_data = (
-        bq_query_to_table(query=split_train_query, table_id=train_table, **kwargs)
+        bq_query_to_table(query=split_train_query, **kwargs)
         .after(ingest)
         .set_display_name("Split train data")
     )
     split_valid_data = (
-        bq_query_to_table(query=split_valid_query, table_id=valid_table, **kwargs)
+        bq_query_to_table(query=split_valid_query, **kwargs)
         .after(ingest)
         .set_display_name("Split validation data")
     )
     split_test_data = (
-        bq_query_to_table(query=split_test_query, table_id=test_table, **kwargs)
+        bq_query_to_table(query=split_test_query, **kwargs)
         .after(ingest)
         .set_display_name("Split test data")
     )
-    data_cleaning = (
-        bq_query_to_table(
-            query=data_cleaning_query, table_id=preprocessed_table, **kwargs
-        )
-        .after(split_train_data)
-        .set_display_name("Clean data")
-    )
 
     # data extraction to gcs
 
@@ -173,10 +163,10 @@ def xgboost_pipeline(
             bq_client_project_id=project_id,
             source_project_id=project_id,
             dataset_id=dataset_id,
-            table_name=preprocessed_table,
+            table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(data_cleaning)
+        .after(split_train_data)
         .set_display_name("Extract train data to storage")
     ).outputs["dataset"]
     valid_dataset = (
diff --git a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql b/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
index de9459fc..fbb6df32 100644
--- a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
@@ -14,26 +14,36 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
-with filter_start_values as (
-    SELECT 
-    IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
+
+CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
+  OPTIONS (
+    description = 'Preprocessing Dataset',
+    location = "{{ dataset_region }}");
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
+WITH filter_start_values AS (
+SELECT
+	IF("{{ filter_start_value }}" = '',
+	CURRENT_DATETIME(),
+	CAST("{{ filter_start_value }}" AS DATETIME)) AS filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
-,filtered_data as (
+,filtered_data AS (
     SELECT
     *
     FROM `{{ source_dataset }}.{{ source_table }}`, filter_start_values
     WHERE
          DATE({{ filter_column }}) BETWEEN
-         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value as DATETIME)), INTERVAL 3 MONTH) AND
+         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value AS DATETIME)), INTERVAL 3 MONTH) AND
          DATE_SUB(DATE(filter_start_value), INTERVAL 2 MONTH)
 )
 -- Use the average trip_seconds as a replacement for NULL or 0 values
-,mean_time as (
+,mean_time AS (
     SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
     FROM filtered_data
 )
-
 SELECT
     CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
     CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
@@ -48,10 +58,11 @@ SELECT
     payment_type,
     company,
     (fare + tips + tolls + extras) AS `{{ target_column }}`,
-FROM filtered_data as t, mean_time as m
+FROM filtered_data AS t, mean_time AS m
 WHERE
     trip_miles > 0 AND fare > 0 AND fare < 1500
     {% for field in ["fare", "trip_start_timestamp", "pickup_longitude",
                 "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
+);
diff --git a/pipelines/src/pipelines/xgboost/training/queries/sample.sql b/pipelines/src/pipelines/xgboost/training/queries/sample.sql
index bb2dc9ce..be8458be 100644
--- a/pipelines/src/pipelines/xgboost/training/queries/sample.sql
+++ b/pipelines/src/pipelines/xgboost/training/queries/sample.sql
@@ -1,6 +1,10 @@
-SELECT *
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ target_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ target_table }}` AS (
+SELECT
+	*
 FROM
- `{{ source_dataset }}.{{ source_table }}` AS t
+	`{{ source_dataset }}.{{ source_table }}` AS t
 WHERE
-    MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-        {{ num_lots }}) IN {{ lots }}
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	{{ num_lots }}) IN {{ lots }});

From 531f125fe2cf97cbbae86238cc8978793c0d098e Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 16 May 2023 11:49:51 +0100
Subject: [PATCH 003/238] feat: combine assets into a single folder

---
 Makefile                                                    | 6 +++---
 .../{pipelines/tensorflow/prediction => }/assets/.gitkeep   | 0
 .../tensorflow/training => }/assets/train_tf_model.py       | 0
 .../xgboost/training => }/assets/train_xgb_model.py         | 0
 pipelines/pipelines/tensorflow/training/pipeline.py         | 2 +-
 pipelines/pipelines/xgboost/prediction/assets/.gitkeep      | 0
 pipelines/pipelines/xgboost/training/assets/.gitkeep        | 0
 pipelines/pipelines/xgboost/training/pipeline.py            | 2 +-
 8 files changed, 5 insertions(+), 5 deletions(-)
 rename pipelines/{pipelines/tensorflow/prediction => }/assets/.gitkeep (100%)
 rename pipelines/{pipelines/tensorflow/training => }/assets/train_tf_model.py (100%)
 rename pipelines/{pipelines/xgboost/training => }/assets/train_xgb_model.py (100%)
 delete mode 100644 pipelines/pipelines/xgboost/prediction/assets/.gitkeep
 delete mode 100644 pipelines/pipelines/xgboost/training/assets/.gitkeep

diff --git a/Makefile b/Makefile
index 74718267..87426406 100644
--- a/Makefile
+++ b/Makefile
@@ -62,9 +62,9 @@ test-all-components: ## Run unit tests for all pipeline components
 		$(MAKE) test-components GROUP=$$(basename $$component_group) ; \
 	done
 
-sync-assets: ## Sync assets folder to GCS. Must specify pipeline=<training|prediction>
-	if [ -d "./pipelines/pipelines/${PIPELINE_TEMPLATE}/$(pipeline)/assets/" ] ; then \
-		gsutil -m rsync -r -d ./pipelines/pipelines/${PIPELINE_TEMPLATE}/$(pipeline)/assets ${PIPELINE_FILES_GCS_PATH}/$(pipeline)/assets ; \
+sync-assets: ## Sync assets folder to GCS.
+	if [ -d "./pipelines/assets" ] ; then \
+		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets ; \
 	fi ;
 
 run: ## Compile pipeline, copy assets to GCS, and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
diff --git a/pipelines/pipelines/tensorflow/prediction/assets/.gitkeep b/pipelines/assets/.gitkeep
similarity index 100%
rename from pipelines/pipelines/tensorflow/prediction/assets/.gitkeep
rename to pipelines/assets/.gitkeep
diff --git a/pipelines/pipelines/tensorflow/training/assets/train_tf_model.py b/pipelines/assets/train_tf_model.py
similarity index 100%
rename from pipelines/pipelines/tensorflow/training/assets/train_tf_model.py
rename to pipelines/assets/train_tf_model.py
diff --git a/pipelines/pipelines/xgboost/training/assets/train_xgb_model.py b/pipelines/assets/train_xgb_model.py
similarity index 100%
rename from pipelines/pipelines/xgboost/training/assets/train_xgb_model.py
rename to pipelines/assets/train_xgb_model.py
diff --git a/pipelines/pipelines/tensorflow/training/pipeline.py b/pipelines/pipelines/tensorflow/training/pipeline.py
index b2ab814a..838c082f 100644
--- a/pipelines/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/pipelines/tensorflow/training/pipeline.py
@@ -81,7 +81,7 @@ def tensorflow_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/training/assets/train_tf_model.py"
+    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_tf_model.py"
     hparams = dict(
         batch_size=100,
         epochs=5,
diff --git a/pipelines/pipelines/xgboost/prediction/assets/.gitkeep b/pipelines/pipelines/xgboost/prediction/assets/.gitkeep
deleted file mode 100644
index e69de29b..00000000
diff --git a/pipelines/pipelines/xgboost/training/assets/.gitkeep b/pipelines/pipelines/xgboost/training/assets/.gitkeep
deleted file mode 100644
index e69de29b..00000000
diff --git a/pipelines/pipelines/xgboost/training/pipeline.py b/pipelines/pipelines/xgboost/training/pipeline.py
index 5fe34056..20c83dfb 100644
--- a/pipelines/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/pipelines/xgboost/training/pipeline.py
@@ -79,7 +79,7 @@ def xgboost_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/training/assets/train_xgb_model.py"
+    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_xgb_model.py"
     hparams = dict(
         n_estimators=200,
         early_stopping_rounds=10,

From 0b8b77f8758d4d64e4b5e1fb4754acc495598c42 Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Tue, 16 May 2023 13:53:18 +0200
Subject: [PATCH 004/238] refactor: replace custom BQ component with
 BigqueryQueryJobOp

---
 .../src/bigquery_components/__init__.py       |  2 -
 .../bigquery_components/bq_query_to_table.py  | 57 ----------------
 pipelines/src/pipelines/__init__.py           |  8 ++-
 .../tensorflow/prediction/pipeline.py         | 12 ++--
 .../pipelines/tensorflow/training/pipeline.py | 66 ++++---------------
 .../training/queries/engineer_features.sql    | 18 -----
 .../tensorflow/training/queries/ingest.sql    | 50 +++++++++-----
 .../tensorflow/training/queries/sample.sql    | 10 ---
 .../pipelines/xgboost/prediction/pipeline.py  | 13 ++--
 .../pipelines/xgboost/training/pipeline.py    | 66 ++++---------------
 .../training/queries/engineer_features.sql    |  4 --
 .../xgboost/training/queries/ingest.sql       | 50 +++++++++-----
 .../xgboost/training/queries/sample.sql       | 10 ---
 13 files changed, 107 insertions(+), 259 deletions(-)
 delete mode 100644 components/bigquery-components/src/bigquery_components/bq_query_to_table.py
 delete mode 100644 pipelines/src/pipelines/tensorflow/training/queries/engineer_features.sql
 delete mode 100644 pipelines/src/pipelines/tensorflow/training/queries/sample.sql
 delete mode 100644 pipelines/src/pipelines/xgboost/training/queries/engineer_features.sql
 delete mode 100644 pipelines/src/pipelines/xgboost/training/queries/sample.sql

diff --git a/components/bigquery-components/src/bigquery_components/__init__.py b/components/bigquery-components/src/bigquery_components/__init__.py
index 2e3870ac..e979abab 100644
--- a/components/bigquery-components/src/bigquery_components/__init__.py
+++ b/components/bigquery-components/src/bigquery_components/__init__.py
@@ -1,9 +1,7 @@
-from .bq_query_to_table import bq_query_to_table
 from .extract_bq_to_dataset import extract_bq_to_dataset
 
 
 __version__ = "0.0.1"
 __all__ = [
-    "bq_query_to_table",
     "extract_bq_to_dataset",
 ]
diff --git a/components/bigquery-components/src/bigquery_components/bq_query_to_table.py b/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
deleted file mode 100644
index 4b6afc29..00000000
--- a/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
+++ /dev/null
@@ -1,57 +0,0 @@
-# Copyright 2022 Google LLC
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from kfp.v2.dsl import component
-
-
-@component(
-    base_image="python:3.7",
-    packages_to_install=["google-cloud-bigquery==2.30.0"],
-)
-def bq_query_to_table(
-    query: str,
-    bq_client_project_id: str,
-    dataset_location: str = "EU",
-) -> None:
-    """
-    Run query & create a new BigQuery table
-    Args:
-        query (str): SQL query to execute, results are saved in a BigQuery table
-        bq_client_project_id (str): project id that will be used by the bq client
-        dataset_location (str): bq dataset location
-        required by the bq query operation. No need to specify destination param
-    Returns:
-        None
-    """
-    from google.cloud.exceptions import GoogleCloudError
-    from google.cloud import bigquery
-    import logging
-
-    logging.getLogger().setLevel(logging.INFO)
-
-    job_config = bigquery.QueryJobConfig()
-
-    bq_client = bigquery.client.Client(
-        project=bq_client_project_id, location=dataset_location
-    )
-    query_job = bq_client.query(query, job_config=job_config)
-
-    try:
-        result = query_job.result()
-        logging.info(f"BQ Job finished")
-    except GoogleCloudError as e:
-        logging.error(e)
-        logging.error(query_job.error_result)
-        logging.error(query_job.errors)
-        raise e
diff --git a/pipelines/src/pipelines/__init__.py b/pipelines/src/pipelines/__init__.py
index 113da917..badd535e 100644
--- a/pipelines/src/pipelines/__init__.py
+++ b/pipelines/src/pipelines/__init__.py
@@ -30,4 +30,10 @@ def generate_query(input_file: Path, **replacements) -> str:
     with open(input_file, "r") as f:
         query_template = f.read()
 
-    return Template(query_template).render(**replacements)
+    # Render the template with the provided replacements
+    query = Template(query_template).render(**replacements)
+
+    # Escape double quotes, newline and tab characters
+    query = query.replace('"', '\\"').replace("\n", "\\n").replace("\t", "\\t")
+
+    return query
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index 3a9fdb02..60ad3b47 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -15,10 +15,10 @@
 import os
 import pathlib
 
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp.v2 import compiler, dsl
 
 from pipelines import generate_query
-from bigquery_components import bq_query_to_table
 from vertex_components import lookup_model, model_batch_predict
 
 
@@ -101,13 +101,9 @@ def tensorflow_pipeline(
     )
 
     # data ingestion and preprocessing operations
-    kwargs = dict(
-        bq_client_project_id=project_id,
-        dataset_location=dataset_location,
-    )
-    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
-        "Ingest data"
-    )
+    ingest = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=ingest_query
+    ).set_display_name("Ingest data")
 
     # lookup champion model
     champion_model = (
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 56aea64c..ba98bea1 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -15,9 +15,10 @@
 import os
 import pathlib
 
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp.v2 import compiler, dsl
 from pipelines import generate_query
-from bigquery_components import bq_query_to_table, extract_bq_to_dataset
+from bigquery_components import extract_bq_to_dataset
 from vertex_components import (
     lookup_model,
     custom_train_job,
@@ -106,57 +107,14 @@ def tensorflow_pipeline(
         filter_column=time_column,
         target_column=label_column_name,
         filter_start_value=timestamp,
+        train_table=train_table,
+        validation_table=valid_table,
+        test_table=test_table,
     )
-    split_train_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=train_table,
-        num_lots=10,
-        lots=tuple(range(8)),
-    )
-    split_valid_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=valid_table,
-        num_lots=10,
-        lots="(8)",
-    )
-    split_test_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=test_table,
-        num_lots=10,
-        lots="(9)",
-    )
-
-    # data ingestion and preprocessing operations
 
-    kwargs = dict(bq_client_project_id=project_id, dataset_location=dataset_location)
-    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
-        "Ingest data"
-    )
-
-    split_train_data = (
-        bq_query_to_table(query=split_train_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split train data")
-    )
-    split_valid_data = (
-        bq_query_to_table(query=split_valid_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split validation data")
-    )
-    split_test_data = (
-        bq_query_to_table(query=split_test_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split test data")
-    )
+    ingest = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=ingest_query
+    ).set_display_name("Ingest data")
 
     # data extraction to gcs
 
@@ -168,8 +126,9 @@ def tensorflow_pipeline(
             table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(split_train_data)
+        .after(ingest)
         .set_display_name("Extract train data to storage")
+        .set_caching_options(False)
     ).outputs["dataset"]
     valid_dataset = (
         extract_bq_to_dataset(
@@ -179,8 +138,9 @@ def tensorflow_pipeline(
             table_name=valid_table,
             dataset_location=dataset_location,
         )
-        .after(split_valid_data)
+        .after(ingest)
         .set_display_name("Extract validation data to storage")
+        .set_caching_options(False)
     ).outputs["dataset"]
     test_dataset = (
         extract_bq_to_dataset(
@@ -191,7 +151,7 @@ def tensorflow_pipeline(
             dataset_location=dataset_location,
             destination_gcs_uri=test_dataset_uri,
         )
-        .after(split_test_data)
+        .after(ingest)
         .set_display_name("Extract test data to storage")
         .set_caching_options(False)
     ).outputs["dataset"]
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/engineer_features.sql b/pipelines/src/pipelines/tensorflow/training/queries/engineer_features.sql
deleted file mode 100644
index b8094a35..00000000
--- a/pipelines/src/pipelines/tensorflow/training/queries/engineer_features.sql
+++ /dev/null
@@ -1,18 +0,0 @@
--- Copyright 2022 Google LLC
-
--- Licensed under the Apache License, Version 2.0 (the "License");
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
-/* The Purpose of this query is to clean the data before the training*/
-SELECT
- *
-FROM `{{ source_dataset }}.{{ source_table }}`
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
index 7f9f3b0b..b3a31606 100644
--- a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
@@ -1,20 +1,3 @@
--- Copyright 2022 Google LLC
-
--- Licensed under the Apache License, Version 2.0 (the "License");
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
--- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
--- This allows us to set the filter_start_value to a specific time for testing or for backfill
-
 CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
   OPTIONS (
     description = 'Preprocessing Dataset',
@@ -66,3 +49,36 @@ WHERE
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
 );
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ train_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ train_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (0, 1, 2, 3, 4, 5, 6, 7));
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ validation_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ validation_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (8));
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ test_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ test_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (9));
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/sample.sql b/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
deleted file mode 100644
index be8458be..00000000
--- a/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
+++ /dev/null
@@ -1,10 +0,0 @@
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ target_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ target_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ source_dataset }}.{{ source_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	{{ num_lots }}) IN {{ lots }});
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index 0c4504ec..7fdea71c 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -15,10 +15,10 @@
 import os
 import pathlib
 
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp.v2 import compiler, dsl
 
 from pipelines import generate_query
-from bigquery_components import bq_query_to_table
 from vertex_components import lookup_model, model_batch_predict
 
 
@@ -96,14 +96,9 @@ def xgboost_pipeline(
         filter_start_value=timestamp,
     )
 
-    # data ingestion and preprocessing operations
-    kwargs = dict(
-        bq_client_project_id=project_id,
-        dataset_location=dataset_location,
-    )
-    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
-        "Ingest data"
-    )
+    ingest = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=ingest_query
+    ).set_display_name("Ingest data")
 
     # lookup champion model
     champion_model = (
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 6c9ad9d9..385e41ab 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -15,9 +15,10 @@
 import os
 import pathlib
 
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp.v2 import compiler, dsl
 from pipelines import generate_query
-from bigquery_components import bq_query_to_table, extract_bq_to_dataset
+from bigquery_components import extract_bq_to_dataset
 from vertex_components import (
     lookup_model,
     custom_train_job,
@@ -104,57 +105,14 @@ def xgboost_pipeline(
         filter_column=time_column,
         target_column=label_column_name,
         filter_start_value=timestamp,
+        train_table=train_table,
+        validation_table=valid_table,
+        test_table=test_table,
     )
-    split_train_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=train_table,
-        num_lots=10,
-        lots=tuple(range(8)),
-    )
-    split_valid_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=valid_table,
-        num_lots=10,
-        lots="(8)",
-    )
-    split_test_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=test_table,
-        num_lots=10,
-        lots="(9)",
-    )
-
-    # data ingestion and preprocessing operations
 
-    kwargs = dict(bq_client_project_id=project_id, dataset_location=dataset_location)
-    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
-        "Ingest data"
-    )
-
-    split_train_data = (
-        bq_query_to_table(query=split_train_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split train data")
-    )
-    split_valid_data = (
-        bq_query_to_table(query=split_valid_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split validation data")
-    )
-    split_test_data = (
-        bq_query_to_table(query=split_test_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split test data")
-    )
+    ingest = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=ingest_query
+    ).set_display_name("Ingest data")
 
     # data extraction to gcs
 
@@ -166,8 +124,9 @@ def xgboost_pipeline(
             table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(split_train_data)
+        .after(ingest)
         .set_display_name("Extract train data to storage")
+        .set_caching_options(False)
     ).outputs["dataset"]
     valid_dataset = (
         extract_bq_to_dataset(
@@ -177,8 +136,9 @@ def xgboost_pipeline(
             table_name=valid_table,
             dataset_location=dataset_location,
         )
-        .after(split_valid_data)
+        .after(ingest)
         .set_display_name("Extract validation data to storage")
+        .set_caching_options(False)
     ).outputs["dataset"]
     test_dataset = (
         extract_bq_to_dataset(
@@ -189,7 +149,7 @@ def xgboost_pipeline(
             dataset_location=dataset_location,
             destination_gcs_uri=test_dataset_uri,
         )
-        .after(split_test_data)
+        .after(ingest)
         .set_display_name("Extract test data to storage")
         .set_caching_options(False)
     ).outputs["dataset"]
diff --git a/pipelines/src/pipelines/xgboost/training/queries/engineer_features.sql b/pipelines/src/pipelines/xgboost/training/queries/engineer_features.sql
deleted file mode 100644
index 148d9ce7..00000000
--- a/pipelines/src/pipelines/xgboost/training/queries/engineer_features.sql
+++ /dev/null
@@ -1,4 +0,0 @@
-/* The Purpose of this query is to clean the data before the training*/
-SELECT
- *
-FROM `{{ source_dataset }}.{{ source_table }}`
diff --git a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql b/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
index fbb6df32..10ecf037 100644
--- a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
@@ -1,20 +1,3 @@
--- Copyright 2022 Google LLC
-
--- Licensed under the Apache License, Version 2.0 (the "License");
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
--- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
--- This allows us to set the filter_start_value to a specific time for testing or for backfill
-
 CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
   OPTIONS (
     description = 'Preprocessing Dataset',
@@ -66,3 +49,36 @@ WHERE
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
 );
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ train_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ train_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (0, 1, 2, 3, 4, 5, 6, 7));
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ validation_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ validation_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (8));
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ test_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ test_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (9));
diff --git a/pipelines/src/pipelines/xgboost/training/queries/sample.sql b/pipelines/src/pipelines/xgboost/training/queries/sample.sql
deleted file mode 100644
index be8458be..00000000
--- a/pipelines/src/pipelines/xgboost/training/queries/sample.sql
+++ /dev/null
@@ -1,10 +0,0 @@
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ target_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ target_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ source_dataset }}.{{ source_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	{{ num_lots }}) IN {{ lots }});

From e784ab1f2226b3a709114bc037ec6ab7f305a8cc Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 16 May 2023 13:07:29 +0100
Subject: [PATCH 005/238] docs: update related to assets

---
 README.md            | 2 +-
 cloudbuild/README.md | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index f83622a7..98051006 100644
--- a/README.md
+++ b/README.md
@@ -190,7 +190,7 @@ When triggering ad hoc runs in your dev/sandbox environment, or when running the
 
 ### Assets
 
-In each pipeline folder, there is an `assets` directory (`pipelines/pipelines/<xgboost|tensorflow>/<training|prediction>/assets/`). This can be used for any additional files that may be needed during execution of the pipelines. 
+Pipeline folder, contains `assets` directory (`pipelines/assets/`). This can be used for any additional files that may be needed during execution of the pipelines. 
 This directory is rsync'd to Google Cloud Storage when running a pipeline in the sandbox environment or as part of the CD pipeline (see [CI/CD setup](cloudbuild/README.md)).
 
 ## Testing
diff --git a/cloudbuild/README.md b/cloudbuild/README.md
index 97eb2a4a..d541b034 100644
--- a/cloudbuild/README.md
+++ b/cloudbuild/README.md
@@ -21,8 +21,8 @@ limitations under the License.
 There are five CI/CD pipelines
 
 1. `pr-checks.yaml` - runs pre-commit checks and unit tests on the custom KFP components, and checks that the ML pipelines (training and prediction) can compile.
-1. `e2e-test.yaml` - copies the "assets" folders to the chosen GCS destination (versioned by git commit hash) and runs end-to-end tests of the training and prediction pipeline.
-1. `release.yaml` - compiles training and prediction pipelines, then copies the compiled pipelines and their respective "assets" folders to the chosen GCS destination (versioned by git tag).
+1. `e2e-test.yaml` - copies the "assets" folder to the chosen GCS destination (versioned by git commit hash) and runs end-to-end tests of the training and prediction pipeline.
+1. `release.yaml` - compiles training and prediction pipelines, then copies the compiled pipelines and "assets" folder to the chosen GCS destination (versioned by git tag).
 1. `terraform-plan.yaml` - Checks the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`), and produces a summary of any proposed changes that will be applied on merge to the main branch.
 1. `terraform-apply.yaml` - Applies the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`).
 

From 15bf42508fa977dd731ba1f4f1acbcbcb2b82f06 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 16 May 2023 14:08:13 +0100
Subject: [PATCH 006/238] ci: ci changes after combined assets

---
 cloudbuild/e2e-test.yaml |  6 ++----
 cloudbuild/release.yaml  | 10 ++++------
 2 files changed, 6 insertions(+), 10 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 1194415e..c8f86917 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -22,10 +22,8 @@ steps:
     args:
       - -c
       - |
-        mkdir -p ${COMMIT_SHA}/training/assets && \
-        mkdir -p ${COMMIT_SHA}/prediction/assets && \
-        cp -r pipelines/pipelines/${_PIPELINE_TEMPLATE}/training/assets ${COMMIT_SHA}/training/ && \
-        cp -r pipelines/pipelines/${_PIPELINE_TEMPLATE}/prediction/assets ${COMMIT_SHA}/prediction/ && \
+        mkdir -p ${COMMIT_SHA}/assets && \
+        cp -r pipelines/assets && \
         gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
 
   # Install Python deps
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 63e60115..adf2a018 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -35,12 +35,10 @@ steps:
     args:
       - -c
       - |
-        mkdir -p ${TAG_NAME}/training/assets && \
-        mkdir -p ${TAG_NAME}/prediction/assets && \
-        cp pipelines/training.json ${TAG_NAME}/training/training.json && \
-        cp pipelines/prediction.json ${TAG_NAME}/prediction/prediction.json && \
-        cp -r pipelines/pipelines/${_PIPELINE_TEMPLATE}/training/assets ${TAG_NAME}/training/ && \
-        cp -r pipelines/pipelines/${_PIPELINE_TEMPLATE}/prediction/assets ${TAG_NAME}/prediction/ && \
+        mkdir -p ${TAG_NAME}/assets && \
+        cp pipelines/training.json ${TAG_NAME}/training.json && \
+        cp pipelines/prediction.json ${TAG_NAME}/prediction.json && \
+        cp -r pipelines/assets ${TAG_NAME} && \
         for dest in ${_PIPELINE_PUBLISH_GCS_PATHS} ; do \
           gsutil cp -r ${TAG_NAME} $$dest ; \
         done

From 4bc0eff627bb217891c4f1556b8bb74331b621ae Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 16 May 2023 14:18:16 +0100
Subject: [PATCH 007/238] ci: cloudbuild assets fix

---
 cloudbuild/e2e-test.yaml |  6 ++++--
 cloudbuild/release.yaml  | 10 ++++++----
 2 files changed, 10 insertions(+), 6 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index c8f86917..f503f5cf 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -22,8 +22,10 @@ steps:
     args:
       - -c
       - |
-        mkdir -p ${COMMIT_SHA}/assets && \
-        cp -r pipelines/assets && \
+        mkdir -p ${COMMIT_SHA}/training/assets && \
+        mkdir -p ${COMMIT_SHA}/prediction/assets && \
+        cp -r pipelines/assets ${COMMIT_SHA}/training/ && \
+        cp -r pipelines/assets ${COMMIT_SHA}/prediction/ && \
         gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
 
   # Install Python deps
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index adf2a018..0804f09f 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -35,10 +35,12 @@ steps:
     args:
       - -c
       - |
-        mkdir -p ${TAG_NAME}/assets && \
-        cp pipelines/training.json ${TAG_NAME}/training.json && \
-        cp pipelines/prediction.json ${TAG_NAME}/prediction.json && \
-        cp -r pipelines/assets ${TAG_NAME} && \
+        mkdir -p ${TAG_NAME}/training/assets && \
+        mkdir -p ${TAG_NAME}/prediction/assets && \
+        cp pipelines/training.json ${TAG_NAME}/training/training.json && \
+        cp pipelines/prediction.json ${TAG_NAME}/prediction/prediction.json && \
+        cp -r pipelines/assets ${TAG_NAME}/training/ && \
+        cp -r pipelines/assets ${TAG_NAME}/prediction/ && \
         for dest in ${_PIPELINE_PUBLISH_GCS_PATHS} ; do \
           gsutil cp -r ${TAG_NAME} $$dest ; \
         done

From bb4bfa1712893c5d486c5c71d31c15ccaea10463 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 16 May 2023 15:12:04 +0100
Subject: [PATCH 008/238] ci: ci changes

---
 cloudbuild/e2e-test.yaml | 6 ++----
 cloudbuild/release.yaml  | 4 ++--
 2 files changed, 4 insertions(+), 6 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index f503f5cf..7e2edcef 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -22,10 +22,8 @@ steps:
     args:
       - -c
       - |
-        mkdir -p ${COMMIT_SHA}/training/assets && \
-        mkdir -p ${COMMIT_SHA}/prediction/assets && \
-        cp -r pipelines/assets ${COMMIT_SHA}/training/ && \
-        cp -r pipelines/assets ${COMMIT_SHA}/prediction/ && \
+        mkdir -p ${COMMIT_SHA}/assets && \
+        cp -r pipelines/assets ${COMMIT_SHA} && \
         gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
 
   # Install Python deps
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 0804f09f..63e60115 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -39,8 +39,8 @@ steps:
         mkdir -p ${TAG_NAME}/prediction/assets && \
         cp pipelines/training.json ${TAG_NAME}/training/training.json && \
         cp pipelines/prediction.json ${TAG_NAME}/prediction/prediction.json && \
-        cp -r pipelines/assets ${TAG_NAME}/training/ && \
-        cp -r pipelines/assets ${TAG_NAME}/prediction/ && \
+        cp -r pipelines/pipelines/${_PIPELINE_TEMPLATE}/training/assets ${TAG_NAME}/training/ && \
+        cp -r pipelines/pipelines/${_PIPELINE_TEMPLATE}/prediction/assets ${TAG_NAME}/prediction/ && \
         for dest in ${_PIPELINE_PUBLISH_GCS_PATHS} ; do \
           gsutil cp -r ${TAG_NAME} $$dest ; \
         done

From 2580bd4b1d417f87bf12bd6d32e511818aefe494 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Mon, 15 May 2023 23:14:26 +0100
Subject: [PATCH 009/238] build(.python-version): change python version from
 3.7 to 3.9

---
 .python-version                                | 2 +-
 components/bigquery-components/.python-version | 2 +-
 components/vertex-components/.python-version   | 2 +-
 pipelines/.python-version                      | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/.python-version b/.python-version
index f7e5aa84..9f3d4c17 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.7.12
+3.9.16
diff --git a/components/bigquery-components/.python-version b/components/bigquery-components/.python-version
index f7e5aa84..9f3d4c17 100644
--- a/components/bigquery-components/.python-version
+++ b/components/bigquery-components/.python-version
@@ -1 +1 @@
-3.7.12
+3.9.16
diff --git a/components/vertex-components/.python-version b/components/vertex-components/.python-version
index f7e5aa84..9f3d4c17 100644
--- a/components/vertex-components/.python-version
+++ b/components/vertex-components/.python-version
@@ -1 +1 @@
-3.7.12
+3.9.16
diff --git a/pipelines/.python-version b/pipelines/.python-version
index f7e5aa84..9f3d4c17 100644
--- a/pipelines/.python-version
+++ b/pipelines/.python-version
@@ -1 +1 @@
-3.7.12
+3.9.16

From 453bb9fc29551962589dda950b79cf16de4c2d51 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Mon, 15 May 2023 23:17:48 +0100
Subject: [PATCH 010/238] build(pyproject.toml): migrate from pipenv to poetry

all pipfile.lock files have been deleted and replaced with poetry.lock files
---
 components/bigquery-components/Pipfile        |   14 -
 components/bigquery-components/Pipfile.lock   | 1220 -----------
 components/bigquery-components/poetry.lock    | 1772 ++++++++++++++++
 components/bigquery-components/pyproject.toml |   36 +-
 components/vertex-components/Pipfile          |   16 -
 components/vertex-components/Pipfile.lock     | 1792 ----------------
 components/vertex-components/poetry.lock      | 1695 +++++++++++++++
 components/vertex-components/pyproject.toml   |   37 +-
 pipelines/Pipfile                             |   19 -
 pipelines/Pipfile.lock                        | 1193 -----------
 pipelines/poetry.lock                         | 1845 +++++++++++++++++
 pipelines/pyproject.toml                      |   35 +-
 poetry.lock                                   | 1845 +++++++++++++++++
 pyproject.toml                                |   26 +
 14 files changed, 7235 insertions(+), 4310 deletions(-)
 delete mode 100644 components/bigquery-components/Pipfile
 delete mode 100644 components/bigquery-components/Pipfile.lock
 create mode 100644 components/bigquery-components/poetry.lock
 delete mode 100644 components/vertex-components/Pipfile
 delete mode 100644 components/vertex-components/Pipfile.lock
 create mode 100644 components/vertex-components/poetry.lock
 delete mode 100644 pipelines/Pipfile
 delete mode 100644 pipelines/Pipfile.lock
 create mode 100644 pipelines/poetry.lock
 create mode 100644 poetry.lock
 create mode 100644 pyproject.toml

diff --git a/components/bigquery-components/Pipfile b/components/bigquery-components/Pipfile
deleted file mode 100644
index cfe725a8..00000000
--- a/components/bigquery-components/Pipfile
+++ /dev/null
@@ -1,14 +0,0 @@
-[[source]]
-url = "https://pypi.org/simple"
-verify_ssl = true
-name = "pypi"
-
-[packages]
-kfp = "==1.8.21"
-
-[dev-packages]
-google-cloud-bigquery = "==2.30.0"
-pytest = ">=7.3.1,<8.0.0"
-
-[requires]
-python_version = "3.7"
diff --git a/components/bigquery-components/Pipfile.lock b/components/bigquery-components/Pipfile.lock
deleted file mode 100644
index 602d5cba..00000000
--- a/components/bigquery-components/Pipfile.lock
+++ /dev/null
@@ -1,1220 +0,0 @@
-{
-    "_meta": {
-        "hash": {
-            "sha256": "5d62fbd9c31800d2f58a5c338a68119081148c391a4437bdc919329e2d2b3029"
-        },
-        "pipfile-spec": 6,
-        "requires": {
-            "python_version": "3.7"
-        },
-        "sources": [
-            {
-                "name": "pypi",
-                "url": "https://pypi.org/simple",
-                "verify_ssl": true
-            }
-        ]
-    },
-    "default": {
-        "absl-py": {
-            "hashes": [
-                "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47",
-                "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==1.4.0"
-        },
-        "attrs": {
-            "hashes": [
-                "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04",
-                "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==23.1.0"
-        },
-        "cachetools": {
-            "hashes": [
-                "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14",
-                "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"
-            ],
-            "markers": "python_version ~= '3.7'",
-            "version": "==5.3.0"
-        },
-        "certifi": {
-            "hashes": [
-                "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7",
-                "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2023.5.7"
-        },
-        "charset-normalizer": {
-            "hashes": [
-                "sha256:04afa6387e2b282cf78ff3dbce20f0cc071c12dc8f685bd40960cc68644cfea6",
-                "sha256:04eefcee095f58eaabe6dc3cc2262f3bcd776d2c67005880894f447b3f2cb9c1",
-                "sha256:0be65ccf618c1e7ac9b849c315cc2e8a8751d9cfdaa43027d4f6624bd587ab7e",
-                "sha256:0c95f12b74681e9ae127728f7e5409cbbef9cd914d5896ef238cc779b8152373",
-                "sha256:0ca564606d2caafb0abe6d1b5311c2649e8071eb241b2d64e75a0d0065107e62",
-                "sha256:10c93628d7497c81686e8e5e557aafa78f230cd9e77dd0c40032ef90c18f2230",
-                "sha256:11d117e6c63e8f495412d37e7dc2e2fff09c34b2d09dbe2bee3c6229577818be",
-                "sha256:11d3bcb7be35e7b1bba2c23beedac81ee893ac9871d0ba79effc7fc01167db6c",
-                "sha256:12a2b561af122e3d94cdb97fe6fb2bb2b82cef0cdca131646fdb940a1eda04f0",
-                "sha256:12d1a39aa6b8c6f6248bb54550efcc1c38ce0d8096a146638fd4738e42284448",
-                "sha256:1435ae15108b1cb6fffbcea2af3d468683b7afed0169ad718451f8db5d1aff6f",
-                "sha256:1c60b9c202d00052183c9be85e5eaf18a4ada0a47d188a83c8f5c5b23252f649",
-                "sha256:1e8fcdd8f672a1c4fc8d0bd3a2b576b152d2a349782d1eb0f6b8e52e9954731d",
-                "sha256:20064ead0717cf9a73a6d1e779b23d149b53daf971169289ed2ed43a71e8d3b0",
-                "sha256:21fa558996782fc226b529fdd2ed7866c2c6ec91cee82735c98a197fae39f706",
-                "sha256:22908891a380d50738e1f978667536f6c6b526a2064156203d418f4856d6e86a",
-                "sha256:3160a0fd9754aab7d47f95a6b63ab355388d890163eb03b2d2b87ab0a30cfa59",
-                "sha256:322102cdf1ab682ecc7d9b1c5eed4ec59657a65e1c146a0da342b78f4112db23",
-                "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5",
-                "sha256:3573d376454d956553c356df45bb824262c397c6e26ce43e8203c4c540ee0acb",
-                "sha256:3747443b6a904001473370d7810aa19c3a180ccd52a7157aacc264a5ac79265e",
-                "sha256:38e812a197bf8e71a59fe55b757a84c1f946d0ac114acafaafaf21667a7e169e",
-                "sha256:3a06f32c9634a8705f4ca9946d667609f52cf130d5548881401f1eb2c39b1e2c",
-                "sha256:3a5fc78f9e3f501a1614a98f7c54d3969f3ad9bba8ba3d9b438c3bc5d047dd28",
-                "sha256:3d9098b479e78c85080c98e1e35ff40b4a31d8953102bb0fd7d1b6f8a2111a3d",
-                "sha256:3dc5b6a8ecfdc5748a7e429782598e4f17ef378e3e272eeb1340ea57c9109f41",
-                "sha256:4155b51ae05ed47199dc5b2a4e62abccb274cee6b01da5b895099b61b1982974",
-                "sha256:49919f8400b5e49e961f320c735388ee686a62327e773fa5b3ce6721f7e785ce",
-                "sha256:53d0a3fa5f8af98a1e261de6a3943ca631c526635eb5817a87a59d9a57ebf48f",
-                "sha256:5f008525e02908b20e04707a4f704cd286d94718f48bb33edddc7d7b584dddc1",
-                "sha256:628c985afb2c7d27a4800bfb609e03985aaecb42f955049957814e0491d4006d",
-                "sha256:65ed923f84a6844de5fd29726b888e58c62820e0769b76565480e1fdc3d062f8",
-                "sha256:6734e606355834f13445b6adc38b53c0fd45f1a56a9ba06c2058f86893ae8017",
-                "sha256:6baf0baf0d5d265fa7944feb9f7451cc316bfe30e8df1a61b1bb08577c554f31",
-                "sha256:6f4f4668e1831850ebcc2fd0b1cd11721947b6dc7c00bf1c6bd3c929ae14f2c7",
-                "sha256:6f5c2e7bc8a4bf7c426599765b1bd33217ec84023033672c1e9a8b35eaeaaaf8",
-                "sha256:6f6c7a8a57e9405cad7485f4c9d3172ae486cfef1344b5ddd8e5239582d7355e",
-                "sha256:7381c66e0561c5757ffe616af869b916c8b4e42b367ab29fedc98481d1e74e14",
-                "sha256:73dc03a6a7e30b7edc5b01b601e53e7fc924b04e1835e8e407c12c037e81adbd",
-                "sha256:74db0052d985cf37fa111828d0dd230776ac99c740e1a758ad99094be4f1803d",
-                "sha256:75f2568b4189dda1c567339b48cba4ac7384accb9c2a7ed655cd86b04055c795",
-                "sha256:78cacd03e79d009d95635e7d6ff12c21eb89b894c354bd2b2ed0b4763373693b",
-                "sha256:80d1543d58bd3d6c271b66abf454d437a438dff01c3e62fdbcd68f2a11310d4b",
-                "sha256:830d2948a5ec37c386d3170c483063798d7879037492540f10a475e3fd6f244b",
-                "sha256:891cf9b48776b5c61c700b55a598621fdb7b1e301a550365571e9624f270c203",
-                "sha256:8f25e17ab3039b05f762b0a55ae0b3632b2e073d9c8fc88e89aca31a6198e88f",
-                "sha256:9a3267620866c9d17b959a84dd0bd2d45719b817245e49371ead79ed4f710d19",
-                "sha256:a04f86f41a8916fe45ac5024ec477f41f886b3c435da2d4e3d2709b22ab02af1",
-                "sha256:aaf53a6cebad0eae578f062c7d462155eada9c172bd8c4d250b8c1d8eb7f916a",
-                "sha256:abc1185d79f47c0a7aaf7e2412a0eb2c03b724581139193d2d82b3ad8cbb00ac",
-                "sha256:ac0aa6cd53ab9a31d397f8303f92c42f534693528fafbdb997c82bae6e477ad9",
-                "sha256:ac3775e3311661d4adace3697a52ac0bab17edd166087d493b52d4f4f553f9f0",
-                "sha256:b06f0d3bf045158d2fb8837c5785fe9ff9b8c93358be64461a1089f5da983137",
-                "sha256:b116502087ce8a6b7a5f1814568ccbd0e9f6cfd99948aa59b0e241dc57cf739f",
-                "sha256:b82fab78e0b1329e183a65260581de4375f619167478dddab510c6c6fb04d9b6",
-                "sha256:bd7163182133c0c7701b25e604cf1611c0d87712e56e88e7ee5d72deab3e76b5",
-                "sha256:c36bcbc0d5174a80d6cccf43a0ecaca44e81d25be4b7f90f0ed7bcfbb5a00909",
-                "sha256:c3af8e0f07399d3176b179f2e2634c3ce9c1301379a6b8c9c9aeecd481da494f",
-                "sha256:c84132a54c750fda57729d1e2599bb598f5fa0344085dbde5003ba429a4798c0",
-                "sha256:cb7b2ab0188829593b9de646545175547a70d9a6e2b63bf2cd87a0a391599324",
-                "sha256:cca4def576f47a09a943666b8f829606bcb17e2bc2d5911a46c8f8da45f56755",
-                "sha256:cf6511efa4801b9b38dc5546d7547d5b5c6ef4b081c60b23e4d941d0eba9cbeb",
-                "sha256:d16fd5252f883eb074ca55cb622bc0bee49b979ae4e8639fff6ca3ff44f9f854",
-                "sha256:d2686f91611f9e17f4548dbf050e75b079bbc2a82be565832bc8ea9047b61c8c",
-                "sha256:d7fc3fca01da18fbabe4625d64bb612b533533ed10045a2ac3dd194bfa656b60",
-                "sha256:dd5653e67b149503c68c4018bf07e42eeed6b4e956b24c00ccdf93ac79cdff84",
-                "sha256:de5695a6f1d8340b12a5d6d4484290ee74d61e467c39ff03b39e30df62cf83a0",
-                "sha256:e0ac8959c929593fee38da1c2b64ee9778733cdf03c482c9ff1d508b6b593b2b",
-                "sha256:e1b25e3ad6c909f398df8921780d6a3d120d8c09466720226fc621605b6f92b1",
-                "sha256:e633940f28c1e913615fd624fcdd72fdba807bf53ea6925d6a588e84e1151531",
-                "sha256:e89df2958e5159b811af9ff0f92614dabf4ff617c03a4c1c6ff53bf1c399e0e1",
-                "sha256:ea9f9c6034ea2d93d9147818f17c2a0860d41b71c38b9ce4d55f21b6f9165a11",
-                "sha256:f645caaf0008bacf349875a974220f1f1da349c5dbe7c4ec93048cdc785a3326",
-                "sha256:f8303414c7b03f794347ad062c0516cee0e15f7a612abd0ce1e25caf6ceb47df",
-                "sha256:fca62a8301b605b954ad2e9c3666f9d97f63872aa4efcae5492baca2056b74ab"
-            ],
-            "markers": "python_full_version >= '3.7.0'",
-            "version": "==3.1.0"
-        },
-        "click": {
-            "hashes": [
-                "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e",
-                "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==8.1.3"
-        },
-        "cloudpickle": {
-            "hashes": [
-                "sha256:61f594d1f4c295fa5cd9014ceb3a1fc4a70b0de1164b94fbc2d854ccba056f9f",
-                "sha256:d89684b8de9e34a2a43b3460fbca07d09d6e25ce858df4d5a44240403b6178f5"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2.2.1"
-        },
-        "deprecated": {
-            "hashes": [
-                "sha256:43ac5335da90c31c24ba028af536a91d41d53f9e6901ddb021bcc572ce44e38d",
-                "sha256:64756e3e14c8c5eea9795d93c524551432a0be75629f8f29e67ab8caf076c76d"
-            ],
-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
-            "version": "==1.2.13"
-        },
-        "docstring-parser": {
-            "hashes": [
-                "sha256:48ddc093e8b1865899956fcc03b03e66bb7240c310fac5af81814580c55bf682",
-                "sha256:d1679b86250d269d06a99670924d6bce45adc00b08069dae8c47d98e89b667a9"
-            ],
-            "markers": "python_version >= '3.6' and python_version < '4.0'",
-            "version": "==0.15"
-        },
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diff --git a/components/bigquery-components/poetry.lock b/components/bigquery-components/poetry.lock
new file mode 100644
index 00000000..9a846c08
--- /dev/null
+++ b/components/bigquery-components/poetry.lock
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+    {file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"},
+    {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
+]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.9,<3.11"
+content-hash = "1f75fb78ca2fd965417d30dd7715e4c282abcd1b53703654e5c022f4d2e79328"
diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index 0ea3c6dc..083448b2 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -1,30 +1,30 @@
-[project]
+[tool.poetry]
 name = "bigquery-components"
-authors = [
-    {name = "Example User", email = "user@example.com"},
-]
-description = "BigQuery components"
+version = "0.1.0"
+authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
+description = "BigQuery components created by Datatonic"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.7",
-]
-requires-python = ">=3.7"
-dynamic = ["version"]
-dependencies = [
-    "kfp == 1.8.21",
+    "Programming Language :: Python :: 3.9",
 ]
 
-[project.optional-dependencies]
-tests = [
-    "google-cloud-bigquery == 2.30.0",
-    "pytest >= 7.3.1,<8.0.0",
-]
+[tool.poetry.dependencies]
+python = ">=3.9,<3.11"
+Jinja2 = ">=3.0.1,<4.0.0"
+google-cloud-aiplatform = "1.24.1"
+google-cloud-pipeline-components = "1.0.42"
+google-cloud-bigquery = "2.30.0"
+kfp = "==1.8.21"
+
+[tool.poetry.group.dev.dependencies]
+pytest = ">=7.3.1,<8.0.0"
+pre-commit = ">=2.14.1,<3.0.0"
 
 [build-system]
-requires = ["setuptools", "wheel"]
-build-backend = "setuptools.build_meta:__legacy__"
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
 
 [tool.flake8]
 max-line-length = 88
diff --git a/components/vertex-components/Pipfile b/components/vertex-components/Pipfile
deleted file mode 100644
index 6de5c5ef..00000000
--- a/components/vertex-components/Pipfile
+++ /dev/null
@@ -1,16 +0,0 @@
-[[source]]
-url = "https://pypi.org/simple"
-verify_ssl = true
-name = "pypi"
-
-[packages]
-kfp = "==1.8.21"
-
-[dev-packages]
-google-cloud-aiplatform = "==1.24.1"
-google-cloud-pipeline-components = "==1.0.42"
-pytest = ">=7.3.1,<8.0.0"
-pre-commit = ">=2.14.1,<3.0.0"
-
-[requires]
-python_version = "3.7"
diff --git a/components/vertex-components/Pipfile.lock b/components/vertex-components/Pipfile.lock
deleted file mode 100644
index e275cc15..00000000
--- a/components/vertex-components/Pipfile.lock
+++ /dev/null
@@ -1,1792 +0,0 @@
-{
-    "_meta": {
-        "hash": {
-            "sha256": "42000dc26266b6808ea2b6a7261983f236b59a8966b57835907a9b134fbef804"
-        },
-        "pipfile-spec": 6,
-        "requires": {
-            "python_version": "3.7"
-        },
-        "sources": [
-            {
-                "name": "pypi",
-                "url": "https://pypi.org/simple",
-                "verify_ssl": true
-            }
-        ]
-    },
-    "default": {
-        "absl-py": {
-            "hashes": [
-                "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47",
-                "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==1.4.0"
-        },
-        "attrs": {
-            "hashes": [
-                "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04",
-                "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==23.1.0"
-        },
-        "cachetools": {
-            "hashes": [
-                "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14",
-                "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"
-            ],
-            "markers": "python_version ~= '3.7'",
-            "version": "==5.3.0"
-        },
-        "certifi": {
-            "hashes": [
-                "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7",
-                "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2023.5.7"
-        },
-        "charset-normalizer": {
-            "hashes": [
-                "sha256:04afa6387e2b282cf78ff3dbce20f0cc071c12dc8f685bd40960cc68644cfea6",
-                "sha256:04eefcee095f58eaabe6dc3cc2262f3bcd776d2c67005880894f447b3f2cb9c1",
-                "sha256:0be65ccf618c1e7ac9b849c315cc2e8a8751d9cfdaa43027d4f6624bd587ab7e",
-                "sha256:0c95f12b74681e9ae127728f7e5409cbbef9cd914d5896ef238cc779b8152373",
-                "sha256:0ca564606d2caafb0abe6d1b5311c2649e8071eb241b2d64e75a0d0065107e62",
-                "sha256:10c93628d7497c81686e8e5e557aafa78f230cd9e77dd0c40032ef90c18f2230",
-                "sha256:11d117e6c63e8f495412d37e7dc2e2fff09c34b2d09dbe2bee3c6229577818be",
-                "sha256:11d3bcb7be35e7b1bba2c23beedac81ee893ac9871d0ba79effc7fc01167db6c",
-                "sha256:12a2b561af122e3d94cdb97fe6fb2bb2b82cef0cdca131646fdb940a1eda04f0",
-                "sha256:12d1a39aa6b8c6f6248bb54550efcc1c38ce0d8096a146638fd4738e42284448",
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diff --git a/components/vertex-components/poetry.lock b/components/vertex-components/poetry.lock
new file mode 100644
index 00000000..45fcd24d
--- /dev/null
+++ b/components/vertex-components/poetry.lock
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+    {file = "wrapt-1.15.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:2cf56d0e237280baed46f0b5316661da892565ff58309d4d2ed7dba763d984b8"},
+    {file = "wrapt-1.15.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:7dc0713bf81287a00516ef43137273b23ee414fe41a3c14be10dd95ed98a2df9"},
+    {file = "wrapt-1.15.0-cp39-cp39-win32.whl", hash = "sha256:46ed616d5fb42f98630ed70c3529541408166c22cdfd4540b88d5f21006b0eff"},
+    {file = "wrapt-1.15.0-cp39-cp39-win_amd64.whl", hash = "sha256:eef4d64c650f33347c1f9266fa5ae001440b232ad9b98f1f43dfe7a79435c0a6"},
+    {file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"},
+    {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
+]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.9,<3.11"
+content-hash = "a33ea27bf21c7344b28dfc284c9da679f3dbd302759f7eb5e929058ebef11572"
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index bc16a237..9011c442 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -1,32 +1,28 @@
-[project]
+[tool.poetry]
 name = "vertex-components"
-authors = [
-    {name = "Example User", email = "user@example.com"},
-]
-description = "Vertex AI components"
+version = "0.1.0"
+authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
+description = "Vertex AI components made by Datatonic"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.7",
-]
-requires-python = ">=3.7"
-dynamic = ["version"]
-dependencies = [
-    "kfp == 1.8.21",
+    "Programming Language :: Python :: 3.9",
 ]
 
-[project.optional-dependencies]
-tests = [
-    "google-cloud-aiplatform == 1.24.1",
-    "google-cloud-pipeline-components == 1.0.42",
-    "pytest >= 7.3.1,<8.0.0",
-    "pre-commit >= 2.14.1,<3.0.0",
-]
+[tool.poetry.dependencies]
+python = ">=3.9,<3.11"
+google-cloud-aiplatform = "1.24.1"
+google-cloud-pipeline-components = "1.0.42"
+kfp = "==1.8.21"
+
+[tool.poetry.group.dev.dependencies]
+pytest = ">=7.3.1,<8.0.0"
+pre-commit = ">=2.14.1,<3.0.0"
 
 [build-system]
-requires = ["setuptools", "wheel"]
-build-backend = "setuptools.build_meta:__legacy__"
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
 
 [tool.flake8]
 max-line-length = 88
@@ -45,3 +41,4 @@ pythonpath = [
 ]
 testpaths = "tests"
 junit_family = "xunit2"
+
diff --git a/pipelines/Pipfile b/pipelines/Pipfile
deleted file mode 100644
index 507b4e6d..00000000
--- a/pipelines/Pipfile
+++ /dev/null
@@ -1,19 +0,0 @@
-[[source]]
-url = "https://pypi.org/simple"
-verify_ssl = true
-name = "pypi"
-
-[packages]
-kfp = "==1.8.21"
-google-cloud-aiplatform = "==1.24.1"
-google-cloud-pipeline-components = "==1.0.42"
-Jinja2 = ">=3.0.1,<4.0.0"
-vertex-components = {editable = true, path = "./../components/vertex-components"}
-bigquery-components = {editable = true, path = "./../components/bigquery-components"}
-
-[dev-packages]
-pytest = ">=7.3.1,<8.0.0"
-pre-commit = ">=2.14.1,<3.0.0"
-
-[requires]
-python_version = "3.7"
diff --git a/pipelines/Pipfile.lock b/pipelines/Pipfile.lock
deleted file mode 100644
index 92d8d064..00000000
--- a/pipelines/Pipfile.lock
+++ /dev/null
@@ -1,1193 +0,0 @@
-{
-    "_meta": {
-        "hash": {
-            "sha256": "c889b828537547fe3e76c0ca6f812f331bffdf13bfd8c72104145db94eb555e0"
-        },
-        "pipfile-spec": 6,
-        "requires": {
-            "python_version": "3.7"
-        },
-        "sources": [
-            {
-                "name": "pypi",
-                "url": "https://pypi.org/simple",
-                "verify_ssl": true
-            }
-        ]
-    },
-    "default": {
-        "absl-py": {
-            "hashes": [
-                "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47",
-                "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==1.4.0"
-        },
-        "attrs": {
-            "hashes": [
-                "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04",
-                "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==23.1.0"
-        },
-        "bigquery-components": {
-            "editable": true,
-            "path": "./../components/bigquery-components"
-        },
-        "cachetools": {
-            "hashes": [
-                "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14",
-                "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"
-            ],
-            "markers": "python_version ~= '3.7'",
-            "version": "==5.3.0"
-        },
-        "certifi": {
-            "hashes": [
-                "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7",
-                "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2023.5.7"
-        },
-        "charset-normalizer": {
-            "hashes": [
-                "sha256:04afa6387e2b282cf78ff3dbce20f0cc071c12dc8f685bd40960cc68644cfea6",
-                "sha256:04eefcee095f58eaabe6dc3cc2262f3bcd776d2c67005880894f447b3f2cb9c1",
-                "sha256:0be65ccf618c1e7ac9b849c315cc2e8a8751d9cfdaa43027d4f6624bd587ab7e",
-                "sha256:0c95f12b74681e9ae127728f7e5409cbbef9cd914d5896ef238cc779b8152373",
-                "sha256:0ca564606d2caafb0abe6d1b5311c2649e8071eb241b2d64e75a0d0065107e62",
-                "sha256:10c93628d7497c81686e8e5e557aafa78f230cd9e77dd0c40032ef90c18f2230",
-                "sha256:11d117e6c63e8f495412d37e7dc2e2fff09c34b2d09dbe2bee3c6229577818be",
-                "sha256:11d3bcb7be35e7b1bba2c23beedac81ee893ac9871d0ba79effc7fc01167db6c",
-                "sha256:12a2b561af122e3d94cdb97fe6fb2bb2b82cef0cdca131646fdb940a1eda04f0",
-                "sha256:12d1a39aa6b8c6f6248bb54550efcc1c38ce0d8096a146638fd4738e42284448",
-                "sha256:1435ae15108b1cb6fffbcea2af3d468683b7afed0169ad718451f8db5d1aff6f",
-                "sha256:1c60b9c202d00052183c9be85e5eaf18a4ada0a47d188a83c8f5c5b23252f649",
-                "sha256:1e8fcdd8f672a1c4fc8d0bd3a2b576b152d2a349782d1eb0f6b8e52e9954731d",
-                "sha256:20064ead0717cf9a73a6d1e779b23d149b53daf971169289ed2ed43a71e8d3b0",
-                "sha256:21fa558996782fc226b529fdd2ed7866c2c6ec91cee82735c98a197fae39f706",
-                "sha256:22908891a380d50738e1f978667536f6c6b526a2064156203d418f4856d6e86a",
-                "sha256:3160a0fd9754aab7d47f95a6b63ab355388d890163eb03b2d2b87ab0a30cfa59",
-                "sha256:322102cdf1ab682ecc7d9b1c5eed4ec59657a65e1c146a0da342b78f4112db23",
-                "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5",
-                "sha256:3573d376454d956553c356df45bb824262c397c6e26ce43e8203c4c540ee0acb",
-                "sha256:3747443b6a904001473370d7810aa19c3a180ccd52a7157aacc264a5ac79265e",
-                "sha256:38e812a197bf8e71a59fe55b757a84c1f946d0ac114acafaafaf21667a7e169e",
-                "sha256:3a06f32c9634a8705f4ca9946d667609f52cf130d5548881401f1eb2c39b1e2c",
-                "sha256:3a5fc78f9e3f501a1614a98f7c54d3969f3ad9bba8ba3d9b438c3bc5d047dd28",
-                "sha256:3d9098b479e78c85080c98e1e35ff40b4a31d8953102bb0fd7d1b6f8a2111a3d",
-                "sha256:3dc5b6a8ecfdc5748a7e429782598e4f17ef378e3e272eeb1340ea57c9109f41",
-                "sha256:4155b51ae05ed47199dc5b2a4e62abccb274cee6b01da5b895099b61b1982974",
-                "sha256:49919f8400b5e49e961f320c735388ee686a62327e773fa5b3ce6721f7e785ce",
-                "sha256:53d0a3fa5f8af98a1e261de6a3943ca631c526635eb5817a87a59d9a57ebf48f",
-                "sha256:5f008525e02908b20e04707a4f704cd286d94718f48bb33edddc7d7b584dddc1",
-                "sha256:628c985afb2c7d27a4800bfb609e03985aaecb42f955049957814e0491d4006d",
-                "sha256:65ed923f84a6844de5fd29726b888e58c62820e0769b76565480e1fdc3d062f8",
-                "sha256:6734e606355834f13445b6adc38b53c0fd45f1a56a9ba06c2058f86893ae8017",
-                "sha256:6baf0baf0d5d265fa7944feb9f7451cc316bfe30e8df1a61b1bb08577c554f31",
-                "sha256:6f4f4668e1831850ebcc2fd0b1cd11721947b6dc7c00bf1c6bd3c929ae14f2c7",
-                "sha256:6f5c2e7bc8a4bf7c426599765b1bd33217ec84023033672c1e9a8b35eaeaaaf8",
-                "sha256:6f6c7a8a57e9405cad7485f4c9d3172ae486cfef1344b5ddd8e5239582d7355e",
-                "sha256:7381c66e0561c5757ffe616af869b916c8b4e42b367ab29fedc98481d1e74e14",
-                "sha256:73dc03a6a7e30b7edc5b01b601e53e7fc924b04e1835e8e407c12c037e81adbd",
-                "sha256:74db0052d985cf37fa111828d0dd230776ac99c740e1a758ad99094be4f1803d",
-                "sha256:75f2568b4189dda1c567339b48cba4ac7384accb9c2a7ed655cd86b04055c795",
-                "sha256:78cacd03e79d009d95635e7d6ff12c21eb89b894c354bd2b2ed0b4763373693b",
-                "sha256:80d1543d58bd3d6c271b66abf454d437a438dff01c3e62fdbcd68f2a11310d4b",
-                "sha256:830d2948a5ec37c386d3170c483063798d7879037492540f10a475e3fd6f244b",
-                "sha256:891cf9b48776b5c61c700b55a598621fdb7b1e301a550365571e9624f270c203",
-                "sha256:8f25e17ab3039b05f762b0a55ae0b3632b2e073d9c8fc88e89aca31a6198e88f",
-                "sha256:9a3267620866c9d17b959a84dd0bd2d45719b817245e49371ead79ed4f710d19",
-                "sha256:a04f86f41a8916fe45ac5024ec477f41f886b3c435da2d4e3d2709b22ab02af1",
-                "sha256:aaf53a6cebad0eae578f062c7d462155eada9c172bd8c4d250b8c1d8eb7f916a",
-                "sha256:abc1185d79f47c0a7aaf7e2412a0eb2c03b724581139193d2d82b3ad8cbb00ac",
-                "sha256:ac0aa6cd53ab9a31d397f8303f92c42f534693528fafbdb997c82bae6e477ad9",
-                "sha256:ac3775e3311661d4adace3697a52ac0bab17edd166087d493b52d4f4f553f9f0",
-                "sha256:b06f0d3bf045158d2fb8837c5785fe9ff9b8c93358be64461a1089f5da983137",
-                "sha256:b116502087ce8a6b7a5f1814568ccbd0e9f6cfd99948aa59b0e241dc57cf739f",
-                "sha256:b82fab78e0b1329e183a65260581de4375f619167478dddab510c6c6fb04d9b6",
-                "sha256:bd7163182133c0c7701b25e604cf1611c0d87712e56e88e7ee5d72deab3e76b5",
-                "sha256:c36bcbc0d5174a80d6cccf43a0ecaca44e81d25be4b7f90f0ed7bcfbb5a00909",
-                "sha256:c3af8e0f07399d3176b179f2e2634c3ce9c1301379a6b8c9c9aeecd481da494f",
-                "sha256:c84132a54c750fda57729d1e2599bb598f5fa0344085dbde5003ba429a4798c0",
-                "sha256:cb7b2ab0188829593b9de646545175547a70d9a6e2b63bf2cd87a0a391599324",
-                "sha256:cca4def576f47a09a943666b8f829606bcb17e2bc2d5911a46c8f8da45f56755",
-                "sha256:cf6511efa4801b9b38dc5546d7547d5b5c6ef4b081c60b23e4d941d0eba9cbeb",
-                "sha256:d16fd5252f883eb074ca55cb622bc0bee49b979ae4e8639fff6ca3ff44f9f854",
-                "sha256:d2686f91611f9e17f4548dbf050e75b079bbc2a82be565832bc8ea9047b61c8c",
-                "sha256:d7fc3fca01da18fbabe4625d64bb612b533533ed10045a2ac3dd194bfa656b60",
-                "sha256:dd5653e67b149503c68c4018bf07e42eeed6b4e956b24c00ccdf93ac79cdff84",
-                "sha256:de5695a6f1d8340b12a5d6d4484290ee74d61e467c39ff03b39e30df62cf83a0",
-                "sha256:e0ac8959c929593fee38da1c2b64ee9778733cdf03c482c9ff1d508b6b593b2b",
-                "sha256:e1b25e3ad6c909f398df8921780d6a3d120d8c09466720226fc621605b6f92b1",
-                "sha256:e633940f28c1e913615fd624fcdd72fdba807bf53ea6925d6a588e84e1151531",
-                "sha256:e89df2958e5159b811af9ff0f92614dabf4ff617c03a4c1c6ff53bf1c399e0e1",
-                "sha256:ea9f9c6034ea2d93d9147818f17c2a0860d41b71c38b9ce4d55f21b6f9165a11",
-                "sha256:f645caaf0008bacf349875a974220f1f1da349c5dbe7c4ec93048cdc785a3326",
-                "sha256:f8303414c7b03f794347ad062c0516cee0e15f7a612abd0ce1e25caf6ceb47df",
-                "sha256:fca62a8301b605b954ad2e9c3666f9d97f63872aa4efcae5492baca2056b74ab"
-            ],
-            "markers": "python_full_version >= '3.7.0'",
-            "version": "==3.1.0"
-        },
-        "click": {
-            "hashes": [
-                "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e",
-                "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==8.1.3"
-        },
-        "cloudpickle": {
-            "hashes": [
-                "sha256:61f594d1f4c295fa5cd9014ceb3a1fc4a70b0de1164b94fbc2d854ccba056f9f",
-                "sha256:d89684b8de9e34a2a43b3460fbca07d09d6e25ce858df4d5a44240403b6178f5"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2.2.1"
-        },
-        "deprecated": {
-            "hashes": [
-                "sha256:43ac5335da90c31c24ba028af536a91d41d53f9e6901ddb021bcc572ce44e38d",
-                "sha256:64756e3e14c8c5eea9795d93c524551432a0be75629f8f29e67ab8caf076c76d"
-            ],
-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
-            "version": "==1.2.13"
-        },
-        "docstring-parser": {
-            "hashes": [
-                "sha256:48ddc093e8b1865899956fcc03b03e66bb7240c310fac5af81814580c55bf682",
-                "sha256:d1679b86250d269d06a99670924d6bce45adc00b08069dae8c47d98e89b667a9"
-            ],
-            "markers": "python_version >= '3.6' and python_version < '4.0'",
-            "version": "==0.15"
-        },
-        "fire": {
-            "hashes": [
-                "sha256:a6b0d49e98c8963910021f92bba66f65ab440da2982b78eb1bbf95a0a34aacc6"
-            ],
-            "version": "==0.5.0"
-        },
-        "google-api-core": {
-            "extras": [
-                "grpc"
-            ],
-            "hashes": [
-                "sha256:4b9bb5d5a380a0befa0573b302651b8a9a89262c1730e37bf423cec511804c22",
-                "sha256:ce222e27b0de0d7bc63eb043b956996d6dccab14cc3b690aaea91c9cc99dc16e"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==2.11.0"
-        },
-        "google-api-python-client": {
-            "hashes": [
-                "sha256:1b4bd42a46321e13c0542a9e4d96fa05d73626f07b39f83a73a947d70ca706a9",
-                "sha256:7e0a1a265c8d3088ee1987778c72683fcb376e32bada8d7767162bd9c503fd9b"
-            ],
-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
-            "version": "==1.12.11"
-        },
-        "google-auth": {
-            "hashes": [
-                "sha256:ce311e2bc58b130fddf316df57c9b3943c2a7b4f6ec31de9663a9333e4064efc",
-                "sha256:f586b274d3eb7bd932ea424b1c702a30e0393a2e2bc4ca3eae8263ffd8be229f"
-            ],
-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'",
-            "version": "==2.17.3"
-        },
-        "google-auth-httplib2": {
-            "hashes": [
-                "sha256:31e49c36c6b5643b57e82617cb3e021e3e1d2df9da63af67252c02fa9c1f4a10",
-                "sha256:a07c39fd632becacd3f07718dfd6021bf396978f03ad3ce4321d060015cc30ac"
-            ],
-            "version": "==0.1.0"
-        },
-        "google-cloud-aiplatform": {
-            "hashes": [
-                "sha256:0ce9e97bf5c977397e52b3b7c4dc78610c135fbde11a60a6c0b77a4fdf776400",
-                "sha256:942765a6bad97e46e262dd6599dc5f171663ce952130e0b0b2eb97e0b1b98bfd"
-            ],
-            "index": "pypi",
-            "version": "==1.24.1"
-        },
-        "google-cloud-bigquery": {
-            "hashes": [
-                "sha256:4b02def076e2db8cec66f65fb627d13904a9fc3cf4fee315ede43dcb7038a8df",
-                "sha256:848a3cbce0ba7d4f1e9551400a7c99aa0eab72290d5a1bbbe69f18a24a10bd3a"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==3.10.0"
-        },
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diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
new file mode 100644
index 00000000..3c0c989a
--- /dev/null
+++ b/pipelines/poetry.lock
@@ -0,0 +1,1845 @@
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+    {file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"},
+    {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
+]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.9"
+content-hash = "61dd42065ded5aa173586b15285aee373d40d89710fff18ae49e546999a29156"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index a5e2cbb7..871e114b 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -1,30 +1,28 @@
-[project]
+[tool.poetry]
 name = "turbo-template"
-authors = [
-    {name = "Example User", email = "user@example.com"},
-]
-description = "Turbo Template"
+version = "0.1.0"
+authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
+description = "Turbo Template developed at Datatonic"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.7",
-]
-requires-python = ">=3.7"
-dynamic = ["version"]
-dependencies = [
-    "kfp == 1.8.21",
+    "Programming Language :: Python :: 3.9",
 ]
 
-[project.optional-dependencies]
-tests = [
-    "google-cloud-bigquery == 2.30.0",
-    "pytest >= 7.3.1,<8.0.0",
-]
+[tool.poetry.dependencies]
+python = "^3.9"
+Jinja2 = ">=3.0.1,<4.0.0"
+google-cloud-aiplatform = "1.24.1"
+google-cloud-pipeline-components = "1.0.42"
+
+[tool.poetry.group.dev.dependencies]
+pytest = ">=7.3.1,<8.0.0"
+pre-commit = ">=2.14.1,<3.0.0"
 
 [build-system]
-requires = ["setuptools", "wheel"]
-build-backend = "setuptools.build_meta:__legacy__"
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
 
 [tool.flake8]
 max-line-length = 88
@@ -43,3 +41,4 @@ pythonpath = [
 ]
 testpaths = "tests"
 junit_family = "xunit2"
+
diff --git a/poetry.lock b/poetry.lock
new file mode 100644
index 00000000..c807fdc1
--- /dev/null
+++ b/poetry.lock
@@ -0,0 +1,1845 @@
+# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
+
+[[package]]
+name = "absl-py"
+version = "1.4.0"
+description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "absl-py-1.4.0.tar.gz", hash = "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"},
+    {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"},
+]
+
+[[package]]
+name = "attrs"
+version = "23.1.0"
+description = "Classes Without Boilerplate"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
+    {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
+]
+
+[package.extras]
+cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
+dev = ["attrs[docs,tests]", "pre-commit"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
+tests = ["attrs[tests-no-zope]", "zope-interface"]
+tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+
+[[package]]
+name = "cachetools"
+version = "5.3.0"
+description = "Extensible memoizing collections and decorators"
+category = "main"
+optional = false
+python-versions = "~=3.7"
+files = [
+    {file = "cachetools-5.3.0-py3-none-any.whl", hash = "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"},
+    {file = "cachetools-5.3.0.tar.gz", hash = "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14"},
+]
+
+[[package]]
+name = "certifi"
+version = "2023.5.7"
+description = "Python package for providing Mozilla's CA Bundle."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "certifi-2023.5.7-py3-none-any.whl", hash = "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"},
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+]
+
+[[package]]
+name = "cfgv"
+version = "3.3.1"
+description = "Validate configuration and produce human readable error messages."
+category = "dev"
+optional = false
+python-versions = ">=3.6.1"
+files = [
+    {file = "cfgv-3.3.1-py2.py3-none-any.whl", hash = "sha256:c6a0883f3917a037485059700b9e75da2464e6c27051014ad85ba6aaa5884426"},
+    {file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"},
+]
+
+[[package]]
+name = "charset-normalizer"
+version = "3.1.0"
+description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+category = "main"
+optional = false
+python-versions = ">=3.7.0"
+files = [
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+]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.9"
+content-hash = "184c13a1c78e0965c5b30675e7eb3b28ac7a39f537b1e551402348108b922376"
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 00000000..3656a839
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,26 @@
+[tool.poetry]
+name = "turbo-template"
+version = "0.1.0"
+description = "Turbo Template developed at Datatonic"
+authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
+
+[tool.poetry.dependencies]
+python = "^3.9"
+Jinja2 = ">=3.0.1,<4.0.0"
+google-cloud-aiplatform = "1.24.1"
+google-cloud-pipeline-components = "1.0.42"
+kfp = "1.8.21"
+
+[tool.poetry.group.dev.dependencies]
+pytest = ">=7.3.1,<8.0.0"
+pre-commit = ">=2.14.1,<3.0.0"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"
+
+[tool.pytest.ini_options]
+pythonpath = [
+  ".",
+]
+

From 432f7dbe687e1287917980cb33fe43ee49499056 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 16 May 2023 11:45:40 +0100
Subject: [PATCH 011/238] refactor(pyproject.toml): remove pyproject.toml from
 root of repo

---
 poetry.lock    | 1845 ------------------------------------------------
 pyproject.toml |   26 -
 2 files changed, 1871 deletions(-)
 delete mode 100644 poetry.lock
 delete mode 100644 pyproject.toml

diff --git a/poetry.lock b/poetry.lock
deleted file mode 100644
index c807fdc1..00000000
--- a/poetry.lock
+++ /dev/null
@@ -1,1845 +0,0 @@
-# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
-
-[[package]]
-name = "absl-py"
-version = "1.4.0"
-description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "absl-py-1.4.0.tar.gz", hash = "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"},
-    {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"},
-]
-
-[[package]]
-name = "attrs"
-version = "23.1.0"
-description = "Classes Without Boilerplate"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
-    {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
-]
-
-[package.extras]
-cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
-tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
-
-[[package]]
-name = "cachetools"
-version = "5.3.0"
-description = "Extensible memoizing collections and decorators"
-category = "main"
-optional = false
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-    {file = "wrapt-1.15.0-py3-none-any.whl", hash = "sha256:64b1df0f83706b4ef4cfb4fb0e4c2669100fd7ecacfb59e091fad300d4e04640"},
-    {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
-]
-
-[metadata]
-lock-version = "2.0"
-python-versions = "^3.9"
-content-hash = "184c13a1c78e0965c5b30675e7eb3b28ac7a39f537b1e551402348108b922376"
diff --git a/pyproject.toml b/pyproject.toml
deleted file mode 100644
index 3656a839..00000000
--- a/pyproject.toml
+++ /dev/null
@@ -1,26 +0,0 @@
-[tool.poetry]
-name = "turbo-template"
-version = "0.1.0"
-description = "Turbo Template developed at Datatonic"
-authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
-
-[tool.poetry.dependencies]
-python = "^3.9"
-Jinja2 = ">=3.0.1,<4.0.0"
-google-cloud-aiplatform = "1.24.1"
-google-cloud-pipeline-components = "1.0.42"
-kfp = "1.8.21"
-
-[tool.poetry.group.dev.dependencies]
-pytest = ">=7.3.1,<8.0.0"
-pre-commit = ">=2.14.1,<3.0.0"
-
-[build-system]
-requires = ["poetry-core>=1.0.0"]
-build-backend = "poetry.core.masonry.api"
-
-[tool.pytest.ini_options]
-pythonpath = [
-  ".",
-]
-

From bd5b47101c9e70f4a8d5d71450be3949d75c0033 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 16 May 2023 11:47:01 +0100
Subject: [PATCH 012/238] refactor(pyproject.toml): rename to pipelines

---
 pipelines/pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 871e114b..7e288fd9 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -1,5 +1,5 @@
 [tool.poetry]
-name = "turbo-template"
+name = "pipelines"
 version = "0.1.0"
 authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
 description = "Turbo Template developed at Datatonic"

From 751a6eab41ecb868db2ee365e3e7e8effb23450e Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 16 May 2023 11:55:14 +0100
Subject: [PATCH 013/238] refactor(pyproject.toml): update author and
 description

---
 components/bigquery-components/pyproject.toml | 6 ++++--
 components/vertex-components/pyproject.toml   | 6 ++++--
 pipelines/pyproject.toml                      | 4 +++-
 3 files changed, 11 insertions(+), 5 deletions(-)

diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index 083448b2..3a51450a 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -1,8 +1,10 @@
 [tool.poetry]
 name = "bigquery-components"
 version = "0.1.0"
-authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
-description = "BigQuery components created by Datatonic"
+authors = [
+    {name = "Example User", email = "user@example.com"},
+]
+description = "Bigquery components for vertex pipelines"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index 9011c442..6ba44118 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -1,8 +1,10 @@
 [tool.poetry]
 name = "vertex-components"
 version = "0.1.0"
-authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
-description = "Vertex AI components made by Datatonic"
+authors = [
+    {name = "Example User", email = "user@example.com"},
+]
+description = "Vertex components for training and prediction using the Chicago Taxi Dataset"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 7e288fd9..b1784b94 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -1,7 +1,9 @@
 [tool.poetry]
 name = "pipelines"
 version = "0.1.0"
-authors = ["roberta nwokonko <roberta.nwokonko@datatonic.com>"]
+authors = [
+    {name = "Example User", email = "user@example.com"},
+]
 description = "Turbo Template developed at Datatonic"
 readme = "README.md"
 classifiers = [

From 43817e5403b01c1f16ec56af8988331d05a9eee5 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 16 May 2023 11:58:41 +0100
Subject: [PATCH 014/238] build(cloudbuild-files): update the CI/CD pipelines
 in the cloudbuild directory to use a python:3.9 image

---
 cloudbuild/e2e-test.yaml      | 2 +-
 cloudbuild/pr-checks.yaml     | 2 +-
 cloudbuild/release.yaml       | 2 +-
 cloudbuild/trigger-tests.yaml | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 3aa9a513..82554d8e 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -30,7 +30,7 @@ steps:
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 5e132a7a..4a8f92cb 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -17,7 +17,7 @@ steps:
   # Install pipenv and deps, run pre-commit and unit tests
   # Then compile pipelines (to make sure they can compile)
   # need to run "git init" for pre-commit checks to work
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 63e60115..d09f451d 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -15,7 +15,7 @@
 steps:
 
   # Install pipenv, install deps, compile pipelines
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/trigger-tests.yaml b/cloudbuild/trigger-tests.yaml
index a3387438..295e2c50 100644
--- a/cloudbuild/trigger-tests.yaml
+++ b/cloudbuild/trigger-tests.yaml
@@ -13,7 +13,7 @@
 # limitations under the License.
 ---
 steps:
-  - name: 'python:3.7'
+  - name: 'python:3.9'
     args:
       - '-c'
       - |

From 0cfb1edb840503c80b34c80ab28c2fe8c3077682 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Wed, 17 May 2023 13:04:13 +0100
Subject: [PATCH 015/238] refactor(cloudbuild): adjust python version

---
 cloudbuild/e2e-test.yaml  | 2 +-
 cloudbuild/pr-checks.yaml | 2 +-
 cloudbuild/release.yaml   | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 82554d8e..3aa9a513 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -30,7 +30,7 @@ steps:
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
-  - name: python:3.9
+  - name: python:3.7
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 4a8f92cb..5e132a7a 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -17,7 +17,7 @@ steps:
   # Install pipenv and deps, run pre-commit and unit tests
   # Then compile pipelines (to make sure they can compile)
   # need to run "git init" for pre-commit checks to work
-  - name: python:3.9
+  - name: python:3.7
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index d09f451d..63e60115 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -15,7 +15,7 @@
 steps:
 
   # Install pipenv, install deps, compile pipelines
-  - name: python:3.9
+  - name: python:3.7
     entrypoint: /bin/sh
     args:
       - -c

From 2f44007ab66e7981048c15094b13d95c48c3ff9d Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Wed, 17 May 2023 14:03:50 +0100
Subject: [PATCH 016/238] build(cloudbuild): update python image from 3.7 to
 3.9

---
 cloudbuild/e2e-test.yaml  | 2 +-
 cloudbuild/pr-checks.yaml | 2 +-
 cloudbuild/release.yaml   | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 3aa9a513..82554d8e 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -30,7 +30,7 @@ steps:
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 5e132a7a..4a8f92cb 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -17,7 +17,7 @@ steps:
   # Install pipenv and deps, run pre-commit and unit tests
   # Then compile pipelines (to make sure they can compile)
   # need to run "git init" for pre-commit checks to work
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 63e60115..d09f451d 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -15,7 +15,7 @@
 steps:
 
   # Install pipenv, install deps, compile pipelines
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c

From 2d62d9f743216dc967df03df02a704bea8ecf03e Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Fri, 12 May 2023 14:52:56 +0200
Subject: [PATCH 017/238] feat: enable multiquery, update queries and pipelines

---
 .../bigquery_components/bq_query_to_table.py  | 20 +--------
 .../tensorflow/prediction/pipeline.py         | 30 +++++++------
 .../tensorflow/prediction/queries/ingest.sql  | 13 +++++-
 .../pipelines/tensorflow/training/pipeline.py | 45 +++++++------------
 .../tensorflow/training/queries/ingest.sql    | 29 ++++++++----
 .../tensorflow/training/queries/sample.sql    | 24 +++-------
 .../pipelines/xgboost/prediction/pipeline.py  | 30 ++++++++-----
 .../xgboost/prediction/queries/ingest.sql     |  9 ++++
 .../pipelines/xgboost/training/pipeline.py    | 44 +++++++-----------
 .../xgboost/training/queries/ingest.sql       | 27 +++++++----
 .../xgboost/training/queries/sample.sql       | 12 +++--
 11 files changed, 145 insertions(+), 138 deletions(-)

diff --git a/components/bigquery-components/src/bigquery_components/bq_query_to_table.py b/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
index 9530bd92..4b6afc29 100644
--- a/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
+++ b/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
@@ -22,25 +22,15 @@
 def bq_query_to_table(
     query: str,
     bq_client_project_id: str,
-    destination_project_id: str,
-    dataset_id: str = None,
-    table_id: str = None,
     dataset_location: str = "EU",
-    query_job_config: dict = None,
 ) -> None:
     """
     Run query & create a new BigQuery table
     Args:
         query (str): SQL query to execute, results are saved in a BigQuery table
         bq_client_project_id (str): project id that will be used by the bq client
-        destination_project_id (str): project id where BQ table will be created
-        dataset_id (str): dataset id where BQ table will be created
-        table_id (str): table name (without project id and dataset id)
         dataset_location (str): bq dataset location
-        query_job_config (dict): dict containing optional parameters
         required by the bq query operation. No need to specify destination param
-        See available parameters here
-        https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.job.QueryJobConfig.html
     Returns:
         None
     """
@@ -50,13 +40,7 @@ def bq_query_to_table(
 
     logging.getLogger().setLevel(logging.INFO)
 
-    if (dataset_id is not None) and (table_id is not None):
-        dest_table_ref = f"{destination_project_id}.{dataset_id}.{table_id}"
-    else:
-        dest_table_ref = None
-    if query_job_config is None:
-        query_job_config = {}
-    job_config = bigquery.QueryJobConfig(destination=dest_table_ref, **query_job_config)
+    job_config = bigquery.QueryJobConfig()
 
     bq_client = bigquery.client.Client(
         project=bq_client_project_id, location=dataset_location
@@ -65,7 +49,7 @@ def bq_query_to_table(
 
     try:
         result = query_job.result()
-        logging.info(f"BQ table {dest_table_ref} created")
+        logging.info(f"BQ Job finished")
     except GoogleCloudError as e:
         logging.error(e)
         logging.error(query_job.error_result)
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index b011b0c1..3a9fdb02 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import os
 import pathlib
 
@@ -29,9 +28,10 @@ def tensorflow_pipeline(
     project_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
     model_name: str = "simple_tensorflow",
-    dataset_id: str = "preprocessing",
+    preprocessing_dataset_id: str = "preprocessing",
     dataset_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_dataset_id: str = "chicago_taxi_trips",
+    prediction_dataset_id: str = "prediction",
     timestamp: str = "2022-12-01 00:00:00",
     batch_prediction_machine_type: str = "n1-standard-4",
     batch_prediction_min_replicas: int = 3,
@@ -49,13 +49,14 @@ def tensorflow_pipeline(
     Args:
         project_id (str): project id of the Google Cloud project
         project_location (str): location of the Google Cloud project
-        pipeline_files_gcs_path (str): GCS path where the pipeline files are located
         ingestion_project_id (str): project id containing the source bigquery data
             for ingestion. This can be the same as `project_id` if the source data is
             in the same project where the ML pipeline is executed.
         model_name (str): name of model
-        model_label (str): label of model
-        dataset_id (str): id of BQ dataset used to store all staging data & predictions
+         preprocessing_dataset_id (str): id of BQ dataset used to
+            store all staging data .
+        prediction_dataset_id (str): id of BQ dataset used to
+            store all predictions.
         dataset_location (str): location of dataset
         ingestion_dataset_id (str): dataset id of ingestion data
         timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
@@ -91,6 +92,10 @@ def tensorflow_pipeline(
         queries_folder / "ingest.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
+        prediction_dataset=f"{ingestion_project_id}.{prediction_dataset_id}",
+        preprocessing_dataset=f"{ingestion_project_id}.{preprocessing_dataset_id}",
+        ingested_table=ingested_table,
+        dataset_region=project_location,
         filter_column=time_column,
         filter_start_value=timestamp,
     )
@@ -98,14 +103,11 @@ def tensorflow_pipeline(
     # data ingestion and preprocessing operations
     kwargs = dict(
         bq_client_project_id=project_id,
-        destination_project_id=project_id,
-        dataset_id=dataset_id,
         dataset_location=dataset_location,
-        query_job_config=json.dumps(dict(write_disposition="WRITE_TRUNCATE")),
     )
-    ingest = bq_query_to_table(
-        query=ingest_query, table_id=ingested_table, **kwargs
-    ).set_display_name("Ingest data")
+    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
+        "Ingest data"
+    )
 
     # lookup champion model
     champion_model = (
@@ -120,8 +122,10 @@ def tensorflow_pipeline(
     )
 
     # batch predict from BigQuery to BigQuery
-    bigquery_source_input_uri = f"bq://{project_id}.{dataset_id}.{ingested_table}"
-    bigquery_destination_output_uri = f"bq://{project_id}.{dataset_id}"
+    bigquery_source_input_uri = (
+        f"bq://{project_id}.{preprocessing_dataset_id}.{ingested_table}"
+    )
+    bigquery_destination_output_uri = f"bq://{project_id}.{prediction_dataset_id}"
     instance_config = {"instanceType": "object"}
 
     # predict data
diff --git a/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
index e01a7c57..5a44d671 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
@@ -14,8 +14,16 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
+CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
+  OPTIONS (
+    description = 'Prediction Dataset',
+    location = "{{ dataset_region }}");
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
 with filter_start_values as (
-    SELECT 
+    SELECT
     IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
@@ -43,7 +51,7 @@ SELECT
     trip_miles,
     CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
                WHEN trip_seconds <= 0 then m.avg_trip_seconds
-               ELSE trip_seconds 
+               ELSE trip_seconds
                END AS FLOAT64) AS trip_seconds,
     payment_type,
     company,
@@ -54,3 +62,4 @@ WHERE
                 "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
+    );
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 2767d210..56aea64c 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import os
 import pathlib
 
@@ -101,6 +100,9 @@ def tensorflow_pipeline(
         queries_folder / "ingest.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        ingested_table=ingested_table,
+        dataset_region=project_location,
         filter_column=time_column,
         target_column=label_column_name,
         filter_start_value=timestamp,
@@ -109,6 +111,8 @@ def tensorflow_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=train_table,
         num_lots=10,
         lots=tuple(range(8)),
     )
@@ -116,6 +120,8 @@ def tensorflow_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=valid_table,
         num_lots=10,
         lots="(8)",
     )
@@ -123,51 +129,34 @@ def tensorflow_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=test_table,
         num_lots=10,
         lots="(9)",
     )
-    data_cleaning_query = generate_query(
-        queries_folder / "engineer_features.sql",
-        source_dataset=dataset_id,
-        source_table=train_table,
-    )
 
     # data ingestion and preprocessing operations
 
-    kwargs = dict(
-        bq_client_project_id=project_id,
-        destination_project_id=project_id,
-        dataset_id=dataset_id,
-        dataset_location=dataset_location,
-        query_job_config=json.dumps(dict(write_disposition="WRITE_TRUNCATE")),
+    kwargs = dict(bq_client_project_id=project_id, dataset_location=dataset_location)
+    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
+        "Ingest data"
     )
-    ingest = bq_query_to_table(
-        query=ingest_query, table_id=ingested_table, **kwargs
-    ).set_display_name("Ingest data")
 
-    # exporting data to GCS from BQ
     split_train_data = (
-        bq_query_to_table(query=split_train_query, table_id=train_table, **kwargs)
+        bq_query_to_table(query=split_train_query, **kwargs)
         .after(ingest)
         .set_display_name("Split train data")
     )
     split_valid_data = (
-        bq_query_to_table(query=split_valid_query, table_id=valid_table, **kwargs)
+        bq_query_to_table(query=split_valid_query, **kwargs)
         .after(ingest)
         .set_display_name("Split validation data")
     )
     split_test_data = (
-        bq_query_to_table(query=split_test_query, table_id=test_table, **kwargs)
+        bq_query_to_table(query=split_test_query, **kwargs)
         .after(ingest)
         .set_display_name("Split test data")
     )
-    data_cleaning = (
-        bq_query_to_table(
-            query=data_cleaning_query, table_id=preprocessed_table, **kwargs
-        )
-        .after(split_train_data)
-        .set_display_name("Clean data")
-    )
 
     # data extraction to gcs
 
@@ -176,10 +165,10 @@ def tensorflow_pipeline(
             bq_client_project_id=project_id,
             source_project_id=project_id,
             dataset_id=dataset_id,
-            table_name=preprocessed_table,
+            table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(data_cleaning)
+        .after(split_train_data)
         .set_display_name("Extract train data to storage")
     ).outputs["dataset"]
     valid_dataset = (
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
index de9459fc..7f9f3b0b 100644
--- a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
@@ -14,26 +14,36 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
-with filter_start_values as (
-    SELECT 
-    IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
+
+CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
+  OPTIONS (
+    description = 'Preprocessing Dataset',
+    location = "{{ dataset_region }}");
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
+WITH filter_start_values AS (
+SELECT
+	IF("{{ filter_start_value }}" = '',
+	CURRENT_DATETIME(),
+	CAST("{{ filter_start_value }}" AS DATETIME)) AS filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
-,filtered_data as (
+,filtered_data AS (
     SELECT
     *
     FROM `{{ source_dataset }}.{{ source_table }}`, filter_start_values
     WHERE
          DATE({{ filter_column }}) BETWEEN
-         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value as DATETIME)), INTERVAL 3 MONTH) AND
+         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value AS DATETIME)), INTERVAL 3 MONTH) AND
          DATE_SUB(DATE(filter_start_value), INTERVAL 2 MONTH)
 )
 -- Use the average trip_seconds as a replacement for NULL or 0 values
-,mean_time as (
+,mean_time AS (
     SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
     FROM filtered_data
 )
-
 SELECT
     CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
     CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
@@ -43,15 +53,16 @@ SELECT
     trip_miles,
     CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
                WHEN trip_seconds <= 0 then m.avg_trip_seconds
-               ELSE trip_seconds 
+               ELSE trip_seconds
                END AS FLOAT64) AS trip_seconds,
     payment_type,
     company,
     (fare + tips + tolls + extras) AS `{{ target_column }}`,
-FROM filtered_data as t, mean_time as m
+FROM filtered_data AS t, mean_time AS m
 WHERE
     trip_miles > 0 AND fare > 0 AND fare < 1500
     {% for field in ["fare", "trip_start_timestamp", "pickup_longitude",
                 "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
+);
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/sample.sql b/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
index bf47bbf6..be8458be 100644
--- a/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
+++ b/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
@@ -1,20 +1,10 @@
--- Copyright 2022 Google LLC
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ target_table }}`;
 
--- Licensed under the Apache License, Version 2.0 (the "License");
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
-SELECT *
+CREATE TABLE `{{ preprocessing_dataset }}.{{ target_table }}` AS (
+SELECT
+	*
 FROM
- `{{ source_dataset }}.{{ source_table }}` AS t
+	`{{ source_dataset }}.{{ source_table }}` AS t
 WHERE
-    MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-        {{ num_lots }}) IN {{ lots }}
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	{{ num_lots }}) IN {{ lots }});
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index ed474eb8..0c4504ec 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import os
 import pathlib
 
@@ -29,9 +28,10 @@ def xgboost_pipeline(
     project_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
     model_name: str = "simple_xgboost",
-    dataset_id: str = "preprocessing",
+    preprocessing_dataset_id: str = "preprocessing",
     dataset_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_dataset_id: str = "chicago_taxi_trips",
+    prediction_dataset_id: str = "prediction",
     timestamp: str = "2022-12-01 00:00:00",
     batch_prediction_machine_type: str = "n1-standard-4",
     batch_prediction_min_replicas: int = 3,
@@ -50,14 +50,17 @@ def xgboost_pipeline(
             for ingestion. This can be the same as `project_id` if the source data is
             in the same project where the ML pipeline is executed.
         model_name (str): name of model
-        dataset_id (str): id of BQ dataset used to store all staging data & predictions
+        preprocessing_dataset_id (str): id of BQ dataset used to
+            store all staging data .
+        prediction_dataset_id (str): id of BQ dataset used to
+            store all predictions.
         dataset_location (str): location of dataset
         ingestion_dataset_id (str): dataset id of ingestion data
         timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
             (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
             If any time part is missing, it will be regarded as zero.
         batch_prediction_machine_type (str): Machine type to be used for Vertex Batch
-            Prediction. Example machine_types - n1-standard-4, n1-standard-16 etc
+            Prediction. Example machine_types - n1-standard-4, n1-standard-16 etc.
         batch_prediction_min_replicas (int): Minimum no of machines to distribute the
             Vertex Batch Prediction job for horizontal scalability
         batch_prediction_max_replicas (int): Maximum no of machines to distribute the
@@ -85,6 +88,10 @@ def xgboost_pipeline(
         queries_folder / "ingest.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
+        prediction_dataset=f"{ingestion_project_id}.{prediction_dataset_id}",
+        preprocessing_dataset=f"{ingestion_project_id}.{preprocessing_dataset_id}",
+        ingested_table=ingested_table,
+        dataset_region=project_location,
         filter_column=time_column,
         filter_start_value=timestamp,
     )
@@ -92,14 +99,11 @@ def xgboost_pipeline(
     # data ingestion and preprocessing operations
     kwargs = dict(
         bq_client_project_id=project_id,
-        destination_project_id=project_id,
-        dataset_id=dataset_id,
         dataset_location=dataset_location,
-        query_job_config=json.dumps(dict(write_disposition="WRITE_TRUNCATE")),
     )
-    ingest = bq_query_to_table(
-        query=ingest_query, table_id=ingested_table, **kwargs
-    ).set_display_name("Ingest data")
+    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
+        "Ingest data"
+    )
 
     # lookup champion model
     champion_model = (
@@ -114,8 +118,10 @@ def xgboost_pipeline(
     )
 
     # batch predict from BigQuery to BigQuery
-    bigquery_source_input_uri = f"bq://{project_id}.{dataset_id}.{ingested_table}"
-    bigquery_destination_output_uri = f"bq://{project_id}.{dataset_id}"
+    bigquery_source_input_uri = (
+        f"bq://{project_id}.{preprocessing_dataset_id}.{ingested_table}"
+    )
+    bigquery_destination_output_uri = f"bq://{project_id}.{prediction_dataset_id}"
 
     batch_prediction = (
         model_batch_predict(
diff --git a/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql b/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
index e01a7c57..bf8fe57a 100644
--- a/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
@@ -14,6 +14,14 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
+CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
+  OPTIONS (
+    description = 'Prediction Dataset',
+    location = "{{ dataset_region }}");
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
 with filter_start_values as (
     SELECT 
     IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
@@ -54,3 +62,4 @@ WHERE
                 "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
+    );
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 27cb47ed..6c9ad9d9 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 import os
 import pathlib
 
@@ -99,6 +98,9 @@ def xgboost_pipeline(
         queries_folder / "ingest.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        ingested_table=ingested_table,
+        dataset_region=project_location,
         filter_column=time_column,
         target_column=label_column_name,
         filter_start_value=timestamp,
@@ -107,6 +109,8 @@ def xgboost_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=train_table,
         num_lots=10,
         lots=tuple(range(8)),
     )
@@ -114,57 +118,43 @@ def xgboost_pipeline(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=valid_table,
         num_lots=10,
         lots="(8)",
     )
-    data_cleaning_query = generate_query(
-        queries_folder / "engineer_features.sql",
-        source_dataset=dataset_id,
-        source_table=train_table,
-    )
     split_test_query = generate_query(
         queries_folder / "sample.sql",
         source_dataset=dataset_id,
         source_table=ingested_table,
+        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
+        target_table=test_table,
         num_lots=10,
         lots="(9)",
     )
 
     # data ingestion and preprocessing operations
 
-    kwargs = dict(
-        bq_client_project_id=project_id,
-        destination_project_id=project_id,
-        dataset_id=dataset_id,
-        dataset_location=dataset_location,
-        query_job_config=json.dumps(dict(write_disposition="WRITE_TRUNCATE")),
+    kwargs = dict(bq_client_project_id=project_id, dataset_location=dataset_location)
+    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
+        "Ingest data"
     )
-    ingest = bq_query_to_table(
-        query=ingest_query, table_id=ingested_table, **kwargs
-    ).set_display_name("Ingest data")
 
     split_train_data = (
-        bq_query_to_table(query=split_train_query, table_id=train_table, **kwargs)
+        bq_query_to_table(query=split_train_query, **kwargs)
         .after(ingest)
         .set_display_name("Split train data")
     )
     split_valid_data = (
-        bq_query_to_table(query=split_valid_query, table_id=valid_table, **kwargs)
+        bq_query_to_table(query=split_valid_query, **kwargs)
         .after(ingest)
         .set_display_name("Split validation data")
     )
     split_test_data = (
-        bq_query_to_table(query=split_test_query, table_id=test_table, **kwargs)
+        bq_query_to_table(query=split_test_query, **kwargs)
         .after(ingest)
         .set_display_name("Split test data")
     )
-    data_cleaning = (
-        bq_query_to_table(
-            query=data_cleaning_query, table_id=preprocessed_table, **kwargs
-        )
-        .after(split_train_data)
-        .set_display_name("Clean data")
-    )
 
     # data extraction to gcs
 
@@ -173,10 +163,10 @@ def xgboost_pipeline(
             bq_client_project_id=project_id,
             source_project_id=project_id,
             dataset_id=dataset_id,
-            table_name=preprocessed_table,
+            table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(data_cleaning)
+        .after(split_train_data)
         .set_display_name("Extract train data to storage")
     ).outputs["dataset"]
     valid_dataset = (
diff --git a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql b/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
index de9459fc..fbb6df32 100644
--- a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
@@ -14,26 +14,36 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
-with filter_start_values as (
-    SELECT 
-    IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
+
+CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
+  OPTIONS (
+    description = 'Preprocessing Dataset',
+    location = "{{ dataset_region }}");
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
+WITH filter_start_values AS (
+SELECT
+	IF("{{ filter_start_value }}" = '',
+	CURRENT_DATETIME(),
+	CAST("{{ filter_start_value }}" AS DATETIME)) AS filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
-,filtered_data as (
+,filtered_data AS (
     SELECT
     *
     FROM `{{ source_dataset }}.{{ source_table }}`, filter_start_values
     WHERE
          DATE({{ filter_column }}) BETWEEN
-         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value as DATETIME)), INTERVAL 3 MONTH) AND
+         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value AS DATETIME)), INTERVAL 3 MONTH) AND
          DATE_SUB(DATE(filter_start_value), INTERVAL 2 MONTH)
 )
 -- Use the average trip_seconds as a replacement for NULL or 0 values
-,mean_time as (
+,mean_time AS (
     SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
     FROM filtered_data
 )
-
 SELECT
     CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
     CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
@@ -48,10 +58,11 @@ SELECT
     payment_type,
     company,
     (fare + tips + tolls + extras) AS `{{ target_column }}`,
-FROM filtered_data as t, mean_time as m
+FROM filtered_data AS t, mean_time AS m
 WHERE
     trip_miles > 0 AND fare > 0 AND fare < 1500
     {% for field in ["fare", "trip_start_timestamp", "pickup_longitude",
                 "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
+);
diff --git a/pipelines/src/pipelines/xgboost/training/queries/sample.sql b/pipelines/src/pipelines/xgboost/training/queries/sample.sql
index bb2dc9ce..be8458be 100644
--- a/pipelines/src/pipelines/xgboost/training/queries/sample.sql
+++ b/pipelines/src/pipelines/xgboost/training/queries/sample.sql
@@ -1,6 +1,10 @@
-SELECT *
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ target_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ target_table }}` AS (
+SELECT
+	*
 FROM
- `{{ source_dataset }}.{{ source_table }}` AS t
+	`{{ source_dataset }}.{{ source_table }}` AS t
 WHERE
-    MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-        {{ num_lots }}) IN {{ lots }}
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	{{ num_lots }}) IN {{ lots }});

From 299f834cedb6e6da3862a29f52d7abd44032c175 Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Tue, 16 May 2023 13:53:18 +0200
Subject: [PATCH 018/238] refactor: replace custom BQ component with
 BigqueryQueryJobOp

---
 .../src/bigquery_components/__init__.py       |  2 -
 .../bigquery_components/bq_query_to_table.py  | 57 ----------------
 pipelines/src/pipelines/__init__.py           |  8 ++-
 .../tensorflow/prediction/pipeline.py         | 12 ++--
 .../pipelines/tensorflow/training/pipeline.py | 66 ++++---------------
 .../training/queries/engineer_features.sql    | 18 -----
 .../tensorflow/training/queries/ingest.sql    | 50 +++++++++-----
 .../tensorflow/training/queries/sample.sql    | 10 ---
 .../pipelines/xgboost/prediction/pipeline.py  | 13 ++--
 .../pipelines/xgboost/training/pipeline.py    | 66 ++++---------------
 .../training/queries/engineer_features.sql    |  4 --
 .../xgboost/training/queries/ingest.sql       | 50 +++++++++-----
 .../xgboost/training/queries/sample.sql       | 10 ---
 13 files changed, 107 insertions(+), 259 deletions(-)
 delete mode 100644 components/bigquery-components/src/bigquery_components/bq_query_to_table.py
 delete mode 100644 pipelines/src/pipelines/tensorflow/training/queries/engineer_features.sql
 delete mode 100644 pipelines/src/pipelines/tensorflow/training/queries/sample.sql
 delete mode 100644 pipelines/src/pipelines/xgboost/training/queries/engineer_features.sql
 delete mode 100644 pipelines/src/pipelines/xgboost/training/queries/sample.sql

diff --git a/components/bigquery-components/src/bigquery_components/__init__.py b/components/bigquery-components/src/bigquery_components/__init__.py
index 2e3870ac..e979abab 100644
--- a/components/bigquery-components/src/bigquery_components/__init__.py
+++ b/components/bigquery-components/src/bigquery_components/__init__.py
@@ -1,9 +1,7 @@
-from .bq_query_to_table import bq_query_to_table
 from .extract_bq_to_dataset import extract_bq_to_dataset
 
 
 __version__ = "0.0.1"
 __all__ = [
-    "bq_query_to_table",
     "extract_bq_to_dataset",
 ]
diff --git a/components/bigquery-components/src/bigquery_components/bq_query_to_table.py b/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
deleted file mode 100644
index 4b6afc29..00000000
--- a/components/bigquery-components/src/bigquery_components/bq_query_to_table.py
+++ /dev/null
@@ -1,57 +0,0 @@
-# Copyright 2022 Google LLC
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from kfp.v2.dsl import component
-
-
-@component(
-    base_image="python:3.7",
-    packages_to_install=["google-cloud-bigquery==2.30.0"],
-)
-def bq_query_to_table(
-    query: str,
-    bq_client_project_id: str,
-    dataset_location: str = "EU",
-) -> None:
-    """
-    Run query & create a new BigQuery table
-    Args:
-        query (str): SQL query to execute, results are saved in a BigQuery table
-        bq_client_project_id (str): project id that will be used by the bq client
-        dataset_location (str): bq dataset location
-        required by the bq query operation. No need to specify destination param
-    Returns:
-        None
-    """
-    from google.cloud.exceptions import GoogleCloudError
-    from google.cloud import bigquery
-    import logging
-
-    logging.getLogger().setLevel(logging.INFO)
-
-    job_config = bigquery.QueryJobConfig()
-
-    bq_client = bigquery.client.Client(
-        project=bq_client_project_id, location=dataset_location
-    )
-    query_job = bq_client.query(query, job_config=job_config)
-
-    try:
-        result = query_job.result()
-        logging.info(f"BQ Job finished")
-    except GoogleCloudError as e:
-        logging.error(e)
-        logging.error(query_job.error_result)
-        logging.error(query_job.errors)
-        raise e
diff --git a/pipelines/src/pipelines/__init__.py b/pipelines/src/pipelines/__init__.py
index 113da917..badd535e 100644
--- a/pipelines/src/pipelines/__init__.py
+++ b/pipelines/src/pipelines/__init__.py
@@ -30,4 +30,10 @@ def generate_query(input_file: Path, **replacements) -> str:
     with open(input_file, "r") as f:
         query_template = f.read()
 
-    return Template(query_template).render(**replacements)
+    # Render the template with the provided replacements
+    query = Template(query_template).render(**replacements)
+
+    # Escape double quotes, newline and tab characters
+    query = query.replace('"', '\\"').replace("\n", "\\n").replace("\t", "\\t")
+
+    return query
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index 3a9fdb02..60ad3b47 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -15,10 +15,10 @@
 import os
 import pathlib
 
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp.v2 import compiler, dsl
 
 from pipelines import generate_query
-from bigquery_components import bq_query_to_table
 from vertex_components import lookup_model, model_batch_predict
 
 
@@ -101,13 +101,9 @@ def tensorflow_pipeline(
     )
 
     # data ingestion and preprocessing operations
-    kwargs = dict(
-        bq_client_project_id=project_id,
-        dataset_location=dataset_location,
-    )
-    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
-        "Ingest data"
-    )
+    ingest = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=ingest_query
+    ).set_display_name("Ingest data")
 
     # lookup champion model
     champion_model = (
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 56aea64c..ba98bea1 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -15,9 +15,10 @@
 import os
 import pathlib
 
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp.v2 import compiler, dsl
 from pipelines import generate_query
-from bigquery_components import bq_query_to_table, extract_bq_to_dataset
+from bigquery_components import extract_bq_to_dataset
 from vertex_components import (
     lookup_model,
     custom_train_job,
@@ -106,57 +107,14 @@ def tensorflow_pipeline(
         filter_column=time_column,
         target_column=label_column_name,
         filter_start_value=timestamp,
+        train_table=train_table,
+        validation_table=valid_table,
+        test_table=test_table,
     )
-    split_train_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=train_table,
-        num_lots=10,
-        lots=tuple(range(8)),
-    )
-    split_valid_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=valid_table,
-        num_lots=10,
-        lots="(8)",
-    )
-    split_test_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=test_table,
-        num_lots=10,
-        lots="(9)",
-    )
-
-    # data ingestion and preprocessing operations
 
-    kwargs = dict(bq_client_project_id=project_id, dataset_location=dataset_location)
-    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
-        "Ingest data"
-    )
-
-    split_train_data = (
-        bq_query_to_table(query=split_train_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split train data")
-    )
-    split_valid_data = (
-        bq_query_to_table(query=split_valid_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split validation data")
-    )
-    split_test_data = (
-        bq_query_to_table(query=split_test_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split test data")
-    )
+    ingest = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=ingest_query
+    ).set_display_name("Ingest data")
 
     # data extraction to gcs
 
@@ -168,8 +126,9 @@ def tensorflow_pipeline(
             table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(split_train_data)
+        .after(ingest)
         .set_display_name("Extract train data to storage")
+        .set_caching_options(False)
     ).outputs["dataset"]
     valid_dataset = (
         extract_bq_to_dataset(
@@ -179,8 +138,9 @@ def tensorflow_pipeline(
             table_name=valid_table,
             dataset_location=dataset_location,
         )
-        .after(split_valid_data)
+        .after(ingest)
         .set_display_name("Extract validation data to storage")
+        .set_caching_options(False)
     ).outputs["dataset"]
     test_dataset = (
         extract_bq_to_dataset(
@@ -191,7 +151,7 @@ def tensorflow_pipeline(
             dataset_location=dataset_location,
             destination_gcs_uri=test_dataset_uri,
         )
-        .after(split_test_data)
+        .after(ingest)
         .set_display_name("Extract test data to storage")
         .set_caching_options(False)
     ).outputs["dataset"]
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/engineer_features.sql b/pipelines/src/pipelines/tensorflow/training/queries/engineer_features.sql
deleted file mode 100644
index b8094a35..00000000
--- a/pipelines/src/pipelines/tensorflow/training/queries/engineer_features.sql
+++ /dev/null
@@ -1,18 +0,0 @@
--- Copyright 2022 Google LLC
-
--- Licensed under the Apache License, Version 2.0 (the "License");
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
-/* The Purpose of this query is to clean the data before the training*/
-SELECT
- *
-FROM `{{ source_dataset }}.{{ source_table }}`
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
index 7f9f3b0b..b3a31606 100644
--- a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
@@ -1,20 +1,3 @@
--- Copyright 2022 Google LLC
-
--- Licensed under the Apache License, Version 2.0 (the "License");
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
--- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
--- This allows us to set the filter_start_value to a specific time for testing or for backfill
-
 CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
   OPTIONS (
     description = 'Preprocessing Dataset',
@@ -66,3 +49,36 @@ WHERE
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
 );
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ train_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ train_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (0, 1, 2, 3, 4, 5, 6, 7));
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ validation_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ validation_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (8));
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ test_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ test_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (9));
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/sample.sql b/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
deleted file mode 100644
index be8458be..00000000
--- a/pipelines/src/pipelines/tensorflow/training/queries/sample.sql
+++ /dev/null
@@ -1,10 +0,0 @@
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ target_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ target_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ source_dataset }}.{{ source_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	{{ num_lots }}) IN {{ lots }});
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index 0c4504ec..7fdea71c 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -15,10 +15,10 @@
 import os
 import pathlib
 
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp.v2 import compiler, dsl
 
 from pipelines import generate_query
-from bigquery_components import bq_query_to_table
 from vertex_components import lookup_model, model_batch_predict
 
 
@@ -96,14 +96,9 @@ def xgboost_pipeline(
         filter_start_value=timestamp,
     )
 
-    # data ingestion and preprocessing operations
-    kwargs = dict(
-        bq_client_project_id=project_id,
-        dataset_location=dataset_location,
-    )
-    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
-        "Ingest data"
-    )
+    ingest = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=ingest_query
+    ).set_display_name("Ingest data")
 
     # lookup champion model
     champion_model = (
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 6c9ad9d9..385e41ab 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -15,9 +15,10 @@
 import os
 import pathlib
 
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp.v2 import compiler, dsl
 from pipelines import generate_query
-from bigquery_components import bq_query_to_table, extract_bq_to_dataset
+from bigquery_components import extract_bq_to_dataset
 from vertex_components import (
     lookup_model,
     custom_train_job,
@@ -104,57 +105,14 @@ def xgboost_pipeline(
         filter_column=time_column,
         target_column=label_column_name,
         filter_start_value=timestamp,
+        train_table=train_table,
+        validation_table=valid_table,
+        test_table=test_table,
     )
-    split_train_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=train_table,
-        num_lots=10,
-        lots=tuple(range(8)),
-    )
-    split_valid_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=valid_table,
-        num_lots=10,
-        lots="(8)",
-    )
-    split_test_query = generate_query(
-        queries_folder / "sample.sql",
-        source_dataset=dataset_id,
-        source_table=ingested_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        target_table=test_table,
-        num_lots=10,
-        lots="(9)",
-    )
-
-    # data ingestion and preprocessing operations
 
-    kwargs = dict(bq_client_project_id=project_id, dataset_location=dataset_location)
-    ingest = bq_query_to_table(query=ingest_query, **kwargs).set_display_name(
-        "Ingest data"
-    )
-
-    split_train_data = (
-        bq_query_to_table(query=split_train_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split train data")
-    )
-    split_valid_data = (
-        bq_query_to_table(query=split_valid_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split validation data")
-    )
-    split_test_data = (
-        bq_query_to_table(query=split_test_query, **kwargs)
-        .after(ingest)
-        .set_display_name("Split test data")
-    )
+    ingest = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=ingest_query
+    ).set_display_name("Ingest data")
 
     # data extraction to gcs
 
@@ -166,8 +124,9 @@ def xgboost_pipeline(
             table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(split_train_data)
+        .after(ingest)
         .set_display_name("Extract train data to storage")
+        .set_caching_options(False)
     ).outputs["dataset"]
     valid_dataset = (
         extract_bq_to_dataset(
@@ -177,8 +136,9 @@ def xgboost_pipeline(
             table_name=valid_table,
             dataset_location=dataset_location,
         )
-        .after(split_valid_data)
+        .after(ingest)
         .set_display_name("Extract validation data to storage")
+        .set_caching_options(False)
     ).outputs["dataset"]
     test_dataset = (
         extract_bq_to_dataset(
@@ -189,7 +149,7 @@ def xgboost_pipeline(
             dataset_location=dataset_location,
             destination_gcs_uri=test_dataset_uri,
         )
-        .after(split_test_data)
+        .after(ingest)
         .set_display_name("Extract test data to storage")
         .set_caching_options(False)
     ).outputs["dataset"]
diff --git a/pipelines/src/pipelines/xgboost/training/queries/engineer_features.sql b/pipelines/src/pipelines/xgboost/training/queries/engineer_features.sql
deleted file mode 100644
index 148d9ce7..00000000
--- a/pipelines/src/pipelines/xgboost/training/queries/engineer_features.sql
+++ /dev/null
@@ -1,4 +0,0 @@
-/* The Purpose of this query is to clean the data before the training*/
-SELECT
- *
-FROM `{{ source_dataset }}.{{ source_table }}`
diff --git a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql b/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
index fbb6df32..10ecf037 100644
--- a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
@@ -1,20 +1,3 @@
--- Copyright 2022 Google LLC
-
--- Licensed under the Apache License, Version 2.0 (the "License");
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
--- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
--- This allows us to set the filter_start_value to a specific time for testing or for backfill
-
 CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
   OPTIONS (
     description = 'Preprocessing Dataset',
@@ -66,3 +49,36 @@ WHERE
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
 );
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ train_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ train_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (0, 1, 2, 3, 4, 5, 6, 7));
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ validation_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ validation_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (8));
+
+DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ test_table }}`;
+
+CREATE TABLE `{{ preprocessing_dataset }}.{{ test_table }}` AS (
+SELECT
+	*
+FROM
+	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
+WHERE
+	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
+	10) IN (9));
diff --git a/pipelines/src/pipelines/xgboost/training/queries/sample.sql b/pipelines/src/pipelines/xgboost/training/queries/sample.sql
deleted file mode 100644
index be8458be..00000000
--- a/pipelines/src/pipelines/xgboost/training/queries/sample.sql
+++ /dev/null
@@ -1,10 +0,0 @@
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ target_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ target_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ source_dataset }}.{{ source_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	{{ num_lots }}) IN {{ lots }});

From 8a7e368e139c625e9456675a551bf1a1c6e1710c Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Thu, 18 May 2023 12:53:00 +0200
Subject: [PATCH 019/238] docs: rename files and add comments

---
 .../pipelines/tensorflow/prediction/queries/ingest.sql    | 4 ++++
 pipelines/src/pipelines/tensorflow/training/pipeline.py   | 8 ++++----
 .../training/queries/{ingest.sql => preprocessing.sql}    | 4 ++++
 .../src/pipelines/xgboost/prediction/queries/ingest.sql   | 4 ++++
 pipelines/src/pipelines/xgboost/training/pipeline.py      | 8 ++++----
 .../training/queries/{ingest.sql => preprocessing.sql}    | 4 ++++
 6 files changed, 24 insertions(+), 8 deletions(-)
 rename pipelines/src/pipelines/tensorflow/training/queries/{ingest.sql => preprocessing.sql} (92%)
 rename pipelines/src/pipelines/xgboost/training/queries/{ingest.sql => preprocessing.sql} (92%)

diff --git a/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
index 5a44d671..010cfaba 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
@@ -14,11 +14,15 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
+
+-- If prediction dataset don't exist, create it
 CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
   OPTIONS (
     description = 'Prediction Dataset',
     location = "{{ dataset_region }}");
 
+-- We recreate the ingestion table every time the pipeline run,
+-- so we need to drop the generated in the  previous run
 DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
 
 CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index ba98bea1..bfeaef8b 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -98,7 +98,7 @@ def tensorflow_pipeline(
     queries_folder = pathlib.Path(__file__).parent / "queries"
 
     ingest_query = generate_query(
-        queries_folder / "ingest.sql",
+        queries_folder / "preprocessing.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
         preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
@@ -127,7 +127,7 @@ def tensorflow_pipeline(
             dataset_location=dataset_location,
         )
         .after(ingest)
-        .set_display_name("Extract train data to storage")
+        .set_display_name("Extract train")
         .set_caching_options(False)
     ).outputs["dataset"]
     valid_dataset = (
@@ -139,7 +139,7 @@ def tensorflow_pipeline(
             dataset_location=dataset_location,
         )
         .after(ingest)
-        .set_display_name("Extract validation data to storage")
+        .set_display_name("Extract validation data")
         .set_caching_options(False)
     ).outputs["dataset"]
     test_dataset = (
@@ -152,7 +152,7 @@ def tensorflow_pipeline(
             destination_gcs_uri=test_dataset_uri,
         )
         .after(ingest)
-        .set_display_name("Extract test data to storage")
+        .set_display_name("Extract test data")
         .set_caching_options(False)
     ).outputs["dataset"]
 
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
similarity index 92%
rename from pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
rename to pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
index b3a31606..d1644958 100644
--- a/pipelines/src/pipelines/tensorflow/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
@@ -1,8 +1,11 @@
+-- If preprocessing dataset don't exist, create it
 CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
   OPTIONS (
     description = 'Preprocessing Dataset',
     location = "{{ dataset_region }}");
 
+-- We recreate the ingestion table every time the pipeline run,
+-- so we need to drop the generated in the  previous run
 DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
 
 CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
@@ -50,6 +53,7 @@ WHERE
     {% endfor %}
 );
 
+-- Drop and creation of train, testing and validations tables
 DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ train_table }}`;
 
 CREATE TABLE `{{ preprocessing_dataset }}.{{ train_table }}` AS (
diff --git a/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql b/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
index bf8fe57a..d6cf4ada 100644
--- a/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
@@ -14,11 +14,15 @@
 
 -- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
+
+-- If prediction dataset don't exist, create it
 CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
   OPTIONS (
     description = 'Prediction Dataset',
     location = "{{ dataset_region }}");
 
+-- We recreate the ingestion table every time the pipeline run,
+-- so we need to drop the generated in the  previous run
 DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
 
 CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 385e41ab..d0a303b2 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -96,7 +96,7 @@ def xgboost_pipeline(
     queries_folder = pathlib.Path(__file__).parent / "queries"
 
     ingest_query = generate_query(
-        queries_folder / "ingest.sql",
+        queries_folder / "preprocessing.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
         preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
@@ -125,7 +125,7 @@ def xgboost_pipeline(
             dataset_location=dataset_location,
         )
         .after(ingest)
-        .set_display_name("Extract train data to storage")
+        .set_display_name("Extract train data")
         .set_caching_options(False)
     ).outputs["dataset"]
     valid_dataset = (
@@ -137,7 +137,7 @@ def xgboost_pipeline(
             dataset_location=dataset_location,
         )
         .after(ingest)
-        .set_display_name("Extract validation data to storage")
+        .set_display_name("Extract validation data")
         .set_caching_options(False)
     ).outputs["dataset"]
     test_dataset = (
@@ -150,7 +150,7 @@ def xgboost_pipeline(
             destination_gcs_uri=test_dataset_uri,
         )
         .after(ingest)
-        .set_display_name("Extract test data to storage")
+        .set_display_name("Extract test data")
         .set_caching_options(False)
     ).outputs["dataset"]
 
diff --git a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql b/pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql
similarity index 92%
rename from pipelines/src/pipelines/xgboost/training/queries/ingest.sql
rename to pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql
index 10ecf037..3672262f 100644
--- a/pipelines/src/pipelines/xgboost/training/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql
@@ -1,8 +1,11 @@
+-- If preprocessing dataset don't exist, create it
 CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
   OPTIONS (
     description = 'Preprocessing Dataset',
     location = "{{ dataset_region }}");
 
+-- We recreate the ingestion table every time the pipeline run,
+-- so we need to drop the generated in the  previous run
 DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
 
 CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
@@ -50,6 +53,7 @@ WHERE
     {% endfor %}
 );
 
+-- Drop and creation of train, testing and validations tables
 DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ train_table }}`;
 
 CREATE TABLE `{{ preprocessing_dataset }}.{{ train_table }}` AS (

From c087024d19dde1ff44b220cbcb03eb5aca27332c Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Fri, 19 May 2023 23:23:45 +0200
Subject: [PATCH 020/238] fix: replace quotes in queries

---
 pipelines/src/pipelines/__init__.py                |  5 +----
 .../pipelines/tensorflow/prediction/pipeline.py    |  2 +-
 .../queries/{ingest.sql => preprocessing.sql}      | 14 +++++++-------
 .../tensorflow/training/queries/preprocessing.sql  | 10 +++++-----
 .../src/pipelines/xgboost/prediction/pipeline.py   |  2 +-
 .../queries/{ingest.sql => preprocessing.sql}      | 14 +++++++-------
 .../xgboost/training/queries/preprocessing.sql     | 10 +++++-----
 7 files changed, 27 insertions(+), 30 deletions(-)
 rename pipelines/src/pipelines/tensorflow/prediction/queries/{ingest.sql => preprocessing.sql} (81%)
 rename pipelines/src/pipelines/xgboost/prediction/queries/{ingest.sql => preprocessing.sql} (81%)

diff --git a/pipelines/src/pipelines/__init__.py b/pipelines/src/pipelines/__init__.py
index badd535e..8eeeff45 100644
--- a/pipelines/src/pipelines/__init__.py
+++ b/pipelines/src/pipelines/__init__.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
+import json
 from pathlib import Path
 from jinja2 import Template
 
@@ -33,7 +33,4 @@ def generate_query(input_file: Path, **replacements) -> str:
     # Render the template with the provided replacements
     query = Template(query_template).render(**replacements)
 
-    # Escape double quotes, newline and tab characters
-    query = query.replace('"', '\\"').replace("\n", "\\n").replace("\t", "\\t")
-
     return query
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index 60ad3b47..8d6344ac 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -89,7 +89,7 @@ def tensorflow_pipeline(
     queries_folder = pathlib.Path(__file__).parent / "queries"
 
     ingest_query = generate_query(
-        queries_folder / "ingest.sql",
+        queries_folder / "preprocessing.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
         prediction_dataset=f"{ingestion_project_id}.{prediction_dataset_id}",
diff --git a/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql b/pipelines/src/pipelines/tensorflow/prediction/queries/preprocessing.sql
similarity index 81%
rename from pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
rename to pipelines/src/pipelines/tensorflow/prediction/queries/preprocessing.sql
index 010cfaba..3e25a603 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/queries/ingest.sql
+++ b/pipelines/src/pipelines/tensorflow/prediction/queries/preprocessing.sql
@@ -1,25 +1,25 @@
 -- Copyright 2022 Google LLC
 
--- Licensed under the Apache License, Version 2.0 (the "License");
+-- Licensed under the Apache License, Version 2.0 (the 'License');
 -- you may not use this file except in compliance with the License.
 -- You may obtain a copy of the License at
 
 --     https://www.apache.org/licenses/LICENSE-2.0
 
 -- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
+-- distributed under the License is distributed on an 'AS IS' BASIS,
 -- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 -- See the License for the specific language governing permissions and
 -- limitations under the License.
 
--- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
+-- Treat 'filter_start_value' as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
 
 -- If prediction dataset don't exist, create it
 CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
   OPTIONS (
     description = 'Prediction Dataset',
-    location = "{{ dataset_region }}");
+    location = '{{ dataset_region }}');
 
 -- We recreate the ingestion table every time the pipeline run,
 -- so we need to drop the generated in the  previous run
@@ -28,7 +28,7 @@ DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
 CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
 with filter_start_values as (
     SELECT
-    IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
+    IF('{{ filter_start_value }}' = '', CURRENT_DATETIME(), CAST('{{ filter_start_value }}' AS DATETIME)) as filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
 ,filtered_data as (
@@ -62,8 +62,8 @@ SELECT
 FROM filtered_data as t, mean_time as m
 WHERE
     trip_miles > 0 AND fare > 0 AND fare < 1500
-    {% for field in ["fare", "trip_start_timestamp", "pickup_longitude",
-                "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
+    {% for field in ['fare', 'trip_start_timestamp', 'pickup_longitude',
+                'pickup_latitude', 'dropoff_longitude', 'dropoff_latitude','payment_type','company'] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
     );
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql b/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
index d1644958..0182aac2 100644
--- a/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
+++ b/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
@@ -2,7 +2,7 @@
 CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
   OPTIONS (
     description = 'Preprocessing Dataset',
-    location = "{{ dataset_region }}");
+    location = '{{ dataset_region }}');
 
 -- We recreate the ingestion table every time the pipeline run,
 -- so we need to drop the generated in the  previous run
@@ -11,9 +11,9 @@ DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
 CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
 WITH filter_start_values AS (
 SELECT
-	IF("{{ filter_start_value }}" = '',
+	IF('{{ filter_start_value }}' = '',
 	CURRENT_DATETIME(),
-	CAST("{{ filter_start_value }}" AS DATETIME)) AS filter_start_value
+	CAST('{{ filter_start_value }}' AS DATETIME)) AS filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
 ,filtered_data AS (
@@ -47,8 +47,8 @@ SELECT
 FROM filtered_data AS t, mean_time AS m
 WHERE
     trip_miles > 0 AND fare > 0 AND fare < 1500
-    {% for field in ["fare", "trip_start_timestamp", "pickup_longitude",
-                "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
+    {% for field in ['fare', 'trip_start_timestamp', 'pickup_longitude',
+                'pickup_latitude', 'dropoff_longitude', 'dropoff_latitude','payment_type','company'] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
 );
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index 7fdea71c..4cd796c1 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -85,7 +85,7 @@ def xgboost_pipeline(
     queries_folder = pathlib.Path(__file__).parent / "queries"
 
     ingest_query = generate_query(
-        queries_folder / "ingest.sql",
+        queries_folder / "preprocessing.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
         prediction_dataset=f"{ingestion_project_id}.{prediction_dataset_id}",
diff --git a/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql b/pipelines/src/pipelines/xgboost/prediction/queries/preprocessing.sql
similarity index 81%
rename from pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
rename to pipelines/src/pipelines/xgboost/prediction/queries/preprocessing.sql
index d6cf4ada..294223a4 100644
--- a/pipelines/src/pipelines/xgboost/prediction/queries/ingest.sql
+++ b/pipelines/src/pipelines/xgboost/prediction/queries/preprocessing.sql
@@ -1,25 +1,25 @@
 -- Copyright 2022 Google LLC
 
--- Licensed under the Apache License, Version 2.0 (the "License");
+-- Licensed under the Apache License, Version 2.0 (the 'License');
 -- you may not use this file except in compliance with the License.
 -- You may obtain a copy of the License at
 
 --     https://www.apache.org/licenses/LICENSE-2.0
 
 -- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an "AS IS" BASIS,
+-- distributed under the License is distributed on an 'AS IS' BASIS,
 -- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 -- See the License for the specific language governing permissions and
 -- limitations under the License.
 
--- Treat "filter_start_value" as the current time, unless it is empty then use CURRENT_DATETIME() instead
+-- Treat 'filter_start_value' as the current time, unless it is empty then use CURRENT_DATETIME() instead
 -- This allows us to set the filter_start_value to a specific time for testing or for backfill
 
 -- If prediction dataset don't exist, create it
 CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
   OPTIONS (
     description = 'Prediction Dataset',
-    location = "{{ dataset_region }}");
+    location = '{{ dataset_region }}');
 
 -- We recreate the ingestion table every time the pipeline run,
 -- so we need to drop the generated in the  previous run
@@ -28,7 +28,7 @@ DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
 CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
 with filter_start_values as (
     SELECT 
-    IF("{{ filter_start_value }}" = '', CURRENT_DATETIME(), CAST("{{ filter_start_value }}" AS DATETIME)) as filter_start_value
+    IF('{{ filter_start_value }}' = '', CURRENT_DATETIME(), CAST('{{ filter_start_value }}' AS DATETIME)) as filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
 ,filtered_data as (
@@ -62,8 +62,8 @@ SELECT
 FROM filtered_data as t, mean_time as m
 WHERE
     trip_miles > 0 AND fare > 0 AND fare < 1500
-    {% for field in ["fare", "trip_start_timestamp", "pickup_longitude",
-                "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
+    {% for field in ['fare', 'trip_start_timestamp', 'pickup_longitude',
+                'pickup_latitude', 'dropoff_longitude', 'dropoff_latitude','payment_type','company'] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
     );
diff --git a/pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql b/pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql
index 3672262f..a7291038 100644
--- a/pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql
+++ b/pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql
@@ -2,7 +2,7 @@
 CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
   OPTIONS (
     description = 'Preprocessing Dataset',
-    location = "{{ dataset_region }}");
+    location = '{{ dataset_region }}');
 
 -- We recreate the ingestion table every time the pipeline run,
 -- so we need to drop the generated in the  previous run
@@ -11,9 +11,9 @@ DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
 CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
 WITH filter_start_values AS (
 SELECT
-	IF("{{ filter_start_value }}" = '',
+	IF('{{ filter_start_value }}' = '',
 	CURRENT_DATETIME(),
-	CAST("{{ filter_start_value }}" AS DATETIME)) AS filter_start_value
+	CAST('{{ filter_start_value }}' AS DATETIME)) AS filter_start_value
 )
 -- Ingest data between 2 and 3 months ago
 ,filtered_data AS (
@@ -47,8 +47,8 @@ SELECT
 FROM filtered_data AS t, mean_time AS m
 WHERE
     trip_miles > 0 AND fare > 0 AND fare < 1500
-    {% for field in ["fare", "trip_start_timestamp", "pickup_longitude",
-                "pickup_latitude", "dropoff_longitude", "dropoff_latitude","payment_type","company"] %}
+    {% for field in ['fare', 'trip_start_timestamp', 'pickup_longitude',
+                'pickup_latitude', 'dropoff_longitude', 'dropoff_latitude','payment_type','company'] %}
         AND `{{ field }}` IS NOT NULL
     {% endfor %}
 );

From e8b492f2343db6144d534d92da851d71c8ee150c Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Sat, 20 May 2023 23:05:29 +0200
Subject: [PATCH 021/238] refactor: rename queries and pipeline steps

---
 pipelines/src/pipelines/__init__.py                  |  7 ++-----
 .../src/pipelines/tensorflow/prediction/pipeline.py  |  8 ++++----
 .../src/pipelines/tensorflow/training/pipeline.py    | 12 ++++++------
 .../src/pipelines/xgboost/prediction/pipeline.py     |  8 ++++----
 pipelines/src/pipelines/xgboost/training/pipeline.py | 12 ++++++------
 5 files changed, 22 insertions(+), 25 deletions(-)

diff --git a/pipelines/src/pipelines/__init__.py b/pipelines/src/pipelines/__init__.py
index 8eeeff45..113da917 100644
--- a/pipelines/src/pipelines/__init__.py
+++ b/pipelines/src/pipelines/__init__.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import json
+
 from pathlib import Path
 from jinja2 import Template
 
@@ -30,7 +30,4 @@ def generate_query(input_file: Path, **replacements) -> str:
     with open(input_file, "r") as f:
         query_template = f.read()
 
-    # Render the template with the provided replacements
-    query = Template(query_template).render(**replacements)
-
-    return query
+    return Template(query_template).render(**replacements)
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index 8d6344ac..7290a4c9 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -88,7 +88,7 @@ def tensorflow_pipeline(
     # operations
     queries_folder = pathlib.Path(__file__).parent / "queries"
 
-    ingest_query = generate_query(
+    preprocessing_query = generate_query(
         queries_folder / "preprocessing.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
@@ -101,8 +101,8 @@ def tensorflow_pipeline(
     )
 
     # data ingestion and preprocessing operations
-    ingest = BigqueryQueryJobOp(
-        project=project_id, location=dataset_location, query=ingest_query
+    preprocessing = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=preprocessing_query
     ).set_display_name("Ingest data")
 
     # lookup champion model
@@ -143,7 +143,7 @@ def tensorflow_pipeline(
             monitoring_skew_config=monitoring_skew_config,
             instance_config=instance_config,
         )
-        .after(ingest)
+        .after(preprocessing)
         .set_display_name("Batch prediction job")
     )
 
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index bfeaef8b..c59a6bd3 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -97,7 +97,7 @@ def tensorflow_pipeline(
 
     queries_folder = pathlib.Path(__file__).parent / "queries"
 
-    ingest_query = generate_query(
+    preprocessing_query = generate_query(
         queries_folder / "preprocessing.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
@@ -112,8 +112,8 @@ def tensorflow_pipeline(
         test_table=test_table,
     )
 
-    ingest = BigqueryQueryJobOp(
-        project=project_id, location=dataset_location, query=ingest_query
+    preprocessing = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=preprocessing_query
     ).set_display_name("Ingest data")
 
     # data extraction to gcs
@@ -126,7 +126,7 @@ def tensorflow_pipeline(
             table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(ingest)
+        .after(preprocessing)
         .set_display_name("Extract train")
         .set_caching_options(False)
     ).outputs["dataset"]
@@ -138,7 +138,7 @@ def tensorflow_pipeline(
             table_name=valid_table,
             dataset_location=dataset_location,
         )
-        .after(ingest)
+        .after(preprocessing)
         .set_display_name("Extract validation data")
         .set_caching_options(False)
     ).outputs["dataset"]
@@ -151,7 +151,7 @@ def tensorflow_pipeline(
             dataset_location=dataset_location,
             destination_gcs_uri=test_dataset_uri,
         )
-        .after(ingest)
+        .after(preprocessing)
         .set_display_name("Extract test data")
         .set_caching_options(False)
     ).outputs["dataset"]
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index 4cd796c1..5592a121 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -84,7 +84,7 @@ def xgboost_pipeline(
     # operations
     queries_folder = pathlib.Path(__file__).parent / "queries"
 
-    ingest_query = generate_query(
+    preprocessing_query = generate_query(
         queries_folder / "preprocessing.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
@@ -96,8 +96,8 @@ def xgboost_pipeline(
         filter_start_value=timestamp,
     )
 
-    ingest = BigqueryQueryJobOp(
-        project=project_id, location=dataset_location, query=ingest_query
+    preprocessing = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=preprocessing_query
     ).set_display_name("Ingest data")
 
     # lookup champion model
@@ -135,7 +135,7 @@ def xgboost_pipeline(
             monitoring_alert_email_addresses=monitoring_alert_email_addresses,
             monitoring_skew_config=monitoring_skew_config,
         )
-        .after(ingest)
+        .after(preprocessing)
         .set_display_name("Batch prediction job")
     )
 
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index d0a303b2..0befe4db 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -95,7 +95,7 @@ def xgboost_pipeline(
 
     queries_folder = pathlib.Path(__file__).parent / "queries"
 
-    ingest_query = generate_query(
+    preprocessing_query = generate_query(
         queries_folder / "preprocessing.sql",
         source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
         source_table=ingestion_table,
@@ -110,8 +110,8 @@ def xgboost_pipeline(
         test_table=test_table,
     )
 
-    ingest = BigqueryQueryJobOp(
-        project=project_id, location=dataset_location, query=ingest_query
+    preprocessing = BigqueryQueryJobOp(
+        project=project_id, location=dataset_location, query=preprocessing_query
     ).set_display_name("Ingest data")
 
     # data extraction to gcs
@@ -124,7 +124,7 @@ def xgboost_pipeline(
             table_name=train_table,
             dataset_location=dataset_location,
         )
-        .after(ingest)
+        .after(preprocessing)
         .set_display_name("Extract train data")
         .set_caching_options(False)
     ).outputs["dataset"]
@@ -136,7 +136,7 @@ def xgboost_pipeline(
             table_name=valid_table,
             dataset_location=dataset_location,
         )
-        .after(ingest)
+        .after(preprocessing)
         .set_display_name("Extract validation data")
         .set_caching_options(False)
     ).outputs["dataset"]
@@ -149,7 +149,7 @@ def xgboost_pipeline(
             dataset_location=dataset_location,
             destination_gcs_uri=test_dataset_uri,
         )
-        .after(ingest)
+        .after(preprocessing)
         .set_display_name("Extract test data")
         .set_caching_options(False)
     ).outputs["dataset"]

From e0b5351ca2592273ba3847606df4a4462c980ba0 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
Date: Mon, 22 May 2023 09:08:15 +0200
Subject: [PATCH 022/238] Update
 pipelines/src/pipelines/tensorflow/training/pipeline.py

---
 pipelines/src/pipelines/tensorflow/training/pipeline.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index c59a6bd3..f6e70525 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -114,7 +114,7 @@ def tensorflow_pipeline(
 
     preprocessing = BigqueryQueryJobOp(
         project=project_id, location=dataset_location, query=preprocessing_query
-    ).set_display_name("Ingest data")
+    ).set_display_name("Ingest & preprocess data")
 
     # data extraction to gcs
 

From ab771688758a5d3584ab18114a3396396fe8bb4a Mon Sep 17 00:00:00 2001
From: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
Date: Mon, 22 May 2023 09:08:20 +0200
Subject: [PATCH 023/238] Update
 pipelines/src/pipelines/xgboost/training/pipeline.py

---
 pipelines/src/pipelines/xgboost/training/pipeline.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 0befe4db..6737a627 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -112,7 +112,7 @@ def xgboost_pipeline(
 
     preprocessing = BigqueryQueryJobOp(
         project=project_id, location=dataset_location, query=preprocessing_query
-    ).set_display_name("Ingest data")
+    ).set_display_name("Ingest & preprocess data")
 
     # data extraction to gcs
 

From 6b32a85ff853587893b4c13e5636af6411257ad5 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Mon, 22 May 2023 10:59:45 +0100
Subject: [PATCH 024/238] feat: changes to release ci/cd

---
 cloudbuild/release.yaml | 10 ++++------
 1 file changed, 4 insertions(+), 6 deletions(-)

diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 63e60115..4a48a1f7 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -35,12 +35,10 @@ steps:
     args:
       - -c
       - |
-        mkdir -p ${TAG_NAME}/training/assets && \
-        mkdir -p ${TAG_NAME}/prediction/assets && \
-        cp pipelines/training.json ${TAG_NAME}/training/training.json && \
-        cp pipelines/prediction.json ${TAG_NAME}/prediction/prediction.json && \
-        cp -r pipelines/pipelines/${_PIPELINE_TEMPLATE}/training/assets ${TAG_NAME}/training/ && \
-        cp -r pipelines/pipelines/${_PIPELINE_TEMPLATE}/prediction/assets ${TAG_NAME}/prediction/ && \
+        mkdir -p ${TAG_NAME}/assets && \
+        cp pipelines/training.json ${TAG_NAME}/training.json && \
+        cp pipelines/prediction.json ${TAG_NAME}/prediction.json && \
+        cp -r pipelines/assets ${TAG_NAME}/assets && \
         for dest in ${_PIPELINE_PUBLISH_GCS_PATHS} ; do \
           gsutil cp -r ${TAG_NAME} $$dest ; \
         done

From af91f0ed5b3a39434c78307cc7f19141dcb793e9 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Mon, 22 May 2023 11:26:57 +0100
Subject: [PATCH 025/238] docs: readme update related to changes to ci/cd

---
 README.md | 12 ++++--------
 1 file changed, 4 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index b57cd4c5..927ea440 100644
--- a/README.md
+++ b/README.md
@@ -242,14 +242,10 @@ Below is a diagram of how the files are published in each environment in the `e2
 ```
 . <-- GCS directory set by _PIPELINE_PUBLISH_GCS_PATH
 └── TAG_NAME or GIT COMMIT HASH <-- Git tag used for the release (release.yaml) OR git commit hash (e2e-test.yaml)
-    ├── prediction
-    │   ├── assets
-    │   │   └── some_useful_file.json
-    │   └── prediction.json   <-- compiled prediction pipeline
-    └── training
-        ├── assets
-        │   └── training_task.py
-        └── training.json   <-- compiled training pipeline
+    ├── training.json
+    ├── prediction.json
+    ├── assets
+    │   └── some_useful_file.json
 ```
 
 4. `terraform-plan.yaml` - Checks the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`), and produces a summary of any proposed changes that will be applied on merge to the main branch.

From 48b7be22bd8d193f45f978e114fcff8daba608c6 Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Mon, 22 May 2023 13:01:42 +0200
Subject: [PATCH 026/238] feat: radd missing tests

---
 Makefile                                      |  12 ++
 .../tests/test_extract_bq_to_dataset.py       |  73 +++++++
 .../tests/test_custom_training_job.py         |  91 +++++++++
 .../tests/test_import_model_evaluation.py     |  51 +++++
 pipelines/Pipfile                             |   1 +
 pipelines/Pipfile.lock                        | 189 ++++++++++++------
 pipelines/pyproject.toml                      |   1 +
 7 files changed, 352 insertions(+), 66 deletions(-)
 create mode 100644 components/bigquery-components/tests/test_extract_bq_to_dataset.py
 create mode 100644 components/vertex-components/tests/test_custom_training_job.py
 create mode 100644 components/vertex-components/tests/test_import_model_evaluation.py

diff --git a/Makefile b/Makefile
index 05a3c1e8..faa0fa43 100644
--- a/Makefile
+++ b/Makefile
@@ -57,6 +57,18 @@ test-all-components: ## Run unit tests for all pipeline components
 		$(MAKE) test-components GROUP=$$(basename $$component_group) ; \
 	done
 
+test-components-coverage: ## Run tests with coverage
+	@cd "components/${GROUP}" && \
+	pipenv run coverage run -m pytest && \
+	pipenv run coverage report -m
+
+test-all-components-coverage: ## Run tests with coverage
+		@set -e && \
+	for component_group in components/*/ ; do \
+		echo "Test components under $$component_group" && \
+		$(MAKE) test-components-coverage GROUP=$$(basename $$component_group) ; \
+	done
+
 sync-assets: ## Sync assets folder to GCS. Must specify pipeline=<training|prediction>
 	@if [ -d "./pipelines/src/pipelines/${PIPELINE_TEMPLATE}/$(pipeline)/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
diff --git a/components/bigquery-components/tests/test_extract_bq_to_dataset.py b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
new file mode 100644
index 00000000..8d83a62b
--- /dev/null
+++ b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
@@ -0,0 +1,73 @@
+import google.cloud.bigquery  # noqa
+from kfp.v2.dsl import Dataset
+from unittest import mock
+
+import bigquery_components
+
+extract_bq_to_dataset = bigquery_components.extract_bq_to_dataset.python_func
+
+
+def test_extract_bq_to_dataset(tmpdir):
+    with mock.patch("google.cloud.bigquery.client.Client") as mock_client, mock.patch(
+        "google.cloud.bigquery.job.ExtractJobConfig"
+    ) as mock_job_config, mock.patch("google.cloud.bigquery.table.Table") as mock_table:
+
+        # Mock the Dataset path
+        mock_path = tmpdir
+
+        # Set up the mock Client
+        mock_client.extract_table.return_value = "my-job"
+
+        # Set up the mock Table
+        mock_table.return_value.table_ref = "my-table"
+
+        # Set up the mock ExtractJob
+        mock_job_config.return_value = "mock-job-config"
+
+        # Call the function
+        extract_bq_to_dataset(
+            bq_client_project_id="my-project-id",
+            source_project_id="source-project-id",
+            dataset_id="dataset-id",
+            table_name="table-name",
+            dataset=Dataset(uri=mock_path),
+            destination_gcs_uri="gs://mock_bucket",
+            dataset_location="EU",
+            extract_job_config=None,
+            skip_if_exists=False,
+        )
+
+        # Check that Client.extract_table was called correctly
+        mock_client.return_value.extract_table.assert_called_once_with(
+            mock_table.return_value, "gs://mock_bucket", job_config="mock-job-config"
+        )
+
+
+def test_extract_bq_to_dataset_skip_existing(tmpdir):
+    with mock.patch("google.cloud.bigquery.client.Client") as mock_client, mock.patch(
+        "google.cloud.bigquery.table.Table"
+    ), mock.patch("google.cloud.bigquery.job.ExtractJobConfig"), mock.patch(
+        "pathlib.Path.exists"
+    ) as mock_path_exists:
+
+        # # Mock the Dataset path
+        mock_path = tmpdir
+
+        # Mock that the destination already exists
+        mock_path_exists.return_value = True
+
+        # Call the function with skip_if_exists set to True
+        extract_bq_to_dataset(
+            bq_client_project_id="my-project-id",
+            source_project_id="source-project-id",
+            dataset_id="dataset-id",
+            table_name="table-name",
+            dataset=Dataset(uri=mock_path),
+            destination_gcs_uri="gs://mock_bucket",
+            dataset_location="EU",
+            extract_job_config=None,
+            skip_if_exists=True,
+        )
+
+        # Ensure that Client.extract_table was not called
+        assert not mock_client.return_value.extract_table.called
diff --git a/components/vertex-components/tests/test_custom_training_job.py b/components/vertex-components/tests/test_custom_training_job.py
new file mode 100644
index 00000000..2658f318
--- /dev/null
+++ b/components/vertex-components/tests/test_custom_training_job.py
@@ -0,0 +1,91 @@
+import google.cloud.aiplatform as aip  # noqa
+from kfp.v2.dsl import Dataset, Metrics, Artifact
+from unittest import mock
+import pytest
+
+
+import vertex_components
+
+custom_train_job = vertex_components.custom_train_job.python_func
+
+
+def test_custom_train_job(tmpdir):
+    with mock.patch(
+        "google.cloud.aiplatform.CustomTrainingJob"
+    ) as mock_job, mock.patch("os.path.exists") as mock_exists, mock.patch(
+        "builtins.open", mock.mock_open(read_data="{}")
+    ) as mock_open:
+
+        mock_exists.return_value = True
+
+        mock_train_data = Dataset(uri=tmpdir)
+        mock_valid_data = Dataset(uri=tmpdir)
+        mock_test_data = Dataset(uri=tmpdir)
+
+        mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
+        mock_metrics = Metrics(uri=tmpdir)
+
+        custom_train_job(
+            train_script_uri="gs://my-bucket/train_script.py",
+            train_data=mock_train_data,
+            valid_data=mock_valid_data,
+            test_data=mock_test_data,
+            project_id="my-project-id",
+            project_location="europe-west4",
+            model_display_name="my-model",
+            train_container_uri="gcr.io/my-project/my-image:latest",
+            serving_container_uri="gcr.io/my-project/my-serving-image:latest",
+            model=mock_model,
+            metrics=mock_metrics,
+            staging_bucket="gs://my-bucket",
+            job_name="my-job",
+        )
+
+        mock_job.assert_called_once_with(
+            project="my-project-id",
+            location="europe-west4",
+            staging_bucket="gs://my-bucket",
+            display_name="my-job",
+            script_path="/gcs/my-bucket/train_script.py",
+            container_uri="gcr.io/my-project/my-image:latest",
+            requirements=None,
+            model_serving_container_image_uri="gcr.io/my-project/my-serving-image:latest",  # noqa: E501
+        )
+
+        mock_open.assert_called_once_with(tmpdir, "r")
+
+
+def test_custom_train_script_not_found(tmpdir):
+    with pytest.raises(ValueError), mock.patch(
+        "google.cloud.aiplatform.CustomTrainingJob"
+    ) as mock_job, mock.patch("os.path.exists") as mock_exists, mock.patch(
+        "builtins.open", mock.mock_open(read_data="{}")
+    ) as mock_open:
+
+        mock_exists.return_value = False  # Simulate script path not found
+
+        mock_train_data = Dataset(uri=tmpdir)
+        mock_valid_data = Dataset(uri=tmpdir)
+        mock_test_data = Dataset(uri=tmpdir)
+
+        mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
+        mock_metrics = Metrics(uri=tmpdir)
+
+        custom_train_job(
+            train_script_uri="gs://my-bucket/train_script.py",
+            train_data=mock_train_data,
+            valid_data=mock_valid_data,
+            test_data=mock_test_data,
+            project_id="my-project-id",
+            project_location="europe-west4",
+            model_display_name="my-model",
+            train_container_uri="gcr.io/my-project/my-image:latest",
+            serving_container_uri="gcr.io/my-project/my-serving-image:latest",
+            model=mock_model,
+            metrics=mock_metrics,
+            staging_bucket="gs://my-bucket",
+            job_name="my-job",
+        )
+
+        mock_job.assert_not_called()
+        mock_open.assert_not_called()
diff --git a/components/vertex-components/tests/test_import_model_evaluation.py b/components/vertex-components/tests/test_import_model_evaluation.py
new file mode 100644
index 00000000..494c78a2
--- /dev/null
+++ b/components/vertex-components/tests/test_import_model_evaluation.py
@@ -0,0 +1,51 @@
+from unittest import mock
+from kfp.v2.dsl import Model, Metrics, Dataset
+
+import vertex_components
+from google.cloud.aiplatform_v1 import ModelEvaluation
+
+
+import_model_evaluation = vertex_components.import_model_evaluation.python_func
+
+
+def test_import_model_evaluation(tmpdir):
+    with mock.patch(
+        "google.cloud.aiplatform_v1.ModelServiceClient"
+    ) as mock_service_client, mock.patch(
+        "builtins.open",
+        mock.mock_open(read_data='{"accuracy": 0.85, "problemType": "classification"}'),
+        create=True,
+    ) as mock_open, mock.patch(
+        "google.protobuf.json_format.ParseDict"
+    ) as mock_parse_dict:
+
+        mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
+        mock_metrics = Metrics(uri=tmpdir)
+        mock_dataset = Dataset(uri=tmpdir)
+
+        mock_service_client_instance = mock_service_client.return_value
+        mock_service_client_instance.import_model_evaluation.return_value = (
+            ModelEvaluation(name="model_evaluation_name")
+        )
+
+        # Set the return value for ParseDict to be a mock ModelEvaluation
+        mock_parse_dict.return_value = mock.MagicMock(spec=ModelEvaluation)
+
+        model_evaluation_name = import_model_evaluation(
+            model=mock_model,
+            metrics=mock_metrics,
+            test_dataset=mock_dataset,
+            pipeline_job_id="1234",
+            project_location="my-location",
+            evaluation_name="Imported evaluation",
+        )
+
+        mock_service_client_instance.import_model_evaluation.assert_called_once_with(
+            parent=mock_model.metadata["resourceName"],
+            model_evaluation=mock_parse_dict.return_value,
+        )
+
+        # Check that open was called with the correct path
+        mock_open.assert_called_once_with(mock_metrics.uri)
+
+        assert model_evaluation_name[0] == "model_evaluation_name"
diff --git a/pipelines/Pipfile b/pipelines/Pipfile
index 507b4e6d..9538e7fc 100644
--- a/pipelines/Pipfile
+++ b/pipelines/Pipfile
@@ -14,6 +14,7 @@ bigquery-components = {editable = true, path = "./../components/bigquery-compone
 [dev-packages]
 pytest = ">=7.3.1,<8.0.0"
 pre-commit = ">=2.14.1,<3.0.0"
+coverage = "==7.2.5"
 
 [requires]
 python_version = "3.7"
diff --git a/pipelines/Pipfile.lock b/pipelines/Pipfile.lock
index 92d8d064..42ce01df 100644
--- a/pipelines/Pipfile.lock
+++ b/pipelines/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "c889b828537547fe3e76c0ca6f812f331bffdf13bfd8c72104145db94eb555e0"
+            "sha256": "2350f00a78fbfb02ef816a1ba3f5316c810e711a7cc685895cb135cb293d38cd"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -192,11 +192,11 @@
         },
         "google-auth": {
             "hashes": [
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-            "version": "==2.17.3"
+            "version": "==2.18.1"
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         "google-auth-httplib2": {
             "hashes": [
@@ -246,11 +246,11 @@
         },
         "google-cloud-resource-manager": {
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@@ -360,53 +360,53 @@
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@@ -784,11 +784,11 @@
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@@ -1019,6 +1019,63 @@
             "markers": "python_full_version >= '3.6.1'",
             "version": "==3.3.1"
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@@ -1068,11 +1125,11 @@
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-            "version": "==1.7.0"
+            "version": "==1.8.0"
         },
         "packaging": {
             "hashes": [
@@ -1084,11 +1141,11 @@
         },
         "platformdirs": {
             "hashes": [
-                "sha256:47692bc24c1958e8b0f13dd727307cff1db103fca36399f457da8e05f222fdc4",
-                "sha256:7954a68d0ba23558d753f73437c55f89027cf8f5108c19844d4b82e5af396335"
+                "sha256:412dae91f52a6f84830f39a8078cecd0e866cb72294a5c66808e74d5e88d251f",
+                "sha256:e2378146f1964972c03c085bb5662ae80b2b8c06226c54b2ff4aa9483e8a13a5"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==3.5.0"
+            "version": "==3.5.1"
         },
         "pluggy": {
             "hashes": [
@@ -1151,11 +1208,11 @@
         },
         "setuptools": {
             "hashes": [
-                "sha256:23aaf86b85ca52ceb801d32703f12d77517b2556af839621c641fca11287952b",
-                "sha256:f104fa03692a2602fa0fec6c6a9e63b6c8a968de13e17c026957dd1f53d80990"
+                "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f",
+                "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==67.7.2"
+            "version": "==67.8.0"
         },
         "tomli": {
             "hashes": [
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index a5e2cbb7..693a3bd8 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -20,6 +20,7 @@ dependencies = [
 tests = [
     "google-cloud-bigquery == 2.30.0",
     "pytest >= 7.3.1,<8.0.0",
+    "coverage = ==7.2.5"
 ]
 
 [build-system]

From 86b47b23e361fb90d6e44239335fbfc9c455433f Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Mon, 22 May 2023 13:30:25 +0200
Subject: [PATCH 027/238] docs: add comments in tests

---
 .../tests/test_extract_bq_to_dataset.py                  | 6 +++---
 .../vertex-components/tests/test_custom_training_job.py  | 9 ++++++++-
 .../tests/test_import_model_evaluation.py                | 9 +++++++++
 3 files changed, 20 insertions(+), 4 deletions(-)

diff --git a/components/bigquery-components/tests/test_extract_bq_to_dataset.py b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
index 8d83a62b..db00da21 100644
--- a/components/bigquery-components/tests/test_extract_bq_to_dataset.py
+++ b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
@@ -37,7 +37,7 @@ def test_extract_bq_to_dataset(tmpdir):
             skip_if_exists=False,
         )
 
-        # Check that Client.extract_table was called correctly
+        # Check that client.extract_table was called correctly
         mock_client.return_value.extract_table.assert_called_once_with(
             mock_table.return_value, "gs://mock_bucket", job_config="mock-job-config"
         )
@@ -50,13 +50,13 @@ def test_extract_bq_to_dataset_skip_existing(tmpdir):
         "pathlib.Path.exists"
     ) as mock_path_exists:
 
-        # # Mock the Dataset path
+        # Mock the Dataset path
         mock_path = tmpdir
 
         # Mock that the destination already exists
         mock_path_exists.return_value = True
 
-        # Call the function with skip_if_exists set to True
+        # Call the function
         extract_bq_to_dataset(
             bq_client_project_id="my-project-id",
             source_project_id="source-project-id",
diff --git a/components/vertex-components/tests/test_custom_training_job.py b/components/vertex-components/tests/test_custom_training_job.py
index 2658f318..cb075c16 100644
--- a/components/vertex-components/tests/test_custom_training_job.py
+++ b/components/vertex-components/tests/test_custom_training_job.py
@@ -16,8 +16,10 @@ def test_custom_train_job(tmpdir):
         "builtins.open", mock.mock_open(read_data="{}")
     ) as mock_open:
 
+        # Mock that the training script exists
         mock_exists.return_value = True
 
+        # Mock Artifacts
         mock_train_data = Dataset(uri=tmpdir)
         mock_valid_data = Dataset(uri=tmpdir)
         mock_test_data = Dataset(uri=tmpdir)
@@ -25,6 +27,7 @@ def test_custom_train_job(tmpdir):
         mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
         mock_metrics = Metrics(uri=tmpdir)
 
+        # Call function
         custom_train_job(
             train_script_uri="gs://my-bucket/train_script.py",
             train_data=mock_train_data,
@@ -41,6 +44,7 @@ def test_custom_train_job(tmpdir):
             job_name="my-job",
         )
 
+        # Assert custom training job is called
         mock_job.assert_called_once_with(
             project="my-project-id",
             location="europe-west4",
@@ -52,6 +56,7 @@ def test_custom_train_job(tmpdir):
             model_serving_container_image_uri="gcr.io/my-project/my-serving-image:latest",  # noqa: E501
         )
 
+        # Assert metrics loading
         mock_open.assert_called_once_with(tmpdir, "r")
 
 
@@ -62,7 +67,8 @@ def test_custom_train_script_not_found(tmpdir):
         "builtins.open", mock.mock_open(read_data="{}")
     ) as mock_open:
 
-        mock_exists.return_value = False  # Simulate script path not found
+        # Mock that the training script is not found
+        mock_exists.return_value = False
 
         mock_train_data = Dataset(uri=tmpdir)
         mock_valid_data = Dataset(uri=tmpdir)
@@ -87,5 +93,6 @@ def test_custom_train_script_not_found(tmpdir):
             job_name="my-job",
         )
 
+        # Assert the custom training job is not executed
         mock_job.assert_not_called()
         mock_open.assert_not_called()
diff --git a/components/vertex-components/tests/test_import_model_evaluation.py b/components/vertex-components/tests/test_import_model_evaluation.py
index 494c78a2..fe1f85eb 100644
--- a/components/vertex-components/tests/test_import_model_evaluation.py
+++ b/components/vertex-components/tests/test_import_model_evaluation.py
@@ -19,11 +19,15 @@ def test_import_model_evaluation(tmpdir):
         "google.protobuf.json_format.ParseDict"
     ) as mock_parse_dict:
 
+        # Mock Artifacts
         mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
         mock_metrics = Metrics(uri=tmpdir)
         mock_dataset = Dataset(uri=tmpdir)
 
+        # Create an instance of the mocked ModelServiceClient.
         mock_service_client_instance = mock_service_client.return_value
+        # When import_model_evaluation is called during the test,
+        # it will return a new ModelEvaluation with the specified name.
         mock_service_client_instance.import_model_evaluation.return_value = (
             ModelEvaluation(name="model_evaluation_name")
         )
@@ -31,6 +35,7 @@ def test_import_model_evaluation(tmpdir):
         # Set the return value for ParseDict to be a mock ModelEvaluation
         mock_parse_dict.return_value = mock.MagicMock(spec=ModelEvaluation)
 
+        # Call the function
         model_evaluation_name = import_model_evaluation(
             model=mock_model,
             metrics=mock_metrics,
@@ -40,6 +45,8 @@ def test_import_model_evaluation(tmpdir):
             evaluation_name="Imported evaluation",
         )
 
+        # Assert that the import_model_evaluation method of
+        # the mocked ModelServiceClient was called
         mock_service_client_instance.import_model_evaluation.assert_called_once_with(
             parent=mock_model.metadata["resourceName"],
             model_evaluation=mock_parse_dict.return_value,
@@ -48,4 +55,6 @@ def test_import_model_evaluation(tmpdir):
         # Check that open was called with the correct path
         mock_open.assert_called_once_with(mock_metrics.uri)
 
+        # Assert that the return value of the import_model_evaluation
+        # function is as expected.
         assert model_evaluation_name[0] == "model_evaluation_name"

From c960f134ea499e728fa63f6c73b946feda4ee2dc Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 09:13:57 +0100
Subject: [PATCH 028/238] refactor(pyproject.toml): change description

---
 components/vertex-components/pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index 6ba44118..e6dc1afd 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -4,7 +4,7 @@ version = "0.1.0"
 authors = [
     {name = "Example User", email = "user@example.com"},
 ]
-description = "Vertex components for training and prediction using the Chicago Taxi Dataset"
+description = "KFP components for interacting with Vertex AI"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",

From 644660e79ce7acfad2ec945aca56dfd22fd12875 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 09:28:34 +0100
Subject: [PATCH 029/238] refactor(pyproject.toml): change description

---
 pipelines/pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index b1784b94..6ef6e2c2 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -4,7 +4,7 @@ version = "0.1.0"
 authors = [
     {name = "Example User", email = "user@example.com"},
 ]
-description = "Turbo Template developed at Datatonic"
+description = "Turbo Template"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",

From 6d9c43fce26fb6c9d4bf0645d526ee7a4bd6aa22 Mon Sep 17 00:00:00 2001
From: ariadnafer <ariadna.fernandez@datatonic.com>
Date: Tue, 23 May 2023 11:16:11 +0200
Subject: [PATCH 030/238] refactor: change patch formatting in all tests

---
 .../tests/test_extract_bq_to_dataset.py       | 119 +++++++--------
 .../tests/test_custom_training_job.py         | 137 +++++++++---------
 .../tests/test_import_model_evaluation.py     |  97 ++++++-------
 .../tests/test_lookup_model.py                | 126 +++++++---------
 .../tests/test_model_batch_predict.py         |  59 ++++----
 .../tests/test_update_best_model.py           |  43 +++---
 6 files changed, 275 insertions(+), 306 deletions(-)

diff --git a/components/bigquery-components/tests/test_extract_bq_to_dataset.py b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
index db00da21..be3084e6 100644
--- a/components/bigquery-components/tests/test_extract_bq_to_dataset.py
+++ b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
@@ -7,67 +7,58 @@
 extract_bq_to_dataset = bigquery_components.extract_bq_to_dataset.python_func
 
 
-def test_extract_bq_to_dataset(tmpdir):
-    with mock.patch("google.cloud.bigquery.client.Client") as mock_client, mock.patch(
-        "google.cloud.bigquery.job.ExtractJobConfig"
-    ) as mock_job_config, mock.patch("google.cloud.bigquery.table.Table") as mock_table:
-
-        # Mock the Dataset path
-        mock_path = tmpdir
-
-        # Set up the mock Client
-        mock_client.extract_table.return_value = "my-job"
-
-        # Set up the mock Table
-        mock_table.return_value.table_ref = "my-table"
-
-        # Set up the mock ExtractJob
-        mock_job_config.return_value = "mock-job-config"
-
-        # Call the function
-        extract_bq_to_dataset(
-            bq_client_project_id="my-project-id",
-            source_project_id="source-project-id",
-            dataset_id="dataset-id",
-            table_name="table-name",
-            dataset=Dataset(uri=mock_path),
-            destination_gcs_uri="gs://mock_bucket",
-            dataset_location="EU",
-            extract_job_config=None,
-            skip_if_exists=False,
-        )
-
-        # Check that client.extract_table was called correctly
-        mock_client.return_value.extract_table.assert_called_once_with(
-            mock_table.return_value, "gs://mock_bucket", job_config="mock-job-config"
-        )
-
-
-def test_extract_bq_to_dataset_skip_existing(tmpdir):
-    with mock.patch("google.cloud.bigquery.client.Client") as mock_client, mock.patch(
-        "google.cloud.bigquery.table.Table"
-    ), mock.patch("google.cloud.bigquery.job.ExtractJobConfig"), mock.patch(
-        "pathlib.Path.exists"
-    ) as mock_path_exists:
-
-        # Mock the Dataset path
-        mock_path = tmpdir
-
-        # Mock that the destination already exists
-        mock_path_exists.return_value = True
-
-        # Call the function
-        extract_bq_to_dataset(
-            bq_client_project_id="my-project-id",
-            source_project_id="source-project-id",
-            dataset_id="dataset-id",
-            table_name="table-name",
-            dataset=Dataset(uri=mock_path),
-            destination_gcs_uri="gs://mock_bucket",
-            dataset_location="EU",
-            extract_job_config=None,
-            skip_if_exists=True,
-        )
-
-        # Ensure that Client.extract_table was not called
-        assert not mock_client.return_value.extract_table.called
+@mock.patch("google.cloud.bigquery.client.Client")
+@mock.patch("google.cloud.bigquery.table.Table")
+@mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
+def test_extract_bq_to_dataset(mock_job_config, mock_table, mock_client, tmpdir):
+    """
+    Checks that the extract_bq_to_dataset is called correctly
+    """
+    mock_path = tmpdir
+    mock_client.extract_table.return_value = "my-job"
+    mock_table.return_value.table_ref = "my-table"
+    mock_job_config.return_value = "mock-job-config"
+
+    extract_bq_to_dataset(
+        bq_client_project_id="my-project-id",
+        source_project_id="source-project-id",
+        dataset_id="dataset-id",
+        table_name="table-name",
+        dataset=Dataset(uri=mock_path),
+        destination_gcs_uri="gs://mock_bucket",
+        dataset_location="EU",
+        extract_job_config=None,
+        skip_if_exists=False,
+    )
+
+    mock_client.return_value.extract_table.assert_called_once_with(
+        mock_table.return_value, "gs://mock_bucket", job_config="mock-job-config"
+    )
+
+
+@mock.patch("google.cloud.bigquery.client.Client")
+@mock.patch("google.cloud.bigquery.table.Table")
+@mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
+@mock.patch("pathlib.Path.exists")
+def test_extract_bq_to_dataset_skip_existing(
+    mock_path_exists, mock_job_config, mock_table, mock_client, tmpdir
+):
+    """
+    Checks that when the dataset exists the method is not called
+    """
+    mock_path = tmpdir
+    mock_path_exists.return_value = True
+
+    extract_bq_to_dataset(
+        bq_client_project_id="my-project-id",
+        source_project_id="source-project-id",
+        dataset_id="dataset-id",
+        table_name="table-name",
+        dataset=Dataset(uri=mock_path),
+        destination_gcs_uri="gs://mock_bucket",
+        dataset_location="EU",
+        extract_job_config=None,
+        skip_if_exists=True,
+    )
+
+    assert not mock_client.return_value.extract_table.called
diff --git a/components/vertex-components/tests/test_custom_training_job.py b/components/vertex-components/tests/test_custom_training_job.py
index cb075c16..46ec46ca 100644
--- a/components/vertex-components/tests/test_custom_training_job.py
+++ b/components/vertex-components/tests/test_custom_training_job.py
@@ -9,74 +9,69 @@
 custom_train_job = vertex_components.custom_train_job.python_func
 
 
-def test_custom_train_job(tmpdir):
-    with mock.patch(
-        "google.cloud.aiplatform.CustomTrainingJob"
-    ) as mock_job, mock.patch("os.path.exists") as mock_exists, mock.patch(
-        "builtins.open", mock.mock_open(read_data="{}")
-    ) as mock_open:
-
-        # Mock that the training script exists
-        mock_exists.return_value = True
-
-        # Mock Artifacts
-        mock_train_data = Dataset(uri=tmpdir)
-        mock_valid_data = Dataset(uri=tmpdir)
-        mock_test_data = Dataset(uri=tmpdir)
-
-        mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
-        mock_metrics = Metrics(uri=tmpdir)
-
-        # Call function
-        custom_train_job(
-            train_script_uri="gs://my-bucket/train_script.py",
-            train_data=mock_train_data,
-            valid_data=mock_valid_data,
-            test_data=mock_test_data,
-            project_id="my-project-id",
-            project_location="europe-west4",
-            model_display_name="my-model",
-            train_container_uri="gcr.io/my-project/my-image:latest",
-            serving_container_uri="gcr.io/my-project/my-serving-image:latest",
-            model=mock_model,
-            metrics=mock_metrics,
-            staging_bucket="gs://my-bucket",
-            job_name="my-job",
-        )
-
-        # Assert custom training job is called
-        mock_job.assert_called_once_with(
-            project="my-project-id",
-            location="europe-west4",
-            staging_bucket="gs://my-bucket",
-            display_name="my-job",
-            script_path="/gcs/my-bucket/train_script.py",
-            container_uri="gcr.io/my-project/my-image:latest",
-            requirements=None,
-            model_serving_container_image_uri="gcr.io/my-project/my-serving-image:latest",  # noqa: E501
-        )
-
-        # Assert metrics loading
-        mock_open.assert_called_once_with(tmpdir, "r")
-
-
-def test_custom_train_script_not_found(tmpdir):
-    with pytest.raises(ValueError), mock.patch(
-        "google.cloud.aiplatform.CustomTrainingJob"
-    ) as mock_job, mock.patch("os.path.exists") as mock_exists, mock.patch(
-        "builtins.open", mock.mock_open(read_data="{}")
-    ) as mock_open:
-
-        # Mock that the training script is not found
-        mock_exists.return_value = False
-
-        mock_train_data = Dataset(uri=tmpdir)
-        mock_valid_data = Dataset(uri=tmpdir)
-        mock_test_data = Dataset(uri=tmpdir)
-
-        mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
-        mock_metrics = Metrics(uri=tmpdir)
-
+@mock.patch("google.cloud.aiplatform.CustomTrainingJob")
+@mock.patch("os.path.exists")
+@mock.patch("builtins.open", new_callable=mock.mock_open, read_data="{}")
+def test_custom_train_job(mock_open, mock_exists, mock_job, tmpdir):
+    """
+    Checks that the custom job method is called
+    """
+    mock_exists.return_value = True
+
+    mock_train_data = Dataset(uri=tmpdir)
+    mock_valid_data = Dataset(uri=tmpdir)
+    mock_test_data = Dataset(uri=tmpdir)
+    mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
+    mock_metrics = Metrics(uri=tmpdir)
+
+    custom_train_job(
+        train_script_uri="gs://my-bucket/train_script.py",
+        train_data=mock_train_data,
+        valid_data=mock_valid_data,
+        test_data=mock_test_data,
+        project_id="my-project-id",
+        project_location="europe-west4",
+        model_display_name="my-model",
+        train_container_uri="gcr.io/my-project/my-image:latest",
+        serving_container_uri="gcr.io/my-project/my-serving-image:latest",
+        model=mock_model,
+        metrics=mock_metrics,
+        staging_bucket="gs://my-bucket",
+        job_name="my-job",
+    )
+
+    mock_job.assert_called_once_with(
+        project="my-project-id",
+        location="europe-west4",
+        staging_bucket="gs://my-bucket",
+        display_name="my-job",
+        script_path="/gcs/my-bucket/train_script.py",
+        container_uri="gcr.io/my-project/my-image:latest",
+        requirements=None,
+        model_serving_container_image_uri="gcr.io/my-project/my-serving-image:latest",  # noqa: E501
+    )
+
+    # Assert metrics loading
+    mock_open.assert_called_once_with(tmpdir, "r")
+
+
+@mock.patch("google.cloud.aiplatform.CustomTrainingJob")
+@mock.patch("os.path.exists")
+@mock.patch("builtins.open", new_callable=mock.mock_open, read_data="{}")
+def test_custom_train_script_not_found(mock_open, mock_exists, mock_job, tmpdir):
+    """
+    Checks that when the training script is not found
+    the method fails
+    """
+    mock_exists.return_value = False
+
+    mock_train_data = Dataset(uri=tmpdir)
+    mock_valid_data = Dataset(uri=tmpdir)
+    mock_test_data = Dataset(uri=tmpdir)
+    mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
+    mock_metrics = Metrics(uri=tmpdir)
+
+    with pytest.raises(ValueError):
         custom_train_job(
             train_script_uri="gs://my-bucket/train_script.py",
             train_data=mock_train_data,
@@ -93,6 +88,6 @@ def test_custom_train_script_not_found(tmpdir):
             job_name="my-job",
         )
 
-        # Assert the custom training job is not executed
-        mock_job.assert_not_called()
-        mock_open.assert_not_called()
+    # Assert the custom training job is not executed
+    mock_job.assert_not_called()
+    mock_open.assert_not_called()
diff --git a/components/vertex-components/tests/test_import_model_evaluation.py b/components/vertex-components/tests/test_import_model_evaluation.py
index fe1f85eb..56cdf8bd 100644
--- a/components/vertex-components/tests/test_import_model_evaluation.py
+++ b/components/vertex-components/tests/test_import_model_evaluation.py
@@ -8,53 +8,50 @@
 import_model_evaluation = vertex_components.import_model_evaluation.python_func
 
 
-def test_import_model_evaluation(tmpdir):
-    with mock.patch(
-        "google.cloud.aiplatform_v1.ModelServiceClient"
-    ) as mock_service_client, mock.patch(
-        "builtins.open",
-        mock.mock_open(read_data='{"accuracy": 0.85, "problemType": "classification"}'),
-        create=True,
-    ) as mock_open, mock.patch(
-        "google.protobuf.json_format.ParseDict"
-    ) as mock_parse_dict:
-
-        # Mock Artifacts
-        mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
-        mock_metrics = Metrics(uri=tmpdir)
-        mock_dataset = Dataset(uri=tmpdir)
-
-        # Create an instance of the mocked ModelServiceClient.
-        mock_service_client_instance = mock_service_client.return_value
-        # When import_model_evaluation is called during the test,
-        # it will return a new ModelEvaluation with the specified name.
-        mock_service_client_instance.import_model_evaluation.return_value = (
-            ModelEvaluation(name="model_evaluation_name")
-        )
-
-        # Set the return value for ParseDict to be a mock ModelEvaluation
-        mock_parse_dict.return_value = mock.MagicMock(spec=ModelEvaluation)
-
-        # Call the function
-        model_evaluation_name = import_model_evaluation(
-            model=mock_model,
-            metrics=mock_metrics,
-            test_dataset=mock_dataset,
-            pipeline_job_id="1234",
-            project_location="my-location",
-            evaluation_name="Imported evaluation",
-        )
-
-        # Assert that the import_model_evaluation method of
-        # the mocked ModelServiceClient was called
-        mock_service_client_instance.import_model_evaluation.assert_called_once_with(
-            parent=mock_model.metadata["resourceName"],
-            model_evaluation=mock_parse_dict.return_value,
-        )
-
-        # Check that open was called with the correct path
-        mock_open.assert_called_once_with(mock_metrics.uri)
-
-        # Assert that the return value of the import_model_evaluation
-        # function is as expected.
-        assert model_evaluation_name[0] == "model_evaluation_name"
+@mock.patch("google.cloud.aiplatform_v1.ModelServiceClient")
+@mock.patch(
+    "builtins.open",
+    new_callable=mock.mock_open,
+    read_data='{"accuracy": 0.85, "problemType": "classification"}',
+)
+@mock.patch("google.protobuf.json_format.ParseDict")
+def test_import_model_evaluation(
+    mock_parse_dict, mock_open, mock_service_client, tmpdir
+):
+    """
+    Checks that when the model evaluation is running and it is writing the metrics
+    """
+    mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
+    mock_metrics = Metrics(uri=tmpdir)
+    mock_dataset = Dataset(uri=tmpdir)
+
+    # Create an instance of the mocked ModelServiceClient.
+    service_client_instance = mock.MagicMock()
+    mock_service_client.return_value = service_client_instance
+    # When import_model_evaluation is called during the test,
+    # it will return a new ModelEvaluation with the specified name.
+    service_client_instance.import_model_evaluation.return_value = ModelEvaluation(
+        name="model_evaluation_name"
+    )
+
+    # Set the return value for ParseDict to be a mock ModelEvaluation
+    mock_parse_dict.return_value = mock.MagicMock(spec=ModelEvaluation)
+
+    model_evaluation_name = import_model_evaluation(
+        model=mock_model,
+        metrics=mock_metrics,
+        test_dataset=mock_dataset,
+        pipeline_job_id="1234",
+        project_location="my-location",
+        evaluation_name="Imported evaluation",
+    )
+
+    service_client_instance.import_model_evaluation.assert_called_once_with(
+        parent=mock_model.metadata["resourceName"],
+        model_evaluation=mock_parse_dict.return_value,
+    )
+
+    # Check that open was called with the correct path
+    mock_open.assert_called_once_with(mock_metrics.uri)
+
+    assert model_evaluation_name[0] == "model_evaluation_name"
diff --git a/components/vertex-components/tests/test_lookup_model.py b/components/vertex-components/tests/test_lookup_model.py
index 1ba31f81..6950dd1b 100644
--- a/components/vertex-components/tests/test_lookup_model.py
+++ b/components/vertex-components/tests/test_lookup_model.py
@@ -22,93 +22,75 @@
 lookup_model = vertex_components.lookup_model.python_func
 
 
-def test_lookup_model(tmpdir):
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model(mock_model, tmpdir):
     """
     Assert lookup_model produces expected resource name, and that list method is
     called with the correct arguemnts
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-
-        # Mock attribute and method
-
-        mock_path = tmpdir
-        mock_model.resource_name = "my-model-resource-name"
-        mock_model.uri = mock_path
-        mock_model.list.return_value = [mock_model]
-
-        # Invoke the model look up
-        found_model_resource_name, _ = lookup_model(
-            model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
-            fail_on_model_not_found=False,
-            model=Model(uri=mock_path),
-        )
-
-        assert found_model_resource_name == "my-model-resource-name"
-
-        # Check the list method was called once with the correct arguments
-        mock_model.list.assert_called_once_with(
-            filter='display_name="my-model"',
-            order_by="create_time desc",
-            location="europe-west4",
-            project="my-project-id",
-        )
-
 
-def test_lookup_model_when_no_models(tmpdir):
+    # Mock attribute and method
+    mock_path = tmpdir
+    mock_model.resource_name = "my-model-resource-name"
+    mock_model.uri = mock_path
+    mock_model.list.return_value = [mock_model]
+
+    # Invoke the model look up
+    found_model_resource_name, _ = lookup_model(
+        model_name="my-model",
+        project_location="europe-west4",
+        project_id="my-project-id",
+        order_models_by="create_time desc",
+        fail_on_model_not_found=False,
+        model=Model(uri=mock_path),
+    )
+
+    assert found_model_resource_name == "my-model-resource-name"
+
+    # Check the list method was called once with the correct arguments
+    mock_model.list.assert_called_once_with(
+        filter='display_name="my-model"',
+        order_by="create_time desc",
+        location="europe-west4",
+        project="my-project-id",
+    )
+
+
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model_when_no_models(mock_model, tmpdir):
     """
     Checks that when there are no models and fail_on_model_found = False,
     lookup_model returns an empty string.
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-        mock_model.list.return_value = []
-        exported_model_resource_name, _ = lookup_model(
-            model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
-            fail_on_model_not_found=False,
-            model=Model(uri=str(tmpdir)),
-        )
+    mock_model.list.return_value = []
+    exported_model_resource_name, _ = lookup_model(
+        model_name="my-model",
+        project_location="europe-west4",
+        project_id="my-project-id",
+        order_models_by="create_time desc",
+        fail_on_model_not_found=False,
+        model=Model(uri=str(tmpdir)),
+    )
+
     print(exported_model_resource_name)
     assert exported_model_resource_name == ""
 
 
-def test_lookup_model_when_no_models_fail(tmpdir):
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model_when_no_models_fail(mock_model, tmpdir):
     """
     Checks that when there are no models and fail_on_model_found = True,
     lookup_model raises a RuntimeError.
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-        mock_model.list.return_value = []
+    mock_model.list.return_value = []
 
-        # Verify that a ValueError is raised
-        with pytest.raises(RuntimeError):
-            lookup_model(
-                model_name="my-model",
-                project_location="europe-west4",
-                project_id="my-project-id",
-                order_models_by="create_time desc",
-                fail_on_model_not_found=True,
-                model=Model(uri=str(tmpdir)),
-            )
+    # Verify that a ValueError is raised
+    with pytest.raises(RuntimeError):
+        lookup_model(
+            model_name="my-model",
+            project_location="europe-west4",
+            project_id="my-project-id",
+            order_models_by="create_time desc",
+            fail_on_model_not_found=True,
+            model=Model(uri=str(tmpdir)),
+        )
diff --git a/components/vertex-components/tests/test_model_batch_predict.py b/components/vertex-components/tests/test_model_batch_predict.py
index 10d9e808..76bca67d 100644
--- a/components/vertex-components/tests/test_model_batch_predict.py
+++ b/components/vertex-components/tests/test_model_batch_predict.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 import json
 import pytest
-from unittest.mock import Mock, patch
+from unittest import mock
 from kfp.v2.dsl import Model
 from google.cloud.aiplatform_v1beta1.types.job_state import JobState
 
@@ -30,7 +30,19 @@
     "targetField": "col",
 }
 
+mock_job1 = mock.Mock()
+mock_job1.name = "mock-batch-job"
+mock_job1.state = JobState.JOB_STATE_SUCCEEDED
 
+
+@mock.patch(
+    "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.create_batch_prediction_job",  # noqa : E501
+    return_value=mock_job1,
+)
+@mock.patch(
+    "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.get_batch_prediction_job",  # noqa : E501
+    return_value=mock_job1,
+)
 @pytest.mark.parametrize(
     (
         "source_format,destination_format,source_uri,monitoring_training_dataset,"
@@ -44,6 +56,8 @@
     ],
 )
 def test_model_batch_predict(
+    create_job,
+    get_job,
     tmpdir,
     source_format,
     destination_format,
@@ -55,37 +69,22 @@ def test_model_batch_predict(
     """
     Asserts model_batch_predict successfully creates requests given different arguments.
     """
-    mock_resource_name = "mock-batch-job"
-
-    mock_job1 = Mock()
-    mock_job1.name = mock_resource_name
-    mock_job1.state = JobState.JOB_STATE_SUCCEEDED
-
     mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
 
-    with patch(
-        "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.create_batch_prediction_job",  # noqa: E501
-        return_value=mock_job1,
-    ) as create_job, patch(
-        "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.get_batch_prediction_job",  # noqa: E501
-        return_value=mock_job1,
-    ) as get_job:
-        (gcp_resources,) = model_batch_predict(
-            model=mock_model,
-            job_display_name="",
-            project_location="",
-            project_id="",
-            source_uri=source_uri,
-            destination_uri=destination_format,
-            source_format=source_format,
-            destination_format=destination_format,
-            monitoring_training_dataset=monitoring_training_dataset,
-            monitoring_alert_email_addresses=monitoring_alert_email_addresses,
-            monitoring_skew_config=monitoring_skew_config,
-        )
+    (gcp_resources,) = model_batch_predict(
+        model=mock_model,
+        job_display_name="",
+        project_location="",
+        project_id="",
+        source_uri=source_uri,
+        destination_uri=destination_format,
+        source_format=source_format,
+        destination_format=destination_format,
+        monitoring_training_dataset=monitoring_training_dataset,
+        monitoring_alert_email_addresses=monitoring_alert_email_addresses,
+        monitoring_skew_config=monitoring_skew_config,
+    )
 
     create_job.assert_called_once()
     get_job.assert_called_once()
-    assert (
-        json.loads(gcp_resources)["resources"][0]["resourceUri"] == mock_resource_name
-    )
+    assert json.loads(gcp_resources)["resources"][0]["resourceUri"] == mock_job1.name
diff --git a/components/vertex-components/tests/test_update_best_model.py b/components/vertex-components/tests/test_update_best_model.py
index bce9a9df..4ef6ba21 100644
--- a/components/vertex-components/tests/test_update_best_model.py
+++ b/components/vertex-components/tests/test_update_best_model.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from unittest.mock import patch
+from unittest import mock
 
 from kfp.v2.dsl import Model
 
@@ -21,26 +21,31 @@
 update_best_model = vertex_components.update_best_model.python_func
 
 
-def test_model_batch_predict(tmpdir):
+@mock.patch("google.cloud.aiplatform.Model")
+@mock.patch("google.cloud.aiplatform.model_evaluation.ModelEvaluation")
+@mock.patch("google.cloud.aiplatform.models.ModelRegistry")
+@mock.patch("google.protobuf.json_format.MessageToDict")
+def test_model_batch_predict(
+    mock_message_to_dict,
+    mock_model_registry,
+    mock_model_evaluation,
+    mock_model_class,
+    tmpdir,
+):
     """
     Asserts model_batch_predict successfully creates requests given different arguments.
     """
     mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
     mock_message = {"metrics": {"rmse": 0.01}}
-
-    with patch("google.cloud.aiplatform.Model",), patch(
-        "google.cloud.aiplatform.model_evaluation.ModelEvaluation",
-    ), patch("google.cloud.aiplatform.models.ModelRegistry",), patch(
-        "google.protobuf.json_format.MessageToDict", return_value=mock_message
-    ):
-
-        (challenger_wins,) = update_best_model(
-            challenger=mock_model,
-            challenger_evaluation="",
-            parent_model="",
-            project_id="",
-            project_location="",
-            eval_metric="rmse",
-            eval_lower_is_better=True,
-        )
-        assert not challenger_wins
+    mock_message_to_dict.return_value = mock_message
+
+    (challenger_wins,) = update_best_model(
+        challenger=mock_model,
+        challenger_evaluation="",
+        parent_model="",
+        project_id="",
+        project_location="",
+        eval_metric="rmse",
+        eval_lower_is_better=True,
+    )
+    assert not challenger_wins

From be883a52798031a14540142b4d4e726b4321c8a0 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 12:09:16 +0100
Subject: [PATCH 031/238] build(Makefile): change all pipenv commands to poetry
 commands

---
 Makefile | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/Makefile b/Makefile
index 05a3c1e8..674e9f6a 100644
--- a/Makefile
+++ b/Makefile
@@ -20,24 +20,24 @@ help: ## Display this help screen
     
 pre-commit: ## Runs the pre-commit checks over entire repo
 	@cd pipelines && \
-	pipenv run pre-commit run --all-files
+	poetry run pre-commit run --all-files
 
 setup: ## Set up local environment for Python development on pipelines
-	@pip install pipenv && \
+	@pip install poetry && \
 	cd pipelines && \
-	pipenv install --dev
+	poetry install --dev
 
 test-trigger: ## Runs unit tests for the pipeline trigger code
 	@cd pipelines && \
-	pipenv run python -m pytest tests/trigger
+	poetry run python -m pytest tests/trigger
 
 compile-pipeline: ## Compile the pipeline to training.json or prediction.json. Must specify pipeline=<training|prediction>
 	@cd pipelines/src && \
-	pipenv run python -m pipelines.${PIPELINE_TEMPLATE}.${pipeline}.pipeline
+	poetry run python -m pipelines.${PIPELINE_TEMPLATE}.${pipeline}.pipeline
 
 setup-components: ## Run unit tests for a component group
 	@cd "components/${GROUP}" && \
-	pipenv install --dev
+	poetry install --dev
 
 setup-all-components: ## Run unit tests for all pipeline components
 	@set -e && \
@@ -48,7 +48,7 @@ setup-all-components: ## Run unit tests for all pipeline components
 
 test-components: ## Run unit tests for a component group
 	@cd "components/${GROUP}" && \
-	pipenv run pytest
+	poetry run pytest
 
 test-all-components: ## Run unit tests for all pipeline components
 	@set -e && \
@@ -69,7 +69,7 @@ run: ## Compile pipeline, copy assets to GCS, and run pipeline in sandbox enviro
 	@ $(MAKE) compile-pipeline && \
 	$(MAKE) sync-assets && \
 	cd pipelines/src && \
-	pipenv run python -m pipelines.trigger --template_path=./$(pipeline).json --enable_caching=$(enable_pipeline_caching)
+	poetry run python -m pipelines.trigger --template_path=./$(pipeline).json --enable_caching=$(enable_pipeline_caching)
 
 sync_assets ?= true
 e2e-tests: ## (Optionally) copy assets to GCS, and perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour). Optionally specify sync_assets=<true|false> (defaults to true)
@@ -79,7 +79,7 @@ e2e-tests: ## (Optionally) copy assets to GCS, and perform end-to-end (E2E) pipe
 		echo "Skipping syncing assets to GCS"; \
     fi && \
 	cd pipelines && \
-	pipenv run pytest --log-cli-level=INFO tests/${PIPELINE_TEMPLATE}/$(pipeline) --enable_caching=$(enable_pipeline_caching)
+	poetry run pytest --log-cli-level=INFO tests/${PIPELINE_TEMPLATE}/$(pipeline) --enable_caching=$(enable_pipeline_caching)
 
 env ?= dev
 deploy-infra: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)

From 170a746bf95634ff7eecc57e68c9970c52340696 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 13:47:27 +0100
Subject: [PATCH 032/238] style(pyproject.toml): correct authors description to
 string type

---
 pipelines/pyproject.toml | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 6ef6e2c2..0c5c74d6 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -1,9 +1,7 @@
 [tool.poetry]
 name = "pipelines"
 version = "0.1.0"
-authors = [
-    {name = "Example User", email = "user@example.com"},
-]
+authors = ["Example User <user@example.com>"]
 description = "Turbo Template"
 readme = "README.md"
 classifiers = [
@@ -43,4 +41,3 @@ pythonpath = [
 ]
 testpaths = "tests"
 junit_family = "xunit2"
-

From 5c3274f75d605b42b735184fcbc8cec440ffe9c4 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 13:55:51 +0100
Subject: [PATCH 033/238] build(Makefile): fix makefile setup instructions

---
 Makefile | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 674e9f6a..76c3f771 100644
--- a/Makefile
+++ b/Makefile
@@ -19,13 +19,14 @@ help: ## Display this help screen
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
     
 pre-commit: ## Runs the pre-commit checks over entire repo
+	@pip install pre-commit \
 	@cd pipelines && \
 	poetry run pre-commit run --all-files
 
 setup: ## Set up local environment for Python development on pipelines
 	@pip install poetry && \
 	cd pipelines && \
-	poetry install --dev
+	poetry install --with dev 
 
 test-trigger: ## Runs unit tests for the pipeline trigger code
 	@cd pipelines && \

From 9ede2582114c5716d74aadd5cfd3fb8b3416ebb1 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 14:45:36 +0100
Subject: [PATCH 034/238] build(Makefile): fix pr-commit issue

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 76c3f771..910dc0b8 100644
--- a/Makefile
+++ b/Makefile
@@ -20,7 +20,7 @@ help: ## Display this help screen
     
 pre-commit: ## Runs the pre-commit checks over entire repo
 	@pip install pre-commit \
-	@cd pipelines && \
+	cd pipelines && \
 	poetry run pre-commit run --all-files
 
 setup: ## Set up local environment for Python development on pipelines

From a5d5d8508b272e38bb6e961838faf4d8ad85e0dd Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 23 May 2023 15:06:13 +0100
Subject: [PATCH 035/238] feat: changes to release ci

---
 cloudbuild/release.yaml | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 4a48a1f7..bf771d5b 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -21,7 +21,6 @@ steps:
       - -c
       - |
         make setup && \
-        make compile-all-components && \
         make compile-pipeline pipeline=training && \
         make compile-pipeline pipeline=prediction
     env:
@@ -36,8 +35,8 @@ steps:
       - -c
       - |
         mkdir -p ${TAG_NAME}/assets && \
-        cp pipelines/training.json ${TAG_NAME}/training.json && \
-        cp pipelines/prediction.json ${TAG_NAME}/prediction.json && \
+        cp pipelines/src/training.json ${TAG_NAME}/training.json && \
+        cp pipelines/src/prediction.json ${TAG_NAME}/prediction.json && \
         cp -r pipelines/assets ${TAG_NAME}/assets && \
         for dest in ${_PIPELINE_PUBLISH_GCS_PATHS} ; do \
           gsutil cp -r ${TAG_NAME} $$dest ; \

From 7cf5b167474fe124b7a637b405d8518ef4c79bf0 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 15:20:33 +0100
Subject: [PATCH 036/238] build(Makefile): fix pre-commit checks

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 910dc0b8..ed496716 100644
--- a/Makefile
+++ b/Makefile
@@ -19,7 +19,7 @@ help: ## Display this help screen
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
     
 pre-commit: ## Runs the pre-commit checks over entire repo
-	@pip install pre-commit \
+	@pip install pre-commit && \
 	cd pipelines && \
 	poetry run pre-commit run --all-files
 

From 68c648486141b64f8f388e99c15e18b125054b04 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 15:23:45 +0100
Subject: [PATCH 037/238] build(Makefile): fix pre-commit issue

---
 Makefile | 1 -
 1 file changed, 1 deletion(-)

diff --git a/Makefile b/Makefile
index ed496716..f342554d 100644
--- a/Makefile
+++ b/Makefile
@@ -19,7 +19,6 @@ help: ## Display this help screen
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
     
 pre-commit: ## Runs the pre-commit checks over entire repo
-	@pip install pre-commit && \
 	cd pipelines && \
 	poetry run pre-commit run --all-files
 

From d40d879777ca9989a704c00f082ffdaeee0ebf6e Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 23 May 2023 15:36:24 +0100
Subject: [PATCH 038/238] feat: fix nested assets folder in release

---
 cloudbuild/release.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index bf771d5b..0f262a52 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -37,7 +37,7 @@ steps:
         mkdir -p ${TAG_NAME}/assets && \
         cp pipelines/src/training.json ${TAG_NAME}/training.json && \
         cp pipelines/src/prediction.json ${TAG_NAME}/prediction.json && \
-        cp -r pipelines/assets ${TAG_NAME}/assets && \
+        cp -r pipelines/assets/* ${TAG_NAME}/assets/ && \
         for dest in ${_PIPELINE_PUBLISH_GCS_PATHS} ; do \
           gsutil cp -r ${TAG_NAME} $$dest ; \
         done

From b9faf753ad4bfea40d4c82959621a109981a15af Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 15:37:12 +0100
Subject: [PATCH 039/238] build(.pre-commit-config.yaml): update from python
 3.7 to 3.9

---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 3bd0bc1e..66dc32d3 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -14,7 +14,7 @@
 
 ---
 default_language_version:
-  python: python3.7
+  python: python3.9
 
 repos:
   - repo: https://github.com/gruntwork-io/pre-commit

From 610bbd341cf93ebdb989bed8967cec8963944e08 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 16:26:10 +0100
Subject: [PATCH 040/238] refactor(.pre-commit-config.yaml): fix pre-commit
 hooks

---
 .pre-commit-config.yaml | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 66dc32d3..a3212993 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -32,10 +32,10 @@ repos:
       - id: no-commit-to-branch
         args: [--branch, main]
 
-  - repo: https://github.com/jumanjihouse/pre-commit-hooks
-    rev: 1.11.0
-    hooks:
-      - id: git-dirty
+  # - repo: https://github.com/jumanjihouse/pre-commit-hooks
+  #   rev: 1.11.0
+  #   hooks:
+  #     - id: git-dirty
 
   - repo: https://github.com/adrienverge/yamllint.git
     rev: v1.26.3

From 5bdad5a3e5627c9fd8d354da4d33341ea0c31d19 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 16:29:28 +0100
Subject: [PATCH 041/238] refactor(.pre-commit-config.yaml): fix pre-commit

---
 .pre-commit-config.yaml | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index a3212993..66dc32d3 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -32,10 +32,10 @@ repos:
       - id: no-commit-to-branch
         args: [--branch, main]
 
-  # - repo: https://github.com/jumanjihouse/pre-commit-hooks
-  #   rev: 1.11.0
-  #   hooks:
-  #     - id: git-dirty
+  - repo: https://github.com/jumanjihouse/pre-commit-hooks
+    rev: 1.11.0
+    hooks:
+      - id: git-dirty
 
   - repo: https://github.com/adrienverge/yamllint.git
     rev: v1.26.3

From ff14b8ce53596f5a8c9f0fe73f4a50c65aacb486 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 23 May 2023 16:33:11 +0100
Subject: [PATCH 042/238] feat: delete assets

---
 .../tensorflow/prediction/assets/.gitkeep     |   0
 .../training/assets/train_tf_model.py         | 299 ------------------
 .../xgboost/prediction/assets/.gitkeep        |   0
 .../xgboost/training/assets/.gitkeep          |   0
 .../training/assets/train_xgb_model.py        | 142 ---------
 5 files changed, 441 deletions(-)
 delete mode 100644 pipelines/src/pipelines/tensorflow/prediction/assets/.gitkeep
 delete mode 100644 pipelines/src/pipelines/tensorflow/training/assets/train_tf_model.py
 delete mode 100644 pipelines/src/pipelines/xgboost/prediction/assets/.gitkeep
 delete mode 100644 pipelines/src/pipelines/xgboost/training/assets/.gitkeep
 delete mode 100644 pipelines/src/pipelines/xgboost/training/assets/train_xgb_model.py

diff --git a/pipelines/src/pipelines/tensorflow/prediction/assets/.gitkeep b/pipelines/src/pipelines/tensorflow/prediction/assets/.gitkeep
deleted file mode 100644
index e69de29b..00000000
diff --git a/pipelines/src/pipelines/tensorflow/training/assets/train_tf_model.py b/pipelines/src/pipelines/tensorflow/training/assets/train_tf_model.py
deleted file mode 100644
index 5d164ae7..00000000
--- a/pipelines/src/pipelines/tensorflow/training/assets/train_tf_model.py
+++ /dev/null
@@ -1,299 +0,0 @@
-import argparse
-import os
-import json
-import logging
-import sys
-
-import tensorflow as tf
-from pathlib import Path
-from tensorflow.data import Dataset
-from tensorflow.keras import Input, Model, optimizers
-from tensorflow.keras.layers import Dense, Normalization, StringLookup, Concatenate
-
-# used for monitoring during prediction time
-TRAINING_DATASET_INFO = "training_dataset.json"
-# numeric/categorical features in Chicago trips dataset to be preprocessed
-NUM_COLS = ["dayofweek", "hourofday", "trip_distance", "trip_miles", "trip_seconds"]
-ORD_COLS = ["company"]
-OHE_COLS = ["payment_type"]
-DEFAULT_HPARAMS = dict(
-    batch_size=100,
-    epochs=1,
-    loss_fn="MeanSquaredError",
-    optimizer="Adam",
-    learning_rate=0.001,
-    metrics=[
-        "RootMeanSquaredError",
-        "MeanAbsoluteError",
-        "MeanAbsolutePercentageError",
-        "MeanSquaredLogarithmicError",
-    ],
-    hidden_units=[(10, "relu")],
-    distribute_strategy="single",
-    early_stopping_epochs=5,
-    label="total_fare",
-)
-
-logging.getLogger().setLevel(logging.INFO)
-
-
-def create_dataset(input_data: Path, label_name: str, model_params: dict) -> Dataset:
-    """Create a TF Dataset from input csv files.
-    Args:
-        input_data (Input[Dataset]): Train/Valid data in CSV format
-        label_name (str): Name of column containing the labels
-        model_params (dict): model parameters
-        file_pattern (str): Read data from one or more files. If empty, then
-            training and validation data is read from single file respectively.
-            For multiple files, use a pattern e.g. "files-*.csv".
-    Returns:
-        dataset (TF Dataset): TF dataset where each element is a (features, labels)
-            tuple that corresponds to a batch of CSV rows
-    """
-
-    # shuffle & shuffle_buffer_size added to rearrange input data
-    # passed into model training
-    # num_rows_for_inference is for auto detection of datatypes
-    # while creating the dataset.
-    # If a float column has a high proportion of integer values (0/1 etc),
-    # the method wrongly detects it as a tf.int32 which fails during training time,
-    # hence the high hardcoded value (default is 100)
-
-    # Apply data sharding: Sharded elements are produced by the dataset
-    # Each worker will process the whole dataset and discard the portion that is
-    # not for itself. Note that for this mode to correctly partitions the dataset
-    # elements, the dataset needs to produce elements in a deterministic order.
-    data_options = tf.data.Options()
-    data_options.experimental_distribute.auto_shard_policy = (
-        tf.data.experimental.AutoShardPolicy.DATA
-    )
-
-    logging.info(f"Creating dataset from CSV file(s) at {input_data}...")
-    created_dataset = tf.data.experimental.make_csv_dataset(
-        file_pattern=str(input_data),
-        batch_size=model_params["batch_size"],
-        label_name=label_name,
-        num_epochs=model_params["epochs"],
-        shuffle=True,
-        shuffle_buffer_size=1000,
-        num_rows_for_inference=20000,
-    )
-    return created_dataset.with_options(data_options)
-
-
-def get_distribution_strategy(distribute_strategy: str) -> tf.distribute.Strategy:
-    """Set distribute strategy based on input string.
-    Args:
-        distribute_strategy (str): single, mirror or multi
-    Returns:
-        strategy (tf.distribute.Strategy): distribution strategy
-    """
-    logging.info(f"Distribution strategy: {distribute_strategy}")
-
-    # Single machine, single compute device
-    if distribute_strategy == "single":
-        if len(tf.config.list_physical_devices("GPU")):
-            strategy = tf.distribute.OneDeviceStrategy(device="/gpu:0")
-        else:
-            strategy = tf.distribute.OneDeviceStrategy(device="/cpu:0")
-    # Single machine, multiple compute device
-    elif distribute_strategy == "mirror":
-        strategy = tf.distribute.MirroredStrategy()
-    # Multiple machine, multiple compute device
-    elif distribute_strategy == "multi":
-        strategy = tf.distribute.MultiWorkerMirroredStrategy()
-    else:
-        raise RuntimeError(f"Distribute strategy: {distribute_strategy} not supported")
-    return strategy
-
-
-def normalization(name: str, dataset: Dataset) -> Normalization:
-    """Create a Normalization layer for a feature.
-    Args:
-        name (str): name of feature to be normalized
-        dataset (Dataset): dataset to adapt layer
-    Returns:
-        normalization layer (Normalization): adapted normalization layer
-            of shape (?,1)
-    """
-    logging.info(f"Normalizing numerical input '{name}'...")
-    x = Normalization(axis=None, name=f"normalize_{name}")
-    x.adapt(dataset.map(lambda y, _: y[name]))
-    return x
-
-
-def str_lookup(name: str, dataset: Dataset, output_mode: str) -> StringLookup:
-    """Create a StringLookup layer for a feature.
-    Args:
-        name (str): name of feature to be encoded
-        dataset (Dataset): dataset to adapt layer
-        output_mode (str): argument for StringLookup layer (e.g. 'one_hot', 'int')
-    Returns:
-        StringLookup layer (StringLookup): adapted StringLookup layer of shape (?,X)
-    """
-    logging.info(f"Encoding categorical input '{name}' ({output_mode})...")
-    x = StringLookup(output_mode=output_mode, name=f"str_lookup_{output_mode}_{name}")
-    x.adapt(dataset.map(lambda y, _: y[name]))
-    logging.info(f"Vocabulary: {x.get_vocabulary()}")
-    return x
-
-
-def build_and_compile_model(dataset: Dataset, model_params: dict) -> Model:
-    """Build and compile model.
-    Args:
-        dataset (Dataset): training dataset
-        model_params (dict): model parameters
-    Returns:
-        model (Model): built and compiled model
-    """
-
-    # create inputs (scalars with shape `()`)
-    num_ins = {name: Input(shape=(), name=name, dtype=tf.float32) for name in NUM_COLS}
-    ord_ins = {name: Input(shape=(), name=name, dtype=tf.string) for name in ORD_COLS}
-    cat_ins = {name: Input(shape=(), name=name, dtype=tf.string) for name in OHE_COLS}
-
-    # join all inputs and expand by 1 dimension. NOTE: this is useful when passing
-    # in scalar inputs to a model in Vertex AI batch predictions or endpoints e.g.
-    # `{"instances": {"input1": 1.0, "input2": "str"}}` instead of
-    # `{"instances": {"input1": [1.0], "input2": ["str"]}`
-    all_ins = {**num_ins, **ord_ins, **cat_ins}
-    exp_ins = {n: tf.expand_dims(i, axis=-1) for n, i in all_ins.items()}
-
-    # preprocess expanded inputs
-    num_encoded = [normalization(n, dataset)(exp_ins[n]) for n in NUM_COLS]
-    ord_encoded = [str_lookup(n, dataset, "int")(exp_ins[n]) for n in ORD_COLS]
-    ohe_encoded = [str_lookup(n, dataset, "one_hot")(exp_ins[n]) for n in OHE_COLS]
-
-    # ensure ordinal encoded layers is of type float32 (like the other layers)
-    ord_encoded = [tf.cast(x, tf.float32) for x in ord_encoded]
-
-    # concat encoded inputs and add dense layers including output layer
-    x = num_encoded + ord_encoded + ohe_encoded
-    x = Concatenate()(x)
-    for units, activation in model_params["hidden_units"]:
-        x = Dense(units, activation=activation)(x)
-    x = Dense(1, name="output", activation="linear")(x)
-
-    model = Model(inputs=all_ins, outputs=x, name="nn_model")
-    model.summary()
-
-    logging.info(f"Use optimizer {model_params['optimizer']}")
-    optimizer = optimizers.get(model_params["optimizer"])
-    optimizer.learning_rate = model_params["learning_rate"]
-
-    model.compile(
-        loss=model_params["loss_fn"],
-        optimizer=optimizer,
-        metrics=model_params["metrics"],
-    )
-
-    return model
-
-
-def _is_chief(strategy: tf.distribute.Strategy) -> bool:
-    """Determine whether current worker is the chief (master). See more info:
-    - https://www.tensorflow.org/tutorials/distribute/multi_worker_with_keras
-    - https://www.tensorflow.org/api_docs/python/tf/distribute/cluster_resolver/ClusterResolver # noqa: E501
-    Args:
-        strategy (tf.distribute.Strategy): strategy
-    Returns:
-        is_chief (bool): True if worker is chief, otherwise False
-    """
-    cr = strategy.cluster_resolver
-    return (cr is None) or (cr.task_type == "chief" and cr.task_id == 0)
-
-
-def _get_temp_dir(dirpath, task_id):
-    base_dirpath = "workertemp_" + str(task_id)
-    temp_dir = os.path.join(dirpath, base_dirpath)
-    tf.io.gfile.makedirs(temp_dir)
-    return temp_dir
-
-
-parser = argparse.ArgumentParser()
-parser.add_argument("--train_data", type=str, required=True)
-parser.add_argument("--valid_data", type=str, required=True)
-parser.add_argument("--test_data", type=str, required=True)
-parser.add_argument("--model", default=os.getenv("AIP_MODEL_DIR"), type=str, help="")
-parser.add_argument("--metrics", type=str, required=True)
-parser.add_argument("--hparams", default={}, type=json.loads)
-args = parser.parse_args()
-
-if args.model.startswith("gs://"):
-    args.model = Path("/gcs/" + args.model[5:])
-
-# merge dictionaries by overwriting default_model_params if provided in model_params
-hparams = {**DEFAULT_HPARAMS, **args.hparams}
-logging.info(f"Using model hyper-parameters: {hparams}")
-label = hparams["label"]
-
-# Set distribute strategy before any TF operations
-strategy = get_distribution_strategy(hparams["distribute_strategy"])
-
-train_ds = create_dataset(Path(args.train_data), label, hparams)
-valid_ds = create_dataset(Path(args.valid_data), label, hparams)
-test_ds = create_dataset(Path(args.test_data), label, hparams)
-
-train_features = list(train_ds.element_spec[0].keys())
-valid_features = list(valid_ds.element_spec[0].keys())
-logging.info(f"Training feature names: {train_features}")
-logging.info(f"Validation feature names: {valid_features}")
-
-if len(train_features) != len(valid_features):
-    raise RuntimeError(f"No. of training features != # validation features")
-
-with strategy.scope():
-    tf_model = build_and_compile_model(train_ds, hparams)
-
-logging.info("Use early stopping")
-callback = tf.keras.callbacks.EarlyStopping(
-    monitor="loss", mode="min", patience=hparams["early_stopping_epochs"]
-)
-
-logging.info("Fit model...")
-history = tf_model.fit(
-    train_ds,
-    batch_size=hparams["batch_size"],
-    epochs=hparams["epochs"],
-    validation_data=valid_ds,
-    callbacks=[callback],
-)
-
-# only persist output files if current worker is chief
-if not _is_chief(strategy):
-    logging.info("not chief node, exiting now")
-    sys.exit()
-
-logging.info(f"Save model to: {args.model}")
-args.model.mkdir(parents=True)
-tf_model.save(str(args.model), save_format="tf")
-
-logging.info(f"Save metrics to: {args.metrics}")
-eval_metrics = dict(zip(tf_model.metrics_names, tf_model.evaluate(test_ds)))
-
-metrics = {
-    "problemType": "regression",
-    "rootMeanSquaredError": eval_metrics["root_mean_squared_error"],
-    "meanAbsoluteError": eval_metrics["mean_absolute_error"],
-    "meanAbsolutePercentageError": eval_metrics["mean_absolute_percentage_error"],
-    "rSquared": None,
-    "rootMeanSquaredLogError": eval_metrics["mean_squared_logarithmic_error"],
-}
-
-with open(args.metrics, "w") as fp:
-    json.dump(metrics, fp)
-
-# Persist URIs of training file(s) for model monitoring in batch predictions
-# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
-# for the expected schema.
-path = args.model / TRAINING_DATASET_INFO
-training_dataset_for_monitoring = {
-    "gcsSource": {"uris": [args.train_data]},
-    "dataFormat": "csv",
-    "targetField": label,
-}
-logging.info(f"Save training dataset info for model monitoring: {path}")
-logging.info(f"Training dataset: {training_dataset_for_monitoring}")
-
-with open(path, "w") as fp:
-    json.dump(training_dataset_for_monitoring, fp)
diff --git a/pipelines/src/pipelines/xgboost/prediction/assets/.gitkeep b/pipelines/src/pipelines/xgboost/prediction/assets/.gitkeep
deleted file mode 100644
index e69de29b..00000000
diff --git a/pipelines/src/pipelines/xgboost/training/assets/.gitkeep b/pipelines/src/pipelines/xgboost/training/assets/.gitkeep
deleted file mode 100644
index e69de29b..00000000
diff --git a/pipelines/src/pipelines/xgboost/training/assets/train_xgb_model.py b/pipelines/src/pipelines/xgboost/training/assets/train_xgb_model.py
deleted file mode 100644
index 71cc65b5..00000000
--- a/pipelines/src/pipelines/xgboost/training/assets/train_xgb_model.py
+++ /dev/null
@@ -1,142 +0,0 @@
-import argparse
-from pathlib import Path
-
-import joblib
-import json
-import os
-import logging
-
-import numpy as np
-import pandas as pd
-from sklearn import metrics
-from sklearn.compose import ColumnTransformer
-from sklearn.pipeline import Pipeline
-from sklearn.preprocessing import StandardScaler, OrdinalEncoder, OneHotEncoder
-from xgboost import XGBRegressor
-
-logging.basicConfig(level=logging.DEBUG)
-
-# used for monitoring during prediction time
-TRAINING_DATASET_INFO = "training_dataset.json"
-# numeric/categorical features in Chicago trips dataset to be preprocessed
-NUM_COLS = ["dayofweek", "hourofday", "trip_distance", "trip_miles", "trip_seconds"]
-ORD_COLS = ["company"]
-OHE_COLS = ["payment_type"]
-
-
-def split_xy(df: pd.DataFrame, label: str) -> (pd.DataFrame, pd.Series):
-    """Split dataframe into X and y."""
-    return df.drop(columns=[label]), df[label]
-
-
-def indices_in_list(elements: list, base_list: list) -> list:
-    """Get indices of specific elements in a base list"""
-    return [idx for idx, elem in enumerate(base_list) if elem in elements]
-
-
-parser = argparse.ArgumentParser()
-parser.add_argument("--train_data", type=str, required=True)
-parser.add_argument("--valid_data", type=str, required=True)
-parser.add_argument("--test_data", type=str, required=True)
-parser.add_argument("--model", default=os.getenv("AIP_MODEL_DIR"), type=str, help="")
-parser.add_argument("--metrics", type=str, required=True)
-parser.add_argument("--hparams", default={}, type=json.loads)
-args = parser.parse_args()
-
-if args.model.startswith("gs://"):
-    args.model = Path("/gcs/" + args.model[5:])
-
-logging.info("Read csv files into dataframes")
-df_train = pd.read_csv(args.train_data)
-df_valid = pd.read_csv(args.valid_data)
-df_test = pd.read_csv(args.test_data)
-
-logging.info("Split dataframes")
-label = args.hparams["label"]
-X_train, y_train = split_xy(df_train, label)
-X_valid, y_valid = split_xy(df_valid, label)
-X_test, y_test = split_xy(df_test, label)
-
-logging.info("Get the number of unique categories for ordinal encoded columns")
-ordinal_columns = X_train[ORD_COLS]
-n_unique_cat = ordinal_columns.nunique()
-
-logging.info("Get indices of columns in base data")
-col_list = X_train.columns.tolist()
-num_indices = indices_in_list(NUM_COLS, col_list)
-cat_indices_onehot = indices_in_list(OHE_COLS, col_list)
-cat_indices_ordinal = indices_in_list(ORD_COLS, col_list)
-
-ordinal_transformers = [
-    (
-        f"ordinal encoding for {ord_col}",
-        OrdinalEncoder(
-            handle_unknown="use_encoded_value", unknown_value=n_unique_cat[ord_col]
-        ),
-        [ord_index],
-    )
-    for ord_col in ORD_COLS
-    for ord_index in cat_indices_ordinal
-]
-all_transformers = [
-    ("numeric_scaling", StandardScaler(), num_indices),
-    (
-        "one_hot_encoding",
-        OneHotEncoder(handle_unknown="ignore"),
-        cat_indices_onehot,
-    ),
-] + ordinal_transformers
-
-logging.info("Build sklearn preprocessing steps")
-preprocesser = ColumnTransformer(transformers=all_transformers)
-logging.info("Build sklearn pipeline with XGBoost model")
-xgb_model = XGBRegressor(**args.hparams)
-
-pipeline = Pipeline(
-    steps=[("feature_engineering", preprocesser), ("train_model", xgb_model)]
-)
-
-logging.info("Transform validation data")
-valid_preprocesser = preprocesser.fit(X_train)
-X_valid_transformed = valid_preprocesser.transform(X_valid)
-
-logging.info("Fit model")
-pipeline.fit(X_train, y_train, train_model__eval_set=[(X_valid_transformed, y_valid)])
-
-logging.info("Predict test data")
-y_pred = pipeline.predict(X_test)
-y_pred = y_pred.clip(0)
-
-metrics = {
-    "problemType": "regression",
-    "rootMeanSquaredError": np.sqrt(metrics.mean_squared_error(y_test, y_pred)),
-    "meanAbsoluteError": metrics.mean_absolute_error(y_test, y_pred),
-    "meanAbsolutePercentageError": metrics.mean_absolute_percentage_error(
-        y_test, y_pred
-    ),
-    "rSquared": metrics.r2_score(y_test, y_pred),
-    "rootMeanSquaredLogError": np.sqrt(metrics.mean_squared_log_error(y_test, y_pred)),
-}
-
-logging.info(f"Save model to: {args.model}")
-args.model.mkdir(parents=True)
-joblib.dump(pipeline, str(args.model / "model.joblib"))
-
-logging.info(f"Metrics: {metrics}")
-with open(args.metrics, "w") as fp:
-    json.dump(metrics, fp)
-
-# Persist URIs of training file(s) for model monitoring in batch predictions
-# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
-# for the expected schema.
-path = args.model / TRAINING_DATASET_INFO
-training_dataset_for_monitoring = {
-    "gcsSource": {"uris": [args.train_data]},
-    "dataFormat": "csv",
-    "targetField": label,
-}
-logging.info(f"Training dataset info: {training_dataset_for_monitoring}")
-
-with open(path, "w") as fp:
-    logging.info(f"Save training dataset info for model monitoring: {path}")
-    json.dump(training_dataset_for_monitoring, fp)

From ee301889d7aeb2662c2b2b841a373294b62bc60e Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 23 May 2023 17:34:33 +0100
Subject: [PATCH 043/238] feat: assets files

---
 pipelines/assets/train_tf_model.py  | 13 +++++++----
 pipelines/assets/train_xgb_model.py | 35 +++++++++++++++++++++--------
 2 files changed, 35 insertions(+), 13 deletions(-)

diff --git a/pipelines/assets/train_tf_model.py b/pipelines/assets/train_tf_model.py
index c89a7880..5d164ae7 100644
--- a/pipelines/assets/train_tf_model.py
+++ b/pipelines/assets/train_tf_model.py
@@ -219,6 +219,9 @@ def _get_temp_dir(dirpath, task_id):
 parser.add_argument("--hparams", default={}, type=json.loads)
 args = parser.parse_args()
 
+if args.model.startswith("gs://"):
+    args.model = Path("/gcs/" + args.model[5:])
+
 # merge dictionaries by overwriting default_model_params if provided in model_params
 hparams = {**DEFAULT_HPARAMS, **args.hparams}
 logging.info(f"Using model hyper-parameters: {hparams}")
@@ -261,9 +264,9 @@ def _get_temp_dir(dirpath, task_id):
     logging.info("not chief node, exiting now")
     sys.exit()
 
-os.makedirs(args.model, exist_ok=True)
 logging.info(f"Save model to: {args.model}")
-tf_model.save(args.model, save_format="tf")
+args.model.mkdir(parents=True)
+tf_model.save(str(args.model), save_format="tf")
 
 logging.info(f"Save metrics to: {args.metrics}")
 eval_metrics = dict(zip(tf_model.metrics_names, tf_model.evaluate(test_ds)))
@@ -281,11 +284,13 @@ def _get_temp_dir(dirpath, task_id):
     json.dump(metrics, fp)
 
 # Persist URIs of training file(s) for model monitoring in batch predictions
-path = Path(args.model) / TRAINING_DATASET_INFO
+# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
+# for the expected schema.
+path = args.model / TRAINING_DATASET_INFO
 training_dataset_for_monitoring = {
     "gcsSource": {"uris": [args.train_data]},
     "dataFormat": "csv",
-    "targetField": hparams["label"],
+    "targetField": label,
 }
 logging.info(f"Save training dataset info for model monitoring: {path}")
 logging.info(f"Training dataset: {training_dataset_for_monitoring}")
diff --git a/pipelines/assets/train_xgb_model.py b/pipelines/assets/train_xgb_model.py
index 31d95247..71cc65b5 100644
--- a/pipelines/assets/train_xgb_model.py
+++ b/pipelines/assets/train_xgb_model.py
@@ -1,4 +1,6 @@
 import argparse
+from pathlib import Path
+
 import joblib
 import json
 import os
@@ -14,7 +16,9 @@
 
 logging.basicConfig(level=logging.DEBUG)
 
-
+# used for monitoring during prediction time
+TRAINING_DATASET_INFO = "training_dataset.json"
+# numeric/categorical features in Chicago trips dataset to be preprocessed
 NUM_COLS = ["dayofweek", "hourofday", "trip_distance", "trip_miles", "trip_seconds"]
 ORD_COLS = ["company"]
 OHE_COLS = ["payment_type"]
@@ -39,6 +43,9 @@ def indices_in_list(elements: list, base_list: list) -> list:
 parser.add_argument("--hparams", default={}, type=json.loads)
 args = parser.parse_args()
 
+if args.model.startswith("gs://"):
+    args.model = Path("/gcs/" + args.model[5:])
+
 logging.info("Read csv files into dataframes")
 df_train = pd.read_csv(args.train_data)
 df_valid = pd.read_csv(args.valid_data)
@@ -111,15 +118,25 @@ def indices_in_list(elements: list, base_list: list) -> list:
     "rootMeanSquaredLogError": np.sqrt(metrics.mean_squared_log_error(y_test, y_pred)),
 }
 
-try:
-    model_path = args.model.replace("gs://", "/gcs/")
-    logging.info(f"Save model to: {model_path}")
-    os.makedirs(model_path, exist_ok=True)
-    joblib.dump(pipeline, model_path + "model.joblib")
-except Exception as e:
-    print(e)
-    raise e
+logging.info(f"Save model to: {args.model}")
+args.model.mkdir(parents=True)
+joblib.dump(pipeline, str(args.model / "model.joblib"))
 
 logging.info(f"Metrics: {metrics}")
 with open(args.metrics, "w") as fp:
     json.dump(metrics, fp)
+
+# Persist URIs of training file(s) for model monitoring in batch predictions
+# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
+# for the expected schema.
+path = args.model / TRAINING_DATASET_INFO
+training_dataset_for_monitoring = {
+    "gcsSource": {"uris": [args.train_data]},
+    "dataFormat": "csv",
+    "targetField": label,
+}
+logging.info(f"Training dataset info: {training_dataset_for_monitoring}")
+
+with open(path, "w") as fp:
+    logging.info(f"Save training dataset info for model monitoring: {path}")
+    json.dump(training_dataset_for_monitoring, fp)

From 95d44f827188f26191f694c0da98726eb87e4e94 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 23 May 2023 19:55:35 +0100
Subject: [PATCH 044/238] style(pyproject.toml): change author description to
 string format

---
 components/bigquery-components/pyproject.toml |  4 +-
 components/vertex-components/pyproject.toml   |  5 +-
 pipelines/poetry.lock                         | 55 ++++---------------
 pipelines/pyproject.toml                      |  2 +
 4 files changed, 14 insertions(+), 52 deletions(-)

diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index 3a51450a..efeaa9f6 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -1,9 +1,7 @@
 [tool.poetry]
 name = "bigquery-components"
 version = "0.1.0"
-authors = [
-    {name = "Example User", email = "user@example.com"},
-]
+authors = ["Example User <user@example.com>"]
 description = "Bigquery components for vertex pipelines"
 readme = "README.md"
 classifiers = [
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index e6dc1afd..37374cff 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -1,9 +1,7 @@
 [tool.poetry]
 name = "vertex-components"
 version = "0.1.0"
-authors = [
-    {name = "Example User", email = "user@example.com"},
-]
+authors = ["Example User <user@example.com>"]
 description = "KFP components for interacting with Vertex AI"
 readme = "README.md"
 classifiers = [
@@ -43,4 +41,3 @@ pythonpath = [
 ]
 testpaths = "tests"
 junit_family = "xunit2"
-
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index 3c0c989a..62a8d667 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -237,7 +237,7 @@ files = [
 name = "exceptiongroup"
 version = "1.1.1"
 description = "Backport of PEP 654 (exception groups)"
-category = "dev"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -281,14 +281,14 @@ termcolor = "*"
 
 [[package]]
 name = "google-api-core"
-version = "2.10.2"
+version = "1.34.0"
 description = "Google API client core library"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.10.2.tar.gz", hash = "sha256:10c06f7739fe57781f87523375e8e1a3a4674bf6392cd6131a3222182b971320"},
-    {file = "google_api_core-2.10.2-py3-none-any.whl", hash = "sha256:34f24bd1d5f72a8c4519773d99ca6bf080a6c4e041b4e9f024fe230191dda62e"},
+    {file = "google-api-core-1.34.0.tar.gz", hash = "sha256:6fb380f49d19ee1d09a9722d0379042b7edb06c0112e4796c7a395078a043e71"},
+    {file = "google_api_core-1.34.0-py3-none-any.whl", hash = "sha256:7421474c39d396a74dfa317dddbc69188f2336835f526087c7648f91105e32ff"},
 ]
 
 [package.dependencies]
@@ -296,7 +296,7 @@ google-auth = ">=1.25.0,<3.0dev"
 googleapis-common-protos = ">=1.56.2,<2.0dev"
 grpcio = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
 grpcio-status = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.0.0dev"
 requests = ">=2.18.0,<3.0.0dev"
 
 [package.extras]
@@ -488,23 +488,6 @@ google-auth = ">=1.25.0,<3.0dev"
 [package.extras]
 grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
-[[package]]
-name = "google-cloud-notebooks"
-version = "1.4.4"
-description = ""
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "google-cloud-notebooks-1.4.4.tar.gz", hash = "sha256:76c1c21f2328c0777c4b0333d1a9adbeeea94cfc9af25fe589bef00a9dae41cd"},
-    {file = "google_cloud_notebooks-1.4.4-py2.py3-none-any.whl", hash = "sha256:b0204d26663df0e460cd4158d6d0747e9e16d70c607e4da99572a77b51cf2e8d"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.32.0,<2.0.0 || >=2.8.0,<3.0.0dev", extras = ["grpc"]}
-proto-plus = ">=1.22.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-
 [[package]]
 name = "google-cloud-notebooks"
 version = "1.7.0"
@@ -550,24 +533,6 @@ protobuf = ">=3.19.0,<4.0.0dev"
 [package.extras]
 tests = ["flake8 (>=3.0.0)", "google-api-core (>=1.31.5,<2.0.0 || >=2.8.0,<3.0.0dev)", "google-cloud-aiplatform (>=1.14.0,<2)", "google-cloud-notebooks (>=0.4.0)", "google-cloud-storage (>=2.2.1,<3)", "googleapis-common-protos (>=1.56.2,<2.0dev)", "grpcio-status (<=1.47.0)", "kfp (>=1.8.9,<2.0.0)", "mock (>=4.0.0)", "protobuf (>=3.19.0,<4.0.0dev)", "pytest (>=6.0.0)"]
 
-[[package]]
-name = "google-cloud-resource-manager"
-version = "1.6.3"
-description = "Google Cloud Resource Manager API client library"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "google-cloud-resource-manager-1.6.3.tar.gz", hash = "sha256:6cf8a9a74e65a03857896967c79307b75805c752ade3bc41224e6167774bc9c9"},
-    {file = "google_cloud_resource_manager-1.6.3-py2.py3-none-any.whl", hash = "sha256:e330883c53c5e3e38a651da85ae0bce201a736b5cd5f9df10941160c6a66ce6e"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.32.0,<2.0.0 || >=2.8.0,<3.0.0dev", extras = ["grpc"]}
-grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
-proto-plus = ">=1.22.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-
 [[package]]
 name = "google-cloud-resource-manager"
 version = "1.10.0"
@@ -868,7 +833,7 @@ files = [
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "dev"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1135,7 +1100,7 @@ test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.3.1)", "pytest-
 name = "pluggy"
 version = "1.0.0"
 description = "plugin and hook calling mechanisms for python"
-category = "dev"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1352,7 +1317,7 @@ files = [
 name = "pytest"
 version = "7.3.1"
 description = "pytest: simple powerful testing with Python"
-category = "dev"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1630,7 +1595,7 @@ tests = ["pytest", "pytest-cov"]
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
-category = "dev"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1842,4 +1807,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "61dd42065ded5aa173586b15285aee373d40d89710fff18ae49e546999a29156"
+content-hash = "3f173b0e8ccc458b480858963ca07ed592426d564e0fa62378a51e325d15f802"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 0c5c74d6..1fdc5156 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -15,6 +15,8 @@ python = "^3.9"
 Jinja2 = ">=3.0.1,<4.0.0"
 google-cloud-aiplatform = "1.24.1"
 google-cloud-pipeline-components = "1.0.42"
+pytest = "^7.3.1"
+
 
 [tool.poetry.group.dev.dependencies]
 pytest = ">=7.3.1,<8.0.0"

From 96aff8b0b5fd70cf8f2109ccbba256a3931575f0 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 24 May 2023 10:47:22 +0100
Subject: [PATCH 045/238] Update Makefile

Co-authored-by: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 337fe89c..df8ed419 100644
--- a/Makefile
+++ b/Makefile
@@ -58,7 +58,7 @@ test-all-components: ## Run unit tests for all pipeline components
 	done
 
 sync-assets: ## Sync assets folder to GCS.
-	@if [ -d "./pipelines/src/pipelines/assets/" ] ; then \
+	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
 		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets ; \
 	else \

From 9f6cbc4b6f992761abfb67174c77f30ab4df2b50 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 24 May 2023 10:48:21 +0100
Subject: [PATCH 046/238] Update README.md

Co-authored-by: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
---
 README.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 927ea440..38615ae0 100644
--- a/README.md
+++ b/README.md
@@ -178,7 +178,8 @@ When triggering ad hoc runs in your dev/sandbox environment, or when running the
 
 ### Assets
 
-Pipeline folder, contains `assets` directory (`pipelines/assets/`). This can be used for any additional files that may be needed during execution of the pipelines. 
+The folder `pipelines/assets/` can be used for any additional files that may be needed during execution of the pipelines. 
+Most importantly this can include your training scripts.
 This directory is rsync'd to Google Cloud Storage when running a pipeline in the sandbox environment or as part of the CD pipeline (see [CI/CD setup](cloudbuild/README.md)).
 
 ## Testing

From 352a4ed50929e9150133c640baff44d66dd54a34 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Thu, 25 May 2023 16:51:18 +0100
Subject: [PATCH 047/238] build(pyproject.toml): update packages

---
 pipelines/poetry.lock    | 240 ++++++++++++++++++++-------------------
 pipelines/pyproject.toml |   9 +-
 2 files changed, 129 insertions(+), 120 deletions(-)

diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index 62a8d667..b04293b3 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -31,6 +31,27 @@ docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-
 tests = ["attrs[tests-no-zope]", "zope-interface"]
 tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
 
+[[package]]
+name = "bigquery-components"
+version = "0.1.0"
+description = "Bigquery components for vertex pipelines"
+category = "main"
+optional = false
+python-versions = ">=3.9,<3.11"
+files = []
+develop = true
+
+[package.dependencies]
+google-cloud-aiplatform = "1.24.1"
+google-cloud-bigquery = "2.30.0"
+google-cloud-pipeline-components = "1.0.42"
+Jinja2 = ">=3.0.1,<4.0.0"
+kfp = "==1.8.21"
+
+[package.source]
+type = "directory"
+url = "../components/bigquery-components"
+
 [[package]]
 name = "cachetools"
 version = "5.3.0"
@@ -279,31 +300,6 @@ files = [
 six = "*"
 termcolor = "*"
 
-[[package]]
-name = "google-api-core"
-version = "1.34.0"
-description = "Google API client core library"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "google-api-core-1.34.0.tar.gz", hash = "sha256:6fb380f49d19ee1d09a9722d0379042b7edb06c0112e4796c7a395078a043e71"},
-    {file = "google_api_core-1.34.0-py3-none-any.whl", hash = "sha256:7421474c39d396a74dfa317dddbc69188f2336835f526087c7648f91105e32ff"},
-]
-
-[package.dependencies]
-google-auth = ">=1.25.0,<3.0dev"
-googleapis-common-protos = ">=1.56.2,<2.0dev"
-grpcio = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-grpcio-status = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.0.0dev"
-requests = ">=2.18.0,<3.0.0dev"
-
-[package.extras]
-grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio-status (>=1.33.2,<2.0dev)"]
-grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
-grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
-
 [[package]]
 name = "google-api-core"
 version = "2.11.0"
@@ -319,10 +315,7 @@ files = [
 [package.dependencies]
 google-auth = ">=2.14.1,<3.0dev"
 googleapis-common-protos = ">=1.56.2,<2.0dev"
-grpcio = [
-    {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""},
-    {version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
-]
+grpcio = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
 grpcio-status = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 requests = ">=2.18.0,<3.0.0dev"
@@ -354,14 +347,14 @@ uritemplate = ">=3.0.0,<4dev"
 
 [[package]]
 name = "google-auth"
-version = "2.18.0"
+version = "2.18.1"
 description = "Google Authentication Library"
 category = "main"
 optional = false
 python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
 files = [
-    {file = "google-auth-2.18.0.tar.gz", hash = "sha256:c66b488a8b005b23ccb97b1198b6cece516c91869091ac5b7c267422db2733c7"},
-    {file = "google_auth-2.18.0-py2.py3-none-any.whl", hash = "sha256:ef3f3a67fa54d421a1c155864570f9a8de9179cedc937bda496b7a8ca338e936"},
+    {file = "google-auth-2.18.1.tar.gz", hash = "sha256:d7a3249027e7f464fbbfd7ee8319a08ad09d2eea51578575c4bd360ffa049ccb"},
+    {file = "google_auth-2.18.1-py2.py3-none-any.whl", hash = "sha256:55a395cdfd3f3dd3f649131d41f97c17b4ed8a2aac1be3502090c716314e8a37"},
 ]
 
 [package.dependencies]
@@ -435,38 +428,34 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "3.10.0"
+version = "2.30.0"
 description = "Google BigQuery API client library"
 category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.6, <3.11"
 files = [
-    {file = "google-cloud-bigquery-3.10.0.tar.gz", hash = "sha256:4b02def076e2db8cec66f65fb627d13904a9fc3cf4fee315ede43dcb7038a8df"},
-    {file = "google_cloud_bigquery-3.10.0-py2.py3-none-any.whl", hash = "sha256:848a3cbce0ba7d4f1e9551400a7c99aa0eab72290d5a1bbbe69f18a24a10bd3a"},
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+    {file = "pydantic-1.10.8-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:93e6bcfccbd831894a6a434b0aeb1947f9e70b7468f274154d03d71fabb1d7c6"},
+    {file = "pydantic-1.10.8-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:191ba419b605f897ede9892f6c56fb182f40a15d309ef0142212200a10af4c18"},
+    {file = "pydantic-1.10.8-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:052d8654cb65174d6f9490cc9b9a200083a82cf5c3c5d3985db765757eb3b375"},
+    {file = "pydantic-1.10.8-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:ceb6a23bf1ba4b837d0cfe378329ad3f351b5897c8d4914ce95b85fba96da5a1"},
+    {file = "pydantic-1.10.8-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:6f2e754d5566f050954727c77f094e01793bcb5725b663bf628fa6743a5a9108"},
+    {file = "pydantic-1.10.8-cp38-cp38-win_amd64.whl", hash = "sha256:6a82d6cda82258efca32b40040228ecf43a548671cb174a1e81477195ed3ed56"},
+    {file = "pydantic-1.10.8-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3e59417ba8a17265e632af99cc5f35ec309de5980c440c255ab1ca3ae96a3e0e"},
+    {file = "pydantic-1.10.8-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:84d80219c3f8d4cad44575e18404099c76851bc924ce5ab1c4c8bb5e2a2227d0"},
+    {file = "pydantic-1.10.8-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2e4148e635994d57d834be1182a44bdb07dd867fa3c2d1b37002000646cc5459"},
+    {file = "pydantic-1.10.8-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:12f7b0bf8553e310e530e9f3a2f5734c68699f42218bf3568ef49cd9b0e44df4"},
+    {file = "pydantic-1.10.8-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:42aa0c4b5c3025483240a25b09f3c09a189481ddda2ea3a831a9d25f444e03c1"},
+    {file = "pydantic-1.10.8-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:17aef11cc1b997f9d574b91909fed40761e13fac438d72b81f902226a69dac01"},
+    {file = "pydantic-1.10.8-cp39-cp39-win_amd64.whl", hash = "sha256:66a703d1983c675a6e0fed8953b0971c44dba48a929a2000a493c3772eb61a5a"},
+    {file = "pydantic-1.10.8-py3-none-any.whl", hash = "sha256:7456eb22ed9aaa24ff3e7b4757da20d9e5ce2a81018c1b3ebd81a0b88a18f3b2"},
+    {file = "pydantic-1.10.8.tar.gz", hash = "sha256:1410275520dfa70effadf4c21811d755e7ef9bb1f1d077a21958153a92c8d9ca"},
 ]
 
 [package.dependencies]
@@ -1392,14 +1375,14 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.30.0"
+version = "2.31.0"
 description = "Python HTTP for Humans."
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "requests-2.30.0-py3-none-any.whl", hash = "sha256:10e94cc4f3121ee6da529d358cdaeaff2f1c409cd377dbc72b825852f2f7e294"},
-    {file = "requests-2.30.0.tar.gz", hash = "sha256:239d7d4458afcb28a692cdd298d87542235f4ca8d36d03a15bfc128a6559a2f4"},
+    {file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
+    {file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
 ]
 
 [package.dependencies]
@@ -1463,19 +1446,19 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "setuptools"
-version = "67.7.2"
+version = "67.8.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "setuptools-67.7.2-py3-none-any.whl", hash = "sha256:23aaf86b85ca52ceb801d32703f12d77517b2556af839621c641fca11287952b"},
-    {file = "setuptools-67.7.2.tar.gz", hash = "sha256:f104fa03692a2602fa0fec6c6a9e63b6c8a968de13e17c026957dd1f53d80990"},
+    {file = "setuptools-67.8.0-py3-none-any.whl", hash = "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f"},
+    {file = "setuptools-67.8.0.tar.gz", hash = "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"},
 ]
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
@@ -1627,14 +1610,14 @@ test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.
 
 [[package]]
 name = "typing-extensions"
-version = "4.5.0"
+version = "4.6.2"
 description = "Backported and Experimental Type Hints for Python 3.7+"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"},
-    {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"},
+    {file = "typing_extensions-4.6.2-py3-none-any.whl", hash = "sha256:3a8b36f13dd5fdc5d1b16fe317f5668545de77fa0b8e02006381fd49d731ab98"},
+    {file = "typing_extensions-4.6.2.tar.gz", hash = "sha256:06006244c70ac8ee83fa8282cb188f697b8db25bc8b4df07be1873c43897060c"},
 ]
 
 [[package]]
@@ -1651,14 +1634,14 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "1.26.15"
+version = "1.26.16"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
-    {file = "urllib3-1.26.15-py2.py3-none-any.whl", hash = "sha256:aa751d169e23c7479ce47a0cb0da579e3ede798f994f5816a74e4f4500dcea42"},
-    {file = "urllib3-1.26.15.tar.gz", hash = "sha256:8a388717b9476f934a21484e8c8e61875ab60644d29b9b39e11e4b9dc1c6b305"},
+    {file = "urllib3-1.26.16-py2.py3-none-any.whl", hash = "sha256:8d36afa7616d8ab714608411b4a3b13e58f463aee519024578e062e141dce20f"},
+    {file = "urllib3-1.26.16.tar.gz", hash = "sha256:8f135f6502756bde6b2a9b28989df5fbe87c9970cecaa69041edcce7f0589b14"},
 ]
 
 [package.extras]
@@ -1666,6 +1649,25 @@ brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
 secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
 socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
+[[package]]
+name = "vertex-components"
+version = "0.1.0"
+description = "KFP components for interacting with Vertex AI"
+category = "main"
+optional = false
+python-versions = ">=3.9,<3.11"
+files = []
+develop = true
+
+[package.dependencies]
+google-cloud-aiplatform = "1.24.1"
+google-cloud-pipeline-components = "1.0.42"
+kfp = "==1.8.21"
+
+[package.source]
+type = "directory"
+url = "../components/vertex-components"
+
 [[package]]
 name = "virtualenv"
 version = "20.23.0"
@@ -1689,14 +1691,14 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "coverage-enable-subprocess
 
 [[package]]
 name = "websocket-client"
-version = "1.5.1"
+version = "1.5.2"
 description = "WebSocket client for Python with low level API options"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "websocket-client-1.5.1.tar.gz", hash = "sha256:3f09e6d8230892547132177f575a4e3e73cfdf06526e20cc02aa1c3b47184d40"},
-    {file = "websocket_client-1.5.1-py3-none-any.whl", hash = "sha256:cdf5877568b7e83aa7cf2244ab56a3213de587bbe0ce9d8b9600fc77b455d89e"},
+    {file = "websocket-client-1.5.2.tar.gz", hash = "sha256:c7d67c13b928645f259d9b847ab5b57fd2d127213ca41ebd880de1f553b7c23b"},
+    {file = "websocket_client-1.5.2-py3-none-any.whl", hash = "sha256:f8c64e28cd700e7ba1f04350d66422b6833b82a796b525a51e740b8cc8dab4b1"},
 ]
 
 [package.extras]
@@ -1806,5 +1808,5 @@ files = [
 
 [metadata]
 lock-version = "2.0"
-python-versions = "^3.9"
-content-hash = "3f173b0e8ccc458b480858963ca07ed592426d564e0fa62378a51e325d15f802"
+python-versions = ">=3.9,<3.11"
+content-hash = "c464813a2e2cb67c3d2e0ae229ca383b847a62fca4486fdf2f8ab90f335c624b"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 1fdc5156..5e714f01 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -9,13 +9,20 @@ classifiers = [
     "Intended Audience :: Developers",
     "Programming Language :: Python :: 3.9",
 ]
+packages = [
+    { include = "pipelines", from = "src" },
+]
+
 
 [tool.poetry.dependencies]
-python = "^3.9"
+python = ">=3.9,<3.11"
 Jinja2 = ">=3.0.1,<4.0.0"
 google-cloud-aiplatform = "1.24.1"
 google-cloud-pipeline-components = "1.0.42"
 pytest = "^7.3.1"
+bigquery-components = { path = "../components/bigquery-components", develop = true }
+vertex-components = { path = "../components/vertex-components", develop = true }
+
 
 
 [tool.poetry.group.dev.dependencies]

From 68a290d7acb55b914a737773c5db02aef9140bfc Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Thu, 25 May 2023 16:58:07 +0100
Subject: [PATCH 048/238] build(makefile): update makefile

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index f342554d..b2138216 100644
--- a/Makefile
+++ b/Makefile
@@ -37,7 +37,7 @@ compile-pipeline: ## Compile the pipeline to training.json or prediction.json. M
 
 setup-components: ## Run unit tests for a component group
 	@cd "components/${GROUP}" && \
-	poetry install --dev
+	poetry install --with dev 
 
 setup-all-components: ## Run unit tests for all pipeline components
 	@set -e && \

From cec9f3e462e0aeb4388f0df917e1fcf5e8cca41c Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 11:05:32 +0100
Subject: [PATCH 049/238] build(pyproject.toml): update poetry dependencies

---
 components/bigquery-components/pyproject.toml | 6 +-----
 components/vertex-components/pyproject.toml   | 5 ++---
 2 files changed, 3 insertions(+), 8 deletions(-)

diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index efeaa9f6..ae6dc103 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -12,15 +12,11 @@ classifiers = [
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
-Jinja2 = ">=3.0.1,<4.0.0"
-google-cloud-aiplatform = "1.24.1"
-google-cloud-pipeline-components = "1.0.42"
-google-cloud-bigquery = "2.30.0"
 kfp = "==1.8.21"
 
 [tool.poetry.group.dev.dependencies]
+google-cloud-bigquery = "2.30.0"
 pytest = ">=7.3.1,<8.0.0"
-pre-commit = ">=2.14.1,<3.0.0"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index 37374cff..62fe0693 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -12,13 +12,12 @@ classifiers = [
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
-google-cloud-aiplatform = "1.24.1"
-google-cloud-pipeline-components = "1.0.42"
 kfp = "==1.8.21"
 
 [tool.poetry.group.dev.dependencies]
+google-cloud-aiplatform = "1.24.1"
+google-cloud-pipeline-components = "1.0.42"
 pytest = ">=7.3.1,<8.0.0"
-pre-commit = ">=2.14.1,<3.0.0"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

From 149ab44fed68b64e604d090500aa9a2d89eb862f Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 11:08:35 +0100
Subject: [PATCH 050/238] build(pyproject.toml): remove pytest from dependecies

---
 pipelines/pyproject.toml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 5e714f01..cf42b576 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -19,7 +19,6 @@ python = ">=3.9,<3.11"
 Jinja2 = ">=3.0.1,<4.0.0"
 google-cloud-aiplatform = "1.24.1"
 google-cloud-pipeline-components = "1.0.42"
-pytest = "^7.3.1"
 bigquery-components = { path = "../components/bigquery-components", develop = true }
 vertex-components = { path = "../components/vertex-components", develop = true }
 

From 341392a6111176c6a20cab9e2719f8445d28c261 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 14:01:09 +0100
Subject: [PATCH 051/238] docs(CONTRIBUTING.md): update docs with poetry
 requirements

---
 CONTRIBUTING.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 9e7f8f89..0bbcb994 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -22,7 +22,7 @@ This guide is chiefly for users wishing to contribute to the opensource version.
 ## Links to Important Resources
 - [pytest](https://docs.pytest.org)
 - [unittest.mock](https://docs.python.org/3/library/unittest.mock.html)
-- [pipenv](https://pipenv-fork.readthedocs.io/en/latest/index.html)
+- [poetry](https://python-poetry.org/docs/#installation)
 - [Kubeflow Pipelines](https://www.kubeflow.org/docs/components/pipelines/overview)
 - [Vertex AI](https://cloud.google.com/vertex-ai/docs)
 - [AI Platform SDK](https://googleapis.dev/python/aiplatform/latest/index.html)

From 1258220877e228da777e964d34d3d7c23e227ca3 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 14:22:53 +0100
Subject: [PATCH 052/238] docs(README.md): update poetry dependencies

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 09940d13..3c7504a5 100644
--- a/README.md
+++ b/README.md
@@ -55,8 +55,8 @@ In a production MLOps solution, your ML pipelines need to be repeatable. So, we
 
 1. Clone the repository locally
 1. Install Python: `pyenv install`
-1. Install pipenv and pipenv dependencies: `make setup`
-1. Install pre-commit hooks: `cd pipelines && pipenv run pre-commit install`
+1. Install poetry and  dependencies: `make setup`
+1. Install pre-commit hooks: `cd pipelines` && run `pre-commit install`
 1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh`
 1. Load the environment variables in `env.sh` by running `source env.sh`
 

From 08c3796512d997ee93a42d1b4060b02bb16a06d3 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 14:26:12 +0100
Subject: [PATCH 053/238] style(pr-checks.yaml): update comment with poetry
 dependency

---
 cloudbuild/pr-checks.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 4a8f92cb..d0747890 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -14,7 +14,7 @@
 ---
 steps:
 
-  # Install pipenv and deps, run pre-commit and unit tests
+  # Install poetry and deps, run pre-commit and unit tests
   # Then compile pipelines (to make sure they can compile)
   # need to run "git init" for pre-commit checks to work
   - name: python:3.9

From 7185dc66d049821c519f3de472cc4538751f29bf Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 14:27:47 +0100
Subject: [PATCH 054/238] style(pr-checks.yaml): update comments with poetry
 dependency

---
 cloudbuild/pr-checks.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index d0747890..969e7bbf 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -37,5 +37,5 @@ steps:
 options:
   logging: CLOUD_LOGGING_ONLY
 
-# Increase timeout to allow pipenv to resolve dependencies
+# Increase timeout to allow poetry to resolve dependencies
 timeout: 3600s

From 7aa2efcddb9ed80a76b8338457fdb61216dabd11 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 14:31:50 +0100
Subject: [PATCH 055/238] style(release.yaml): update comments with poetry
 dependency

---
 cloudbuild/release.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index d09f451d..9d0f4226 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -14,7 +14,7 @@
 ---
 steps:
 
-  # Install pipenv, install deps, compile pipelines
+  # Install poetry, install deps, compile pipelines
   - name: python:3.9
     entrypoint: /bin/sh
     args:

From 86fc9217269da4d274ea934b0e7f0dc46a8ccc09 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 14:41:46 +0100
Subject: [PATCH 056/238] style(README.md): update comments with poetry
 dependency

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 3c7504a5..6932dd99 100644
--- a/README.md
+++ b/README.md
@@ -56,7 +56,7 @@ In a production MLOps solution, your ML pipelines need to be repeatable. So, we
 1. Clone the repository locally
 1. Install Python: `pyenv install`
 1. Install poetry and  dependencies: `make setup`
-1. Install pre-commit hooks: `cd pipelines` && run `pre-commit install`
+1. Install pre-commit hooks: `cd pipelines` && `poetry run pre-commit install`
 1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh`
 1. Load the environment variables in `env.sh` by running `source env.sh`
 

From bcea327f9098c8811d65ba588c365db5c026c241 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 14:44:29 +0100
Subject: [PATCH 057/238] style(README.md): update comments with poetry
 dependency

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 6932dd99..bce38968 100644
--- a/README.md
+++ b/README.md
@@ -56,7 +56,7 @@ In a production MLOps solution, your ML pipelines need to be repeatable. So, we
 1. Clone the repository locally
 1. Install Python: `pyenv install`
 1. Install poetry and  dependencies: `make setup`
-1. Install pre-commit hooks: `cd pipelines` && `poetry run pre-commit install`
+1. Install pre-commit hooks: `cd pipelines && poetry run pre-commit install`
 1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh`
 1. Load the environment variables in `env.sh` by running `source env.sh`
 

From 9bf426c119d2642b2abe47957b252d8f2c606dba Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 15:07:31 +0100
Subject: [PATCH 058/238] style(README.md): update comments with how to install
 new component package into pipeline package

---
 components/README.md | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/components/README.md b/components/README.md
index e1b5fac9..5c724aac 100644
--- a/components/README.md
+++ b/components/README.md
@@ -6,20 +6,21 @@ This directory contains multiple Python packages that are used to define pipelin
 
 To create a new set of components (with different Python dependencies), copy one of the existing subdirectories and rename the different files and directories as appropriate (e.g. `bigquery-components` -> `my-new-components`). You will also need to update any references in the Python files themselves, as well as the `Pipfile` and `pyproject.toml`.
 
-Your Python dependencies should be defined in `Pipfile`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
+Your Python dependencies should be defined in `poetry.lock file`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
 
-- In `Pipfile`, add `kfp` to the `[packages]` section (pinned to a specific version), and add any dependencies that your component uses under `[dev-packages]` (each pinned to a specific version)
+- In `pyproject.toml`, add `kfp` to the `[packages]` section (pinned to a specific version), and add any dependencies that your component uses under `[dev-packages]` (each pinned to a specific version)
 - In `pyproject.toml`, add `kfp` to the `[dependencies]` section (pinned to a specific version), and add any dependencies that your component uses under `[[project.optional-dependencies]` -> `tests` (each pinned to a specific version)
 - In `packages_to_install` (in the `@component` decorator used to define your component), add any dependencies that your component uses (each pinned to a specific version)
 
 Define your pipeline components using the `@component` decorator in Python files under `my-new-components/src/my-new-components`. You will need to update the `__init__.py` file to provide tests - see the [Kubeflow Pipelines documentation](https://www.kubeflow.org/docs/components/pipelines/v1/sdk-v2/python-function-components/#building-python-function-based-components) for more information about writing pipeline components.
 
-Finally, you will need to install this new components package into the [`pipelines`](../pipelines) package. In [`pipelines/Pipfile`](../pipelines/Pipfile), add the following line to the `packages` section:
-```ini
-my-new-components = {editable = true, path = "./../components/my-new-components"}
-```
+Finally, you will need to install this new components package into the [`pipelines`](../pipelines) package. In [`pipelines/pyproject.toml`](../pipelines/pyproject.toml), add the following line to the `packages` section:
 
-Once you have added this line to [`pipelines/Pipfile`](../pipelines/Pipfile), run `make setup` from the root of the repository to install the new components package into the `pipelines` package.
+```
+[tool.poetry.dependencies]
+my-new-components = { path = "../components/my-new-components", develop = true }
+```
+Once you have added this line to [`pipelines/pyproject.toml`](../pipelines/pyproject.toml), run `make setup` from the root of the repository to install the new components package into the `pipelines` package.
 
 ## Testing components
 

From 67abb5e2d409bad78e29109feaaad27253add87e Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 15:10:04 +0100
Subject: [PATCH 059/238] style(CONTRIBUTING.md): update docs with poetry
 requirements

---
 CONTRIBUTING.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 0bbcb994..da7e6ba7 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -211,12 +211,12 @@ def test_vertex_endpoint_uri(output_uri: str):
 ```
 
 ## Adding or changing python dependencies
-We use [pipenv](https://pipenv-fork.readthedocs.io/en/latest/index.html) to handle our packages and their dependencies. Each group of pipeline components (e.g. [aiplatform](./pipeline_components/aiplatform/)) containers its own pipenv environment, and there is a [separate pipenv environment](./pipelines/) for the ML pipelines themselves and the pipeline trigger code.
+We use [poetry](https://python-poetry.org/docs/#installation) to handle our packages and their dependencies. Each group of pipeline components (e.g. [aiplatform](./pipeline_components/aiplatform/)) containers its own poetry environment, and there is a [separate poetry environment](./pipelines/) for the ML pipelines themselves and the pipeline trigger code.
 
 ### Adding python dependencies
 You may need to add new packages for your own use cases. To do this, run the following from the relevant directory ([pipelines](./pipelines) for the main ML pipeline dependencies or the directory of the relevant component group e.g. [aiplatform](./pipeline_components/aiplatform/)):
 ```
-pipenv install <package name>
+poetry install <package name>
 ```
 
 ## Committing Changes
@@ -260,7 +260,7 @@ make pre-commit
 - **Checks fail and displays an error message**. Some errors cannot be automatically fixed by pre-commit hooks, and instead they will display the error number and the file and line which failed. For more details beyond the error message, you can look up the error number online. The most common errors are caused by lines which exceed the character limit. Once you identify the cause of the error, you will need to fix this in your code, add the edited file to the staging area, and then commit again.
 
 ### Commit changes to Python packages and dependencies
-If you have changes to `Pipfile` and `Pipfile.lock`, please make sure you commit these files!
+If you have changes to `pyproject.toml` and `poetry.lock`, please make sure you commit these files!
 
 ## Makefile
 This project contains a [Makefile](Makefile) which contains "rules" describing the commands to be executed by the system. These allow you to quickly and easily run commands for specific purposes, for example running all of the unit-tests, or compiling a pipeline. You can find the full set of available `make` rules by running:

From 6a7b6d9afc2eda80effa24595999bc899f9d3360 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 15:13:02 +0100
Subject: [PATCH 060/238] style(README.md): update comments with how to install
 new component package into pipeline package

---
 components/README.md | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/components/README.md b/components/README.md
index 5c724aac..1512b7e4 100644
--- a/components/README.md
+++ b/components/README.md
@@ -14,10 +14,9 @@ Your Python dependencies should be defined in `poetry.lock file`, `pyproject.tom
 
 Define your pipeline components using the `@component` decorator in Python files under `my-new-components/src/my-new-components`. You will need to update the `__init__.py` file to provide tests - see the [Kubeflow Pipelines documentation](https://www.kubeflow.org/docs/components/pipelines/v1/sdk-v2/python-function-components/#building-python-function-based-components) for more information about writing pipeline components.
 
-Finally, you will need to install this new components package into the [`pipelines`](../pipelines) package. In [`pipelines/pyproject.toml`](../pipelines/pyproject.toml), add the following line to the `packages` section:
+Finally, you will need to install this new components package into the [`pipelines`](../pipelines) package. In [`pipelines/pyproject.toml`](../pipelines/pyproject.toml), add the following line to the `tool.poetry.dependencies` section:
 
 ```
-[tool.poetry.dependencies]
 my-new-components = { path = "../components/my-new-components", develop = true }
 ```
 Once you have added this line to [`pipelines/pyproject.toml`](../pipelines/pyproject.toml), run `make setup` from the root of the repository to install the new components package into the `pipelines` package.

From 94cd885bf8395f9fe99e143faf3cf4900d1d54b5 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 15:18:26 +0100
Subject: [PATCH 061/238] style(README.md): update comments to reflect poetry
 package installation

---
 components/README.md | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/components/README.md b/components/README.md
index 1512b7e4..2a41ac1f 100644
--- a/components/README.md
+++ b/components/README.md
@@ -8,8 +8,7 @@ To create a new set of components (with different Python dependencies), copy one
 
 Your Python dependencies should be defined in `poetry.lock file`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
 
-- In `pyproject.toml`, add `kfp` to the `[packages]` section (pinned to a specific version), and add any dependencies that your component uses under `[dev-packages]` (each pinned to a specific version)
-- In `pyproject.toml`, add `kfp` to the `[dependencies]` section (pinned to a specific version), and add any dependencies that your component uses under `[[project.optional-dependencies]` -> `tests` (each pinned to a specific version)
+- In `pyproject.toml`, add `kfp` to the `[dependencies]` section (pinned to a specific version), and add any dependencies that your component uses under `[tool.poetry.dependencies]`(each pinned to a specific version)
 - In `packages_to_install` (in the `@component` decorator used to define your component), add any dependencies that your component uses (each pinned to a specific version)
 
 Define your pipeline components using the `@component` decorator in Python files under `my-new-components/src/my-new-components`. You will need to update the `__init__.py` file to provide tests - see the [Kubeflow Pipelines documentation](https://www.kubeflow.org/docs/components/pipelines/v1/sdk-v2/python-function-components/#building-python-function-based-components) for more information about writing pipeline components.

From 05378d948a0b6bde03525d5e0908f687170b3233 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 15:21:24 +0100
Subject: [PATCH 062/238] style(README.md): update with poetry requirements

---
 components/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/README.md b/components/README.md
index 2a41ac1f..6f58f74b 100644
--- a/components/README.md
+++ b/components/README.md
@@ -4,7 +4,7 @@ This directory contains multiple Python packages that are used to define pipelin
 
 ## Creating a new pipeline components package
 
-To create a new set of components (with different Python dependencies), copy one of the existing subdirectories and rename the different files and directories as appropriate (e.g. `bigquery-components` -> `my-new-components`). You will also need to update any references in the Python files themselves, as well as the `Pipfile` and `pyproject.toml`.
+To create a new set of components (with different Python dependencies), copy one of the existing subdirectories and rename the different files and directories as appropriate (e.g. `bigquery-components` -> `my-new-components`). You will also need to update any references in the Python files themselves, as well as the `poetry.lock file` and `pyproject.toml`.
 
 Your Python dependencies should be defined in `poetry.lock file`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
 

From 736392cb4f630d00d2af63ff400b084199c540fb Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 16:12:39 +0100
Subject: [PATCH 063/238] build(poetry.lock): update poetry.lock file

---
 components/bigquery-components/poetry.lock | 513 +++------------------
 components/vertex-components/poetry.lock   | 272 +++--------
 2 files changed, 141 insertions(+), 644 deletions(-)

diff --git a/components/bigquery-components/poetry.lock b/components/bigquery-components/poetry.lock
index 9a846c08..8a60aaaf 100644
--- a/components/bigquery-components/poetry.lock
+++ b/components/bigquery-components/poetry.lock
@@ -55,18 +55,6 @@ files = [
     {file = "certifi-2023.5.7.tar.gz", hash = "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7"},
 ]
 
-[[package]]
-name = "cfgv"
-version = "3.3.1"
-description = "Validate configuration and produce human readable error messages."
-category = "dev"
-optional = false
-python-versions = ">=3.6.1"
-files = [
-    {file = "cfgv-3.3.1-py2.py3-none-any.whl", hash = "sha256:c6a0883f3917a037485059700b9e75da2464e6c27051014ad85ba6aaa5884426"},
-    {file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"},
-]
-
 [[package]]
 name = "charset-normalizer"
 version = "3.1.0"
@@ -209,18 +197,6 @@ wrapt = ">=1.10,<2"
 [package.extras]
 dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"]
 
-[[package]]
-name = "distlib"
-version = "0.3.6"
-description = "Distribution utilities"
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "distlib-0.3.6-py2.py3-none-any.whl", hash = "sha256:f35c4b692542ca110de7ef0bea44d73981caeb34ca0b9b6b2e6d7790dda8f80e"},
-    {file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"},
-]
-
 [[package]]
 name = "docstring-parser"
 version = "0.15"
@@ -248,22 +224,6 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
-[[package]]
-name = "filelock"
-version = "3.12.0"
-description = "A platform independent file lock."
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "filelock-3.12.0-py3-none-any.whl", hash = "sha256:ad98852315c2ab702aeb628412cbf7e95b7ce8c3bf9565670b4eaecf1db370a9"},
-    {file = "filelock-3.12.0.tar.gz", hash = "sha256:fc03ae43288c013d2ea83c8597001b1129db351aad9c57fe2409327916b8e718"},
-]
-
-[package.extras]
-docs = ["furo (>=2023.3.27)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
-
 [[package]]
 name = "fire"
 version = "0.5.0"
@@ -326,20 +286,20 @@ uritemplate = ">=3.0.0,<4dev"
 
 [[package]]
 name = "google-auth"
-version = "2.18.0"
+version = "2.19.0"
 description = "Google Authentication Library"
 category = "main"
 optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
+python-versions = ">=3.6"
 files = [
-    {file = "google-auth-2.18.0.tar.gz", hash = "sha256:c66b488a8b005b23ccb97b1198b6cece516c91869091ac5b7c267422db2733c7"},
-    {file = "google_auth-2.18.0-py2.py3-none-any.whl", hash = "sha256:ef3f3a67fa54d421a1c155864570f9a8de9179cedc937bda496b7a8ca338e936"},
+    {file = "google-auth-2.19.0.tar.gz", hash = "sha256:f39d528077ac540793dd3c22a8706178f157642a67d874db25c640b7fead277e"},
+    {file = "google_auth-2.19.0-py2.py3-none-any.whl", hash = "sha256:be617bfaf77774008e9d177573f782e109188c8a64ae6e744285df5cea3e7df6"},
 ]
 
 [package.dependencies]
 cachetools = ">=2.0.0,<6.0"
 pyasn1-modules = ">=0.2.1"
-rsa = {version = ">=3.1.4,<5", markers = "python_version >= \"3.6\""}
+rsa = ">=3.1.4,<5"
 six = ">=1.9.0"
 urllib3 = "<2.0"
 
@@ -367,49 +327,11 @@ google-auth = "*"
 httplib2 = ">=0.15.0"
 six = "*"
 
-[[package]]
-name = "google-cloud-aiplatform"
-version = "1.24.1"
-description = "Vertex AI API client library"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "google-cloud-aiplatform-1.24.1.tar.gz", hash = "sha256:0ce9e97bf5c977397e52b3b7c4dc78610c135fbde11a60a6c0b77a4fdf776400"},
-    {file = "google_cloud_aiplatform-1.24.1-py2.py3-none-any.whl", hash = "sha256:942765a6bad97e46e262dd6599dc5f171663ce952130e0b0b2eb97e0b1b98bfd"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.32.0,<2.0.0 || >=2.8.0,<3.0.0dev", extras = ["grpc"]}
-google-cloud-bigquery = ">=1.15.0,<4.0.0dev"
-google-cloud-resource-manager = ">=1.3.3,<3.0.0dev"
-google-cloud-storage = ">=1.32.0,<3.0.0dev"
-packaging = ">=14.3"
-proto-plus = ">=1.22.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-shapely = "<2.0.0"
-
-[package.extras]
-autologging = ["mlflow (>=1.27.0,<=2.1.1)"]
-cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
-datasets = ["pyarrow (>=3.0.0,<8.0dev)"]
-endpoint = ["requests (>=2.28.1)"]
-full = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pyyaml (>=5.3,<6)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
-lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"]
-metadata = ["numpy (>=1.15.0)", "pandas (>=1.0.0)"]
-pipelines = ["pyyaml (>=5.3,<6)"]
-prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<0.76.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"]
-private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"]
-tensorboard = ["tensorflow (>=2.3.0,<3.0.0dev)"]
-testing = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "grpcio-testing", "ipython", "kfp", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3,<6)", "requests (>=2.28.1)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
-vizier = ["google-vizier (==0.0.4)"]
-xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
-
 [[package]]
 name = "google-cloud-bigquery"
 version = "2.30.0"
 description = "Google BigQuery API client library"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6, <3.11"
 files = [
@@ -456,66 +378,6 @@ google-auth = ">=1.25.0,<3.0dev"
 [package.extras]
 grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
-[[package]]
-name = "google-cloud-notebooks"
-version = "1.7.0"
-description = "Google Cloud Notebooks API client library"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "google-cloud-notebooks-1.7.0.tar.gz", hash = "sha256:dac73a5cd983a4344d1fa96f9a8e5849b0ff75d7a5fdde921023a2ef4566e75e"},
-    {file = "google_cloud_notebooks-1.7.0-py2.py3-none-any.whl", hash = "sha256:8fbffb7ba535fc02c61f135d8863324a5a2d20dd58cafaae592f0b0172d6bdab"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]}
-grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
-proto-plus = ">=1.22.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-
-[[package]]
-name = "google-cloud-pipeline-components"
-version = "1.0.42"
-description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
-category = "main"
-optional = false
-python-versions = "*"
-files = [
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-
-[package.dependencies]
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-google-cloud-notebooks = ">=0.4.0"
-google-cloud-storage = ">=2.2.1,<3"
-googleapis-common-protos = ">=1.56.2,<2.0dev"
-grpcio-status = "<=1.47.0"
-kfp = ">=1.8.9,<2.0.0"
-protobuf = ">=3.19.0,<4.0.0dev"
-
-[package.extras]
-tests = ["flake8 (>=3.0.0)", "google-api-core (>=1.31.5,<2.0.0 || >=2.8.0,<3.0.0dev)", "google-cloud-aiplatform (>=1.14.0,<2)", "google-cloud-notebooks (>=0.4.0)", "google-cloud-storage (>=2.2.1,<3)", "googleapis-common-protos (>=1.56.2,<2.0dev)", "grpcio-status (<=1.47.0)", "kfp (>=1.8.9,<2.0.0)", "mock (>=4.0.0)", "protobuf (>=3.19.0,<4.0.0dev)", "pytest (>=6.0.0)"]
-
-[[package]]
-name = "google-cloud-resource-manager"
-version = "1.10.0"
-description = "Google Cloud Resource Manager API client library"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
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-
-[package.dependencies]
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-grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
-proto-plus = ">=1.22.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-
 [[package]]
 name = "google-cloud-storage"
 version = "2.9.0"
@@ -651,34 +513,16 @@ files = [
 ]
 
 [package.dependencies]
-grpcio = {version = ">=1.44.0,<2.0.0dev", optional = true, markers = "extra == \"grpc\""}
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 
 [package.extras]
 grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
 
-[[package]]
-name = "grpc-google-iam-v1"
-version = "0.12.6"
-description = "IAM API client library"
-category = "main"
-optional = false
-python-versions = ">=3.7"
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-grpcio = ">=1.44.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-
 [[package]]
 name = "grpcio"
 version = "1.54.2"
 description = "HTTP/2-based RPC framework"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -734,19 +578,19 @@ protobuf = ["grpcio-tools (>=1.54.2)"]
 
 [[package]]
 name = "grpcio-status"
-version = "1.47.0"
+version = "1.48.2"
 description = "Status proto mapping for gRPC"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
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 [package.dependencies]
 googleapis-common-protos = ">=1.5.5"
-grpcio = ">=1.47.0"
+grpcio = ">=1.48.2"
 protobuf = ">=3.12.0"
 
 [[package]]
@@ -764,21 +608,6 @@ files = [
 [package.dependencies]
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-[[package]]
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-category = "dev"
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-python-versions = ">=3.7"
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-
-[package.extras]
-license = ["ukkonen"]
-
 [[package]]
 name = "idna"
 version = "3.4"
@@ -803,24 +632,6 @@ files = [
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-
-[package.dependencies]
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-
-[package.extras]
-i18n = ["Babel (>=2.7)"]
-
 [[package]]
 name = "jsonschema"
 version = "4.17.3"
@@ -938,81 +749,6 @@ websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.0 || >=0.43.0"
 [package.extras]
 adal = ["adal (>=1.0.2)"]
 
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-
-[[package]]
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-category = "dev"
-optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
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-
-[package.dependencies]
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-
 [[package]]
 name = "oauthlib"
 version = "3.2.2"
@@ -1034,7 +770,7 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1042,22 +778,6 @@ files = [
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 ]
 
-[[package]]
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-description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
-category = "dev"
-optional = false
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 [package.dependencies]
@@ -1354,14 +1055,14 @@ files = [
 
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 description = "Python HTTP for Humans."
 category = "main"
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-    {file = "Shapely-1.8.5.post1-cp39-cp39-win32.whl", hash = "sha256:8e59817b0fe63d34baedaabba8c393c0090f061917d18fc0bcc2f621937a8f73"},
-    {file = "Shapely-1.8.5.post1-cp39-cp39-win_amd64.whl", hash = "sha256:e9c30b311de2513555ab02464ebb76115d242842b29c412f5a9aa0cac57be9f6"},
-    {file = "Shapely-1.8.5.post1.tar.gz", hash = "sha256:ef3be705c3eac282a28058e6c6e5503419b250f482320df2172abcbea642c831"},
-]
-
-[package.extras]
-all = ["numpy", "pytest", "pytest-cov"]
-test = ["pytest", "pytest-cov"]
-vectorized = ["numpy"]
-
 [[package]]
 name = "six"
 version = "1.16.0"
@@ -1589,14 +1233,14 @@ test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.
 
 [[package]]
 name = "typing-extensions"
-version = "4.5.0"
+version = "4.6.2"
 description = "Backported and Experimental Type Hints for Python 3.7+"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"},
-    {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"},
+    {file = "typing_extensions-4.6.2-py3-none-any.whl", hash = "sha256:3a8b36f13dd5fdc5d1b16fe317f5668545de77fa0b8e02006381fd49d731ab98"},
+    {file = "typing_extensions-4.6.2.tar.gz", hash = "sha256:06006244c70ac8ee83fa8282cb188f697b8db25bc8b4df07be1873c43897060c"},
 ]
 
 [[package]]
@@ -1613,14 +1257,14 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "1.26.15"
+version = "1.26.16"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
-    {file = "urllib3-1.26.15-py2.py3-none-any.whl", hash = "sha256:aa751d169e23c7479ce47a0cb0da579e3ede798f994f5816a74e4f4500dcea42"},
-    {file = "urllib3-1.26.15.tar.gz", hash = "sha256:8a388717b9476f934a21484e8c8e61875ab60644d29b9b39e11e4b9dc1c6b305"},
+    {file = "urllib3-1.26.16-py2.py3-none-any.whl", hash = "sha256:8d36afa7616d8ab714608411b4a3b13e58f463aee519024578e062e141dce20f"},
+    {file = "urllib3-1.26.16.tar.gz", hash = "sha256:8f135f6502756bde6b2a9b28989df5fbe87c9970cecaa69041edcce7f0589b14"},
 ]
 
 [package.extras]
@@ -1628,37 +1272,16 @@ brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
 secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
 socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
-[[package]]
-name = "virtualenv"
-version = "20.23.0"
-description = "Virtual Python Environment builder"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "virtualenv-20.23.0-py3-none-any.whl", hash = "sha256:6abec7670e5802a528357fdc75b26b9f57d5d92f29c5462ba0fbe45feacc685e"},
-    {file = "virtualenv-20.23.0.tar.gz", hash = "sha256:a85caa554ced0c0afbd0d638e7e2d7b5f92d23478d05d17a76daeac8f279f924"},
-]
-
-[package.dependencies]
-distlib = ">=0.3.6,<1"
-filelock = ">=3.11,<4"
-platformdirs = ">=3.2,<4"
-
-[package.extras]
-docs = ["furo (>=2023.3.27)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=22.12)"]
-test = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.3.1)", "pytest-env (>=0.8.1)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=67.7.1)", "time-machine (>=2.9)"]
-
 [[package]]
 name = "websocket-client"
-version = "1.5.1"
+version = "1.5.2"
 description = "WebSocket client for Python with low level API options"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "websocket-client-1.5.1.tar.gz", hash = "sha256:3f09e6d8230892547132177f575a4e3e73cfdf06526e20cc02aa1c3b47184d40"},
-    {file = "websocket_client-1.5.1-py3-none-any.whl", hash = "sha256:cdf5877568b7e83aa7cf2244ab56a3213de587bbe0ce9d8b9600fc77b455d89e"},
+    {file = "websocket-client-1.5.2.tar.gz", hash = "sha256:c7d67c13b928645f259d9b847ab5b57fd2d127213ca41ebd880de1f553b7c23b"},
+    {file = "websocket_client-1.5.2-py3-none-any.whl", hash = "sha256:f8c64e28cd700e7ba1f04350d66422b6833b82a796b525a51e740b8cc8dab4b1"},
 ]
 
 [package.extras]
@@ -1769,4 +1392,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "1f75fb78ca2fd965417d30dd7715e4c282abcd1b53703654e5c022f4d2e79328"
+content-hash = "ec83532f673f942df8b19c490393de3a75bd4d1841ba3dc58958e39c311536de"
diff --git a/components/vertex-components/poetry.lock b/components/vertex-components/poetry.lock
index 45fcd24d..8a328b03 100644
--- a/components/vertex-components/poetry.lock
+++ b/components/vertex-components/poetry.lock
@@ -55,18 +55,6 @@ files = [
     {file = "certifi-2023.5.7.tar.gz", hash = "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7"},
 ]
 
-[[package]]
-name = "cfgv"
-version = "3.3.1"
-description = "Validate configuration and produce human readable error messages."
-category = "dev"
-optional = false
-python-versions = ">=3.6.1"
-files = [
-    {file = "cfgv-3.3.1-py2.py3-none-any.whl", hash = "sha256:c6a0883f3917a037485059700b9e75da2464e6c27051014ad85ba6aaa5884426"},
-    {file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"},
-]
-
 [[package]]
 name = "charset-normalizer"
 version = "3.1.0"
@@ -209,18 +197,6 @@ wrapt = ">=1.10,<2"
 [package.extras]
 dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"]
 
-[[package]]
-name = "distlib"
-version = "0.3.6"
-description = "Distribution utilities"
-category = "dev"
-optional = false
-python-versions = "*"
-files = [
-    {file = "distlib-0.3.6-py2.py3-none-any.whl", hash = "sha256:f35c4b692542ca110de7ef0bea44d73981caeb34ca0b9b6b2e6d7790dda8f80e"},
-    {file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"},
-]
-
 [[package]]
 name = "docstring-parser"
 version = "0.15"
@@ -248,22 +224,6 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
-[[package]]
-name = "filelock"
-version = "3.12.0"
-description = "A platform independent file lock."
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "filelock-3.12.0-py3-none-any.whl", hash = "sha256:ad98852315c2ab702aeb628412cbf7e95b7ce8c3bf9565670b4eaecf1db370a9"},
-    {file = "filelock-3.12.0.tar.gz", hash = "sha256:fc03ae43288c013d2ea83c8597001b1129db351aad9c57fe2409327916b8e718"},
-]
-
-[package.extras]
-docs = ["furo (>=2023.3.27)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
-
 [[package]]
 name = "fire"
 version = "0.5.0"
@@ -326,20 +286,20 @@ uritemplate = ">=3.0.0,<4dev"
 
 [[package]]
 name = "google-auth"
-version = "2.18.0"
+version = "2.19.0"
 description = "Google Authentication Library"
 category = "main"
 optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
+python-versions = ">=3.6"
 files = [
-    {file = "google-auth-2.18.0.tar.gz", hash = "sha256:c66b488a8b005b23ccb97b1198b6cece516c91869091ac5b7c267422db2733c7"},
-    {file = "google_auth-2.18.0-py2.py3-none-any.whl", hash = "sha256:ef3f3a67fa54d421a1c155864570f9a8de9179cedc937bda496b7a8ca338e936"},
+    {file = "google-auth-2.19.0.tar.gz", hash = "sha256:f39d528077ac540793dd3c22a8706178f157642a67d874db25c640b7fead277e"},
+    {file = "google_auth-2.19.0-py2.py3-none-any.whl", hash = "sha256:be617bfaf77774008e9d177573f782e109188c8a64ae6e744285df5cea3e7df6"},
 ]
 
 [package.dependencies]
 cachetools = ">=2.0.0,<6.0"
 pyasn1-modules = ">=0.2.1"
-rsa = {version = ">=3.1.4,<5", markers = "python_version >= \"3.6\""}
+rsa = ">=3.1.4,<5"
 six = ">=1.9.0"
 urllib3 = "<2.0"
 
@@ -371,7 +331,7 @@ six = "*"
 name = "google-cloud-aiplatform"
 version = "1.24.1"
 description = "Vertex AI API client library"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -409,7 +369,7 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 name = "google-cloud-bigquery"
 version = "3.10.0"
 description = "Google BigQuery API client library"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -461,7 +421,7 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 name = "google-cloud-notebooks"
 version = "1.7.0"
 description = "Google Cloud Notebooks API client library"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -479,7 +439,7 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 name = "google-cloud-pipeline-components"
 version = "1.0.42"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
-category = "main"
+category = "dev"
 optional = false
 python-versions = "*"
 files = [
@@ -501,14 +461,14 @@ tests = ["flake8 (>=3.0.0)", "google-api-core (>=1.31.5,<2.0.0 || >=2.8.0,<3.0.0
 
 [[package]]
 name = "google-cloud-resource-manager"
-version = "1.10.0"
+version = "1.10.1"
 description = "Google Cloud Resource Manager API client library"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-resource-manager-1.10.0.tar.gz", hash = "sha256:bfc3e60eb92e25ac562a9248bb8fc17e9bef04c3dc9f031ffbe0dfe28d919287"},
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+    {file = "google-cloud-resource-manager-1.10.1.tar.gz", hash = "sha256:c974fb6f9810476cf7b63ea89394c1a8df47f7f2dc2303e728bb74b500bcde67"},
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 ]
 
 [package.dependencies]
@@ -662,7 +622,7 @@ grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
 name = "grpc-google-iam-v1"
 version = "0.12.6"
 description = "IAM API client library"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -679,7 +639,7 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 name = "grpcio"
 version = "1.54.2"
 description = "HTTP/2-based RPC framework"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -737,7 +697,7 @@ protobuf = ["grpcio-tools (>=1.54.2)"]
 name = "grpcio-status"
 version = "1.47.0"
 description = "Status proto mapping for gRPC"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -765,21 +725,6 @@ files = [
 [package.dependencies]
 pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""}
 
-[[package]]
-name = "identify"
-version = "2.5.24"
-description = "File identification library for Python"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
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-]
-
-[package.extras]
-license = ["ukkonen"]
-
 [[package]]
 name = "idna"
 version = "3.4"
@@ -921,21 +866,6 @@ websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.0 || >=0.43.0"
 [package.extras]
 adal = ["adal (>=1.0.2)"]
 
-[[package]]
-name = "nodeenv"
-version = "1.8.0"
-description = "Node.js virtual environment builder"
-category = "dev"
-optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
-files = [
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-]
-
-[package.dependencies]
-setuptools = "*"
-
 [[package]]
 name = "oauthlib"
 version = "3.2.2"
@@ -957,7 +887,7 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -965,22 +895,6 @@ files = [
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
 ]
 
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-name = "platformdirs"
-version = "3.5.1"
-description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
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-
 [[package]]
 name = "pluggy"
 version = "1.0.0"
@@ -997,30 +911,11 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
-[[package]]
-name = "pre-commit"
-version = "2.21.0"
-description = "A framework for managing and maintaining multi-language pre-commit hooks."
-category = "dev"
-optional = false
-python-versions = ">=3.7"
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-
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-identify = ">=1.0.0"
-nodeenv = ">=0.11.1"
-pyyaml = ">=5.1"
-virtualenv = ">=20.10.0"
-
 [[package]]
 name = "proto-plus"
 version = "1.22.2"
 description = "Beautiful, Pythonic protocol buffers."
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1095,48 +990,48 @@ pyasn1 = ">=0.4.6,<0.6.0"
 
 [[package]]
 name = "pydantic"
-version = "1.10.7"
+version = "1.10.8"
 description = "Data validation and settings management using python type hints"
 category = "main"
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 python-versions = ">=3.7"
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+    {file = "pydantic-1.10.8-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:17aef11cc1b997f9d574b91909fed40761e13fac438d72b81f902226a69dac01"},
+    {file = "pydantic-1.10.8-cp39-cp39-win_amd64.whl", hash = "sha256:66a703d1983c675a6e0fed8953b0971c44dba48a929a2000a493c3772eb61a5a"},
+    {file = "pydantic-1.10.8-py3-none-any.whl", hash = "sha256:7456eb22ed9aaa24ff3e7b4757da20d9e5ce2a81018c1b3ebd81a0b88a18f3b2"},
+    {file = "pydantic-1.10.8.tar.gz", hash = "sha256:1410275520dfa70effadf4c21811d755e7ef9bb1f1d077a21958153a92c8d9ca"},
 ]
 
 [package.dependencies]
@@ -1277,14 +1172,14 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.30.0"
+version = "2.31.0"
 description = "Python HTTP for Humans."
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "requests-2.30.0-py3-none-any.whl", hash = "sha256:10e94cc4f3121ee6da529d358cdaeaff2f1c409cd377dbc72b825852f2f7e294"},
-    {file = "requests-2.30.0.tar.gz", hash = "sha256:239d7d4458afcb28a692cdd298d87542235f4ca8d36d03a15bfc128a6559a2f4"},
+    {file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
+    {file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
 ]
 
 [package.dependencies]
@@ -1348,26 +1243,26 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "setuptools"
-version = "67.7.2"
+version = "67.8.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "setuptools-67.7.2-py3-none-any.whl", hash = "sha256:23aaf86b85ca52ceb801d32703f12d77517b2556af839621c641fca11287952b"},
-    {file = "setuptools-67.7.2.tar.gz", hash = "sha256:f104fa03692a2602fa0fec6c6a9e63b6c8a968de13e17c026957dd1f53d80990"},
+    {file = "setuptools-67.8.0-py3-none-any.whl", hash = "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f"},
+    {file = "setuptools-67.8.0.tar.gz", hash = "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"},
 ]
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
 name = "shapely"
 version = "1.8.5.post1"
 description = "Geometric objects, predicates, and operations"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1512,14 +1407,14 @@ test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.
 
 [[package]]
 name = "typing-extensions"
-version = "4.5.0"
+version = "4.6.2"
 description = "Backported and Experimental Type Hints for Python 3.7+"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "typing_extensions-4.5.0-py3-none-any.whl", hash = "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"},
-    {file = "typing_extensions-4.5.0.tar.gz", hash = "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb"},
+    {file = "typing_extensions-4.6.2-py3-none-any.whl", hash = "sha256:3a8b36f13dd5fdc5d1b16fe317f5668545de77fa0b8e02006381fd49d731ab98"},
+    {file = "typing_extensions-4.6.2.tar.gz", hash = "sha256:06006244c70ac8ee83fa8282cb188f697b8db25bc8b4df07be1873c43897060c"},
 ]
 
 [[package]]
@@ -1536,14 +1431,14 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "1.26.15"
+version = "1.26.16"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
-    {file = "urllib3-1.26.15-py2.py3-none-any.whl", hash = "sha256:aa751d169e23c7479ce47a0cb0da579e3ede798f994f5816a74e4f4500dcea42"},
-    {file = "urllib3-1.26.15.tar.gz", hash = "sha256:8a388717b9476f934a21484e8c8e61875ab60644d29b9b39e11e4b9dc1c6b305"},
+    {file = "urllib3-1.26.16-py2.py3-none-any.whl", hash = "sha256:8d36afa7616d8ab714608411b4a3b13e58f463aee519024578e062e141dce20f"},
+    {file = "urllib3-1.26.16.tar.gz", hash = "sha256:8f135f6502756bde6b2a9b28989df5fbe87c9970cecaa69041edcce7f0589b14"},
 ]
 
 [package.extras]
@@ -1551,37 +1446,16 @@ brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
 secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
 socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
-[[package]]
-name = "virtualenv"
-version = "20.23.0"
-description = "Virtual Python Environment builder"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "virtualenv-20.23.0-py3-none-any.whl", hash = "sha256:6abec7670e5802a528357fdc75b26b9f57d5d92f29c5462ba0fbe45feacc685e"},
-    {file = "virtualenv-20.23.0.tar.gz", hash = "sha256:a85caa554ced0c0afbd0d638e7e2d7b5f92d23478d05d17a76daeac8f279f924"},
-]
-
-[package.dependencies]
-distlib = ">=0.3.6,<1"
-filelock = ">=3.11,<4"
-platformdirs = ">=3.2,<4"
-
-[package.extras]
-docs = ["furo (>=2023.3.27)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=22.12)"]
-test = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.3.1)", "pytest-env (>=0.8.1)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=67.7.1)", "time-machine (>=2.9)"]
-
 [[package]]
 name = "websocket-client"
-version = "1.5.1"
+version = "1.5.2"
 description = "WebSocket client for Python with low level API options"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "websocket-client-1.5.1.tar.gz", hash = "sha256:3f09e6d8230892547132177f575a4e3e73cfdf06526e20cc02aa1c3b47184d40"},
-    {file = "websocket_client-1.5.1-py3-none-any.whl", hash = "sha256:cdf5877568b7e83aa7cf2244ab56a3213de587bbe0ce9d8b9600fc77b455d89e"},
+    {file = "websocket-client-1.5.2.tar.gz", hash = "sha256:c7d67c13b928645f259d9b847ab5b57fd2d127213ca41ebd880de1f553b7c23b"},
+    {file = "websocket_client-1.5.2-py3-none-any.whl", hash = "sha256:f8c64e28cd700e7ba1f04350d66422b6833b82a796b525a51e740b8cc8dab4b1"},
 ]
 
 [package.extras]
@@ -1692,4 +1566,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "a33ea27bf21c7344b28dfc284c9da679f3dbd302759f7eb5e929058ebef11572"
+content-hash = "1f97617d2b92c562860cb6db2c44356f2a71e8c3444e15edc0a798edc8f5f564"

From 369d99d2802cd5fe15f5a9fefff437f8b995ada7 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 26 May 2023 16:56:10 +0100
Subject: [PATCH 064/238] style(README.md): update with poetry requirements

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index bce38968..0414b7c6 100644
--- a/README.md
+++ b/README.md
@@ -55,7 +55,7 @@ In a production MLOps solution, your ML pipelines need to be repeatable. So, we
 
 1. Clone the repository locally
 1. Install Python: `pyenv install`
-1. Install poetry and  dependencies: `make setup`
+1. Install poetry and poetry dependencies: `make setup`
 1. Install pre-commit hooks: `cd pipelines && poetry run pre-commit install`
 1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh`
 1. Load the environment variables in `env.sh` by running `source env.sh`

From d6afa104acca5e9460648aef8d965dbf8ba0c71e Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 09:19:35 +0100
Subject: [PATCH 065/238] build(src): update the base images of components to
 python 3.9

---
 .../src/bigquery_components/extract_bq_to_dataset.py            | 2 +-
 .../src/vertex_components/update_best_model.py                  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py b/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
index 3effe09a..10cd5bf4 100644
--- a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
+++ b/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
@@ -16,7 +16,7 @@
 
 
 @component(
-    base_image="python:3.7",
+    base_image="python:3.9",
     packages_to_install=["google-cloud-bigquery==2.30.0"],
 )
 def extract_bq_to_dataset(
diff --git a/components/vertex-components/src/vertex_components/update_best_model.py b/components/vertex-components/src/vertex_components/update_best_model.py
index eeb45461..14762906 100644
--- a/components/vertex-components/src/vertex_components/update_best_model.py
+++ b/components/vertex-components/src/vertex_components/update_best_model.py
@@ -17,7 +17,7 @@
 
 
 @component(
-    base_image="python:3.7",
+    base_image="python:3.9",
     packages_to_install=["google-cloud-aiplatform==1.24.1"],
 )
 def update_best_model(

From 28251c6e29d66f3af69ea16d5cf2be4fbbbf89a0 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 10:22:22 +0100
Subject: [PATCH 066/238] build(.python-version): change python version from
 3.9 to 3.7

---
 components/bigquery-components/.python-version | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/bigquery-components/.python-version b/components/bigquery-components/.python-version
index 9f3d4c17..475ba515 100644
--- a/components/bigquery-components/.python-version
+++ b/components/bigquery-components/.python-version
@@ -1 +1 @@
-3.9.16
+3.7

From 358abc2b9d4ad4989bce6a31a91211caef735471 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 10:24:40 +0100
Subject: [PATCH 067/238] build(.python-vesrion): python 3.7 to 3.9

---
 components/bigquery-components/.python-version | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/bigquery-components/.python-version b/components/bigquery-components/.python-version
index 475ba515..9f3d4c17 100644
--- a/components/bigquery-components/.python-version
+++ b/components/bigquery-components/.python-version
@@ -1 +1 @@
-3.7
+3.9.16

From b58e20bf5299aac885f34eaa580f09a8ffdfeaf4 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 30 May 2023 10:26:18 +0100
Subject: [PATCH 068/238] feat: merge conflict

---
 Makefile                                      |  17 ++
 .../tests/test_extract_bq_to_dataset.py       |  64 ++++++
 .../tests/test_custom_training_job.py         |  93 +++++++++
 .../tests/test_import_model_evaluation.py     |  57 ++++++
 .../tests/test_lookup_model.py                | 126 +++++-------
 .../tests/test_model_batch_predict.py         |  59 +++---
 .../tests/test_update_best_model.py           |  43 ++--
 pipelines/Pipfile                             |   1 +
 pipelines/Pipfile.lock                        | 189 ++++++++++++------
 pipelines/pyproject.toml                      |   1 +
 10 files changed, 463 insertions(+), 187 deletions(-)
 create mode 100644 components/bigquery-components/tests/test_extract_bq_to_dataset.py
 create mode 100644 components/vertex-components/tests/test_custom_training_job.py
 create mode 100644 components/vertex-components/tests/test_import_model_evaluation.py

diff --git a/Makefile b/Makefile
index df8ed419..88b75c84 100644
--- a/Makefile
+++ b/Makefile
@@ -57,8 +57,25 @@ test-all-components: ## Run unit tests for all pipeline components
 		$(MAKE) test-components GROUP=$$(basename $$component_group) ; \
 	done
 
+<<<<<<< HEAD
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
+=======
+test-components-coverage: ## Run tests with coverage
+	@cd "components/${GROUP}" && \
+	pipenv run coverage run -m pytest && \
+	pipenv run coverage report -m
+
+test-all-components-coverage: ## Run tests with coverage
+		@set -e && \
+	for component_group in components/*/ ; do \
+		echo "Test components under $$component_group" && \
+		$(MAKE) test-components-coverage GROUP=$$(basename $$component_group) ; \
+	done
+
+sync-assets: ## Sync assets folder to GCS. Must specify pipeline=<training|prediction>
+	@if [ -d "./pipelines/src/pipelines/${PIPELINE_TEMPLATE}/$(pipeline)/assets/" ] ; then \
+>>>>>>> develop
 		echo "Syncing assets to GCS" && \
 		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets ; \
 	else \
diff --git a/components/bigquery-components/tests/test_extract_bq_to_dataset.py b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
new file mode 100644
index 00000000..be3084e6
--- /dev/null
+++ b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
@@ -0,0 +1,64 @@
+import google.cloud.bigquery  # noqa
+from kfp.v2.dsl import Dataset
+from unittest import mock
+
+import bigquery_components
+
+extract_bq_to_dataset = bigquery_components.extract_bq_to_dataset.python_func
+
+
+@mock.patch("google.cloud.bigquery.client.Client")
+@mock.patch("google.cloud.bigquery.table.Table")
+@mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
+def test_extract_bq_to_dataset(mock_job_config, mock_table, mock_client, tmpdir):
+    """
+    Checks that the extract_bq_to_dataset is called correctly
+    """
+    mock_path = tmpdir
+    mock_client.extract_table.return_value = "my-job"
+    mock_table.return_value.table_ref = "my-table"
+    mock_job_config.return_value = "mock-job-config"
+
+    extract_bq_to_dataset(
+        bq_client_project_id="my-project-id",
+        source_project_id="source-project-id",
+        dataset_id="dataset-id",
+        table_name="table-name",
+        dataset=Dataset(uri=mock_path),
+        destination_gcs_uri="gs://mock_bucket",
+        dataset_location="EU",
+        extract_job_config=None,
+        skip_if_exists=False,
+    )
+
+    mock_client.return_value.extract_table.assert_called_once_with(
+        mock_table.return_value, "gs://mock_bucket", job_config="mock-job-config"
+    )
+
+
+@mock.patch("google.cloud.bigquery.client.Client")
+@mock.patch("google.cloud.bigquery.table.Table")
+@mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
+@mock.patch("pathlib.Path.exists")
+def test_extract_bq_to_dataset_skip_existing(
+    mock_path_exists, mock_job_config, mock_table, mock_client, tmpdir
+):
+    """
+    Checks that when the dataset exists the method is not called
+    """
+    mock_path = tmpdir
+    mock_path_exists.return_value = True
+
+    extract_bq_to_dataset(
+        bq_client_project_id="my-project-id",
+        source_project_id="source-project-id",
+        dataset_id="dataset-id",
+        table_name="table-name",
+        dataset=Dataset(uri=mock_path),
+        destination_gcs_uri="gs://mock_bucket",
+        dataset_location="EU",
+        extract_job_config=None,
+        skip_if_exists=True,
+    )
+
+    assert not mock_client.return_value.extract_table.called
diff --git a/components/vertex-components/tests/test_custom_training_job.py b/components/vertex-components/tests/test_custom_training_job.py
new file mode 100644
index 00000000..46ec46ca
--- /dev/null
+++ b/components/vertex-components/tests/test_custom_training_job.py
@@ -0,0 +1,93 @@
+import google.cloud.aiplatform as aip  # noqa
+from kfp.v2.dsl import Dataset, Metrics, Artifact
+from unittest import mock
+import pytest
+
+
+import vertex_components
+
+custom_train_job = vertex_components.custom_train_job.python_func
+
+
+@mock.patch("google.cloud.aiplatform.CustomTrainingJob")
+@mock.patch("os.path.exists")
+@mock.patch("builtins.open", new_callable=mock.mock_open, read_data="{}")
+def test_custom_train_job(mock_open, mock_exists, mock_job, tmpdir):
+    """
+    Checks that the custom job method is called
+    """
+    mock_exists.return_value = True
+
+    mock_train_data = Dataset(uri=tmpdir)
+    mock_valid_data = Dataset(uri=tmpdir)
+    mock_test_data = Dataset(uri=tmpdir)
+    mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
+    mock_metrics = Metrics(uri=tmpdir)
+
+    custom_train_job(
+        train_script_uri="gs://my-bucket/train_script.py",
+        train_data=mock_train_data,
+        valid_data=mock_valid_data,
+        test_data=mock_test_data,
+        project_id="my-project-id",
+        project_location="europe-west4",
+        model_display_name="my-model",
+        train_container_uri="gcr.io/my-project/my-image:latest",
+        serving_container_uri="gcr.io/my-project/my-serving-image:latest",
+        model=mock_model,
+        metrics=mock_metrics,
+        staging_bucket="gs://my-bucket",
+        job_name="my-job",
+    )
+
+    mock_job.assert_called_once_with(
+        project="my-project-id",
+        location="europe-west4",
+        staging_bucket="gs://my-bucket",
+        display_name="my-job",
+        script_path="/gcs/my-bucket/train_script.py",
+        container_uri="gcr.io/my-project/my-image:latest",
+        requirements=None,
+        model_serving_container_image_uri="gcr.io/my-project/my-serving-image:latest",  # noqa: E501
+    )
+
+    # Assert metrics loading
+    mock_open.assert_called_once_with(tmpdir, "r")
+
+
+@mock.patch("google.cloud.aiplatform.CustomTrainingJob")
+@mock.patch("os.path.exists")
+@mock.patch("builtins.open", new_callable=mock.mock_open, read_data="{}")
+def test_custom_train_script_not_found(mock_open, mock_exists, mock_job, tmpdir):
+    """
+    Checks that when the training script is not found
+    the method fails
+    """
+    mock_exists.return_value = False
+
+    mock_train_data = Dataset(uri=tmpdir)
+    mock_valid_data = Dataset(uri=tmpdir)
+    mock_test_data = Dataset(uri=tmpdir)
+    mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
+    mock_metrics = Metrics(uri=tmpdir)
+
+    with pytest.raises(ValueError):
+        custom_train_job(
+            train_script_uri="gs://my-bucket/train_script.py",
+            train_data=mock_train_data,
+            valid_data=mock_valid_data,
+            test_data=mock_test_data,
+            project_id="my-project-id",
+            project_location="europe-west4",
+            model_display_name="my-model",
+            train_container_uri="gcr.io/my-project/my-image:latest",
+            serving_container_uri="gcr.io/my-project/my-serving-image:latest",
+            model=mock_model,
+            metrics=mock_metrics,
+            staging_bucket="gs://my-bucket",
+            job_name="my-job",
+        )
+
+    # Assert the custom training job is not executed
+    mock_job.assert_not_called()
+    mock_open.assert_not_called()
diff --git a/components/vertex-components/tests/test_import_model_evaluation.py b/components/vertex-components/tests/test_import_model_evaluation.py
new file mode 100644
index 00000000..56cdf8bd
--- /dev/null
+++ b/components/vertex-components/tests/test_import_model_evaluation.py
@@ -0,0 +1,57 @@
+from unittest import mock
+from kfp.v2.dsl import Model, Metrics, Dataset
+
+import vertex_components
+from google.cloud.aiplatform_v1 import ModelEvaluation
+
+
+import_model_evaluation = vertex_components.import_model_evaluation.python_func
+
+
+@mock.patch("google.cloud.aiplatform_v1.ModelServiceClient")
+@mock.patch(
+    "builtins.open",
+    new_callable=mock.mock_open,
+    read_data='{"accuracy": 0.85, "problemType": "classification"}',
+)
+@mock.patch("google.protobuf.json_format.ParseDict")
+def test_import_model_evaluation(
+    mock_parse_dict, mock_open, mock_service_client, tmpdir
+):
+    """
+    Checks that when the model evaluation is running and it is writing the metrics
+    """
+    mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
+    mock_metrics = Metrics(uri=tmpdir)
+    mock_dataset = Dataset(uri=tmpdir)
+
+    # Create an instance of the mocked ModelServiceClient.
+    service_client_instance = mock.MagicMock()
+    mock_service_client.return_value = service_client_instance
+    # When import_model_evaluation is called during the test,
+    # it will return a new ModelEvaluation with the specified name.
+    service_client_instance.import_model_evaluation.return_value = ModelEvaluation(
+        name="model_evaluation_name"
+    )
+
+    # Set the return value for ParseDict to be a mock ModelEvaluation
+    mock_parse_dict.return_value = mock.MagicMock(spec=ModelEvaluation)
+
+    model_evaluation_name = import_model_evaluation(
+        model=mock_model,
+        metrics=mock_metrics,
+        test_dataset=mock_dataset,
+        pipeline_job_id="1234",
+        project_location="my-location",
+        evaluation_name="Imported evaluation",
+    )
+
+    service_client_instance.import_model_evaluation.assert_called_once_with(
+        parent=mock_model.metadata["resourceName"],
+        model_evaluation=mock_parse_dict.return_value,
+    )
+
+    # Check that open was called with the correct path
+    mock_open.assert_called_once_with(mock_metrics.uri)
+
+    assert model_evaluation_name[0] == "model_evaluation_name"
diff --git a/components/vertex-components/tests/test_lookup_model.py b/components/vertex-components/tests/test_lookup_model.py
index 1ba31f81..6950dd1b 100644
--- a/components/vertex-components/tests/test_lookup_model.py
+++ b/components/vertex-components/tests/test_lookup_model.py
@@ -22,93 +22,75 @@
 lookup_model = vertex_components.lookup_model.python_func
 
 
-def test_lookup_model(tmpdir):
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model(mock_model, tmpdir):
     """
     Assert lookup_model produces expected resource name, and that list method is
     called with the correct arguemnts
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-
-        # Mock attribute and method
-
-        mock_path = tmpdir
-        mock_model.resource_name = "my-model-resource-name"
-        mock_model.uri = mock_path
-        mock_model.list.return_value = [mock_model]
-
-        # Invoke the model look up
-        found_model_resource_name, _ = lookup_model(
-            model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
-            fail_on_model_not_found=False,
-            model=Model(uri=mock_path),
-        )
-
-        assert found_model_resource_name == "my-model-resource-name"
-
-        # Check the list method was called once with the correct arguments
-        mock_model.list.assert_called_once_with(
-            filter='display_name="my-model"',
-            order_by="create_time desc",
-            location="europe-west4",
-            project="my-project-id",
-        )
-
 
-def test_lookup_model_when_no_models(tmpdir):
+    # Mock attribute and method
+    mock_path = tmpdir
+    mock_model.resource_name = "my-model-resource-name"
+    mock_model.uri = mock_path
+    mock_model.list.return_value = [mock_model]
+
+    # Invoke the model look up
+    found_model_resource_name, _ = lookup_model(
+        model_name="my-model",
+        project_location="europe-west4",
+        project_id="my-project-id",
+        order_models_by="create_time desc",
+        fail_on_model_not_found=False,
+        model=Model(uri=mock_path),
+    )
+
+    assert found_model_resource_name == "my-model-resource-name"
+
+    # Check the list method was called once with the correct arguments
+    mock_model.list.assert_called_once_with(
+        filter='display_name="my-model"',
+        order_by="create_time desc",
+        location="europe-west4",
+        project="my-project-id",
+    )
+
+
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model_when_no_models(mock_model, tmpdir):
     """
     Checks that when there are no models and fail_on_model_found = False,
     lookup_model returns an empty string.
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-        mock_model.list.return_value = []
-        exported_model_resource_name, _ = lookup_model(
-            model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
-            fail_on_model_not_found=False,
-            model=Model(uri=str(tmpdir)),
-        )
+    mock_model.list.return_value = []
+    exported_model_resource_name, _ = lookup_model(
+        model_name="my-model",
+        project_location="europe-west4",
+        project_id="my-project-id",
+        order_models_by="create_time desc",
+        fail_on_model_not_found=False,
+        model=Model(uri=str(tmpdir)),
+    )
+
     print(exported_model_resource_name)
     assert exported_model_resource_name == ""
 
 
-def test_lookup_model_when_no_models_fail(tmpdir):
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model_when_no_models_fail(mock_model, tmpdir):
     """
     Checks that when there are no models and fail_on_model_found = True,
     lookup_model raises a RuntimeError.
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-        mock_model.list.return_value = []
+    mock_model.list.return_value = []
 
-        # Verify that a ValueError is raised
-        with pytest.raises(RuntimeError):
-            lookup_model(
-                model_name="my-model",
-                project_location="europe-west4",
-                project_id="my-project-id",
-                order_models_by="create_time desc",
-                fail_on_model_not_found=True,
-                model=Model(uri=str(tmpdir)),
-            )
+    # Verify that a ValueError is raised
+    with pytest.raises(RuntimeError):
+        lookup_model(
+            model_name="my-model",
+            project_location="europe-west4",
+            project_id="my-project-id",
+            order_models_by="create_time desc",
+            fail_on_model_not_found=True,
+            model=Model(uri=str(tmpdir)),
+        )
diff --git a/components/vertex-components/tests/test_model_batch_predict.py b/components/vertex-components/tests/test_model_batch_predict.py
index 10d9e808..76bca67d 100644
--- a/components/vertex-components/tests/test_model_batch_predict.py
+++ b/components/vertex-components/tests/test_model_batch_predict.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 import json
 import pytest
-from unittest.mock import Mock, patch
+from unittest import mock
 from kfp.v2.dsl import Model
 from google.cloud.aiplatform_v1beta1.types.job_state import JobState
 
@@ -30,7 +30,19 @@
     "targetField": "col",
 }
 
+mock_job1 = mock.Mock()
+mock_job1.name = "mock-batch-job"
+mock_job1.state = JobState.JOB_STATE_SUCCEEDED
 
+
+@mock.patch(
+    "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.create_batch_prediction_job",  # noqa : E501
+    return_value=mock_job1,
+)
+@mock.patch(
+    "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.get_batch_prediction_job",  # noqa : E501
+    return_value=mock_job1,
+)
 @pytest.mark.parametrize(
     (
         "source_format,destination_format,source_uri,monitoring_training_dataset,"
@@ -44,6 +56,8 @@
     ],
 )
 def test_model_batch_predict(
+    create_job,
+    get_job,
     tmpdir,
     source_format,
     destination_format,
@@ -55,37 +69,22 @@ def test_model_batch_predict(
     """
     Asserts model_batch_predict successfully creates requests given different arguments.
     """
-    mock_resource_name = "mock-batch-job"
-
-    mock_job1 = Mock()
-    mock_job1.name = mock_resource_name
-    mock_job1.state = JobState.JOB_STATE_SUCCEEDED
-
     mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
 
-    with patch(
-        "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.create_batch_prediction_job",  # noqa: E501
-        return_value=mock_job1,
-    ) as create_job, patch(
-        "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.get_batch_prediction_job",  # noqa: E501
-        return_value=mock_job1,
-    ) as get_job:
-        (gcp_resources,) = model_batch_predict(
-            model=mock_model,
-            job_display_name="",
-            project_location="",
-            project_id="",
-            source_uri=source_uri,
-            destination_uri=destination_format,
-            source_format=source_format,
-            destination_format=destination_format,
-            monitoring_training_dataset=monitoring_training_dataset,
-            monitoring_alert_email_addresses=monitoring_alert_email_addresses,
-            monitoring_skew_config=monitoring_skew_config,
-        )
+    (gcp_resources,) = model_batch_predict(
+        model=mock_model,
+        job_display_name="",
+        project_location="",
+        project_id="",
+        source_uri=source_uri,
+        destination_uri=destination_format,
+        source_format=source_format,
+        destination_format=destination_format,
+        monitoring_training_dataset=monitoring_training_dataset,
+        monitoring_alert_email_addresses=monitoring_alert_email_addresses,
+        monitoring_skew_config=monitoring_skew_config,
+    )
 
     create_job.assert_called_once()
     get_job.assert_called_once()
-    assert (
-        json.loads(gcp_resources)["resources"][0]["resourceUri"] == mock_resource_name
-    )
+    assert json.loads(gcp_resources)["resources"][0]["resourceUri"] == mock_job1.name
diff --git a/components/vertex-components/tests/test_update_best_model.py b/components/vertex-components/tests/test_update_best_model.py
index bce9a9df..4ef6ba21 100644
--- a/components/vertex-components/tests/test_update_best_model.py
+++ b/components/vertex-components/tests/test_update_best_model.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from unittest.mock import patch
+from unittest import mock
 
 from kfp.v2.dsl import Model
 
@@ -21,26 +21,31 @@
 update_best_model = vertex_components.update_best_model.python_func
 
 
-def test_model_batch_predict(tmpdir):
+@mock.patch("google.cloud.aiplatform.Model")
+@mock.patch("google.cloud.aiplatform.model_evaluation.ModelEvaluation")
+@mock.patch("google.cloud.aiplatform.models.ModelRegistry")
+@mock.patch("google.protobuf.json_format.MessageToDict")
+def test_model_batch_predict(
+    mock_message_to_dict,
+    mock_model_registry,
+    mock_model_evaluation,
+    mock_model_class,
+    tmpdir,
+):
     """
     Asserts model_batch_predict successfully creates requests given different arguments.
     """
     mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
     mock_message = {"metrics": {"rmse": 0.01}}
-
-    with patch("google.cloud.aiplatform.Model",), patch(
-        "google.cloud.aiplatform.model_evaluation.ModelEvaluation",
-    ), patch("google.cloud.aiplatform.models.ModelRegistry",), patch(
-        "google.protobuf.json_format.MessageToDict", return_value=mock_message
-    ):
-
-        (challenger_wins,) = update_best_model(
-            challenger=mock_model,
-            challenger_evaluation="",
-            parent_model="",
-            project_id="",
-            project_location="",
-            eval_metric="rmse",
-            eval_lower_is_better=True,
-        )
-        assert not challenger_wins
+    mock_message_to_dict.return_value = mock_message
+
+    (challenger_wins,) = update_best_model(
+        challenger=mock_model,
+        challenger_evaluation="",
+        parent_model="",
+        project_id="",
+        project_location="",
+        eval_metric="rmse",
+        eval_lower_is_better=True,
+    )
+    assert not challenger_wins
diff --git a/pipelines/Pipfile b/pipelines/Pipfile
index 507b4e6d..9538e7fc 100644
--- a/pipelines/Pipfile
+++ b/pipelines/Pipfile
@@ -14,6 +14,7 @@ bigquery-components = {editable = true, path = "./../components/bigquery-compone
 [dev-packages]
 pytest = ">=7.3.1,<8.0.0"
 pre-commit = ">=2.14.1,<3.0.0"
+coverage = "==7.2.5"
 
 [requires]
 python_version = "3.7"
diff --git a/pipelines/Pipfile.lock b/pipelines/Pipfile.lock
index 92d8d064..42ce01df 100644
--- a/pipelines/Pipfile.lock
+++ b/pipelines/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "c889b828537547fe3e76c0ca6f812f331bffdf13bfd8c72104145db94eb555e0"
+            "sha256": "2350f00a78fbfb02ef816a1ba3f5316c810e711a7cc685895cb135cb293d38cd"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -192,11 +192,11 @@
         },
         "google-auth": {
             "hashes": [
-                "sha256:ce311e2bc58b130fddf316df57c9b3943c2a7b4f6ec31de9663a9333e4064efc",
-                "sha256:f586b274d3eb7bd932ea424b1c702a30e0393a2e2bc4ca3eae8263ffd8be229f"
+                "sha256:55a395cdfd3f3dd3f649131d41f97c17b4ed8a2aac1be3502090c716314e8a37",
+                "sha256:d7a3249027e7f464fbbfd7ee8319a08ad09d2eea51578575c4bd360ffa049ccb"
             ],
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'",
-            "version": "==2.17.3"
+            "version": "==2.18.1"
         },
         "google-auth-httplib2": {
             "hashes": [
@@ -246,11 +246,11 @@
         },
         "google-cloud-resource-manager": {
             "hashes": [
-                "sha256:26beb595b957972df50173f1d0fd51c00d280551eac73566017ebdda62b1616a",
-                "sha256:bfc3e60eb92e25ac562a9248bb8fc17e9bef04c3dc9f031ffbe0dfe28d919287"
+                "sha256:41a2204532f084c707fde0bc1a9bc95c7e0b739d7072dd0b8a25106667a56184",
+                "sha256:c974fb6f9810476cf7b63ea89394c1a8df47f7f2dc2303e728bb74b500bcde67"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==1.10.0"
+            "version": "==1.10.1"
         },
         "google-cloud-storage": {
             "hashes": [
@@ -360,53 +360,53 @@
         },
         "grpcio": {
             "hashes": [
-                "sha256:02000b005bc8b72ff50c477b6431e8886b29961159e8b8d03c00b3dd9139baed",
-                "sha256:031bbd26656e0739e4b2c81c172155fb26e274b8d0312d67aefc730bcba915b6",
-                "sha256:1209d6b002b26e939e4c8ea37a3d5b4028eb9555394ea69fb1adbd4b61a10bb8",
-                "sha256:125ed35aa3868efa82eabffece6264bf638cfdc9f0cd58ddb17936684aafd0f8",
-                "sha256:1382bc499af92901c2240c4d540c74eae8a671e4fe9839bfeefdfcc3a106b5e2",
-                "sha256:16bca8092dd994f2864fdab278ae052fad4913f36f35238b2dd11af2d55a87db",
-                "sha256:1c59d899ee7160638613a452f9a4931de22623e7ba17897d8e3e348c2e9d8d0b",
-                "sha256:1d109df30641d050e009105f9c9ca5a35d01e34d2ee2a4e9c0984d392fd6d704",
-                "sha256:1fa7d6ddd33abbd3c8b3d7d07c56c40ea3d1891ce3cd2aa9fa73105ed5331866",
-                "sha256:21c4a1aae861748d6393a3ff7867473996c139a77f90326d9f4104bebb22d8b8",
-                "sha256:224166f06ccdaf884bf35690bf4272997c1405de3035d61384ccb5b25a4c1ca8",
-                "sha256:2262bd3512ba9e9f0e91d287393df6f33c18999317de45629b7bd46c40f16ba9",
-                "sha256:2585b3c294631a39b33f9f967a59b0fad23b1a71a212eba6bc1e3ca6e6eec9ee",
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+                "sha256:c2392f5b5d84b71d853918687d806c1aa4308109e5ca158a16e16a6be71041eb",
+                "sha256:c72956972e4b508dd39fdc7646637a791a9665b478e768ffa5f4fe42123d5de1",
+                "sha256:dc80c9c6b608bf98066a038e0172013a49cfa9a08d53335aefefda2c64fc68f4",
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+                "sha256:f900ed4ad7a0f1f05d35f955e0943944d5a75f607a836958c6b8ab2a81730ef2",
+                "sha256:fd6c6c29717724acf9fc1847c4515d57e4dc12762452457b9cb37461f30a81bb"
+            ],
+            "version": "==1.54.2"
         },
         "grpcio-status": {
             "hashes": [
@@ -784,11 +784,11 @@
         },
         "setuptools": {
             "hashes": [
-                "sha256:23aaf86b85ca52ceb801d32703f12d77517b2556af839621c641fca11287952b",
-                "sha256:f104fa03692a2602fa0fec6c6a9e63b6c8a968de13e17c026957dd1f53d80990"
+                "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f",
+                "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==67.7.2"
+            "version": "==67.8.0"
         },
         "shapely": {
             "hashes": [
@@ -1019,6 +1019,63 @@
             "markers": "python_full_version >= '3.6.1'",
             "version": "==3.3.1"
         },
+        "coverage": {
+            "hashes": [
+                "sha256:0342a28617e63ad15d96dca0f7ae9479a37b7d8a295f749c14f3436ea59fdcb3",
+                "sha256:066b44897c493e0dcbc9e6a6d9f8bbb6607ef82367cf6810d387c09f0cd4fe9a",
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+                "sha256:12580845917b1e59f8a1c2ffa6af6d0908cb39220f3019e36c110c943dc875b0",
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+                "sha256:292300f76440651529b8ceec283a9370532f4ecba9ad67d120617021bb5ef139",
+                "sha256:30dcaf05adfa69c2a7b9f7dfd9f60bc8e36b282d7ed25c308ef9e114de7fc23b",
+                "sha256:338aa9d9883aaaad53695cb14ccdeb36d4060485bb9388446330bef9c361c252",
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+                "sha256:38c0a497a000d50491055805313ed83ddba069353d102ece8aef5d11b5faf045",
+                "sha256:40cc0f91c6cde033da493227797be2826cbf8f388eaa36a0271a97a332bfd7ce",
+                "sha256:4436cc9ba5414c2c998eaedee5343f49c02ca93b21769c5fdfa4f9d799e84200",
+                "sha256:509ecd8334c380000d259dc66feb191dd0a93b21f2453faa75f7f9cdcefc0718",
+                "sha256:5c587f52c81211d4530fa6857884d37f514bcf9453bdeee0ff93eaaf906a5c1b",
+                "sha256:5f3671662dc4b422b15776cdca89c041a6349b4864a43aa2350b6b0b03bbcc7f",
+                "sha256:6599bf92f33ab041e36e06d25890afbdf12078aacfe1f1d08c713906e49a3fe5",
+                "sha256:6e8a95f243d01ba572341c52f89f3acb98a3b6d1d5d830efba86033dd3687ade",
+                "sha256:706ec567267c96717ab9363904d846ec009a48d5f832140b6ad08aad3791b1f5",
+                "sha256:780551e47d62095e088f251f5db428473c26db7829884323e56d9c0c3118791a",
+                "sha256:7ff8f3fb38233035028dbc93715551d81eadc110199e14bbbfa01c5c4a43f8d8",
+                "sha256:828189fcdda99aae0d6bf718ea766b2e715eabc1868670a0a07bf8404bf58c33",
+                "sha256:857abe2fa6a4973f8663e039ead8d22215d31db613ace76e4a98f52ec919068e",
+                "sha256:883123d0bbe1c136f76b56276074b0c79b5817dd4238097ffa64ac67257f4b6c",
+                "sha256:8877d9b437b35a85c18e3c6499b23674684bf690f5d96c1006a1ef61f9fdf0f3",
+                "sha256:8e575a59315a91ccd00c7757127f6b2488c2f914096077c745c2f1ba5b8c0969",
+                "sha256:97072cc90f1009386c8a5b7de9d4fc1a9f91ba5ef2146c55c1f005e7b5c5e068",
+                "sha256:9a22cbb5ede6fade0482111fa7f01115ff04039795d7092ed0db43522431b4f2",
+                "sha256:a063aad9f7b4c9f9da7b2550eae0a582ffc7623dca1c925e50c3fbde7a579771",
+                "sha256:a08c7401d0b24e8c2982f4e307124b671c6736d40d1c39e09d7a8687bddf83ed",
+                "sha256:a0b273fe6dc655b110e8dc89b8ec7f1a778d78c9fd9b4bda7c384c8906072212",
+                "sha256:a2b3b05e22a77bb0ae1a3125126a4e08535961c946b62f30985535ed40e26614",
+                "sha256:a66e055254a26c82aead7ff420d9fa8dc2da10c82679ea850d8feebf11074d88",
+                "sha256:aa387bd7489f3e1787ff82068b295bcaafbf6f79c3dad3cbc82ef88ce3f48ad3",
+                "sha256:ae453f655640157d76209f42c62c64c4d4f2c7f97256d3567e3b439bd5c9b06c",
+                "sha256:b5016e331b75310610c2cf955d9f58a9749943ed5f7b8cfc0bb89c6134ab0a84",
+                "sha256:b9a4ee55174b04f6af539218f9f8083140f61a46eabcaa4234f3c2a452c4ed11",
+                "sha256:bd3b4b8175c1db502adf209d06136c000df4d245105c8839e9d0be71c94aefe1",
+                "sha256:bebea5f5ed41f618797ce3ffb4606c64a5de92e9c3f26d26c2e0aae292f015c1",
+                "sha256:c10fbc8a64aa0f3ed136b0b086b6b577bc64d67d5581acd7cc129af52654384e",
+                "sha256:c2c41c1b1866b670573657d584de413df701f482574bad7e28214a2362cb1fd1",
+                "sha256:cf97ed82ca986e5c637ea286ba2793c85325b30f869bf64d3009ccc1a31ae3fd",
+                "sha256:d1f25ee9de21a39b3a8516f2c5feb8de248f17da7eead089c2e04aa097936b47",
+                "sha256:d2fbc2a127e857d2f8898aaabcc34c37771bf78a4d5e17d3e1f5c30cd0cbc62a",
+                "sha256:dc945064a8783b86fcce9a0a705abd7db2117d95e340df8a4333f00be5efb64c",
+                "sha256:ddc5a54edb653e9e215f75de377354e2455376f416c4378e1d43b08ec50acc31",
+                "sha256:e8834e5f17d89e05697c3c043d3e58a8b19682bf365048837383abfe39adaed5",
+                "sha256:ef9659d1cda9ce9ac9585c045aaa1e59223b143f2407db0eaee0b61a4f266fb6",
+                "sha256:f6f5cab2d7f0c12f8187a376cc6582c477d2df91d63f75341307fcdcb5d60303",
+                "sha256:f81c9b4bd8aa747d417407a7f6f0b1469a43b36a85748145e144ac4e8d303cb5",
+                "sha256:f99ef080288f09ffc687423b8d60978cf3a465d3f404a18d1a05474bd8575a47"
+            ],
+            "index": "pypi",
+            "version": "==7.2.5"
+        },
         "distlib": {
             "hashes": [
                 "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46",
@@ -1068,11 +1125,11 @@
         },
         "nodeenv": {
             "hashes": [
-                "sha256:27083a7b96a25f2f5e1d8cb4b6317ee8aeda3bdd121394e5ac54e498028a042e",
-                "sha256:e0e7f7dfb85fc5394c6fe1e8fa98131a2473e04311a45afb6508f7cf1836fa2b"
+                "sha256:d51e0c37e64fbf47d017feac3145cdbb58836d7eee8c6f6d3b6880c5456227d2",
+                "sha256:df865724bb3c3adc86b3876fa209771517b0cfe596beff01a92700e0e8be4cec"
             ],
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6'",
-            "version": "==1.7.0"
+            "version": "==1.8.0"
         },
         "packaging": {
             "hashes": [
@@ -1084,11 +1141,11 @@
         },
         "platformdirs": {
             "hashes": [
-                "sha256:47692bc24c1958e8b0f13dd727307cff1db103fca36399f457da8e05f222fdc4",
-                "sha256:7954a68d0ba23558d753f73437c55f89027cf8f5108c19844d4b82e5af396335"
+                "sha256:412dae91f52a6f84830f39a8078cecd0e866cb72294a5c66808e74d5e88d251f",
+                "sha256:e2378146f1964972c03c085bb5662ae80b2b8c06226c54b2ff4aa9483e8a13a5"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==3.5.0"
+            "version": "==3.5.1"
         },
         "pluggy": {
             "hashes": [
@@ -1151,11 +1208,11 @@
         },
         "setuptools": {
             "hashes": [
-                "sha256:23aaf86b85ca52ceb801d32703f12d77517b2556af839621c641fca11287952b",
-                "sha256:f104fa03692a2602fa0fec6c6a9e63b6c8a968de13e17c026957dd1f53d80990"
+                "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f",
+                "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==67.7.2"
+            "version": "==67.8.0"
         },
         "tomli": {
             "hashes": [
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index a5e2cbb7..693a3bd8 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -20,6 +20,7 @@ dependencies = [
 tests = [
     "google-cloud-bigquery == 2.30.0",
     "pytest >= 7.3.1,<8.0.0",
+    "coverage = ==7.2.5"
 ]
 
 [build-system]

From d856cd3bd738a83b96a65e74917bd8715ac55234 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 30 May 2023 10:41:54 +0100
Subject: [PATCH 069/238] Revert "feat: merge conflict"

This reverts commit b58e20bf5299aac885f34eaa580f09a8ffdfeaf4.
---
 Makefile                                      |  17 --
 .../tests/test_extract_bq_to_dataset.py       |  64 ------
 .../tests/test_custom_training_job.py         |  93 ---------
 .../tests/test_import_model_evaluation.py     |  57 ------
 .../tests/test_lookup_model.py                | 126 +++++++-----
 .../tests/test_model_batch_predict.py         |  59 +++---
 .../tests/test_update_best_model.py           |  43 ++--
 pipelines/Pipfile                             |   1 -
 pipelines/Pipfile.lock                        | 189 ++++++------------
 pipelines/pyproject.toml                      |   1 -
 10 files changed, 187 insertions(+), 463 deletions(-)
 delete mode 100644 components/bigquery-components/tests/test_extract_bq_to_dataset.py
 delete mode 100644 components/vertex-components/tests/test_custom_training_job.py
 delete mode 100644 components/vertex-components/tests/test_import_model_evaluation.py

diff --git a/Makefile b/Makefile
index 88b75c84..df8ed419 100644
--- a/Makefile
+++ b/Makefile
@@ -57,25 +57,8 @@ test-all-components: ## Run unit tests for all pipeline components
 		$(MAKE) test-components GROUP=$$(basename $$component_group) ; \
 	done
 
-<<<<<<< HEAD
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
-=======
-test-components-coverage: ## Run tests with coverage
-	@cd "components/${GROUP}" && \
-	pipenv run coverage run -m pytest && \
-	pipenv run coverage report -m
-
-test-all-components-coverage: ## Run tests with coverage
-		@set -e && \
-	for component_group in components/*/ ; do \
-		echo "Test components under $$component_group" && \
-		$(MAKE) test-components-coverage GROUP=$$(basename $$component_group) ; \
-	done
-
-sync-assets: ## Sync assets folder to GCS. Must specify pipeline=<training|prediction>
-	@if [ -d "./pipelines/src/pipelines/${PIPELINE_TEMPLATE}/$(pipeline)/assets/" ] ; then \
->>>>>>> develop
 		echo "Syncing assets to GCS" && \
 		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets ; \
 	else \
diff --git a/components/bigquery-components/tests/test_extract_bq_to_dataset.py b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
deleted file mode 100644
index be3084e6..00000000
--- a/components/bigquery-components/tests/test_extract_bq_to_dataset.py
+++ /dev/null
@@ -1,64 +0,0 @@
-import google.cloud.bigquery  # noqa
-from kfp.v2.dsl import Dataset
-from unittest import mock
-
-import bigquery_components
-
-extract_bq_to_dataset = bigquery_components.extract_bq_to_dataset.python_func
-
-
-@mock.patch("google.cloud.bigquery.client.Client")
-@mock.patch("google.cloud.bigquery.table.Table")
-@mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
-def test_extract_bq_to_dataset(mock_job_config, mock_table, mock_client, tmpdir):
-    """
-    Checks that the extract_bq_to_dataset is called correctly
-    """
-    mock_path = tmpdir
-    mock_client.extract_table.return_value = "my-job"
-    mock_table.return_value.table_ref = "my-table"
-    mock_job_config.return_value = "mock-job-config"
-
-    extract_bq_to_dataset(
-        bq_client_project_id="my-project-id",
-        source_project_id="source-project-id",
-        dataset_id="dataset-id",
-        table_name="table-name",
-        dataset=Dataset(uri=mock_path),
-        destination_gcs_uri="gs://mock_bucket",
-        dataset_location="EU",
-        extract_job_config=None,
-        skip_if_exists=False,
-    )
-
-    mock_client.return_value.extract_table.assert_called_once_with(
-        mock_table.return_value, "gs://mock_bucket", job_config="mock-job-config"
-    )
-
-
-@mock.patch("google.cloud.bigquery.client.Client")
-@mock.patch("google.cloud.bigquery.table.Table")
-@mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
-@mock.patch("pathlib.Path.exists")
-def test_extract_bq_to_dataset_skip_existing(
-    mock_path_exists, mock_job_config, mock_table, mock_client, tmpdir
-):
-    """
-    Checks that when the dataset exists the method is not called
-    """
-    mock_path = tmpdir
-    mock_path_exists.return_value = True
-
-    extract_bq_to_dataset(
-        bq_client_project_id="my-project-id",
-        source_project_id="source-project-id",
-        dataset_id="dataset-id",
-        table_name="table-name",
-        dataset=Dataset(uri=mock_path),
-        destination_gcs_uri="gs://mock_bucket",
-        dataset_location="EU",
-        extract_job_config=None,
-        skip_if_exists=True,
-    )
-
-    assert not mock_client.return_value.extract_table.called
diff --git a/components/vertex-components/tests/test_custom_training_job.py b/components/vertex-components/tests/test_custom_training_job.py
deleted file mode 100644
index 46ec46ca..00000000
--- a/components/vertex-components/tests/test_custom_training_job.py
+++ /dev/null
@@ -1,93 +0,0 @@
-import google.cloud.aiplatform as aip  # noqa
-from kfp.v2.dsl import Dataset, Metrics, Artifact
-from unittest import mock
-import pytest
-
-
-import vertex_components
-
-custom_train_job = vertex_components.custom_train_job.python_func
-
-
-@mock.patch("google.cloud.aiplatform.CustomTrainingJob")
-@mock.patch("os.path.exists")
-@mock.patch("builtins.open", new_callable=mock.mock_open, read_data="{}")
-def test_custom_train_job(mock_open, mock_exists, mock_job, tmpdir):
-    """
-    Checks that the custom job method is called
-    """
-    mock_exists.return_value = True
-
-    mock_train_data = Dataset(uri=tmpdir)
-    mock_valid_data = Dataset(uri=tmpdir)
-    mock_test_data = Dataset(uri=tmpdir)
-    mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
-    mock_metrics = Metrics(uri=tmpdir)
-
-    custom_train_job(
-        train_script_uri="gs://my-bucket/train_script.py",
-        train_data=mock_train_data,
-        valid_data=mock_valid_data,
-        test_data=mock_test_data,
-        project_id="my-project-id",
-        project_location="europe-west4",
-        model_display_name="my-model",
-        train_container_uri="gcr.io/my-project/my-image:latest",
-        serving_container_uri="gcr.io/my-project/my-serving-image:latest",
-        model=mock_model,
-        metrics=mock_metrics,
-        staging_bucket="gs://my-bucket",
-        job_name="my-job",
-    )
-
-    mock_job.assert_called_once_with(
-        project="my-project-id",
-        location="europe-west4",
-        staging_bucket="gs://my-bucket",
-        display_name="my-job",
-        script_path="/gcs/my-bucket/train_script.py",
-        container_uri="gcr.io/my-project/my-image:latest",
-        requirements=None,
-        model_serving_container_image_uri="gcr.io/my-project/my-serving-image:latest",  # noqa: E501
-    )
-
-    # Assert metrics loading
-    mock_open.assert_called_once_with(tmpdir, "r")
-
-
-@mock.patch("google.cloud.aiplatform.CustomTrainingJob")
-@mock.patch("os.path.exists")
-@mock.patch("builtins.open", new_callable=mock.mock_open, read_data="{}")
-def test_custom_train_script_not_found(mock_open, mock_exists, mock_job, tmpdir):
-    """
-    Checks that when the training script is not found
-    the method fails
-    """
-    mock_exists.return_value = False
-
-    mock_train_data = Dataset(uri=tmpdir)
-    mock_valid_data = Dataset(uri=tmpdir)
-    mock_test_data = Dataset(uri=tmpdir)
-    mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
-    mock_metrics = Metrics(uri=tmpdir)
-
-    with pytest.raises(ValueError):
-        custom_train_job(
-            train_script_uri="gs://my-bucket/train_script.py",
-            train_data=mock_train_data,
-            valid_data=mock_valid_data,
-            test_data=mock_test_data,
-            project_id="my-project-id",
-            project_location="europe-west4",
-            model_display_name="my-model",
-            train_container_uri="gcr.io/my-project/my-image:latest",
-            serving_container_uri="gcr.io/my-project/my-serving-image:latest",
-            model=mock_model,
-            metrics=mock_metrics,
-            staging_bucket="gs://my-bucket",
-            job_name="my-job",
-        )
-
-    # Assert the custom training job is not executed
-    mock_job.assert_not_called()
-    mock_open.assert_not_called()
diff --git a/components/vertex-components/tests/test_import_model_evaluation.py b/components/vertex-components/tests/test_import_model_evaluation.py
deleted file mode 100644
index 56cdf8bd..00000000
--- a/components/vertex-components/tests/test_import_model_evaluation.py
+++ /dev/null
@@ -1,57 +0,0 @@
-from unittest import mock
-from kfp.v2.dsl import Model, Metrics, Dataset
-
-import vertex_components
-from google.cloud.aiplatform_v1 import ModelEvaluation
-
-
-import_model_evaluation = vertex_components.import_model_evaluation.python_func
-
-
-@mock.patch("google.cloud.aiplatform_v1.ModelServiceClient")
-@mock.patch(
-    "builtins.open",
-    new_callable=mock.mock_open,
-    read_data='{"accuracy": 0.85, "problemType": "classification"}',
-)
-@mock.patch("google.protobuf.json_format.ParseDict")
-def test_import_model_evaluation(
-    mock_parse_dict, mock_open, mock_service_client, tmpdir
-):
-    """
-    Checks that when the model evaluation is running and it is writing the metrics
-    """
-    mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
-    mock_metrics = Metrics(uri=tmpdir)
-    mock_dataset = Dataset(uri=tmpdir)
-
-    # Create an instance of the mocked ModelServiceClient.
-    service_client_instance = mock.MagicMock()
-    mock_service_client.return_value = service_client_instance
-    # When import_model_evaluation is called during the test,
-    # it will return a new ModelEvaluation with the specified name.
-    service_client_instance.import_model_evaluation.return_value = ModelEvaluation(
-        name="model_evaluation_name"
-    )
-
-    # Set the return value for ParseDict to be a mock ModelEvaluation
-    mock_parse_dict.return_value = mock.MagicMock(spec=ModelEvaluation)
-
-    model_evaluation_name = import_model_evaluation(
-        model=mock_model,
-        metrics=mock_metrics,
-        test_dataset=mock_dataset,
-        pipeline_job_id="1234",
-        project_location="my-location",
-        evaluation_name="Imported evaluation",
-    )
-
-    service_client_instance.import_model_evaluation.assert_called_once_with(
-        parent=mock_model.metadata["resourceName"],
-        model_evaluation=mock_parse_dict.return_value,
-    )
-
-    # Check that open was called with the correct path
-    mock_open.assert_called_once_with(mock_metrics.uri)
-
-    assert model_evaluation_name[0] == "model_evaluation_name"
diff --git a/components/vertex-components/tests/test_lookup_model.py b/components/vertex-components/tests/test_lookup_model.py
index 6950dd1b..1ba31f81 100644
--- a/components/vertex-components/tests/test_lookup_model.py
+++ b/components/vertex-components/tests/test_lookup_model.py
@@ -22,75 +22,93 @@
 lookup_model = vertex_components.lookup_model.python_func
 
 
-@mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model(mock_model, tmpdir):
+def test_lookup_model(tmpdir):
     """
     Assert lookup_model produces expected resource name, and that list method is
     called with the correct arguemnts
+
+    Args:
+        tmpdir: built-in pytest tmpdir fixture
+
+    Returns:
+        None
     """
+    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
+
+        # Mock attribute and method
+
+        mock_path = tmpdir
+        mock_model.resource_name = "my-model-resource-name"
+        mock_model.uri = mock_path
+        mock_model.list.return_value = [mock_model]
+
+        # Invoke the model look up
+        found_model_resource_name, _ = lookup_model(
+            model_name="my-model",
+            project_location="europe-west4",
+            project_id="my-project-id",
+            order_models_by="create_time desc",
+            fail_on_model_not_found=False,
+            model=Model(uri=mock_path),
+        )
+
+        assert found_model_resource_name == "my-model-resource-name"
+
+        # Check the list method was called once with the correct arguments
+        mock_model.list.assert_called_once_with(
+            filter='display_name="my-model"',
+            order_by="create_time desc",
+            location="europe-west4",
+            project="my-project-id",
+        )
+
 
-    # Mock attribute and method
-    mock_path = tmpdir
-    mock_model.resource_name = "my-model-resource-name"
-    mock_model.uri = mock_path
-    mock_model.list.return_value = [mock_model]
-
-    # Invoke the model look up
-    found_model_resource_name, _ = lookup_model(
-        model_name="my-model",
-        project_location="europe-west4",
-        project_id="my-project-id",
-        order_models_by="create_time desc",
-        fail_on_model_not_found=False,
-        model=Model(uri=mock_path),
-    )
-
-    assert found_model_resource_name == "my-model-resource-name"
-
-    # Check the list method was called once with the correct arguments
-    mock_model.list.assert_called_once_with(
-        filter='display_name="my-model"',
-        order_by="create_time desc",
-        location="europe-west4",
-        project="my-project-id",
-    )
-
-
-@mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model_when_no_models(mock_model, tmpdir):
+def test_lookup_model_when_no_models(tmpdir):
     """
     Checks that when there are no models and fail_on_model_found = False,
     lookup_model returns an empty string.
-    """
-    mock_model.list.return_value = []
-    exported_model_resource_name, _ = lookup_model(
-        model_name="my-model",
-        project_location="europe-west4",
-        project_id="my-project-id",
-        order_models_by="create_time desc",
-        fail_on_model_not_found=False,
-        model=Model(uri=str(tmpdir)),
-    )
 
+    Args:
+        tmpdir: built-in pytest tmpdir fixture
+
+    Returns:
+        None
+    """
+    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
+        mock_model.list.return_value = []
+        exported_model_resource_name, _ = lookup_model(
+            model_name="my-model",
+            project_location="europe-west4",
+            project_id="my-project-id",
+            order_models_by="create_time desc",
+            fail_on_model_not_found=False,
+            model=Model(uri=str(tmpdir)),
+        )
     print(exported_model_resource_name)
     assert exported_model_resource_name == ""
 
 
-@mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model_when_no_models_fail(mock_model, tmpdir):
+def test_lookup_model_when_no_models_fail(tmpdir):
     """
     Checks that when there are no models and fail_on_model_found = True,
     lookup_model raises a RuntimeError.
+
+    Args:
+        tmpdir: built-in pytest tmpdir fixture
+
+    Returns:
+        None
     """
-    mock_model.list.return_value = []
+    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
+        mock_model.list.return_value = []
 
-    # Verify that a ValueError is raised
-    with pytest.raises(RuntimeError):
-        lookup_model(
-            model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
-            fail_on_model_not_found=True,
-            model=Model(uri=str(tmpdir)),
-        )
+        # Verify that a ValueError is raised
+        with pytest.raises(RuntimeError):
+            lookup_model(
+                model_name="my-model",
+                project_location="europe-west4",
+                project_id="my-project-id",
+                order_models_by="create_time desc",
+                fail_on_model_not_found=True,
+                model=Model(uri=str(tmpdir)),
+            )
diff --git a/components/vertex-components/tests/test_model_batch_predict.py b/components/vertex-components/tests/test_model_batch_predict.py
index 76bca67d..10d9e808 100644
--- a/components/vertex-components/tests/test_model_batch_predict.py
+++ b/components/vertex-components/tests/test_model_batch_predict.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 import json
 import pytest
-from unittest import mock
+from unittest.mock import Mock, patch
 from kfp.v2.dsl import Model
 from google.cloud.aiplatform_v1beta1.types.job_state import JobState
 
@@ -30,19 +30,7 @@
     "targetField": "col",
 }
 
-mock_job1 = mock.Mock()
-mock_job1.name = "mock-batch-job"
-mock_job1.state = JobState.JOB_STATE_SUCCEEDED
 
-
-@mock.patch(
-    "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.create_batch_prediction_job",  # noqa : E501
-    return_value=mock_job1,
-)
-@mock.patch(
-    "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.get_batch_prediction_job",  # noqa : E501
-    return_value=mock_job1,
-)
 @pytest.mark.parametrize(
     (
         "source_format,destination_format,source_uri,monitoring_training_dataset,"
@@ -56,8 +44,6 @@
     ],
 )
 def test_model_batch_predict(
-    create_job,
-    get_job,
     tmpdir,
     source_format,
     destination_format,
@@ -69,22 +55,37 @@ def test_model_batch_predict(
     """
     Asserts model_batch_predict successfully creates requests given different arguments.
     """
+    mock_resource_name = "mock-batch-job"
+
+    mock_job1 = Mock()
+    mock_job1.name = mock_resource_name
+    mock_job1.state = JobState.JOB_STATE_SUCCEEDED
+
     mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
 
-    (gcp_resources,) = model_batch_predict(
-        model=mock_model,
-        job_display_name="",
-        project_location="",
-        project_id="",
-        source_uri=source_uri,
-        destination_uri=destination_format,
-        source_format=source_format,
-        destination_format=destination_format,
-        monitoring_training_dataset=monitoring_training_dataset,
-        monitoring_alert_email_addresses=monitoring_alert_email_addresses,
-        monitoring_skew_config=monitoring_skew_config,
-    )
+    with patch(
+        "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.create_batch_prediction_job",  # noqa: E501
+        return_value=mock_job1,
+    ) as create_job, patch(
+        "google.cloud.aiplatform_v1beta1.services.job_service.JobServiceClient.get_batch_prediction_job",  # noqa: E501
+        return_value=mock_job1,
+    ) as get_job:
+        (gcp_resources,) = model_batch_predict(
+            model=mock_model,
+            job_display_name="",
+            project_location="",
+            project_id="",
+            source_uri=source_uri,
+            destination_uri=destination_format,
+            source_format=source_format,
+            destination_format=destination_format,
+            monitoring_training_dataset=monitoring_training_dataset,
+            monitoring_alert_email_addresses=monitoring_alert_email_addresses,
+            monitoring_skew_config=monitoring_skew_config,
+        )
 
     create_job.assert_called_once()
     get_job.assert_called_once()
-    assert json.loads(gcp_resources)["resources"][0]["resourceUri"] == mock_job1.name
+    assert (
+        json.loads(gcp_resources)["resources"][0]["resourceUri"] == mock_resource_name
+    )
diff --git a/components/vertex-components/tests/test_update_best_model.py b/components/vertex-components/tests/test_update_best_model.py
index 4ef6ba21..bce9a9df 100644
--- a/components/vertex-components/tests/test_update_best_model.py
+++ b/components/vertex-components/tests/test_update_best_model.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from unittest import mock
+from unittest.mock import patch
 
 from kfp.v2.dsl import Model
 
@@ -21,31 +21,26 @@
 update_best_model = vertex_components.update_best_model.python_func
 
 
-@mock.patch("google.cloud.aiplatform.Model")
-@mock.patch("google.cloud.aiplatform.model_evaluation.ModelEvaluation")
-@mock.patch("google.cloud.aiplatform.models.ModelRegistry")
-@mock.patch("google.protobuf.json_format.MessageToDict")
-def test_model_batch_predict(
-    mock_message_to_dict,
-    mock_model_registry,
-    mock_model_evaluation,
-    mock_model_class,
-    tmpdir,
-):
+def test_model_batch_predict(tmpdir):
     """
     Asserts model_batch_predict successfully creates requests given different arguments.
     """
     mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
     mock_message = {"metrics": {"rmse": 0.01}}
-    mock_message_to_dict.return_value = mock_message
-
-    (challenger_wins,) = update_best_model(
-        challenger=mock_model,
-        challenger_evaluation="",
-        parent_model="",
-        project_id="",
-        project_location="",
-        eval_metric="rmse",
-        eval_lower_is_better=True,
-    )
-    assert not challenger_wins
+
+    with patch("google.cloud.aiplatform.Model",), patch(
+        "google.cloud.aiplatform.model_evaluation.ModelEvaluation",
+    ), patch("google.cloud.aiplatform.models.ModelRegistry",), patch(
+        "google.protobuf.json_format.MessageToDict", return_value=mock_message
+    ):
+
+        (challenger_wins,) = update_best_model(
+            challenger=mock_model,
+            challenger_evaluation="",
+            parent_model="",
+            project_id="",
+            project_location="",
+            eval_metric="rmse",
+            eval_lower_is_better=True,
+        )
+        assert not challenger_wins
diff --git a/pipelines/Pipfile b/pipelines/Pipfile
index 9538e7fc..507b4e6d 100644
--- a/pipelines/Pipfile
+++ b/pipelines/Pipfile
@@ -14,7 +14,6 @@ bigquery-components = {editable = true, path = "./../components/bigquery-compone
 [dev-packages]
 pytest = ">=7.3.1,<8.0.0"
 pre-commit = ">=2.14.1,<3.0.0"
-coverage = "==7.2.5"
 
 [requires]
 python_version = "3.7"
diff --git a/pipelines/Pipfile.lock b/pipelines/Pipfile.lock
index 42ce01df..92d8d064 100644
--- a/pipelines/Pipfile.lock
+++ b/pipelines/Pipfile.lock
@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "2350f00a78fbfb02ef816a1ba3f5316c810e711a7cc685895cb135cb293d38cd"
+            "sha256": "c889b828537547fe3e76c0ca6f812f331bffdf13bfd8c72104145db94eb555e0"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -192,11 +192,11 @@
         },
         "google-auth": {
             "hashes": [
-                "sha256:55a395cdfd3f3dd3f649131d41f97c17b4ed8a2aac1be3502090c716314e8a37",
-                "sha256:d7a3249027e7f464fbbfd7ee8319a08ad09d2eea51578575c4bd360ffa049ccb"
+                "sha256:ce311e2bc58b130fddf316df57c9b3943c2a7b4f6ec31de9663a9333e4064efc",
+                "sha256:f586b274d3eb7bd932ea424b1c702a30e0393a2e2bc4ca3eae8263ffd8be229f"
             ],
             "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'",
-            "version": "==2.18.1"
+            "version": "==2.17.3"
         },
         "google-auth-httplib2": {
             "hashes": [
@@ -246,11 +246,11 @@
         },
         "google-cloud-resource-manager": {
             "hashes": [
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         "google-cloud-storage": {
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@@ -360,53 +360,53 @@
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@@ -784,11 +784,11 @@
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@@ -1019,63 +1019,6 @@
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@@ -1125,11 +1068,11 @@
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@@ -1141,11 +1084,11 @@
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@@ -1208,11 +1151,11 @@
         },
         "setuptools": {
             "hashes": [
-                "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f",
-                "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"
+                "sha256:23aaf86b85ca52ceb801d32703f12d77517b2556af839621c641fca11287952b",
+                "sha256:f104fa03692a2602fa0fec6c6a9e63b6c8a968de13e17c026957dd1f53d80990"
             ],
             "markers": "python_version >= '3.7'",
-            "version": "==67.8.0"
+            "version": "==67.7.2"
         },
         "tomli": {
             "hashes": [
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 693a3bd8..a5e2cbb7 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -20,7 +20,6 @@ dependencies = [
 tests = [
     "google-cloud-bigquery == 2.30.0",
     "pytest >= 7.3.1,<8.0.0",
-    "coverage = ==7.2.5"
 ]
 
 [build-system]

From 386349daa990c925f50ed2a25cea8b5cdc95998b Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 13:50:15 +0100
Subject: [PATCH 070/238] style(README.md): add instructions for python version
 detection

---
 README.md | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/README.md b/README.md
index 0414b7c6..8c9651e1 100644
--- a/README.md
+++ b/README.md
@@ -60,6 +60,13 @@ In a production MLOps solution, your ML pipelines need to be repeatable. So, we
 1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh`
 1. Load the environment variables in `env.sh` by running `source env.sh`
 
+please note: `poetry install` or `poetry add`, installs packages within the project's virtual environment. If you use pip directly, you might accidentally install packages globally or in the wrong environment, leading to conflicts or difficulties in managing dependencies.
+
+### Configuring poetry to detect python version using pyenv
+
+1. run in terminal `poetry config virtualenvs.prefer-active-python true`
+1. Manage and install project's dependencies using `poetry install`
+
 ### Deploying Cloud Infrastructure
 
 The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):

From ee462f024bf7d6aac6fdd8607b949ba7471f3935 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 13:51:56 +0100
Subject: [PATCH 071/238] style(Makefile): remove pip install poetry from setup
 command

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 09441314..a9438069 100644
--- a/Makefile
+++ b/Makefile
@@ -23,7 +23,7 @@ pre-commit: ## Runs the pre-commit checks over entire repo
 	poetry run pre-commit run --all-files
 
 setup: ## Set up local environment for Python development on pipelines
-	@pip install poetry && \
+	@poetry install && \
 	cd pipelines && \
 	poetry install --with dev 
 

From 7d18fa86e76f53406df413507e7463e969b159e5 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 15:39:06 +0100
Subject: [PATCH 072/238] build: revert python version from 3.9 to 3.7

---
 .pre-commit-config.yaml                       |    2 +-
 .python-version                               |    2 +-
 cloudbuild/e2e-test.yaml                      |    2 +-
 cloudbuild/pr-checks.yaml                     |    2 +-
 cloudbuild/release.yaml                       |    2 +-
 cloudbuild/trigger-tests.yaml                 |    2 +-
 .../bigquery-components/.python-version       |    2 +-
 components/bigquery-components/poetry.lock    |  101 +-
 components/bigquery-components/pyproject.toml |    4 +-
 .../extract_bq_to_dataset.py                  |    2 +-
 components/vertex-components/.python-version  |    2 +-
 components/vertex-components/poetry.lock      |  101 +-
 components/vertex-components/pyproject.toml   |    4 +-
 .../vertex_components/update_best_model.py    |    2 +-
 pipelines/.python-version                     |    2 +-
 pipelines/Pipfile                             |   20 -
 pipelines/Pipfile.lock                        | 1250 -----------------
 pipelines/poetry.lock                         |  171 ++-
 pipelines/pyproject.toml                      |    7 +-
 19 files changed, 325 insertions(+), 1355 deletions(-)
 delete mode 100644 pipelines/Pipfile
 delete mode 100644 pipelines/Pipfile.lock

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 66dc32d3..3bd0bc1e 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -14,7 +14,7 @@
 
 ---
 default_language_version:
-  python: python3.9
+  python: python3.7
 
 repos:
   - repo: https://github.com/gruntwork-io/pre-commit
diff --git a/.python-version b/.python-version
index 9f3d4c17..8a433dd7 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.9.16
+3.7.12 
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 82554d8e..3aa9a513 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -30,7 +30,7 @@ steps:
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
-  - name: python:3.9
+  - name: python:3.7
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 969e7bbf..9f0f4347 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -17,7 +17,7 @@ steps:
   # Install poetry and deps, run pre-commit and unit tests
   # Then compile pipelines (to make sure they can compile)
   # need to run "git init" for pre-commit checks to work
-  - name: python:3.9
+  - name: python:3.7
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 9d0f4226..b5664ec0 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -15,7 +15,7 @@
 steps:
 
   # Install poetry, install deps, compile pipelines
-  - name: python:3.9
+  - name: python:3.7
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/trigger-tests.yaml b/cloudbuild/trigger-tests.yaml
index 295e2c50..a3387438 100644
--- a/cloudbuild/trigger-tests.yaml
+++ b/cloudbuild/trigger-tests.yaml
@@ -13,7 +13,7 @@
 # limitations under the License.
 ---
 steps:
-  - name: 'python:3.9'
+  - name: 'python:3.7'
     args:
       - '-c'
       - |
diff --git a/components/bigquery-components/.python-version b/components/bigquery-components/.python-version
index 9f3d4c17..8a433dd7 100644
--- a/components/bigquery-components/.python-version
+++ b/components/bigquery-components/.python-version
@@ -1 +1 @@
-3.9.16
+3.7.12 
diff --git a/components/bigquery-components/poetry.lock b/components/bigquery-components/poetry.lock
index 8a60aaaf..8f0f3273 100644
--- a/components/bigquery-components/poetry.lock
+++ b/components/bigquery-components/poetry.lock
@@ -24,6 +24,9 @@ files = [
     {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
 ]
 
+[package.dependencies]
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
+
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
 dev = ["attrs[docs,tests]", "pre-commit"]
@@ -33,14 +36,14 @@ tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pyte
 
 [[package]]
 name = "cachetools"
-version = "5.3.0"
+version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
 category = "main"
 optional = false
-python-versions = "~=3.7"
+python-versions = ">=3.7"
 files = [
-    {file = "cachetools-5.3.0-py3-none-any.whl", hash = "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"},
-    {file = "cachetools-5.3.0.tar.gz", hash = "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14"},
+    {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
+    {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
 ]
 
 [[package]]
@@ -154,6 +157,7 @@ files = [
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
 [[package]]
 name = "cloudpickle"
@@ -181,21 +185,21 @@ files = [
 
 [[package]]
 name = "deprecated"
-version = "1.2.13"
+version = "1.2.14"
 description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
 category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
-    {file = "Deprecated-1.2.13-py2.py3-none-any.whl", hash = "sha256:64756e3e14c8c5eea9795d93c524551432a0be75629f8f29e67ab8caf076c76d"},
-    {file = "Deprecated-1.2.13.tar.gz", hash = "sha256:43ac5335da90c31c24ba028af536a91d41d53f9e6901ddb021bcc572ce44e38d"},
+    {file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
+    {file = "Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3"},
 ]
 
 [package.dependencies]
 wrapt = ">=1.10,<2"
 
 [package.extras]
-dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"]
+dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
 
 [[package]]
 name = "docstring-parser"
@@ -620,6 +624,46 @@ files = [
     {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
 ]
 
+[[package]]
+name = "importlib-metadata"
+version = "6.6.0"
+description = "Read metadata from Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_metadata-6.6.0-py3-none-any.whl", hash = "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed"},
+    {file = "importlib_metadata-6.6.0.tar.gz", hash = "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
+zipp = ">=0.5"
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+perf = ["ipython"]
+testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
+
+[[package]]
+name = "importlib-resources"
+version = "5.12.0"
+description = "Read resources from Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
+    {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
+]
+
+[package.dependencies]
+zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -646,7 +690,11 @@ files = [
 
 [package.dependencies]
 attrs = ">=17.4.0"
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
+importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
+pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
 pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
+typing-extensions = {version = "*", markers = "python_version < \"3.8\""}
 
 [package.extras]
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
@@ -685,6 +733,7 @@ requests-toolbelt = ">=0.8.0,<1"
 strip-hints = ">=0.1.8,<1"
 tabulate = ">=0.8.6,<1"
 typer = ">=0.3.2,<1.0"
+typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
 uritemplate = ">=3.0.1,<4"
 urllib3 = "<2"
 
@@ -778,6 +827,18 @@ files = [
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
 ]
 
+[[package]]
+name = "pkgutil-resolve-name"
+version = "1.3.10"
+description = "Resolve a name to an object."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "pkgutil_resolve_name-1.3.10-py3-none-any.whl", hash = "sha256:ca27cc078d25c5ad71a9de0a7a330146c4e014c2462d9af19c6b828280649c5e"},
+    {file = "pkgutil_resolve_name-1.3.10.tar.gz", hash = "sha256:357d6c9e6a755653cfd78893817c0853af365dd51ec97f3d358a819373bbd174"},
+]
+
 [[package]]
 name = "pluggy"
 version = "1.0.0"
@@ -790,6 +851,9 @@ files = [
     {file = "pluggy-1.0.0.tar.gz", hash = "sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159"},
 ]
 
+[package.dependencies]
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
+
 [package.extras]
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
@@ -991,6 +1055,7 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
 exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
 iniconfig = "*"
 packaging = "*"
 pluggy = ">=0.12,<2.0"
@@ -1389,7 +1454,23 @@ files = [
     {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
 ]
 
+[[package]]
+name = "zipp"
+version = "3.15.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
+    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.9,<3.11"
-content-hash = "ec83532f673f942df8b19c490393de3a75bd4d1841ba3dc58958e39c311536de"
+python-versions = ">=3.7,<3.11"
+content-hash = "d7bc7cb1b7d234cc70d56b33a1253a6a52b0f6d9ab3114fd47ab47dbfcdadfa0"
diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index ae6dc103..19db2207 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -7,11 +7,11 @@ readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.7",
 ]
 
 [tool.poetry.dependencies]
-python = ">=3.9,<3.11"
+python = ">=3.7,<3.11"
 kfp = "==1.8.21"
 
 [tool.poetry.group.dev.dependencies]
diff --git a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py b/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
index 10cd5bf4..3effe09a 100644
--- a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
+++ b/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
@@ -16,7 +16,7 @@
 
 
 @component(
-    base_image="python:3.9",
+    base_image="python:3.7",
     packages_to_install=["google-cloud-bigquery==2.30.0"],
 )
 def extract_bq_to_dataset(
diff --git a/components/vertex-components/.python-version b/components/vertex-components/.python-version
index 9f3d4c17..8a433dd7 100644
--- a/components/vertex-components/.python-version
+++ b/components/vertex-components/.python-version
@@ -1 +1 @@
-3.9.16
+3.7.12 
diff --git a/components/vertex-components/poetry.lock b/components/vertex-components/poetry.lock
index 8a328b03..ca09c083 100644
--- a/components/vertex-components/poetry.lock
+++ b/components/vertex-components/poetry.lock
@@ -24,6 +24,9 @@ files = [
     {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
 ]
 
+[package.dependencies]
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
+
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
 dev = ["attrs[docs,tests]", "pre-commit"]
@@ -33,14 +36,14 @@ tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pyte
 
 [[package]]
 name = "cachetools"
-version = "5.3.0"
+version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
 category = "main"
 optional = false
-python-versions = "~=3.7"
+python-versions = ">=3.7"
 files = [
-    {file = "cachetools-5.3.0-py3-none-any.whl", hash = "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"},
-    {file = "cachetools-5.3.0.tar.gz", hash = "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14"},
+    {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
+    {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
 ]
 
 [[package]]
@@ -154,6 +157,7 @@ files = [
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
 [[package]]
 name = "cloudpickle"
@@ -181,21 +185,21 @@ files = [
 
 [[package]]
 name = "deprecated"
-version = "1.2.13"
+version = "1.2.14"
 description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
 category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
-    {file = "Deprecated-1.2.13-py2.py3-none-any.whl", hash = "sha256:64756e3e14c8c5eea9795d93c524551432a0be75629f8f29e67ab8caf076c76d"},
-    {file = "Deprecated-1.2.13.tar.gz", hash = "sha256:43ac5335da90c31c24ba028af536a91d41d53f9e6901ddb021bcc572ce44e38d"},
+    {file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
+    {file = "Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3"},
 ]
 
 [package.dependencies]
 wrapt = ">=1.10,<2"
 
 [package.extras]
-dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"]
+dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
 
 [[package]]
 name = "docstring-parser"
@@ -737,6 +741,46 @@ files = [
     {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
 ]
 
+[[package]]
+name = "importlib-metadata"
+version = "6.6.0"
+description = "Read metadata from Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_metadata-6.6.0-py3-none-any.whl", hash = "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed"},
+    {file = "importlib_metadata-6.6.0.tar.gz", hash = "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
+zipp = ">=0.5"
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+perf = ["ipython"]
+testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
+
+[[package]]
+name = "importlib-resources"
+version = "5.12.0"
+description = "Read resources from Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
+    {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
+]
+
+[package.dependencies]
+zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -763,7 +807,11 @@ files = [
 
 [package.dependencies]
 attrs = ">=17.4.0"
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
+importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
+pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
 pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
+typing-extensions = {version = "*", markers = "python_version < \"3.8\""}
 
 [package.extras]
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
@@ -802,6 +850,7 @@ requests-toolbelt = ">=0.8.0,<1"
 strip-hints = ">=0.1.8,<1"
 tabulate = ">=0.8.6,<1"
 typer = ">=0.3.2,<1.0"
+typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
 uritemplate = ">=3.0.1,<4"
 urllib3 = "<2"
 
@@ -895,6 +944,18 @@ files = [
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
 ]
 
+[[package]]
+name = "pkgutil-resolve-name"
+version = "1.3.10"
+description = "Resolve a name to an object."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "pkgutil_resolve_name-1.3.10-py3-none-any.whl", hash = "sha256:ca27cc078d25c5ad71a9de0a7a330146c4e014c2462d9af19c6b828280649c5e"},
+    {file = "pkgutil_resolve_name-1.3.10.tar.gz", hash = "sha256:357d6c9e6a755653cfd78893817c0853af365dd51ec97f3d358a819373bbd174"},
+]
+
 [[package]]
 name = "pluggy"
 version = "1.0.0"
@@ -907,6 +968,9 @@ files = [
     {file = "pluggy-1.0.0.tar.gz", hash = "sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159"},
 ]
 
+[package.dependencies]
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
+
 [package.extras]
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
@@ -1108,6 +1172,7 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
 exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
 iniconfig = "*"
 packaging = "*"
 pluggy = ">=0.12,<2.0"
@@ -1563,7 +1628,23 @@ files = [
     {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
 ]
 
+[[package]]
+name = "zipp"
+version = "3.15.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
+    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.9,<3.11"
-content-hash = "1f97617d2b92c562860cb6db2c44356f2a71e8c3444e15edc0a798edc8f5f564"
+python-versions = ">=3.7,<3.11"
+content-hash = "9ab64756b47c22efb2437659a3a7b8ca9a5b5c019f86217a03bdfbfb620d83ee"
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index 62fe0693..91f212a6 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -7,11 +7,11 @@ readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.7",
 ]
 
 [tool.poetry.dependencies]
-python = ">=3.9,<3.11"
+python = ">=3.7,<3.11"
 kfp = "==1.8.21"
 
 [tool.poetry.group.dev.dependencies]
diff --git a/components/vertex-components/src/vertex_components/update_best_model.py b/components/vertex-components/src/vertex_components/update_best_model.py
index 14762906..eeb45461 100644
--- a/components/vertex-components/src/vertex_components/update_best_model.py
+++ b/components/vertex-components/src/vertex_components/update_best_model.py
@@ -17,7 +17,7 @@
 
 
 @component(
-    base_image="python:3.9",
+    base_image="python:3.7",
     packages_to_install=["google-cloud-aiplatform==1.24.1"],
 )
 def update_best_model(
diff --git a/pipelines/.python-version b/pipelines/.python-version
index 9f3d4c17..8a433dd7 100644
--- a/pipelines/.python-version
+++ b/pipelines/.python-version
@@ -1 +1 @@
-3.9.16
+3.7.12 
diff --git a/pipelines/Pipfile b/pipelines/Pipfile
deleted file mode 100644
index 9538e7fc..00000000
--- a/pipelines/Pipfile
+++ /dev/null
@@ -1,20 +0,0 @@
-[[source]]
-url = "https://pypi.org/simple"
-verify_ssl = true
-name = "pypi"
-
-[packages]
-kfp = "==1.8.21"
-google-cloud-aiplatform = "==1.24.1"
-google-cloud-pipeline-components = "==1.0.42"
-Jinja2 = ">=3.0.1,<4.0.0"
-vertex-components = {editable = true, path = "./../components/vertex-components"}
-bigquery-components = {editable = true, path = "./../components/bigquery-components"}
-
-[dev-packages]
-pytest = ">=7.3.1,<8.0.0"
-pre-commit = ">=2.14.1,<3.0.0"
-coverage = "==7.2.5"
-
-[requires]
-python_version = "3.7"
diff --git a/pipelines/Pipfile.lock b/pipelines/Pipfile.lock
deleted file mode 100644
index 42ce01df..00000000
--- a/pipelines/Pipfile.lock
+++ /dev/null
@@ -1,1250 +0,0 @@
-{
-    "_meta": {
-        "hash": {
-            "sha256": "2350f00a78fbfb02ef816a1ba3f5316c810e711a7cc685895cb135cb293d38cd"
-        },
-        "pipfile-spec": 6,
-        "requires": {
-            "python_version": "3.7"
-        },
-        "sources": [
-            {
-                "name": "pypi",
-                "url": "https://pypi.org/simple",
-                "verify_ssl": true
-            }
-        ]
-    },
-    "default": {
-        "absl-py": {
-            "hashes": [
-                "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47",
-                "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==1.4.0"
-        },
-        "attrs": {
-            "hashes": [
-                "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04",
-                "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==23.1.0"
-        },
-        "bigquery-components": {
-            "editable": true,
-            "path": "./../components/bigquery-components"
-        },
-        "cachetools": {
-            "hashes": [
-                "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14",
-                "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"
-            ],
-            "markers": "python_version ~= '3.7'",
-            "version": "==5.3.0"
-        },
-        "certifi": {
-            "hashes": [
-                "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7",
-                "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"
-            ],
-            "markers": "python_version >= '3.6'",
-            "version": "==2023.5.7"
-        },
-        "charset-normalizer": {
-            "hashes": [
-                "sha256:04afa6387e2b282cf78ff3dbce20f0cc071c12dc8f685bd40960cc68644cfea6",
-                "sha256:04eefcee095f58eaabe6dc3cc2262f3bcd776d2c67005880894f447b3f2cb9c1",
-                "sha256:0be65ccf618c1e7ac9b849c315cc2e8a8751d9cfdaa43027d4f6624bd587ab7e",
-                "sha256:0c95f12b74681e9ae127728f7e5409cbbef9cd914d5896ef238cc779b8152373",
-                "sha256:0ca564606d2caafb0abe6d1b5311c2649e8071eb241b2d64e75a0d0065107e62",
-                "sha256:10c93628d7497c81686e8e5e557aafa78f230cd9e77dd0c40032ef90c18f2230",
-                "sha256:11d117e6c63e8f495412d37e7dc2e2fff09c34b2d09dbe2bee3c6229577818be",
-                "sha256:11d3bcb7be35e7b1bba2c23beedac81ee893ac9871d0ba79effc7fc01167db6c",
-                "sha256:12a2b561af122e3d94cdb97fe6fb2bb2b82cef0cdca131646fdb940a1eda04f0",
-                "sha256:12d1a39aa6b8c6f6248bb54550efcc1c38ce0d8096a146638fd4738e42284448",
-                "sha256:1435ae15108b1cb6fffbcea2af3d468683b7afed0169ad718451f8db5d1aff6f",
-                "sha256:1c60b9c202d00052183c9be85e5eaf18a4ada0a47d188a83c8f5c5b23252f649",
-                "sha256:1e8fcdd8f672a1c4fc8d0bd3a2b576b152d2a349782d1eb0f6b8e52e9954731d",
-                "sha256:20064ead0717cf9a73a6d1e779b23d149b53daf971169289ed2ed43a71e8d3b0",
-                "sha256:21fa558996782fc226b529fdd2ed7866c2c6ec91cee82735c98a197fae39f706",
-                "sha256:22908891a380d50738e1f978667536f6c6b526a2064156203d418f4856d6e86a",
-                "sha256:3160a0fd9754aab7d47f95a6b63ab355388d890163eb03b2d2b87ab0a30cfa59",
-                "sha256:322102cdf1ab682ecc7d9b1c5eed4ec59657a65e1c146a0da342b78f4112db23",
-                "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5",
-                "sha256:3573d376454d956553c356df45bb824262c397c6e26ce43e8203c4c540ee0acb",
-                "sha256:3747443b6a904001473370d7810aa19c3a180ccd52a7157aacc264a5ac79265e",
-                "sha256:38e812a197bf8e71a59fe55b757a84c1f946d0ac114acafaafaf21667a7e169e",
-                "sha256:3a06f32c9634a8705f4ca9946d667609f52cf130d5548881401f1eb2c39b1e2c",
-                "sha256:3a5fc78f9e3f501a1614a98f7c54d3969f3ad9bba8ba3d9b438c3bc5d047dd28",
-                "sha256:3d9098b479e78c85080c98e1e35ff40b4a31d8953102bb0fd7d1b6f8a2111a3d",
-                "sha256:3dc5b6a8ecfdc5748a7e429782598e4f17ef378e3e272eeb1340ea57c9109f41",
-                "sha256:4155b51ae05ed47199dc5b2a4e62abccb274cee6b01da5b895099b61b1982974",
-                "sha256:49919f8400b5e49e961f320c735388ee686a62327e773fa5b3ce6721f7e785ce",
-                "sha256:53d0a3fa5f8af98a1e261de6a3943ca631c526635eb5817a87a59d9a57ebf48f",
-                "sha256:5f008525e02908b20e04707a4f704cd286d94718f48bb33edddc7d7b584dddc1",
-                "sha256:628c985afb2c7d27a4800bfb609e03985aaecb42f955049957814e0491d4006d",
-                "sha256:65ed923f84a6844de5fd29726b888e58c62820e0769b76565480e1fdc3d062f8",
-                "sha256:6734e606355834f13445b6adc38b53c0fd45f1a56a9ba06c2058f86893ae8017",
-                "sha256:6baf0baf0d5d265fa7944feb9f7451cc316bfe30e8df1a61b1bb08577c554f31",
-                "sha256:6f4f4668e1831850ebcc2fd0b1cd11721947b6dc7c00bf1c6bd3c929ae14f2c7",
-                "sha256:6f5c2e7bc8a4bf7c426599765b1bd33217ec84023033672c1e9a8b35eaeaaaf8",
-                "sha256:6f6c7a8a57e9405cad7485f4c9d3172ae486cfef1344b5ddd8e5239582d7355e",
-                "sha256:7381c66e0561c5757ffe616af869b916c8b4e42b367ab29fedc98481d1e74e14",
-                "sha256:73dc03a6a7e30b7edc5b01b601e53e7fc924b04e1835e8e407c12c037e81adbd",
-                "sha256:74db0052d985cf37fa111828d0dd230776ac99c740e1a758ad99094be4f1803d",
-                "sha256:75f2568b4189dda1c567339b48cba4ac7384accb9c2a7ed655cd86b04055c795",
-                "sha256:78cacd03e79d009d95635e7d6ff12c21eb89b894c354bd2b2ed0b4763373693b",
-                "sha256:80d1543d58bd3d6c271b66abf454d437a438dff01c3e62fdbcd68f2a11310d4b",
-                "sha256:830d2948a5ec37c386d3170c483063798d7879037492540f10a475e3fd6f244b",
-                "sha256:891cf9b48776b5c61c700b55a598621fdb7b1e301a550365571e9624f270c203",
-                "sha256:8f25e17ab3039b05f762b0a55ae0b3632b2e073d9c8fc88e89aca31a6198e88f",
-                "sha256:9a3267620866c9d17b959a84dd0bd2d45719b817245e49371ead79ed4f710d19",
-                "sha256:a04f86f41a8916fe45ac5024ec477f41f886b3c435da2d4e3d2709b22ab02af1",
-                "sha256:aaf53a6cebad0eae578f062c7d462155eada9c172bd8c4d250b8c1d8eb7f916a",
-                "sha256:abc1185d79f47c0a7aaf7e2412a0eb2c03b724581139193d2d82b3ad8cbb00ac",
-                "sha256:ac0aa6cd53ab9a31d397f8303f92c42f534693528fafbdb997c82bae6e477ad9",
-                "sha256:ac3775e3311661d4adace3697a52ac0bab17edd166087d493b52d4f4f553f9f0",
-                "sha256:b06f0d3bf045158d2fb8837c5785fe9ff9b8c93358be64461a1089f5da983137",
-                "sha256:b116502087ce8a6b7a5f1814568ccbd0e9f6cfd99948aa59b0e241dc57cf739f",
-                "sha256:b82fab78e0b1329e183a65260581de4375f619167478dddab510c6c6fb04d9b6",
-                "sha256:bd7163182133c0c7701b25e604cf1611c0d87712e56e88e7ee5d72deab3e76b5",
-                "sha256:c36bcbc0d5174a80d6cccf43a0ecaca44e81d25be4b7f90f0ed7bcfbb5a00909",
-                "sha256:c3af8e0f07399d3176b179f2e2634c3ce9c1301379a6b8c9c9aeecd481da494f",
-                "sha256:c84132a54c750fda57729d1e2599bb598f5fa0344085dbde5003ba429a4798c0",
-                "sha256:cb7b2ab0188829593b9de646545175547a70d9a6e2b63bf2cd87a0a391599324",
-                "sha256:cca4def576f47a09a943666b8f829606bcb17e2bc2d5911a46c8f8da45f56755",
-                "sha256:cf6511efa4801b9b38dc5546d7547d5b5c6ef4b081c60b23e4d941d0eba9cbeb",
-                "sha256:d16fd5252f883eb074ca55cb622bc0bee49b979ae4e8639fff6ca3ff44f9f854",
-                "sha256:d2686f91611f9e17f4548dbf050e75b079bbc2a82be565832bc8ea9047b61c8c",
-                "sha256:d7fc3fca01da18fbabe4625d64bb612b533533ed10045a2ac3dd194bfa656b60",
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-                "sha256:31ef31af7e474a8d8995027fefdfcf509b5c913ff31f2015b4ec4beb26a6f658",
-                "sha256:e2f91727039fc39a92f58a588a25b87f936de6567eed4f0e673e0507edc75bad"
-            ],
-            "index": "pypi",
-            "version": "==2.21.0"
-        },
-        "pytest": {
-            "hashes": [
-                "sha256:3799fa815351fea3a5e96ac7e503a96fa51cc9942c3753cda7651b93c1cfa362",
-                "sha256:434afafd78b1d78ed0addf160ad2b77a30d35d4bdf8af234fe621919d9ed15e3"
-            ],
-            "index": "pypi",
-            "version": "==7.3.1"
-        },
-        "pyyaml": {
-            "hashes": [
-                "sha256:08682f6b72c722394747bddaf0aa62277e02557c0fd1c42cb853016a38f8dedf",
-                "sha256:0f5f5786c0e09baddcd8b4b45f20a7b5d61a7e7e99846e3c799b05c7c53fa696",
-                "sha256:129def1b7c1bf22faffd67b8f3724645203b79d8f4cc81f674654d9902cb4393",
-                "sha256:294db365efa064d00b8d1ef65d8ea2c3426ac366c0c4368d930bf1c5fb497f77",
-                "sha256:3b2b1824fe7112845700f815ff6a489360226a5609b96ec2190a45e62a9fc922",
-                "sha256:3bd0e463264cf257d1ffd2e40223b197271046d09dadf73a0fe82b9c1fc385a5",
-                "sha256:4465124ef1b18d9ace298060f4eccc64b0850899ac4ac53294547536533800c8",
-                "sha256:49d4cdd9065b9b6e206d0595fee27a96b5dd22618e7520c33204a4a3239d5b10",
-                "sha256:4e0583d24c881e14342eaf4ec5fbc97f934b999a6828693a99157fde912540cc",
-                "sha256:5accb17103e43963b80e6f837831f38d314a0495500067cb25afab2e8d7a4018",
-                "sha256:607774cbba28732bfa802b54baa7484215f530991055bb562efbed5b2f20a45e",
-                "sha256:6c78645d400265a062508ae399b60b8c167bf003db364ecb26dcab2bda048253",
-                "sha256:72a01f726a9c7851ca9bfad6fd09ca4e090a023c00945ea05ba1638c09dc3347",
-                "sha256:74c1485f7707cf707a7aef42ef6322b8f97921bd89be2ab6317fd782c2d53183",
-                "sha256:895f61ef02e8fed38159bb70f7e100e00f471eae2bc838cd0f4ebb21e28f8541",
-                "sha256:8c1be557ee92a20f184922c7b6424e8ab6691788e6d86137c5d93c1a6ec1b8fb",
-                "sha256:bb4191dfc9306777bc594117aee052446b3fa88737cd13b7188d0e7aa8162185",
-                "sha256:bfb51918d4ff3d77c1c856a9699f8492c612cde32fd3bcd344af9be34999bfdc",
-                "sha256:c20cfa2d49991c8b4147af39859b167664f2ad4561704ee74c1de03318e898db",
-                "sha256:cb333c16912324fd5f769fff6bc5de372e9e7a202247b48870bc251ed40239aa",
-                "sha256:d2d9808ea7b4af864f35ea216be506ecec180628aced0704e34aca0b040ffe46",
-                "sha256:d483ad4e639292c90170eb6f7783ad19490e7a8defb3e46f97dfe4bacae89122",
-                "sha256:dd5de0646207f053eb0d6c74ae45ba98c3395a571a2891858e87df7c9b9bd51b",
-                "sha256:e1d4970ea66be07ae37a3c2e48b5ec63f7ba6804bdddfdbd3cfd954d25a82e63",
-                "sha256:e4fac90784481d221a8e4b1162afa7c47ed953be40d31ab4629ae917510051df",
-                "sha256:fa5ae20527d8e831e8230cbffd9f8fe952815b2b7dae6ffec25318803a7528fc",
-                "sha256:fd7f6999a8070df521b6384004ef42833b9bd62cfee11a09bda1079b4b704247",
-                "sha256:fdc842473cd33f45ff6bce46aea678a54e3d21f1b61a7750ce3c498eedfe25d6",
-                "sha256:fe69978f3f768926cfa37b867e3843918e012cf83f680806599ddce33c2c68b0"
-            ],
-            "markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3, 3.4, 3.5'",
-            "version": "==5.4.1"
-        },
-        "setuptools": {
-            "hashes": [
-                "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f",
-                "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==67.8.0"
-        },
-        "tomli": {
-            "hashes": [
-                "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc",
-                "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"
-            ],
-            "markers": "python_version < '3.11'",
-            "version": "==2.0.1"
-        },
-        "typing-extensions": {
-            "hashes": [
-                "sha256:5cb5f4a79139d699607b3ef622a1dedafa84e115ab0024e0d9c044a9479ca7cb",
-                "sha256:fb33085c39dd998ac16d1431ebc293a8b3eedd00fd4a32de0ff79002c19511b4"
-            ],
-            "markers": "python_version < '3.9'",
-            "version": "==4.5.0"
-        },
-        "virtualenv": {
-            "hashes": [
-                "sha256:6abec7670e5802a528357fdc75b26b9f57d5d92f29c5462ba0fbe45feacc685e",
-                "sha256:a85caa554ced0c0afbd0d638e7e2d7b5f92d23478d05d17a76daeac8f279f924"
-            ],
-            "markers": "python_version >= '3.7'",
-            "version": "==20.23.0"
-        },
-        "zipp": {
-            "hashes": [
-                "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b",
-                "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"
-            ],
-            "markers": "python_version < '3.10'",
-            "version": "==3.15.0"
-        }
-    }
-}
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index b04293b3..1069ab60 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -24,6 +24,9 @@ files = [
     {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
 ]
 
+[package.dependencies]
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
+
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
 dev = ["attrs[docs,tests]", "pre-commit"]
@@ -37,15 +40,11 @@ version = "0.1.0"
 description = "Bigquery components for vertex pipelines"
 category = "main"
 optional = false
-python-versions = ">=3.9,<3.11"
+python-versions = ">=3.7,<3.11"
 files = []
 develop = true
 
 [package.dependencies]
-google-cloud-aiplatform = "1.24.1"
-google-cloud-bigquery = "2.30.0"
-google-cloud-pipeline-components = "1.0.42"
-Jinja2 = ">=3.0.1,<4.0.0"
 kfp = "==1.8.21"
 
 [package.source]
@@ -54,14 +53,14 @@ url = "../components/bigquery-components"
 
 [[package]]
 name = "cachetools"
-version = "5.3.0"
+version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
 category = "main"
 optional = false
-python-versions = "~=3.7"
+python-versions = ">=3.7"
 files = [
-    {file = "cachetools-5.3.0-py3-none-any.whl", hash = "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"},
-    {file = "cachetools-5.3.0.tar.gz", hash = "sha256:13dfddc7b8df938c21a940dfa6557ce6e94a2f1cdfa58eb90c805721d58f2c14"},
+    {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
+    {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
 ]
 
 [[package]]
@@ -187,6 +186,7 @@ files = [
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
 [[package]]
 name = "cloudpickle"
@@ -214,21 +214,21 @@ files = [
 
 [[package]]
 name = "deprecated"
-version = "1.2.13"
+version = "1.2.14"
 description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
 category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
-    {file = "Deprecated-1.2.13-py2.py3-none-any.whl", hash = "sha256:64756e3e14c8c5eea9795d93c524551432a0be75629f8f29e67ab8caf076c76d"},
-    {file = "Deprecated-1.2.13.tar.gz", hash = "sha256:43ac5335da90c31c24ba028af536a91d41d53f9e6901ddb021bcc572ce44e38d"},
+    {file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
+    {file = "Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3"},
 ]
 
 [package.dependencies]
 wrapt = ">=1.10,<2"
 
 [package.extras]
-dev = ["PyTest", "PyTest (<5)", "PyTest-Cov", "PyTest-Cov (<2.6)", "bump2version (<1)", "configparser (<5)", "importlib-metadata (<3)", "importlib-resources (<4)", "sphinx (<2)", "sphinxcontrib-websupport (<2)", "tox", "zipp (<2)"]
+dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
 
 [[package]]
 name = "distlib"
@@ -258,7 +258,7 @@ files = [
 name = "exceptiongroup"
 version = "1.1.1"
 description = "Backport of PEP 654 (exception groups)"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -347,20 +347,20 @@ uritemplate = ">=3.0.0,<4dev"
 
 [[package]]
 name = "google-auth"
-version = "2.18.1"
+version = "2.19.0"
 description = "Google Authentication Library"
 category = "main"
 optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
+python-versions = ">=3.6"
 files = [
-    {file = "google-auth-2.18.1.tar.gz", hash = "sha256:d7a3249027e7f464fbbfd7ee8319a08ad09d2eea51578575c4bd360ffa049ccb"},
-    {file = "google_auth-2.18.1-py2.py3-none-any.whl", hash = "sha256:55a395cdfd3f3dd3f649131d41f97c17b4ed8a2aac1be3502090c716314e8a37"},
+    {file = "google-auth-2.19.0.tar.gz", hash = "sha256:f39d528077ac540793dd3c22a8706178f157642a67d874db25c640b7fead277e"},
+    {file = "google_auth-2.19.0-py2.py3-none-any.whl", hash = "sha256:be617bfaf77774008e9d177573f782e109188c8a64ae6e744285df5cea3e7df6"},
 ]
 
 [package.dependencies]
 cachetools = ">=2.0.0,<6.0"
 pyasn1-modules = ">=0.2.1"
-rsa = {version = ">=3.1.4,<5", markers = "python_version >= \"3.6\""}
+rsa = ">=3.1.4,<5"
 six = ">=1.9.0"
 urllib3 = "<2.0"
 
@@ -428,34 +428,35 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "2.30.0"
+version = "3.10.0"
 description = "Google BigQuery API client library"
 category = "main"
 optional = false
-python-versions = ">=3.6, <3.11"
+python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-bigquery-2.30.0.tar.gz", hash = "sha256:fdb57aa5e8af7d692eb5835739d9339dc1b5e89836430fe88dd1ddc1b0047639"},
-    {file = "google_cloud_bigquery-2.30.0-py2.py3-none-any.whl", hash = "sha256:f6546ee96d57f45eaac8c4b24b52228a7f21a33669730efc9e69569bc88a04ad"},
+    {file = "google-cloud-bigquery-3.10.0.tar.gz", hash = "sha256:4b02def076e2db8cec66f65fb627d13904a9fc3cf4fee315ede43dcb7038a8df"},
+    {file = "google_cloud_bigquery-3.10.0-py2.py3-none-any.whl", hash = "sha256:848a3cbce0ba7d4f1e9551400a7c99aa0eab72290d5a1bbbe69f18a24a10bd3a"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.29.0,<3.0.0dev", extras = ["grpc"]}
-google-cloud-core = ">=1.4.1,<3.0.0dev"
+google-api-core = {version = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
+google-cloud-core = ">=1.6.0,<3.0.0dev"
 google-resumable-media = ">=0.6.0,<3.0dev"
-grpcio = ">=1.38.1,<2.0dev"
-packaging = ">=14.3"
-proto-plus = ">=1.10.0"
-protobuf = ">=3.12.0"
+grpcio = ">=1.47.0,<2.0dev"
+packaging = ">=20.0.0"
+proto-plus = ">=1.15.0,<2.0.0dev"
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 python-dateutil = ">=2.7.2,<3.0dev"
-requests = ">=2.18.0,<3.0.0dev"
+requests = ">=2.21.0,<3.0.0dev"
 
 [package.extras]
-all = ["Shapely (>=1.6.0,<2.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.0.0,<3.0.0dev)", "grpcio (>=1.38.1,<2.0dev)", "opentelemetry-api (>=0.11b0)", "opentelemetry-instrumentation (>=0.11b0)", "opentelemetry-sdk (>=0.11b0)", "pandas (>=0.24.2)", "pyarrow (>=3.0.0,<7.0dev)", "tqdm (>=4.7.4,<5.0.0dev)"]
-bignumeric-type = ["pyarrow (>=3.0.0,<7.0dev)"]
-bqstorage = ["google-cloud-bigquery-storage (>=2.0.0,<3.0.0dev)", "grpcio (>=1.38.1,<2.0dev)", "pyarrow (>=3.0.0,<7.0dev)"]
-geopandas = ["Shapely (>=1.6.0,<2.0dev)", "geopandas (>=0.9.0,<1.0dev)"]
-opentelemetry = ["opentelemetry-api (>=0.11b0)", "opentelemetry-instrumentation (>=0.11b0)", "opentelemetry-sdk (>=0.11b0)"]
-pandas = ["pandas (>=0.24.2)", "pyarrow (>=3.0.0,<7.0dev)"]
+all = ["Shapely (>=1.8.4,<2.0dev)", "db-dtypes (>=0.3.0,<2.0.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)", "ipywidgets (>=7.7.0)", "opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)", "tqdm (>=4.7.4,<5.0.0dev)"]
+bqstorage = ["google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "pyarrow (>=3.0.0)"]
+geopandas = ["Shapely (>=1.8.4,<2.0dev)", "geopandas (>=0.9.0,<1.0dev)"]
+ipython = ["ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)"]
+ipywidgets = ["ipykernel (>=6.0.0)", "ipywidgets (>=7.7.0)"]
+opentelemetry = ["opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)"]
+pandas = ["db-dtypes (>=0.3.0,<2.0.0dev)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)"]
 tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 
 [[package]]
@@ -812,11 +813,51 @@ files = [
     {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
 ]
 
+[[package]]
+name = "importlib-metadata"
+version = "6.6.0"
+description = "Read metadata from Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_metadata-6.6.0-py3-none-any.whl", hash = "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed"},
+    {file = "importlib_metadata-6.6.0.tar.gz", hash = "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
+zipp = ">=0.5"
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+perf = ["ipython"]
+testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
+
+[[package]]
+name = "importlib-resources"
+version = "5.12.0"
+description = "Read resources from Python packages"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
+    {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
+]
+
+[package.dependencies]
+zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -856,7 +897,11 @@ files = [
 
 [package.dependencies]
 attrs = ">=17.4.0"
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
+importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
+pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
 pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
+typing-extensions = {version = "*", markers = "python_version < \"3.8\""}
 
 [package.extras]
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
@@ -895,6 +940,7 @@ requests-toolbelt = ">=0.8.0,<1"
 strip-hints = ">=0.1.8,<1"
 tabulate = ">=0.8.6,<1"
 typer = ">=0.3.2,<1.0"
+typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
 uritemplate = ">=3.0.1,<4"
 urllib3 = "<2"
 
@@ -1063,6 +1109,18 @@ files = [
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
 ]
 
+[[package]]
+name = "pkgutil-resolve-name"
+version = "1.3.10"
+description = "Resolve a name to an object."
+category = "main"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "pkgutil_resolve_name-1.3.10-py3-none-any.whl", hash = "sha256:ca27cc078d25c5ad71a9de0a7a330146c4e014c2462d9af19c6b828280649c5e"},
+    {file = "pkgutil_resolve_name-1.3.10.tar.gz", hash = "sha256:357d6c9e6a755653cfd78893817c0853af365dd51ec97f3d358a819373bbd174"},
+]
+
 [[package]]
 name = "platformdirs"
 version = "3.5.1"
@@ -1075,6 +1133,9 @@ files = [
     {file = "platformdirs-3.5.1.tar.gz", hash = "sha256:412dae91f52a6f84830f39a8078cecd0e866cb72294a5c66808e74d5e88d251f"},
 ]
 
+[package.dependencies]
+typing-extensions = {version = ">=4.5", markers = "python_version < \"3.8\""}
+
 [package.extras]
 docs = ["furo (>=2023.3.27)", "proselint (>=0.13)", "sphinx (>=6.2.1)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.3.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"]
@@ -1083,7 +1144,7 @@ test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.3.1)", "pytest-
 name = "pluggy"
 version = "1.0.0"
 description = "plugin and hook calling mechanisms for python"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1091,6 +1152,9 @@ files = [
     {file = "pluggy-1.0.0.tar.gz", hash = "sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159"},
 ]
 
+[package.dependencies]
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
+
 [package.extras]
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
@@ -1110,6 +1174,7 @@ files = [
 [package.dependencies]
 cfgv = ">=2.0.0"
 identify = ">=1.0.0"
+importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 nodeenv = ">=0.11.1"
 pyyaml = ">=5.1"
 virtualenv = ">=20.10.0"
@@ -1300,7 +1365,7 @@ files = [
 name = "pytest"
 version = "7.3.1"
 description = "pytest: simple powerful testing with Python"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1311,6 +1376,7 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
 exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
+importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
 iniconfig = "*"
 packaging = "*"
 pluggy = ">=0.12,<2.0"
@@ -1578,7 +1644,7 @@ tests = ["pytest", "pytest-cov"]
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
-category = "main"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1655,13 +1721,11 @@ version = "0.1.0"
 description = "KFP components for interacting with Vertex AI"
 category = "main"
 optional = false
-python-versions = ">=3.9,<3.11"
+python-versions = ">=3.7,<3.11"
 files = []
 develop = true
 
 [package.dependencies]
-google-cloud-aiplatform = "1.24.1"
-google-cloud-pipeline-components = "1.0.42"
 kfp = "==1.8.21"
 
 [package.source]
@@ -1683,6 +1747,7 @@ files = [
 [package.dependencies]
 distlib = ">=0.3.6,<1"
 filelock = ">=3.11,<4"
+importlib-metadata = {version = ">=6.4.1", markers = "python_version < \"3.8\""}
 platformdirs = ">=3.2,<4"
 
 [package.extras]
@@ -1806,7 +1871,23 @@ files = [
     {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
 ]
 
+[[package]]
+name = "zipp"
+version = "3.15.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
+    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.9,<3.11"
-content-hash = "c464813a2e2cb67c3d2e0ae229ca383b847a62fca4486fdf2f8ab90f335c624b"
+python-versions = ">=3.7,<3.11"
+content-hash = "3daa25983216b9a58680e4423147d310550b5277bffaca44f1284d421086506d"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index cf42b576..049fbeaa 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -7,23 +7,20 @@ readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.7",
 ]
 packages = [
     { include = "pipelines", from = "src" },
 ]
 
-
 [tool.poetry.dependencies]
-python = ">=3.9,<3.11"
+python = ">=3.7,<3.11"
 Jinja2 = ">=3.0.1,<4.0.0"
 google-cloud-aiplatform = "1.24.1"
 google-cloud-pipeline-components = "1.0.42"
 bigquery-components = { path = "../components/bigquery-components", develop = true }
 vertex-components = { path = "../components/vertex-components", develop = true }
 
-
-
 [tool.poetry.group.dev.dependencies]
 pytest = ">=7.3.1,<8.0.0"
 pre-commit = ">=2.14.1,<3.0.0"

From fc131744d86f0cdf3395a0a198d44655cab3cf02 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 16:19:54 +0100
Subject: [PATCH 073/238] style(Makefile): fix Makefile

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 422fe6b7..258df1d0 100644
--- a/Makefile
+++ b/Makefile
@@ -23,7 +23,7 @@ pre-commit: ## Runs the pre-commit checks over entire repo
 	poetry run pre-commit run --all-files
 
 setup: ## Set up local environment for Python development on pipelines
-	@poetry install && \
+	@pip install poetry && \
 	cd pipelines && \
 	poetry install --with dev 
 

From ee5bb52c15946f45e0d67e4213bf519e5ca20d3b Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 18:28:52 +0100
Subject: [PATCH 074/238] style(pyproject.toml): change description

---
 pipelines/pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 049fbeaa..69ab2a3e 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -2,7 +2,7 @@
 name = "pipelines"
 version = "0.1.0"
 authors = ["Example User <user@example.com>"]
-description = "Turbo Template"
+description = "Vertex AI Pipelines end-to-end sample"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",

From 43463f86d9636bd80e63124f64a9b8c7af037fea Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 18:31:20 +0100
Subject: [PATCH 075/238] style(pyproject.toml): change description

---
 components/bigquery-components/pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index 19db2207..ee3e0477 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -2,7 +2,7 @@
 name = "bigquery-components"
 version = "0.1.0"
 authors = ["Example User <user@example.com>"]
-description = "Bigquery components for vertex pipelines"
+description = "KubeFlow components for BigQuery"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",

From bf2fa788016f273c626ccbf6a404a807c35f901e Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 18:32:58 +0100
Subject: [PATCH 076/238] docs(README.md): update docs

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index db16eafd..0d4a2b9f 100644
--- a/README.md
+++ b/README.md
@@ -64,8 +64,8 @@ please note: `poetry install` or `poetry add`, installs packages within the proj
 
 ### Configuring poetry to detect python version using pyenv
 
-1. run in terminal `poetry config virtualenvs.prefer-active-python true`
-1. Manage and install project's dependencies using `poetry install`
+1. Run `poetry config virtualenvs.prefer-active-python true`
+1. Install project dependencies using `poetry install`
 
 ### Deploying Cloud Infrastructure
 

From e39dc49195e1f110810c6e6049066094e38818fd Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 18:34:56 +0100
Subject: [PATCH 077/238] docs(CONTRIBUTING.md): update docs

---
 CONTRIBUTING.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index da7e6ba7..39ee273e 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -211,7 +211,7 @@ def test_vertex_endpoint_uri(output_uri: str):
 ```
 
 ## Adding or changing python dependencies
-We use [poetry](https://python-poetry.org/docs/#installation) to handle our packages and their dependencies. Each group of pipeline components (e.g. [aiplatform](./pipeline_components/aiplatform/)) containers its own poetry environment, and there is a [separate poetry environment](./pipelines/) for the ML pipelines themselves and the pipeline trigger code.
+We use [poetry](https://python-poetry.org/docs/#installation) to handle our packages and their dependencies. Each group of pipeline components (e.g. [vertex](./components/vertex-components/)) includes its own poetry environment, and there is a [separate poetry environment](./pipelines/) for the ML pipelines themselves and the pipeline trigger code.
 
 ### Adding python dependencies
 You may need to add new packages for your own use cases. To do this, run the following from the relevant directory ([pipelines](./pipelines) for the main ML pipeline dependencies or the directory of the relevant component group e.g. [aiplatform](./pipeline_components/aiplatform/)):

From 4adc66e0686c6bc43cf89a4eb0becff62b1e6c32 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 18:37:24 +0100
Subject: [PATCH 078/238] style(pyproject.toml): change description

---
 components/vertex-components/pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index 91f212a6..f608436f 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -2,7 +2,7 @@
 name = "vertex-components"
 version = "0.1.0"
 authors = ["Example User <user@example.com>"]
-description = "KFP components for interacting with Vertex AI"
+description = "KubeFlow components for Vertex AI"
 readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",

From ebcc5915e422a1bdaae0b9db29be2e89db96aa56 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 18:42:07 +0100
Subject: [PATCH 079/238] style(.python-version): fix python version

---
 .python-version                              | 2 +-
 components/vertex-components/.python-version | 2 +-
 pipelines/.python-version                    | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/.python-version b/.python-version
index 8a433dd7..f7e5aa84 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.7.12 
+3.7.12
diff --git a/components/vertex-components/.python-version b/components/vertex-components/.python-version
index 8a433dd7..f7e5aa84 100644
--- a/components/vertex-components/.python-version
+++ b/components/vertex-components/.python-version
@@ -1 +1 @@
-3.7.12 
+3.7.12
diff --git a/pipelines/.python-version b/pipelines/.python-version
index 8a433dd7..f7e5aa84 100644
--- a/pipelines/.python-version
+++ b/pipelines/.python-version
@@ -1 +1 @@
-3.7.12 
+3.7.12

From 3a694cddcaaa71869e6572dfc56ed89fe64dd000 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 30 May 2023 18:44:49 +0100
Subject: [PATCH 080/238] style(Makefile): update makefile

---
 Makefile | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Makefile b/Makefile
index 258df1d0..0b9b5aa5 100644
--- a/Makefile
+++ b/Makefile
@@ -25,7 +25,7 @@ pre-commit: ## Runs the pre-commit checks over entire repo
 setup: ## Set up local environment for Python development on pipelines
 	@pip install poetry && \
 	cd pipelines && \
-	poetry install --with dev 
+	poetry install --with dev
 
 test-trigger: ## Runs unit tests for the pipeline trigger code
 	@cd pipelines && \
@@ -37,7 +37,7 @@ compile-pipeline: ## Compile the pipeline to training.json or prediction.json. M
 
 setup-components: ## Run unit tests for a component group
 	@cd "components/${GROUP}" && \
-	poetry install --with dev 
+	poetry install --with dev
 
 setup-all-components: ## Run unit tests for all pipeline components
 	@set -e && \

From f74931b46877eebc9939af17824108a49b57e5a9 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Wed, 31 May 2023 12:56:59 +0100
Subject: [PATCH 081/238] Add ADDITIONAL_SUFFIX environment variable

- include in env.sh.example
- adjust xgboost training pipeline
- adjust Makefile
---
 Makefile                                             | 2 +-
 env.sh.example                                       | 1 +
 pipelines/src/pipelines/xgboost/training/pipeline.py | 9 +++++++--
 3 files changed, 9 insertions(+), 3 deletions(-)

diff --git a/Makefile b/Makefile
index 4dc752c9..176371ca 100644
--- a/Makefile
+++ b/Makefile
@@ -72,7 +72,7 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
-		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets ; \
+		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets${ADDITIONAL_SUFFIX} ; \
 	else \
 		echo "No assets folder found" ; \
 	fi ;
diff --git a/env.sh.example b/env.sh.example
index 59b518f6..455baeb3 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -20,6 +20,7 @@ export VERTEX_CMEK_IDENTIFIER= # optional
 export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
+export ADDITIONAL_SUFFIX= # optional, add underscore for better readability e.g. _suffix
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 8499ce8a..565b985c 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -39,6 +39,7 @@ def xgboost_pipeline(
     timestamp: str = "2022-12-01 00:00:00",
     staging_bucket: str = os.environ.get("VERTEX_PIPELINE_ROOT"),
     pipeline_files_gcs_path: str = os.environ.get("PIPELINE_FILES_GCS_PATH"),
+    additional_suffix: str = os.environ.get("ADDITIONAL_SUFFIX"),
     test_dataset_uri: str = "",
 ):
     """
@@ -64,6 +65,8 @@ def xgboost_pipeline(
         staging_bucket (str): Staging bucket for pipeline artifacts.
         pipeline_files_gcs_path (str): GCS path where the pipeline files are located.
         test_dataset_uri (str): Optional. GCS URI of statis held-out test dataset.
+        additional_suffix (str): Optional. Additional suffix to append GCS asset path
+            and BQ tables that get overwritten.
     """
 
     # Create variables to ensure the same arguments are passed
@@ -71,14 +74,16 @@ def xgboost_pipeline(
     label_column_name = "total_fare"
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_xgb_training"  # suffix to table names
+    table_suffix = "_xgb_training" + str(additional_suffix)  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     preprocessed_table = "preprocessed_data" + table_suffix
     train_table = "train_data" + table_suffix
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_xgb_model.py"
+    train_script_uri = (
+        f"{pipeline_files_gcs_path}/assets{additional_suffix}/train_xgb_model.py"
+    )
     hparams = dict(
         n_estimators=200,
         early_stopping_rounds=10,

From db7fe79df85038eb996208bb915a9f9e229e07f3 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
Date: Fri, 2 Jun 2023 08:56:30 +0200
Subject: [PATCH 082/238] Update components/README.md

---
 components/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/README.md b/components/README.md
index 6f58f74b..b168bcca 100644
--- a/components/README.md
+++ b/components/README.md
@@ -4,7 +4,7 @@ This directory contains multiple Python packages that are used to define pipelin
 
 ## Creating a new pipeline components package
 
-To create a new set of components (with different Python dependencies), copy one of the existing subdirectories and rename the different files and directories as appropriate (e.g. `bigquery-components` -> `my-new-components`). You will also need to update any references in the Python files themselves, as well as the `poetry.lock file` and `pyproject.toml`.
+To create a new set of components (with different Python dependencies), copy one of the existing subdirectories and rename the different files and directories as appropriate (e.g. `vertex-components` -> `my-new-components`). You will also need to update any references in the Python files themselves, as well as `poetry.lock` and `pyproject.toml`.
 
 Your Python dependencies should be defined in `poetry.lock file`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
 

From f5a5572255feb465def22054a47986a9597695d9 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
Date: Fri, 2 Jun 2023 08:56:38 +0200
Subject: [PATCH 083/238] Update components/README.md

---
 components/README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/README.md b/components/README.md
index b168bcca..f601b9bf 100644
--- a/components/README.md
+++ b/components/README.md
@@ -6,7 +6,7 @@ This directory contains multiple Python packages that are used to define pipelin
 
 To create a new set of components (with different Python dependencies), copy one of the existing subdirectories and rename the different files and directories as appropriate (e.g. `vertex-components` -> `my-new-components`). You will also need to update any references in the Python files themselves, as well as `poetry.lock` and `pyproject.toml`.
 
-Your Python dependencies should be defined in `poetry.lock file`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
+Your Python dependencies should be defined in `poetry.lock`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
 
 - In `pyproject.toml`, add `kfp` to the `[dependencies]` section (pinned to a specific version), and add any dependencies that your component uses under `[tool.poetry.dependencies]`(each pinned to a specific version)
 - In `packages_to_install` (in the `@component` decorator used to define your component), add any dependencies that your component uses (each pinned to a specific version)

From 8df34131713862a36b9f35fa67a7f1e410ff3024 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
Date: Fri, 2 Jun 2023 08:56:47 +0200
Subject: [PATCH 084/238] Update components/bigquery-components/.python-version

---
 components/bigquery-components/.python-version | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/components/bigquery-components/.python-version b/components/bigquery-components/.python-version
index 8a433dd7..f7e5aa84 100644
--- a/components/bigquery-components/.python-version
+++ b/components/bigquery-components/.python-version
@@ -1 +1 @@
-3.7.12 
+3.7.12

From ee5c1aaca8071ce830ef060f9275ea5bf1fc848d Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Fri, 2 Jun 2023 09:13:21 +0200
Subject: [PATCH 085/238] Cleanup

---
 .gitignore | 7 -------
 Makefile   | 9 +++++----
 README.md  | 3 ++-
 3 files changed, 7 insertions(+), 12 deletions(-)

diff --git a/.gitignore b/.gitignore
index c9c0cfa7..930b7889 100644
--- a/.gitignore
+++ b/.gitignore
@@ -95,13 +95,6 @@ target/
 profile_default/
 ipython_config.py
 
-# pipenv
-#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
-#   However, in case of collaboration, if having platform-specific dependencies or dependencies
-#   having no cross-platform support, pipenv may install dependencies that don't work, or not
-#   install all needed dependencies.
-#Pipfile.lock
-
 # PEP 582; used by e.g. github.com/David-OConnor/pyflow
 __pypackages__/
 
diff --git a/Makefile b/Makefile
index 0b9b5aa5..359c9a88 100644
--- a/Makefile
+++ b/Makefile
@@ -23,7 +23,8 @@ pre-commit: ## Runs the pre-commit checks over entire repo
 	poetry run pre-commit run --all-files
 
 setup: ## Set up local environment for Python development on pipelines
-	@pip install poetry && \
+	@pip install pip --upgrade && \
+	pip install poetry --upgrade && \
 	cd pipelines && \
 	poetry install --with dev
 
@@ -59,11 +60,11 @@ test-all-components: ## Run unit tests for all pipeline components
 
 test-components-coverage: ## Run tests with coverage
 	@cd "components/${GROUP}" && \
-	pipenv run coverage run -m pytest && \
-	pipenv run coverage report -m
+	poetry run coverage run -m pytest && \
+	poetry run coverage report -m
 
 test-all-components-coverage: ## Run tests with coverage
-		@set -e && \
+	@set -e && \
 	for component_group in components/*/ ; do \
 		echo "Test components under $$component_group" && \
 		$(MAKE) test-components-coverage GROUP=$$(basename $$component_group) ; \
diff --git a/README.md b/README.md
index 0d4a2b9f..a26f5ff4 100644
--- a/README.md
+++ b/README.md
@@ -60,7 +60,8 @@ In a production MLOps solution, your ML pipelines need to be repeatable. So, we
 1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh`
 1. Load the environment variables in `env.sh` by running `source env.sh`
 
-please note: `poetry install` or `poetry add`, installs packages within the project's virtual environment. If you use pip directly, you might accidentally install packages globally or in the wrong environment, leading to conflicts or difficulties in managing dependencies.
+Note: `poetry install` or `poetry add`, installs packages within the project's virtual environment. 
+If you use `pip` directly, you might accidentally install packages globally or in the wrong environment, leading to conflicts or difficulties in managing dependencies.
 
 ### Configuring poetry to detect python version using pyenv
 

From 874d2823954fc0535f451a2edb44bf5d02ca7ae9 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Fri, 2 Jun 2023 12:15:43 +0100
Subject: [PATCH 086/238] build(pyproject.toml): add coverage package

---
 .python-version          |  2 +-
 pipelines/poetry.lock    | 88 ++++++++++++++++++++++++++++++++++------
 pipelines/pyproject.toml |  1 +
 3 files changed, 78 insertions(+), 13 deletions(-)

diff --git a/.python-version b/.python-version
index f7e5aa84..8a433dd7 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.7.12
+3.7.12 
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index 1069ab60..e8388b8a 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -37,7 +37,7 @@ tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pyte
 [[package]]
 name = "bigquery-components"
 version = "0.1.0"
-description = "Bigquery components for vertex pipelines"
+description = "KubeFlow components for BigQuery"
 category = "main"
 optional = false
 python-versions = ">=3.7,<3.11"
@@ -212,6 +212,70 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "coverage"
+version = "7.2.5"
+description = "Code coverage measurement for Python"
+category = "dev"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "coverage-7.2.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:883123d0bbe1c136f76b56276074b0c79b5817dd4238097ffa64ac67257f4b6c"},
+    {file = "coverage-7.2.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d2fbc2a127e857d2f8898aaabcc34c37771bf78a4d5e17d3e1f5c30cd0cbc62a"},
+    {file = "coverage-7.2.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5f3671662dc4b422b15776cdca89c041a6349b4864a43aa2350b6b0b03bbcc7f"},
+    {file = "coverage-7.2.5-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:780551e47d62095e088f251f5db428473c26db7829884323e56d9c0c3118791a"},
+    {file = "coverage-7.2.5-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:066b44897c493e0dcbc9e6a6d9f8bbb6607ef82367cf6810d387c09f0cd4fe9a"},
+    {file = "coverage-7.2.5-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:b9a4ee55174b04f6af539218f9f8083140f61a46eabcaa4234f3c2a452c4ed11"},
+    {file = "coverage-7.2.5-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:706ec567267c96717ab9363904d846ec009a48d5f832140b6ad08aad3791b1f5"},
+    {file = "coverage-7.2.5-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ae453f655640157d76209f42c62c64c4d4f2c7f97256d3567e3b439bd5c9b06c"},
+    {file = "coverage-7.2.5-cp310-cp310-win32.whl", hash = "sha256:f81c9b4bd8aa747d417407a7f6f0b1469a43b36a85748145e144ac4e8d303cb5"},
+    {file = "coverage-7.2.5-cp310-cp310-win_amd64.whl", hash = "sha256:dc945064a8783b86fcce9a0a705abd7db2117d95e340df8a4333f00be5efb64c"},
+    {file = "coverage-7.2.5-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:40cc0f91c6cde033da493227797be2826cbf8f388eaa36a0271a97a332bfd7ce"},
+    {file = "coverage-7.2.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a66e055254a26c82aead7ff420d9fa8dc2da10c82679ea850d8feebf11074d88"},
+    {file = "coverage-7.2.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c10fbc8a64aa0f3ed136b0b086b6b577bc64d67d5581acd7cc129af52654384e"},
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+    {file = "coverage-7.2.5-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:292300f76440651529b8ceec283a9370532f4ecba9ad67d120617021bb5ef139"},
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+    {file = "coverage-7.2.5-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:a08c7401d0b24e8c2982f4e307124b671c6736d40d1c39e09d7a8687bddf83ed"},
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+    {file = "coverage-7.2.5-cp311-cp311-win_amd64.whl", hash = "sha256:97072cc90f1009386c8a5b7de9d4fc1a9f91ba5ef2146c55c1f005e7b5c5e068"},
+    {file = "coverage-7.2.5-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:bebea5f5ed41f618797ce3ffb4606c64a5de92e9c3f26d26c2e0aae292f015c1"},
+    {file = "coverage-7.2.5-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:828189fcdda99aae0d6bf718ea766b2e715eabc1868670a0a07bf8404bf58c33"},
+    {file = "coverage-7.2.5-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:6e8a95f243d01ba572341c52f89f3acb98a3b6d1d5d830efba86033dd3687ade"},
+    {file = "coverage-7.2.5-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e8834e5f17d89e05697c3c043d3e58a8b19682bf365048837383abfe39adaed5"},
+    {file = "coverage-7.2.5-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:d1f25ee9de21a39b3a8516f2c5feb8de248f17da7eead089c2e04aa097936b47"},
+    {file = "coverage-7.2.5-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:1637253b11a18f453e34013c665d8bf15904c9e3c44fbda34c643fbdc9d452cd"},
+    {file = "coverage-7.2.5-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:8e575a59315a91ccd00c7757127f6b2488c2f914096077c745c2f1ba5b8c0969"},
+    {file = "coverage-7.2.5-cp37-cp37m-win32.whl", hash = "sha256:509ecd8334c380000d259dc66feb191dd0a93b21f2453faa75f7f9cdcefc0718"},
+    {file = "coverage-7.2.5-cp37-cp37m-win_amd64.whl", hash = "sha256:12580845917b1e59f8a1c2ffa6af6d0908cb39220f3019e36c110c943dc875b0"},
+    {file = "coverage-7.2.5-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:b5016e331b75310610c2cf955d9f58a9749943ed5f7b8cfc0bb89c6134ab0a84"},
+    {file = "coverage-7.2.5-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:373ea34dca98f2fdb3e5cb33d83b6d801007a8074f992b80311fc589d3e6b790"},
+    {file = "coverage-7.2.5-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a063aad9f7b4c9f9da7b2550eae0a582ffc7623dca1c925e50c3fbde7a579771"},
+    {file = "coverage-7.2.5-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:38c0a497a000d50491055805313ed83ddba069353d102ece8aef5d11b5faf045"},
+    {file = "coverage-7.2.5-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a2b3b05e22a77bb0ae1a3125126a4e08535961c946b62f30985535ed40e26614"},
+    {file = "coverage-7.2.5-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:0342a28617e63ad15d96dca0f7ae9479a37b7d8a295f749c14f3436ea59fdcb3"},
+    {file = "coverage-7.2.5-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:cf97ed82ca986e5c637ea286ba2793c85325b30f869bf64d3009ccc1a31ae3fd"},
+    {file = "coverage-7.2.5-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:c2c41c1b1866b670573657d584de413df701f482574bad7e28214a2362cb1fd1"},
+    {file = "coverage-7.2.5-cp38-cp38-win32.whl", hash = "sha256:10b15394c13544fce02382360cab54e51a9e0fd1bd61ae9ce012c0d1e103c813"},
+    {file = "coverage-7.2.5-cp38-cp38-win_amd64.whl", hash = "sha256:a0b273fe6dc655b110e8dc89b8ec7f1a778d78c9fd9b4bda7c384c8906072212"},
+    {file = "coverage-7.2.5-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:5c587f52c81211d4530fa6857884d37f514bcf9453bdeee0ff93eaaf906a5c1b"},
+    {file = "coverage-7.2.5-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:4436cc9ba5414c2c998eaedee5343f49c02ca93b21769c5fdfa4f9d799e84200"},
+    {file = "coverage-7.2.5-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6599bf92f33ab041e36e06d25890afbdf12078aacfe1f1d08c713906e49a3fe5"},
+    {file = "coverage-7.2.5-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:857abe2fa6a4973f8663e039ead8d22215d31db613ace76e4a98f52ec919068e"},
+    {file = "coverage-7.2.5-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f6f5cab2d7f0c12f8187a376cc6582c477d2df91d63f75341307fcdcb5d60303"},
+    {file = "coverage-7.2.5-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:aa387bd7489f3e1787ff82068b295bcaafbf6f79c3dad3cbc82ef88ce3f48ad3"},
+    {file = "coverage-7.2.5-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:156192e5fd3dbbcb11cd777cc469cf010a294f4c736a2b2c891c77618cb1379a"},
+    {file = "coverage-7.2.5-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:bd3b4b8175c1db502adf209d06136c000df4d245105c8839e9d0be71c94aefe1"},
+    {file = "coverage-7.2.5-cp39-cp39-win32.whl", hash = "sha256:ddc5a54edb653e9e215f75de377354e2455376f416c4378e1d43b08ec50acc31"},
+    {file = "coverage-7.2.5-cp39-cp39-win_amd64.whl", hash = "sha256:338aa9d9883aaaad53695cb14ccdeb36d4060485bb9388446330bef9c361c252"},
+    {file = "coverage-7.2.5-pp37.pp38.pp39-none-any.whl", hash = "sha256:8877d9b437b35a85c18e3c6499b23674684bf690f5d96c1006a1ef61f9fdf0f3"},
+    {file = "coverage-7.2.5.tar.gz", hash = "sha256:f99ef080288f09ffc687423b8d60978cf3a465d3f404a18d1a05474bd8575a47"},
+]
+
+[package.extras]
+toml = ["tomli"]
+
 [[package]]
 name = "deprecated"
 version = "1.2.14"
@@ -347,14 +411,14 @@ uritemplate = ">=3.0.0,<4dev"
 
 [[package]]
 name = "google-auth"
-version = "2.19.0"
+version = "2.19.1"
 description = "Google Authentication Library"
 category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "google-auth-2.19.0.tar.gz", hash = "sha256:f39d528077ac540793dd3c22a8706178f157642a67d874db25c640b7fead277e"},
-    {file = "google_auth-2.19.0-py2.py3-none-any.whl", hash = "sha256:be617bfaf77774008e9d177573f782e109188c8a64ae6e744285df5cea3e7df6"},
+    {file = "google-auth-2.19.1.tar.gz", hash = "sha256:a9cfa88b3e16196845e64a3658eb953992129d13ac7337b064c6546f77c17183"},
+    {file = "google_auth-2.19.1-py2.py3-none-any.whl", hash = "sha256:ea165e014c7cbd496558796b627c271aa8c18b4cba79dc1cc962b24c5efdfb85"},
 ]
 
 [package.dependencies]
@@ -428,14 +492,14 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "3.10.0"
+version = "3.11.0"
 description = "Google BigQuery API client library"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-bigquery-3.10.0.tar.gz", hash = "sha256:4b02def076e2db8cec66f65fb627d13904a9fc3cf4fee315ede43dcb7038a8df"},
-    {file = "google_cloud_bigquery-3.10.0-py2.py3-none-any.whl", hash = "sha256:848a3cbce0ba7d4f1e9551400a7c99aa0eab72290d5a1bbbe69f18a24a10bd3a"},
+    {file = "google-cloud-bigquery-3.11.0.tar.gz", hash = "sha256:3a1c1b3566f9f27ea83a36aaf54eb879444ee73ef42456764018a0b3b556d0fb"},
+    {file = "google_cloud_bigquery-3.11.0-py2.py3-none-any.whl", hash = "sha256:f568c36dfc9b8a2cf7e8ac10dd0889e0a52e8edf3dd556f3dd1eb441eda14364"},
 ]
 
 [package.dependencies]
@@ -1676,14 +1740,14 @@ test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.
 
 [[package]]
 name = "typing-extensions"
-version = "4.6.2"
+version = "4.6.3"
 description = "Backported and Experimental Type Hints for Python 3.7+"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "typing_extensions-4.6.2-py3-none-any.whl", hash = "sha256:3a8b36f13dd5fdc5d1b16fe317f5668545de77fa0b8e02006381fd49d731ab98"},
-    {file = "typing_extensions-4.6.2.tar.gz", hash = "sha256:06006244c70ac8ee83fa8282cb188f697b8db25bc8b4df07be1873c43897060c"},
+    {file = "typing_extensions-4.6.3-py3-none-any.whl", hash = "sha256:88a4153d8505aabbb4e13aacb7c486c2b4a33ca3b3f807914a9b4c844c471c26"},
+    {file = "typing_extensions-4.6.3.tar.gz", hash = "sha256:d91d5919357fe7f681a9f2b5b4cb2a5f1ef0a1e9f59c4d8ff0d3491e05c0ffd5"},
 ]
 
 [[package]]
@@ -1718,7 +1782,7 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 [[package]]
 name = "vertex-components"
 version = "0.1.0"
-description = "KFP components for interacting with Vertex AI"
+description = "KubeFlow components for Vertex AI"
 category = "main"
 optional = false
 python-versions = ">=3.7,<3.11"
@@ -1890,4 +1954,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.7,<3.11"
-content-hash = "3daa25983216b9a58680e4423147d310550b5277bffaca44f1284d421086506d"
+content-hash = "60130a208e8b1b38937ed8c91f1aa32e75c3c86be061ca321457ebc6f3a7d72c"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 69ab2a3e..9548d91c 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -24,6 +24,7 @@ vertex-components = { path = "../components/vertex-components", develop = true }
 [tool.poetry.group.dev.dependencies]
 pytest = ">=7.3.1,<8.0.0"
 pre-commit = ">=2.14.1,<3.0.0"
+coverage = "==7.2.5"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]

From 2a763771875f4100e7467c6a2ebfb83abfa33e63 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 1 Jun 2023 10:25:37 +0100
Subject: [PATCH 087/238] feat: return gcp resources (draft)

---
 .../src/vertex_components/custom_train_job.py | 24 ++++++++++++++++---
 1 file changed, 21 insertions(+), 3 deletions(-)

diff --git a/components/vertex-components/src/vertex_components/custom_train_job.py b/components/vertex-components/src/vertex_components/custom_train_job.py
index 0a2773bd..c79836dc 100644
--- a/components/vertex-components/src/vertex_components/custom_train_job.py
+++ b/components/vertex-components/src/vertex_components/custom_train_job.py
@@ -1,5 +1,5 @@
 # Copyright 2022 Google LLC
-from typing import List, Dict
+from typing import List, Dict, NamedTuple
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -18,7 +18,7 @@
 
 @component(
     base_image="python:3.7",
-    packages_to_install=["google-cloud-aiplatform==1.24.1"],
+    packages_to_install=["google-cloud-aiplatform==1.24.1", "google-cloud-pipeline-components==1.0.42"],
 )
 def custom_train_job(
     train_script_uri: str,
@@ -41,7 +41,7 @@ def custom_train_job(
     accelerator_type: str = "ACCELERATOR_TYPE_UNSPECIFIED",
     accelerator_count: int = 0,
     parent_model: str = None,
-):
+) -> NamedTuple("Outputs",  [("gcp_resources", str)]):
     """Run a custom training job using a training script.
 
     The provided script will be invoked by passing the following command-line arguments:
@@ -93,6 +93,8 @@ def custom_train_job(
     import os.path
     import time
     import google.cloud.aiplatform as aip
+    from google_cloud_pipeline_components.proto.gcp_resources_pb2 import GcpResources
+    from google.protobuf.json_format import MessageToJson
 
     logging.info(f"Using train script: {train_script_uri}")
     script_path = "/gcs/" + train_script_uri[5:]
@@ -143,3 +145,19 @@ def custom_train_job(
     for k, v in parsed_metrics.items():
         if type(v) is float:
             metrics.log_metric(k, v)
+    
+    custom_train_job_name = job.name
+    logging.info(f"CustomJobName: {job.name }")
+
+    custom_train_job_resources = GcpResources()
+    ctr = custom_train_job_resources.resources.add()
+    ctr.resource_type = "CustomJob"
+    ctr.resource_uri=f"https://{project_location}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{project_location}/customJobs/{custom_train_job_name}"
+    # ctr.resource_uri=f"https://{project_location}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{project_location}/trainingPipelines/{custom_train_job_name}" ?
+
+    gcp_resources=MessageToJson(custom_train_job_resources)
+    logging.info(f"GCPresources -: {gcp_resources }")
+    return gcp_resources
+
+    # return NamedTuple("Outputs", [("gcp_resources", str)])(gcp_resources) ?
+

From 3b68c316109df569a1cd8b1f0e794a71132d7db0 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 1 Jun 2023 11:31:22 +0100
Subject: [PATCH 088/238] feat: return gcp_resources

---
 .../src/vertex_components/custom_train_job.py   | 17 +++++------------
 1 file changed, 5 insertions(+), 12 deletions(-)

diff --git a/components/vertex-components/src/vertex_components/custom_train_job.py b/components/vertex-components/src/vertex_components/custom_train_job.py
index c79836dc..ead998ca 100644
--- a/components/vertex-components/src/vertex_components/custom_train_job.py
+++ b/components/vertex-components/src/vertex_components/custom_train_job.py
@@ -87,6 +87,7 @@ def custom_train_job(
     Returns:
         parent_model (str): Resource URI of the parent model (empty string if the
             trained model is the first model version of its kind).
+        NamedTuple: gcp_resources for Vertex AI UI integration.
     """
     import json
     import logging
@@ -146,18 +147,10 @@ def custom_train_job(
         if type(v) is float:
             metrics.log_metric(k, v)
     
-    custom_train_job_name = job.name
-    logging.info(f"CustomJobName: {job.name }")
-
+    # return GCP resource for Vertex AI UI integration
     custom_train_job_resources = GcpResources()
     ctr = custom_train_job_resources.resources.add()
-    ctr.resource_type = "CustomJob"
-    ctr.resource_uri=f"https://{project_location}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{project_location}/customJobs/{custom_train_job_name}"
-    # ctr.resource_uri=f"https://{project_location}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{project_location}/trainingPipelines/{custom_train_job_name}" ?
-
+    ctr.resource_type = "CustomTrainingJob"
+    ctr.resource_uri=f"https://{project_location}-aiplatform.googleapis.com/v1/{job.resource_name}"
     gcp_resources=MessageToJson(custom_train_job_resources)
-    logging.info(f"GCPresources -: {gcp_resources }")
-    return gcp_resources
-
-    # return NamedTuple("Outputs", [("gcp_resources", str)])(gcp_resources) ?
-
+    return (gcp_resources,)

From 62ce7e37f2159608e20e2cab0b434388e3b3cfc0 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 1 Jun 2023 12:38:17 +0100
Subject: [PATCH 089/238] feat: change uri

---
 .../src/vertex_components/custom_train_job.py                 | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/components/vertex-components/src/vertex_components/custom_train_job.py b/components/vertex-components/src/vertex_components/custom_train_job.py
index ead998ca..172df2cd 100644
--- a/components/vertex-components/src/vertex_components/custom_train_job.py
+++ b/components/vertex-components/src/vertex_components/custom_train_job.py
@@ -150,7 +150,7 @@ def custom_train_job(
     # return GCP resource for Vertex AI UI integration
     custom_train_job_resources = GcpResources()
     ctr = custom_train_job_resources.resources.add()
-    ctr.resource_type = "CustomTrainingJob"
-    ctr.resource_uri=f"https://{project_location}-aiplatform.googleapis.com/v1/{job.resource_name}"
+    ctr.resource_type = "CustomJob"
+    ctr.resource_uri=f"https://{project_location}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{project_location}/customJobs/{job.name}"
     gcp_resources=MessageToJson(custom_train_job_resources)
     return (gcp_resources,)

From becdefd46110e9ed04ddfd96ac03b182686857bd Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 1 Jun 2023 14:55:02 +0100
Subject: [PATCH 090/238] feat: change resource uri to backingCustomJob

---
 .../src/vertex_components/custom_train_job.py                 | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/components/vertex-components/src/vertex_components/custom_train_job.py b/components/vertex-components/src/vertex_components/custom_train_job.py
index 172df2cd..f25b8077 100644
--- a/components/vertex-components/src/vertex_components/custom_train_job.py
+++ b/components/vertex-components/src/vertex_components/custom_train_job.py
@@ -147,10 +147,12 @@ def custom_train_job(
         if type(v) is float:
             metrics.log_metric(k, v)
     
+
     # return GCP resource for Vertex AI UI integration
+    custom_job_name = job.to_dict()['trainingTaskMetadata']['backingCustomJob']
     custom_train_job_resources = GcpResources()
     ctr = custom_train_job_resources.resources.add()
     ctr.resource_type = "CustomJob"
-    ctr.resource_uri=f"https://{project_location}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{project_location}/customJobs/{job.name}"
+    ctr.resource_uri=custom_job_name
     gcp_resources=MessageToJson(custom_train_job_resources)
     return (gcp_resources,)

From cca75d5d713ea3398dfbf4cb540f8b92f9702d1a Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 1 Jun 2023 16:13:07 +0100
Subject: [PATCH 091/238] style: formatting

---
 .../src/vertex_components/custom_train_job.py      | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/components/vertex-components/src/vertex_components/custom_train_job.py b/components/vertex-components/src/vertex_components/custom_train_job.py
index f25b8077..9cc51b17 100644
--- a/components/vertex-components/src/vertex_components/custom_train_job.py
+++ b/components/vertex-components/src/vertex_components/custom_train_job.py
@@ -18,7 +18,10 @@
 
 @component(
     base_image="python:3.7",
-    packages_to_install=["google-cloud-aiplatform==1.24.1", "google-cloud-pipeline-components==1.0.42"],
+    packages_to_install=[
+        "google-cloud-aiplatform==1.24.1",
+        "google-cloud-pipeline-components==1.0.42",
+    ],
 )
 def custom_train_job(
     train_script_uri: str,
@@ -41,7 +44,7 @@ def custom_train_job(
     accelerator_type: str = "ACCELERATOR_TYPE_UNSPECIFIED",
     accelerator_count: int = 0,
     parent_model: str = None,
-) -> NamedTuple("Outputs",  [("gcp_resources", str)]):
+) -> NamedTuple("Outputs", [("gcp_resources", str)]):
     """Run a custom training job using a training script.
 
     The provided script will be invoked by passing the following command-line arguments:
@@ -146,13 +149,12 @@ def custom_train_job(
     for k, v in parsed_metrics.items():
         if type(v) is float:
             metrics.log_metric(k, v)
-    
 
     # return GCP resource for Vertex AI UI integration
-    custom_job_name = job.to_dict()['trainingTaskMetadata']['backingCustomJob']
+    custom_job_name = job.to_dict()["trainingTaskMetadata"]["backingCustomJob"]
     custom_train_job_resources = GcpResources()
     ctr = custom_train_job_resources.resources.add()
     ctr.resource_type = "CustomJob"
-    ctr.resource_uri=custom_job_name
-    gcp_resources=MessageToJson(custom_train_job_resources)
+    ctr.resource_uri = custom_job_name
+    gcp_resources = MessageToJson(custom_train_job_resources)
     return (gcp_resources,)

From 15675d413f2df18a772ea1f5ed85850abcc80f38 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Fri, 2 Jun 2023 09:33:03 +0100
Subject: [PATCH 092/238] test: gcp resources unit tests

---
 .../tests/test_custom_training_job.py            | 16 +++++++++++++---
 1 file changed, 13 insertions(+), 3 deletions(-)

diff --git a/components/vertex-components/tests/test_custom_training_job.py b/components/vertex-components/tests/test_custom_training_job.py
index 46ec46ca..ac7675c4 100644
--- a/components/vertex-components/tests/test_custom_training_job.py
+++ b/components/vertex-components/tests/test_custom_training_job.py
@@ -2,7 +2,7 @@
 from kfp.v2.dsl import Dataset, Metrics, Artifact
 from unittest import mock
 import pytest
-
+import json
 
 import vertex_components
 
@@ -24,7 +24,12 @@ def test_custom_train_job(mock_open, mock_exists, mock_job, tmpdir):
     mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
     mock_metrics = Metrics(uri=tmpdir)
 
-    custom_train_job(
+    mock_job_instance = mock_job.return_value
+    mock_job_instance.to_dict.return_value = {
+        "trainingTaskMetadata": {"backingCustomJob": "mock_custom_job_name"}
+    }
+
+    (gcp_resources,) = custom_train_job(
         train_script_uri="gs://my-bucket/train_script.py",
         train_data=mock_train_data,
         valid_data=mock_valid_data,
@@ -53,6 +58,11 @@ def test_custom_train_job(mock_open, mock_exists, mock_job, tmpdir):
 
     # Assert metrics loading
     mock_open.assert_called_once_with(tmpdir, "r")
+    # Assert gcp_resources contains the expected value
+    assert (
+        json.loads(gcp_resources)["resources"][0]["resourceUri"]
+        == "mock_custom_job_name"
+    )
 
 
 @mock.patch("google.cloud.aiplatform.CustomTrainingJob")
@@ -72,7 +82,7 @@ def test_custom_train_script_not_found(mock_open, mock_exists, mock_job, tmpdir)
     mock_metrics = Metrics(uri=tmpdir)
 
     with pytest.raises(ValueError):
-        custom_train_job(
+        (gcp_resources,) = custom_train_job(
             train_script_uri="gs://my-bucket/train_script.py",
             train_data=mock_train_data,
             valid_data=mock_valid_data,

From ece44440fd4f1306c3e0dfd03a48af03ec912882 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Mon, 5 Jun 2023 10:06:34 +0100
Subject: [PATCH 093/238] Add ADDITIONAL_SUFFIX for all other pipelines

---
 .../src/pipelines/tensorflow/prediction/pipeline.py      | 5 ++++-
 pipelines/src/pipelines/tensorflow/training/pipeline.py  | 9 +++++++--
 pipelines/src/pipelines/xgboost/prediction/pipeline.py   | 5 ++++-
 3 files changed, 15 insertions(+), 4 deletions(-)

diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index 7290a4c9..a3e29c54 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -36,6 +36,7 @@ def tensorflow_pipeline(
     batch_prediction_machine_type: str = "n1-standard-4",
     batch_prediction_min_replicas: int = 3,
     batch_prediction_max_replicas: int = 10,
+    additional_suffix: str = os.environ.get("ADDITIONAL_SUFFIX"),
 ):
     """
     Tensorflow prediction pipeline which:
@@ -68,6 +69,8 @@ def tensorflow_pipeline(
             Vertex Batch Prediction job for horizontal scalability
         batch_prediction_max_replicas (int): Maximum no of machines to distribute the
             Vertex Batch Prediction job for horizontal scalability.
+        additional_suffix (str): Optional. Additional suffix to append GCS asset path
+            and BQ tables that get overwritten.
 
     Returns:
         None
@@ -79,7 +82,7 @@ def tensorflow_pipeline(
     file_pattern = ""  # e.g. "files-*.csv", used as file pattern on storage
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_tf_prediction"  # suffix to table names
+    table_suffix = "_tf_prediction" + str(additional_suffix)  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     monitoring_alert_email_addresses = []
     monitoring_skew_config = {"defaultSkewThreshold": {"value": 0.001}}
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 0dfb1bb2..90b48b08 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -39,6 +39,7 @@ def tensorflow_pipeline(
     timestamp: str = "2022-12-01 00:00:00",
     staging_bucket: str = os.environ.get("VERTEX_PIPELINE_ROOT"),
     pipeline_files_gcs_path: str = os.environ.get("PIPELINE_FILES_GCS_PATH"),
+    additional_suffix: str = os.environ.get("ADDITIONAL_SUFFIX"),
     test_dataset_uri: str = "",
 ):
     """
@@ -65,6 +66,8 @@ def tensorflow_pipeline(
             If any time part is missing, it will be regarded as zero.
         staging_bucket (str): Staging bucket for pipeline artifacts.
         pipeline_files_gcs_path (str): GCS path where the pipeline files are located
+        additional_suffix (str): Optional. Additional suffix to append GCS asset path
+            and BQ tables that get overwritten.
         test_dataset_uri (str): Optional. GCS URI of statis held-out test dataset.
     """
 
@@ -73,14 +76,16 @@ def tensorflow_pipeline(
     label_column_name = "total_fare"
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_tf_training"  # suffix to table names
+    table_suffix = "_tf_training" + str(additional_suffix)  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     preprocessed_table = "preprocessed_data" + table_suffix
     train_table = "train_data" + table_suffix
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_tf_model.py"
+    train_script_uri = (
+        f"{pipeline_files_gcs_path}/assets{additional_suffix}/train_tf_model.py"
+    )
     hparams = dict(
         batch_size=100,
         epochs=5,
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index 5592a121..3c83d490 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -36,6 +36,7 @@ def xgboost_pipeline(
     batch_prediction_machine_type: str = "n1-standard-4",
     batch_prediction_min_replicas: int = 3,
     batch_prediction_max_replicas: int = 10,
+    additional_suffix: str = os.environ.get("ADDITIONAL_SUFFIX"),
 ):
     """
     XGB prediction pipeline which:
@@ -65,6 +66,8 @@ def xgboost_pipeline(
             Vertex Batch Prediction job for horizontal scalability
         batch_prediction_max_replicas (int): Maximum no of machines to distribute the
             Vertex Batch Prediction job for horizontal scalability.
+        additional_suffix (str): Optional. Additional suffix to append GCS asset path
+            and BQ tables that get overwritten.
 
     Returns:
         None
@@ -75,7 +78,7 @@ def xgboost_pipeline(
     # into different components of the pipeline
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_xgb_prediction"  # suffix to table names
+    table_suffix = "_xgb_prediction" + str(additional_suffix)  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     monitoring_alert_email_addresses = []
     monitoring_skew_config = {"defaultSkewThreshold": {"value": 0.001}}

From 3ea015a2876f46a96a8e9029bc8378e4a5a64a83 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Mon, 5 Jun 2023 10:09:32 +0100
Subject: [PATCH 094/238] more comprehensive comment for ADDITIONAL_SUFFIX

---
 env.sh.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.sh.example b/env.sh.example
index 455baeb3..b4064f21 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -20,7 +20,7 @@ export VERTEX_CMEK_IDENTIFIER= # optional
 export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
-export ADDITIONAL_SUFFIX= # optional, add underscore for better readability e.g. _suffix
+export ADDITIONAL_SUFFIX= # optional, additional suffix to for BQ and GCS resource names to prevent developers overwriting when working in the same Google Cloud Project
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com

From 01e7d02ca783d59f07912fc2bda7dfa1d30be9c8 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Mon, 5 Jun 2023 11:08:51 +0100
Subject: [PATCH 095/238] extend comment for ADDITIONAL_SUFFIX

---
 env.sh.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.sh.example b/env.sh.example
index b4064f21..c4d7f303 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -20,7 +20,7 @@ export VERTEX_CMEK_IDENTIFIER= # optional
 export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
-export ADDITIONAL_SUFFIX= # optional, additional suffix to for BQ and GCS resource names to prevent developers overwriting when working in the same Google Cloud Project
+export ADDITIONAL_SUFFIX= # optional, additional suffix (e.g. _<your name>) for BQ and GCS outputs to prevent developers overwriting them when working in the same Google Cloud Project.
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com

From 6d6fc45674f15ccda4f0de7101e6c22f9bcade55 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Mon, 5 Jun 2023 11:42:10 +0100
Subject: [PATCH 096/238] Add empty ADDITIONAL_SUFFIX in cloudbuild e2e tests

---
 cloudbuild/e2e-test.yaml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index c2e28095..13a2b0f9 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -45,6 +45,7 @@ steps:
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
       - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
+      - ADDITIONAL_SUFFIX=
 
 options:
   logging: CLOUD_LOGGING_ONLY

From 8e54ee18f584d6f043fc170fa83203d7bcd19107 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Mon, 5 Jun 2023 13:13:40 +0100
Subject: [PATCH 097/238] Combine ADDITIONAL_SUFFIX into
 PIPELINE_FILES_GCS_PATH

---
 Makefile                                                | 2 +-
 env.sh.example                                          | 2 +-
 pipelines/src/pipelines/tensorflow/training/pipeline.py | 5 +----
 pipelines/src/pipelines/xgboost/training/pipeline.py    | 4 +---
 4 files changed, 4 insertions(+), 9 deletions(-)

diff --git a/Makefile b/Makefile
index 2342612a..8627895a 100644
--- a/Makefile
+++ b/Makefile
@@ -73,7 +73,7 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
-		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets${ADDITIONAL_SUFFIX} ; \
+		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}; \
 	else \
 		echo "No assets folder found" ; \
 	fi ;
diff --git a/env.sh.example b/env.sh.example
index c4d7f303..c6bd03e3 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -24,5 +24,5 @@ export ADDITIONAL_SUFFIX= # optional, additional suffix (e.g. _<your name>) for
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets
+export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/assets${ADDITIONAL_SUFFIX}
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 90b48b08..36f042a6 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -52,7 +52,6 @@ def tensorflow_pipeline(
     Args:
         project_id (str): project id of the Google Cloud project
         project_location (str): location of the Google Cloud project
-        pipeline_files_gcs_path (str): GCS path where the pipeline files are located
         ingestion_project_id (str): project id containing the source bigquery data
             for ingestion. This can be the same as `project_id` if the source data is
             in the same project where the ML pipeline is executed.
@@ -83,9 +82,7 @@ def tensorflow_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = (
-        f"{pipeline_files_gcs_path}/assets{additional_suffix}/train_tf_model.py"
-    )
+    train_script_uri = f"{pipeline_files_gcs_path}/train_tf_model.py"
     hparams = dict(
         batch_size=100,
         epochs=5,
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 565b985c..7cbecbd1 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -81,9 +81,7 @@ def xgboost_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = (
-        f"{pipeline_files_gcs_path}/assets{additional_suffix}/train_xgb_model.py"
-    )
+    train_script_uri = f"{pipeline_files_gcs_path}/train_xgb_model.py"
     hparams = dict(
         n_estimators=200,
         early_stopping_rounds=10,

From 52e6ac3fe8d948df419a7632bbb31d3190564ff1 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 09:37:55 +0100
Subject: [PATCH 098/238] Change to RESOURCE_SUFFIX env var that is the current
 git user name

---
 Makefile                                                  | 3 +++
 cloudbuild/e2e-test.yaml                                  | 2 +-
 env.sh.example                                            | 4 +++-
 pipelines/src/pipelines/tensorflow/prediction/pipeline.py | 8 ++++----
 pipelines/src/pipelines/tensorflow/training/pipeline.py   | 8 ++++----
 pipelines/src/pipelines/xgboost/prediction/pipeline.py    | 8 ++++----
 pipelines/src/pipelines/xgboost/training/pipeline.py      | 8 ++++----
 7 files changed, 23 insertions(+), 18 deletions(-)

diff --git a/Makefile b/Makefile
index 8627895a..c3d1ad8d 100644
--- a/Makefile
+++ b/Makefile
@@ -15,6 +15,9 @@
 -include env.sh
 export
 
+RESOURCE_SUFFIX := $(shell . env.sh && echo $$RESOURCE_SUFFIX)
+PIPELINE_FILES_GCS_PATH := $(shell . env.sh && echo $$PIPELINE_FILES_GCS_PATH)
+
 help: ## Display this help screen
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
     
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 13a2b0f9..923275d9 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -45,7 +45,7 @@ steps:
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
       - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
-      - ADDITIONAL_SUFFIX=
+      - RESOURCE_SUFFIX=_${$SHORT_SHA}
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/env.sh.example b/env.sh.example
index c6bd03e3..b7289123 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -20,7 +20,9 @@ export VERTEX_CMEK_IDENTIFIER= # optional
 export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
-export ADDITIONAL_SUFFIX= # optional, additional suffix (e.g. _<your name>) for BQ and GCS outputs to prevent developers overwriting them when working in the same Google Cloud Project.
+
+# Suffix to facilitate running concurrent pipelines in the same Google Cloud project. Uncomment if working in a team to avoid overwriting resources during development 
+# export RESOURCE_SUFFIX=_$(git config --get user.name)
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index a3e29c54..ff25c119 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -36,7 +36,7 @@ def tensorflow_pipeline(
     batch_prediction_machine_type: str = "n1-standard-4",
     batch_prediction_min_replicas: int = 3,
     batch_prediction_max_replicas: int = 10,
-    additional_suffix: str = os.environ.get("ADDITIONAL_SUFFIX"),
+    resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
 ):
     """
     Tensorflow prediction pipeline which:
@@ -69,8 +69,8 @@ def tensorflow_pipeline(
             Vertex Batch Prediction job for horizontal scalability
         batch_prediction_max_replicas (int): Maximum no of machines to distribute the
             Vertex Batch Prediction job for horizontal scalability.
-        additional_suffix (str): Optional. Additional suffix to append GCS asset path
-            and BQ tables that get overwritten.
+        resource_suffix (str): Optional. Additional suffix to append GCS resources
+            that get overwritten.
 
     Returns:
         None
@@ -82,7 +82,7 @@ def tensorflow_pipeline(
     file_pattern = ""  # e.g. "files-*.csv", used as file pattern on storage
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_tf_prediction" + str(additional_suffix)  # suffix to table names
+    table_suffix = "_tf_prediction" + str(resource_suffix)  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     monitoring_alert_email_addresses = []
     monitoring_skew_config = {"defaultSkewThreshold": {"value": 0.001}}
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 36f042a6..9f1d0544 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -39,7 +39,7 @@ def tensorflow_pipeline(
     timestamp: str = "2022-12-01 00:00:00",
     staging_bucket: str = os.environ.get("VERTEX_PIPELINE_ROOT"),
     pipeline_files_gcs_path: str = os.environ.get("PIPELINE_FILES_GCS_PATH"),
-    additional_suffix: str = os.environ.get("ADDITIONAL_SUFFIX"),
+    resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
     test_dataset_uri: str = "",
 ):
     """
@@ -65,8 +65,8 @@ def tensorflow_pipeline(
             If any time part is missing, it will be regarded as zero.
         staging_bucket (str): Staging bucket for pipeline artifacts.
         pipeline_files_gcs_path (str): GCS path where the pipeline files are located
-        additional_suffix (str): Optional. Additional suffix to append GCS asset path
-            and BQ tables that get overwritten.
+        resource_suffix (str): Optional. Additional suffix to append GCS resources
+            that get overwritten.
         test_dataset_uri (str): Optional. GCS URI of statis held-out test dataset.
     """
 
@@ -75,7 +75,7 @@ def tensorflow_pipeline(
     label_column_name = "total_fare"
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_tf_training" + str(additional_suffix)  # suffix to table names
+    table_suffix = "_tf_training" + str(resource_suffix)  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     preprocessed_table = "preprocessed_data" + table_suffix
     train_table = "train_data" + table_suffix
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index 3c83d490..f077d32c 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -36,7 +36,7 @@ def xgboost_pipeline(
     batch_prediction_machine_type: str = "n1-standard-4",
     batch_prediction_min_replicas: int = 3,
     batch_prediction_max_replicas: int = 10,
-    additional_suffix: str = os.environ.get("ADDITIONAL_SUFFIX"),
+    resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
 ):
     """
     XGB prediction pipeline which:
@@ -66,8 +66,8 @@ def xgboost_pipeline(
             Vertex Batch Prediction job for horizontal scalability
         batch_prediction_max_replicas (int): Maximum no of machines to distribute the
             Vertex Batch Prediction job for horizontal scalability.
-        additional_suffix (str): Optional. Additional suffix to append GCS asset path
-            and BQ tables that get overwritten.
+        resource_suffix (str): Optional. Additional suffix to append GCS resources
+            that get overwritten.
 
     Returns:
         None
@@ -78,7 +78,7 @@ def xgboost_pipeline(
     # into different components of the pipeline
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_xgb_prediction" + str(additional_suffix)  # suffix to table names
+    table_suffix = "_xgb_prediction" + str(resource_suffix)  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     monitoring_alert_email_addresses = []
     monitoring_skew_config = {"defaultSkewThreshold": {"value": 0.001}}
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 7cbecbd1..64f3061c 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -39,7 +39,7 @@ def xgboost_pipeline(
     timestamp: str = "2022-12-01 00:00:00",
     staging_bucket: str = os.environ.get("VERTEX_PIPELINE_ROOT"),
     pipeline_files_gcs_path: str = os.environ.get("PIPELINE_FILES_GCS_PATH"),
-    additional_suffix: str = os.environ.get("ADDITIONAL_SUFFIX"),
+    resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
     test_dataset_uri: str = "",
 ):
     """
@@ -64,9 +64,9 @@ def xgboost_pipeline(
             If any time part is missing, it will be regarded as zero.
         staging_bucket (str): Staging bucket for pipeline artifacts.
         pipeline_files_gcs_path (str): GCS path where the pipeline files are located.
+        resource_suffix (str): Optional. Additional suffix to append GCS resources
+            that get overwritten.
         test_dataset_uri (str): Optional. GCS URI of statis held-out test dataset.
-        additional_suffix (str): Optional. Additional suffix to append GCS asset path
-            and BQ tables that get overwritten.
     """
 
     # Create variables to ensure the same arguments are passed
@@ -74,7 +74,7 @@ def xgboost_pipeline(
     label_column_name = "total_fare"
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_xgb_training" + str(additional_suffix)  # suffix to table names
+    table_suffix = "_xgb_training" + str(resource_suffix)  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     preprocessed_table = "preprocessed_data" + table_suffix
     train_table = "train_data" + table_suffix

From 630833ce90b26a7e9b6a2c618942e82effc50342 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 09:45:04 +0100
Subject: [PATCH 099/238] Update README.md with info about RESOURCE_SUFFIX

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index a26f5ff4..25bdb446 100644
--- a/README.md
+++ b/README.md
@@ -178,6 +178,8 @@ This will execute the pipeline using the chosen template on Vertex AI, namely it
 1. Copy the `assets` folders to Cloud Storage
 1. Trigger the pipeline with the help of `pipelines/trigger/main.py`
 
+To avoid resource conflicts when running pipelines concurrently in the same Google Cloud project with multiple developers, uncomment the `RESOURCE_SUFFIX` environment variable in your `env.sh` file. This will append your Git username as the suffix to Google resources and ensure each developer's resources remain unique and separate, preventing unintentional overwriting.
+
 #### Pipeline input parameters
 
 The ML pipelines have input parameters. As you can see in the pipeline definition files (`pipelines/pipelines/<xgboost|tensorflow>/<training|prediction>/pipeline.py`), they have default values, and some of these default values are derived from environment variables (which in turn are defined in `env.sh`).

From d850a5a35860e735887896ec1e0e2f6ab27ce819 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 10:13:44 +0100
Subject: [PATCH 100/238] Comment out Make variables to check if they're
 affecting e2e tests

---
 Makefile | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Makefile b/Makefile
index c3d1ad8d..a639ae6a 100644
--- a/Makefile
+++ b/Makefile
@@ -15,8 +15,8 @@
 -include env.sh
 export
 
-RESOURCE_SUFFIX := $(shell . env.sh && echo $$RESOURCE_SUFFIX)
-PIPELINE_FILES_GCS_PATH := $(shell . env.sh && echo $$PIPELINE_FILES_GCS_PATH)
+# RESOURCE_SUFFIX := $(shell . env.sh && echo $$RESOURCE_SUFFIX)
+# PIPELINE_FILES_GCS_PATH := $(shell . env.sh && echo $$PIPELINE_FILES_GCS_PATH)
 
 help: ## Display this help screen
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'

From f8ef02b2b79d1df9b3972599ad7c1433fc2d024c Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 10:25:03 +0100
Subject: [PATCH 101/238] Fix e2e tests by sourcing env.sh as part of Make
 commands

---
 Makefile                 | 9 ++++-----
 cloudbuild/e2e-test.yaml | 2 +-
 2 files changed, 5 insertions(+), 6 deletions(-)

diff --git a/Makefile b/Makefile
index a639ae6a..6c52aded 100644
--- a/Makefile
+++ b/Makefile
@@ -15,9 +15,6 @@
 -include env.sh
 export
 
-# RESOURCE_SUFFIX := $(shell . env.sh && echo $$RESOURCE_SUFFIX)
-# PIPELINE_FILES_GCS_PATH := $(shell . env.sh && echo $$PIPELINE_FILES_GCS_PATH)
-
 help: ## Display this help screen
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
     
@@ -36,7 +33,8 @@ test-trigger: ## Runs unit tests for the pipeline trigger code
 	poetry run python -m pytest tests/trigger
 
 compile-pipeline: ## Compile the pipeline to training.json or prediction.json. Must specify pipeline=<training|prediction>
-	@cd pipelines/src && \
+	@source ./env.sh && \
+	cd pipelines/src && \
 	poetry run python -m pipelines.${PIPELINE_TEMPLATE}.${pipeline}.pipeline
 
 setup-components: ## Run unit tests for a component group
@@ -76,7 +74,8 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
-		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}; \
+		source ./env.sh && \
+		gsutil -m rsync -r -d ./pipelines/assets $$PIPELINE_FILES_GCS_PATH; \
 	else \
 		echo "No assets folder found" ; \
 	fi ;
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 923275d9..412536f8 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -45,7 +45,7 @@ steps:
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
       - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
-      - RESOURCE_SUFFIX=_${$SHORT_SHA}
+      - RESOURCE_SUFFIX=_${SHORT_SHA}
 
 options:
   logging: CLOUD_LOGGING_ONLY

From b4e2abcafa81b90dd7bb3aa2e9a04a905ecfd580 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 10:30:27 +0100
Subject: [PATCH 102/238] Change from source to . in makefile

---
 Makefile | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Makefile b/Makefile
index 6c52aded..6e9276c8 100644
--- a/Makefile
+++ b/Makefile
@@ -33,7 +33,7 @@ test-trigger: ## Runs unit tests for the pipeline trigger code
 	poetry run python -m pytest tests/trigger
 
 compile-pipeline: ## Compile the pipeline to training.json or prediction.json. Must specify pipeline=<training|prediction>
-	@source ./env.sh && \
+	@. ./env.sh && \
 	cd pipelines/src && \
 	poetry run python -m pipelines.${PIPELINE_TEMPLATE}.${pipeline}.pipeline
 
@@ -74,7 +74,7 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
-		source ./env.sh && \
+		. ./env.sh && \
 		gsutil -m rsync -r -d ./pipelines/assets $$PIPELINE_FILES_GCS_PATH; \
 	else \
 		echo "No assets folder found" ; \

From dba5afd3d9dbffe993a7a714cf14767f51992ba4 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 10:44:50 +0100
Subject: [PATCH 103/238] Try using conditional assignment in Makefile to fix
 e2e tests

---
 Makefile | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/Makefile b/Makefile
index 6e9276c8..adeb7724 100644
--- a/Makefile
+++ b/Makefile
@@ -12,6 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+RESOURCE_SUFFIX ?= $(shell . env.sh && echo $$RESOURCE_SUFFIX)
+PIPELINE_FILES_GCS_PATH ?= $(shell . env.sh && echo $$PIPELINE_FILES_GCS_PATH)
+
 -include env.sh
 export
 
@@ -33,8 +36,7 @@ test-trigger: ## Runs unit tests for the pipeline trigger code
 	poetry run python -m pytest tests/trigger
 
 compile-pipeline: ## Compile the pipeline to training.json or prediction.json. Must specify pipeline=<training|prediction>
-	@. ./env.sh && \
-	cd pipelines/src && \
+	@cd pipelines/src && \
 	poetry run python -m pipelines.${PIPELINE_TEMPLATE}.${pipeline}.pipeline
 
 setup-components: ## Run unit tests for a component group
@@ -74,7 +76,6 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
-		. ./env.sh && \
 		gsutil -m rsync -r -d ./pipelines/assets $$PIPELINE_FILES_GCS_PATH; \
 	else \
 		echo "No assets folder found" ; \

From 1b11d02d6e802ff263f084eea5fee70296aa6782 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 11:00:03 +0100
Subject: [PATCH 104/238] Update PIPELINE_FILES_GCS_PATH env var in e2e tests
 to include assets sub directory

---
 Makefile                 | 2 +-
 cloudbuild/e2e-test.yaml | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/Makefile b/Makefile
index adeb7724..fba2a29e 100644
--- a/Makefile
+++ b/Makefile
@@ -76,7 +76,7 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
-		gsutil -m rsync -r -d ./pipelines/assets $$PIPELINE_FILES_GCS_PATH; \
+		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}; \
 	else \
 		echo "No assets folder found" ; \
 	fi ;
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 412536f8..d2754603 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -44,7 +44,7 @@ steps:
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
-      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
+      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}/assets
       - RESOURCE_SUFFIX=_${SHORT_SHA}
 
 options:

From 617ed59ff9a29e5385db43350b551f869381b354 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 16:33:51 +0100
Subject: [PATCH 105/238] Revert to letting users specify their own suffix

---
 Makefile       | 3 ---
 README.md      | 2 +-
 env.sh.example | 4 ++--
 3 files changed, 3 insertions(+), 6 deletions(-)

diff --git a/Makefile b/Makefile
index fba2a29e..8627895a 100644
--- a/Makefile
+++ b/Makefile
@@ -12,9 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-RESOURCE_SUFFIX ?= $(shell . env.sh && echo $$RESOURCE_SUFFIX)
-PIPELINE_FILES_GCS_PATH ?= $(shell . env.sh && echo $$PIPELINE_FILES_GCS_PATH)
-
 -include env.sh
 export
 
diff --git a/README.md b/README.md
index 25bdb446..6fcd6069 100644
--- a/README.md
+++ b/README.md
@@ -178,7 +178,7 @@ This will execute the pipeline using the chosen template on Vertex AI, namely it
 1. Copy the `assets` folders to Cloud Storage
 1. Trigger the pipeline with the help of `pipelines/trigger/main.py`
 
-To avoid resource conflicts when running pipelines concurrently in the same Google Cloud project with multiple developers, uncomment the `RESOURCE_SUFFIX` environment variable in your `env.sh` file. This will append your Git username as the suffix to Google resources and ensure each developer's resources remain unique and separate, preventing unintentional overwriting.
+To avoid resource conflicts when running pipelines concurrently in the same Google Cloud project with multiple developers, populate the `RESOURCE_SUFFIX` environment variable in your `env.sh` file. This will append your defined suffix to Google resources and ensure each developer's resources remain unique and separate, preventing unintentional overwriting.
 
 #### Pipeline input parameters
 
diff --git a/env.sh.example b/env.sh.example
index b7289123..530189f6 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -21,8 +21,8 @@ export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
 
-# Suffix to facilitate running concurrent pipelines in the same Google Cloud project. Uncomment if working in a team to avoid overwriting resources during development 
-# export RESOURCE_SUFFIX=_$(git config --get user.name)
+# Suffix (e.g. _<your name>) to facilitate running concurrent pipelines in the same Google Cloud project. Populate if working in a team to avoid overwriting resources during development 
+export RESOURCE_SUFFIX=
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com

From c480f6f9cbd7fa26ebdd911431f32cda018f8e97 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 16:35:34 +0100
Subject: [PATCH 106/238] RESOURCE_SUFFIX typo in env.sh.example

---
 env.sh.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.sh.example b/env.sh.example
index 530189f6..99fa5181 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -26,5 +26,5 @@ export RESOURCE_SUFFIX=
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/assets${ADDITIONAL_SUFFIX}
+export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/assets${RESOURCE_SUFFIX}
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root

From 60de248fde1c6ed37180b8fbf6b75412a05f52f8 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 17:33:23 +0100
Subject: [PATCH 107/238] Revert including `assets` as part of
 pipeline_files_gcs_path

---
 Makefile                                                | 2 +-
 env.sh.example                                          | 2 +-
 pipelines/src/pipelines/tensorflow/training/pipeline.py | 2 +-
 pipelines/src/pipelines/xgboost/training/pipeline.py    | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/Makefile b/Makefile
index 8627895a..7e762bbd 100644
--- a/Makefile
+++ b/Makefile
@@ -73,7 +73,7 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
-		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}; \
+		gsutil -m rsync -r  ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets; \
 	else \
 		echo "No assets folder found" ; \
 	fi ;
diff --git a/env.sh.example b/env.sh.example
index 99fa5181..627502c4 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -26,5 +26,5 @@ export RESOURCE_SUFFIX=
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/assets${RESOURCE_SUFFIX}
+export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/${RESOURCE_SUFFIX}
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 9f1d0544..f4474fb8 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -82,7 +82,7 @@ def tensorflow_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/train_tf_model.py"
+    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_tf_model.py"
     hparams = dict(
         batch_size=100,
         epochs=5,
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 64f3061c..e0e041a7 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -81,7 +81,7 @@ def xgboost_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/train_xgb_model.py"
+    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_xgb_model.py"
     hparams = dict(
         n_estimators=200,
         early_stopping_rounds=10,

From 020bc8a140472cc09ae7e3eb5026e91f92840f73 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 8 Jun 2023 17:51:32 +0100
Subject: [PATCH 108/238] Revert "Revert including `assets` as part of
 pipeline_files_gcs_path"

This reverts commit 60de248fde1c6ed37180b8fbf6b75412a05f52f8.
---
 Makefile                                                | 2 +-
 env.sh.example                                          | 2 +-
 pipelines/src/pipelines/tensorflow/training/pipeline.py | 2 +-
 pipelines/src/pipelines/xgboost/training/pipeline.py    | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/Makefile b/Makefile
index 7e762bbd..8627895a 100644
--- a/Makefile
+++ b/Makefile
@@ -73,7 +73,7 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ] ; then \
 		echo "Syncing assets to GCS" && \
-		gsutil -m rsync -r  ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}/assets; \
+		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}; \
 	else \
 		echo "No assets folder found" ; \
 	fi ;
diff --git a/env.sh.example b/env.sh.example
index 627502c4..99fa5181 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -26,5 +26,5 @@ export RESOURCE_SUFFIX=
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/${RESOURCE_SUFFIX}
+export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/assets${RESOURCE_SUFFIX}
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index f4474fb8..9f1d0544 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -82,7 +82,7 @@ def tensorflow_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_tf_model.py"
+    train_script_uri = f"{pipeline_files_gcs_path}/train_tf_model.py"
     hparams = dict(
         batch_size=100,
         epochs=5,
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index e0e041a7..64f3061c 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -81,7 +81,7 @@ def xgboost_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_xgb_model.py"
+    train_script_uri = f"{pipeline_files_gcs_path}/train_xgb_model.py"
     hparams = dict(
         n_estimators=200,
         early_stopping_rounds=10,

From b4623a9268f16f2c4501fff1f5e36b67a542376e Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Fri, 9 Jun 2023 16:39:08 +0100
Subject: [PATCH 109/238] Revert PIPELINE_GCS_PATH to NOT include assets
 subdirectory

---
 Makefile                                           | 14 +++++++++-----
 cloudbuild/e2e-test.yaml                           |  4 ++--
 env.sh.example                                     |  2 +-
 .../src/pipelines/tensorflow/training/pipeline.py  |  2 +-
 .../src/pipelines/xgboost/training/pipeline.py     |  2 +-
 5 files changed, 14 insertions(+), 10 deletions(-)

diff --git a/Makefile b/Makefile
index 8627895a..11ea0ccf 100644
--- a/Makefile
+++ b/Makefile
@@ -71,12 +71,16 @@ test-all-components-coverage: ## Run tests with coverage
 	done
 
 sync-assets: ## Sync assets folder to GCS.
-	@if [ -d "./pipelines/assets/" ] ; then \
-		echo "Syncing assets to GCS" && \
-		gsutil -m rsync -r -d ./pipelines/assets ${PIPELINE_FILES_GCS_PATH}; \
+	@if [ -d "./pipelines/assets/" ]; then \
+		echo "Syncing assets to GCS"; \
+		if [[ "$${PIPELINE_FILES_GCS_PATH}" == */ ]]; then \
+    		gsutil -m rsync -r -d ./pipelines/assets "$${PIPELINE_FILES_GCS_PATH}assets"; \
+		else \
+    		gsutil -m rsync -r -d ./pipelines/assets "$${PIPELINE_FILES_GCS_PATH}/assets"; \
+		fi; \
 	else \
-		echo "No assets folder found" ; \
-	fi ;
+		echo "No assets folder found"; \
+	fi;
 
 run: ## Compile pipeline, copy assets to GCS, and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
 	@ $(MAKE) compile-pipeline && \
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index d2754603..431bd515 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -44,8 +44,8 @@ steps:
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
-      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}/assets
-      - RESOURCE_SUFFIX=_${SHORT_SHA}
+      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
+      - RESOURCE_SUFFIX=_${COMMIT_SHA}
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/env.sh.example b/env.sh.example
index 99fa5181..627502c4 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -26,5 +26,5 @@ export RESOURCE_SUFFIX=
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/assets${RESOURCE_SUFFIX}
+export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/${RESOURCE_SUFFIX}
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 9f1d0544..f4474fb8 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -82,7 +82,7 @@ def tensorflow_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/train_tf_model.py"
+    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_tf_model.py"
     hparams = dict(
         batch_size=100,
         epochs=5,
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 64f3061c..e0e041a7 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -81,7 +81,7 @@ def xgboost_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/train_xgb_model.py"
+    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_xgb_model.py"
     hparams = dict(
         n_estimators=200,
         early_stopping_rounds=10,

From b318d077c700e2280e1856ab8759d51336ffb545 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Fri, 9 Jun 2023 16:42:24 +0100
Subject: [PATCH 110/238] update scheduled_jobs.auto.tfvars.example

---
 .../scheduled_jobs.auto.tfvars.example                 | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
index a92fd2df..a08ca038 100644
--- a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
+++ b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
@@ -26,7 +26,7 @@ cloud_schedulers_config = {
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west2"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
+      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>/assets"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
       model_label = "label_name"
@@ -49,7 +49,7 @@ cloud_schedulers_config = {
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
+      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>/assets"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
       model_label = "label_name"
@@ -70,12 +70,12 @@ cloud_schedulers_config = {
     description  = "Trigger my TensorFlow training pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
-    template_path = "gs://my-assets-bucket/<Git tag>/training/training.json"
+    template_path = "gs://my-assets-bucket/<Git tag>/assets/training/training.json"
     enable_caching = null
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
+      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>/assets"
       ingestion_project_id = "my-project-id"
       model_name = "tensorflow_with_preprocessing"
       model_label = "label_name"
@@ -98,7 +98,7 @@ cloud_schedulers_config = {
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
+      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>/assets"
       ingestion_project_id = "my-project-id"
       model_name = "tensorflow_with_preprocessing"
       model_label = "label_name"

From 29e25b02180bb8427b690e249b1bd74a94288ee8 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Mon, 12 Jun 2023 12:49:43 +0100
Subject: [PATCH 111/238] Add single quotes in env.sh.example comment

---
 env.sh.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.sh.example b/env.sh.example
index 627502c4..24622887 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -21,7 +21,7 @@ export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
 
-# Suffix (e.g. _<your name>) to facilitate running concurrent pipelines in the same Google Cloud project. Populate if working in a team to avoid overwriting resources during development 
+# Suffix (e.g. '_<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Populate if working in a team to avoid overwriting resources during development 
 export RESOURCE_SUFFIX=
 
 # Leave as-is

From 14f354d49ede7ab3f526fadf14985b2fc6681d04 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Wed, 14 Jun 2023 11:02:59 +0100
Subject: [PATCH 112/238] revert changes made to pipeline_files_gcs_path in
 scheduled_jobs.auto.tfvars.example

---
 .../scheduled_jobs.auto.tfvars.example                 | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
index a08ca038..a92fd2df 100644
--- a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
+++ b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
@@ -26,7 +26,7 @@ cloud_schedulers_config = {
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west2"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>/assets"
+      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
       model_label = "label_name"
@@ -49,7 +49,7 @@ cloud_schedulers_config = {
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>/assets"
+      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
       model_label = "label_name"
@@ -70,12 +70,12 @@ cloud_schedulers_config = {
     description  = "Trigger my TensorFlow training pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
-    template_path = "gs://my-assets-bucket/<Git tag>/assets/training/training.json"
+    template_path = "gs://my-assets-bucket/<Git tag>/training/training.json"
     enable_caching = null
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>/assets"
+      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
       ingestion_project_id = "my-project-id"
       model_name = "tensorflow_with_preprocessing"
       model_label = "label_name"
@@ -98,7 +98,7 @@ cloud_schedulers_config = {
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>/assets"
+      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
       ingestion_project_id = "my-project-id"
       model_name = "tensorflow_with_preprocessing"
       model_label = "label_name"

From d240286fa957bcee58627ea47b2b86aa3f402762 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Thu, 15 Jun 2023 12:41:00 +0100
Subject: [PATCH 113/238] Handle resource suffix in Makefile

---
 Makefile | 7 ++-----
 1 file changed, 2 insertions(+), 5 deletions(-)

diff --git a/Makefile b/Makefile
index 11ea0ccf..ad275e40 100644
--- a/Makefile
+++ b/Makefile
@@ -73,11 +73,8 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ]; then \
 		echo "Syncing assets to GCS"; \
-		if [[ "$${PIPELINE_FILES_GCS_PATH}" == */ ]]; then \
-    		gsutil -m rsync -r -d ./pipelines/assets "$${PIPELINE_FILES_GCS_PATH}assets"; \
-		else \
-    		gsutil -m rsync -r -d ./pipelines/assets "$${PIPELINE_FILES_GCS_PATH}/assets"; \
-		fi; \
+		PIPELINE_FILES_GCS_PATH=$${PIPELINE_FILES_GCS_PATH}$(if $(strip $(RESOURCE_SUFFIX)),/$(RESOURCE_SUFFIX)); \
+		gsutil -m rsync -r -d ./pipelines/assets "$${PIPELINE_FILES_GCS_PATH}/assets"; \
 	else \
 		echo "No assets folder found"; \
 	fi;

From cbac0c082f219d7a5de4bff9a6853f29cc6cd209 Mon Sep 17 00:00:00 2001
From: rachel-datatonic <rachel.le@datatonic.com>
Date: Mon, 26 Jun 2023 18:02:17 +0100
Subject: [PATCH 114/238] set the logging level to DEBUG in the sandbox_run
 function without causing duplicated logs

---
 pipelines/src/pipelines/trigger/main.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/pipelines/src/pipelines/trigger/main.py b/pipelines/src/pipelines/trigger/main.py
index 8aae023f..491361e2 100644
--- a/pipelines/src/pipelines/trigger/main.py
+++ b/pipelines/src/pipelines/trigger/main.py
@@ -191,7 +191,9 @@ def sandbox_run(args: List[str] = None) -> aiplatform.PipelineJob:
     Returns the PipelineJob object of the triggered pipeline run.
     Usage: python main.py --template_path=pipeline.json --enable_caching=true
     """
-    logging.basicConfig(level=logging.DEBUG)
+    logger = logging.getLogger(__name__)
+    logger.setLevel(logging.DEBUG)
+    logger.debug("This is a debug message")
 
     parser = argparse.ArgumentParser()
     parser.add_argument(

From 40ac52f92659d7fff4ce1c0b961ab22627198378 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Mon, 26 Jun 2023 21:20:13 +0200
Subject: [PATCH 115/238] Fix RESOURCE_SUFFIX bug

---
 Makefile       | 12 ++++++++++--
 env.sh.example |  2 +-
 2 files changed, 11 insertions(+), 3 deletions(-)

diff --git a/Makefile b/Makefile
index ad275e40..c7cff312 100644
--- a/Makefile
+++ b/Makefile
@@ -15,6 +15,15 @@
 -include env.sh
 export
 
+# Check if RESOURCE_SUFFIX is empty
+ifeq ($(strip $(RESOURCE_SUFFIX)),)
+  PIPELINE_FILES_GCS_PATH := gs://${VERTEX_PROJECT_ID}-pl-assets
+else
+  PIPELINE_FILES_GCS_PATH := gs://${VERTEX_PROJECT_ID}-pl-assets/$(RESOURCE_SUFFIX)
+endif
+
+export PIPELINE_FILES_GCS_PATH
+
 help: ## Display this help screen
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
     
@@ -73,8 +82,7 @@ test-all-components-coverage: ## Run tests with coverage
 sync-assets: ## Sync assets folder to GCS.
 	@if [ -d "./pipelines/assets/" ]; then \
 		echo "Syncing assets to GCS"; \
-		PIPELINE_FILES_GCS_PATH=$${PIPELINE_FILES_GCS_PATH}$(if $(strip $(RESOURCE_SUFFIX)),/$(RESOURCE_SUFFIX)); \
-		gsutil -m rsync -r -d ./pipelines/assets "$${PIPELINE_FILES_GCS_PATH}/assets"; \
+		gsutil -m rsync -r -d ./pipelines/assets $(PIPELINE_FILES_GCS_PATH)/assets ; \
 	else \
 		echo "No assets folder found"; \
 	fi;
diff --git a/env.sh.example b/env.sh.example
index 24622887..d8d355a7 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -26,5 +26,5 @@ export RESOURCE_SUFFIX=
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/${RESOURCE_SUFFIX}
+export PIPELINE_FILES_GCS_PATH="gs://${VERTEX_PROJECT_ID}-pl-assets"
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root

From 2492cffcc04b6829bbad7b14e11f0669639f146b Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Mon, 26 Jun 2023 21:23:46 +0200
Subject: [PATCH 116/238] Remove double quotes from PIPELINE_FILES_GCS_PATH

---
 env.sh.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.sh.example b/env.sh.example
index d8d355a7..bd838c01 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -26,5 +26,5 @@ export RESOURCE_SUFFIX=
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH="gs://${VERTEX_PROJECT_ID}-pl-assets"
+export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root

From 9d6a6a8b6eb76c427f2598c2c53ed55da4870bd6 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Tue, 27 Jun 2023 09:29:38 +0200
Subject: [PATCH 117/238] Fix e2e tests by using RESOURCE_SUFFIX when uploading
 assets

---
 cloudbuild/e2e-test.yaml | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 431bd515..2f5039d4 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -24,7 +24,9 @@ steps:
       - |
         mkdir -p ${COMMIT_SHA}/assets && \
         cp -r pipelines/assets ${COMMIT_SHA} && \
-        gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
+        gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${RESOURCE_SUFFIX}
+    env:
+      - RESOURCE_SUFFIX=_${COMMIT_SHA}
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
@@ -44,8 +46,8 @@ steps:
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
-      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
       - RESOURCE_SUFFIX=_${COMMIT_SHA}
+      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${RESOURCE_SUFFIX}
 
 options:
   logging: CLOUD_LOGGING_ONLY

From a8a22afcb41fba1740394730241d4f27f3e0303c Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Tue, 27 Jun 2023 10:30:22 +0200
Subject: [PATCH 118/238] Use custom substitutions for RESOURCE_SUFFIX in
 e2e-tests

---
 cloudbuild/e2e-test.yaml | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 2f5039d4..71aa800a 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -25,8 +25,8 @@ steps:
         mkdir -p ${COMMIT_SHA}/assets && \
         cp -r pipelines/assets ${COMMIT_SHA} && \
         gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${RESOURCE_SUFFIX}
-    env:
-      - RESOURCE_SUFFIX=_${COMMIT_SHA}
+    substitutions:
+      RESOURCE_SUFFIX: _${COMMIT_SHA}
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
@@ -46,8 +46,10 @@ steps:
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
-      - RESOURCE_SUFFIX=_${COMMIT_SHA}
+      - RESOURCE_SUFFIX=${RESOURCE_SUFFIX}
       - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${RESOURCE_SUFFIX}
+    substitutions:
+      RESOURCE_SUFFIX: _${COMMIT_SHA}
 
 options:
   logging: CLOUD_LOGGING_ONLY

From 938200cb2633d0901343ad5e309fb31e10bb6597 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Tue, 27 Jun 2023 10:32:30 +0200
Subject: [PATCH 119/238] Move substitutions to EOF in e2e-test.yaml

---
 cloudbuild/e2e-test.yaml | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 71aa800a..861a48d1 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -25,8 +25,6 @@ steps:
         mkdir -p ${COMMIT_SHA}/assets && \
         cp -r pipelines/assets ${COMMIT_SHA} && \
         gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${RESOURCE_SUFFIX}
-    substitutions:
-      RESOURCE_SUFFIX: _${COMMIT_SHA}
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
@@ -48,8 +46,9 @@ steps:
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
       - RESOURCE_SUFFIX=${RESOURCE_SUFFIX}
       - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${RESOURCE_SUFFIX}
-    substitutions:
-      RESOURCE_SUFFIX: _${COMMIT_SHA}
+
+substitutions:
+  RESOURCE_SUFFIX: _${COMMIT_SHA}
 
 options:
   logging: CLOUD_LOGGING_ONLY

From 97a080f6b10bafd715549a1c64f2f44d95914a07 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Tue, 27 Jun 2023 10:35:17 +0200
Subject: [PATCH 120/238] ADD underscore to RESOURCE_SUFFIX in e2e-tests.yaml

---
 cloudbuild/e2e-test.yaml | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 861a48d1..237784e5 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -24,7 +24,7 @@ steps:
       - |
         mkdir -p ${COMMIT_SHA}/assets && \
         cp -r pipelines/assets ${COMMIT_SHA} && \
-        gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${RESOURCE_SUFFIX}
+        gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${_RESOURCE_SUFFIX}
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
@@ -44,11 +44,11 @@ steps:
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
-      - RESOURCE_SUFFIX=${RESOURCE_SUFFIX}
-      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${RESOURCE_SUFFIX}
+      - RESOURCE_SUFFIX=${_RESOURCE_SUFFIX}
+      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${_RESOURCE_SUFFIX}
 
 substitutions:
-  RESOURCE_SUFFIX: _${COMMIT_SHA}
+  _RESOURCE_SUFFIX: _${COMMIT_SHA}
 
 options:
   logging: CLOUD_LOGGING_ONLY

From e9d410b608bea329827c5ff1ecd07ca530581307 Mon Sep 17 00:00:00 2001
From: rachel-datatonic <rachel.le@datatonic.com>
Date: Tue, 27 Jun 2023 10:17:58 +0100
Subject: [PATCH 121/238] remove log in sandbox_run to avoid duplicated log

---
 pipelines/src/pipelines/trigger/main.py | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/pipelines/src/pipelines/trigger/main.py b/pipelines/src/pipelines/trigger/main.py
index 491361e2..fc8263fc 100644
--- a/pipelines/src/pipelines/trigger/main.py
+++ b/pipelines/src/pipelines/trigger/main.py
@@ -15,7 +15,6 @@
 import argparse
 import base64
 import json
-import logging
 import os
 import distutils.util
 from typing import Optional, List
@@ -191,10 +190,6 @@ def sandbox_run(args: List[str] = None) -> aiplatform.PipelineJob:
     Returns the PipelineJob object of the triggered pipeline run.
     Usage: python main.py --template_path=pipeline.json --enable_caching=true
     """
-    logger = logging.getLogger(__name__)
-    logger.setLevel(logging.DEBUG)
-    logger.debug("This is a debug message")
-
     parser = argparse.ArgumentParser()
     parser.add_argument(
         "--template_path", help="Path to the compiled pipeline (JSON)", type=str

From 600e3e9c6d3118064d35f3a7c6f456508c4424b3 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Tue, 27 Jun 2023 11:22:35 +0200
Subject: [PATCH 122/238] Simplify solution by giving  RESOURCE_SUFFIX a
 default value

---
 Makefile                 | 8 --------
 cloudbuild/e2e-test.yaml | 9 +++------
 env.sh.example           | 6 +++---
 3 files changed, 6 insertions(+), 17 deletions(-)

diff --git a/Makefile b/Makefile
index c7cff312..2ce9ca3b 100644
--- a/Makefile
+++ b/Makefile
@@ -15,14 +15,6 @@
 -include env.sh
 export
 
-# Check if RESOURCE_SUFFIX is empty
-ifeq ($(strip $(RESOURCE_SUFFIX)),)
-  PIPELINE_FILES_GCS_PATH := gs://${VERTEX_PROJECT_ID}-pl-assets
-else
-  PIPELINE_FILES_GCS_PATH := gs://${VERTEX_PROJECT_ID}-pl-assets/$(RESOURCE_SUFFIX)
-endif
-
-export PIPELINE_FILES_GCS_PATH
 
 help: ## Display this help screen
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 237784e5..431bd515 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -24,7 +24,7 @@ steps:
       - |
         mkdir -p ${COMMIT_SHA}/assets && \
         cp -r pipelines/assets ${COMMIT_SHA} && \
-        gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${_RESOURCE_SUFFIX}
+        gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
@@ -44,11 +44,8 @@ steps:
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
-      - RESOURCE_SUFFIX=${_RESOURCE_SUFFIX}
-      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${_RESOURCE_SUFFIX}
-
-substitutions:
-  _RESOURCE_SUFFIX: _${COMMIT_SHA}
+      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
+      - RESOURCE_SUFFIX=_${COMMIT_SHA}
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/env.sh.example b/env.sh.example
index bd838c01..9041c783 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -21,10 +21,10 @@ export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
 
-# Suffix (e.g. '_<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Populate if working in a team to avoid overwriting resources during development 
-export RESOURCE_SUFFIX=
+# Suffix (e.g. '_<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development 
+export RESOURCE_SUFFIX=_default
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets
+export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/${RESOURCE_SUFFIX}
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root

From 25a39906cef57f2ca6c1c672e8746bae66f5d8c3 Mon Sep 17 00:00:00 2001
From: jan-zajac-dt <jan.zajac@datatonic.com>
Date: Tue, 27 Jun 2023 14:42:49 +0200
Subject: [PATCH 123/238] remove underscore from suffix in env.sh.example and
 adjust pipelines to add it for BigQuery tables

---
 cloudbuild/e2e-test.yaml                                | 2 +-
 env.sh.example                                          | 4 ++--
 pipelines/src/pipelines/tensorflow/training/pipeline.py | 2 +-
 pipelines/src/pipelines/xgboost/training/pipeline.py    | 2 +-
 4 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 431bd515..b71430d2 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -45,7 +45,7 @@ steps:
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
       - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
-      - RESOURCE_SUFFIX=_${COMMIT_SHA}
+      - RESOURCE_SUFFIX=${COMMIT_SHA}
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/env.sh.example b/env.sh.example
index 9041c783..3e747dfe 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -21,8 +21,8 @@ export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
 
-# Suffix (e.g. '_<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development 
-export RESOURCE_SUFFIX=_default
+# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development 
+export RESOURCE_SUFFIX=default
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index f4474fb8..371928f5 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -75,7 +75,7 @@ def tensorflow_pipeline(
     label_column_name = "total_fare"
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_tf_training" + str(resource_suffix)  # suffix to table names
+    table_suffix = f"_tf_training_{resource_suffix}"  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     preprocessed_table = "preprocessed_data" + table_suffix
     train_table = "train_data" + table_suffix
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index e0e041a7..7db36231 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -74,7 +74,7 @@ def xgboost_pipeline(
     label_column_name = "total_fare"
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_xgb_training" + str(resource_suffix)  # suffix to table names
+    table_suffix = f"_xgb_training_{resource_suffix}"  # suffix to table names
     ingested_table = "ingested_data" + table_suffix
     preprocessed_table = "preprocessed_data" + table_suffix
     train_table = "train_data" + table_suffix

From a981b7329e715b301a2d38ce50d9ffb3430cfcaf Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 10 Jul 2023 21:21:25 +0100
Subject: [PATCH 124/238] feat: upgrade to KFP V2

---
 components/bigquery-components/poetry.lock    | 555 +---------------
 components/bigquery-components/pyproject.toml |   2 +-
 .../extract_bq_to_dataset.py                  |   2 +-
 .../tests/test_extract_bq_to_dataset.py       |   2 +-
 components/vertex-components/poetry.lock      | 602 +----------------
 components/vertex-components/pyproject.toml   |   4 +-
 .../src/vertex_components/custom_train_job.py |   2 +-
 .../import_model_evaluation.py                |   2 +-
 .../src/vertex_components/lookup_model.py     |   2 +-
 .../vertex_components/model_batch_predict.py  |   2 +-
 .../vertex_components/update_best_model.py    |   2 +-
 .../tests/test_custom_training_job.py         |   2 +-
 .../tests/test_import_model_evaluation.py     |   2 +-
 .../tests/test_lookup_model.py                |   2 +-
 .../tests/test_model_batch_predict.py         |   2 +-
 .../tests/test_update_best_model.py           |   2 +-
 pipelines/poetry.lock                         | 619 +-----------------
 pipelines/pyproject.toml                      |   3 +-
 .../tensorflow/prediction/pipeline.py         |   2 +-
 .../pipelines/tensorflow/training/pipeline.py |   2 +-
 .../pipelines/xgboost/prediction/pipeline.py  |   2 +-
 .../pipelines/xgboost/training/pipeline.py    |   2 +-
 pipelines/tests/e2e/test_e2e.py               |   2 +-
 23 files changed, 113 insertions(+), 1706 deletions(-)

diff --git a/components/bigquery-components/poetry.lock b/components/bigquery-components/poetry.lock
index 8f0f3273..7fa1ecb4 100644
--- a/components/bigquery-components/poetry.lock
+++ b/components/bigquery-components/poetry.lock
@@ -1,44 +1,9 @@
-# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
-
-[[package]]
-name = "absl-py"
-version = "1.4.0"
-description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "absl-py-1.4.0.tar.gz", hash = "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"},
-    {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"},
-]
-
-[[package]]
-name = "attrs"
-version = "23.1.0"
-description = "Classes Without Boilerplate"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
-    {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
-]
-
-[package.dependencies]
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
-
-[package.extras]
-cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
-tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
 
 [[package]]
 name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -50,7 +15,6 @@ files = [
 name = "certifi"
 version = "2023.5.7"
 description = "Python package for providing Mozilla's CA Bundle."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -62,7 +26,6 @@ files = [
 name = "charset-normalizer"
 version = "3.1.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -147,7 +110,6 @@ files = [
 name = "click"
 version = "8.1.3"
 description = "Composable command line interface toolkit"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -159,23 +121,10 @@ files = [
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
-[[package]]
-name = "cloudpickle"
-version = "2.2.1"
-description = "Extended pickling support for Python objects"
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "cloudpickle-2.2.1-py3-none-any.whl", hash = "sha256:61f594d1f4c295fa5cd9014ceb3a1fc4a70b0de1164b94fbc2d854ccba056f9f"},
-    {file = "cloudpickle-2.2.1.tar.gz", hash = "sha256:d89684b8de9e34a2a43b3460fbca07d09d6e25ce858df4d5a44240403b6178f5"},
-]
-
 [[package]]
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -183,29 +132,10 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
-[[package]]
-name = "deprecated"
-version = "1.2.14"
-description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
-    {file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
-    {file = "Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3"},
-]
-
-[package.dependencies]
-wrapt = ">=1.10,<2"
-
-[package.extras]
-dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
-
 [[package]]
 name = "docstring-parser"
 version = "0.15"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
-category = "main"
 optional = false
 python-versions = ">=3.6,<4.0"
 files = [
@@ -217,7 +147,6 @@ files = [
 name = "exceptiongroup"
 version = "1.1.1"
 description = "Backport of PEP 654 (exception groups)"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -228,26 +157,10 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
-[[package]]
-name = "fire"
-version = "0.5.0"
-description = "A library for automatically generating command line interfaces."
-category = "main"
-optional = false
-python-versions = "*"
-files = [
-    {file = "fire-0.5.0.tar.gz", hash = "sha256:a6b0d49e98c8963910021f92bba66f65ab440da2982b78eb1bbf95a0a34aacc6"},
-]
-
-[package.dependencies]
-six = "*"
-termcolor = "*"
-
 [[package]]
 name = "google-api-core"
 version = "2.11.0"
 description = "Google API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -268,31 +181,10 @@ grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status
 grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
 grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
 
-[[package]]
-name = "google-api-python-client"
-version = "1.12.11"
-description = "Google API Client Library for Python"
-category = "main"
-optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*"
-files = [
-    {file = "google-api-python-client-1.12.11.tar.gz", hash = "sha256:1b4bd42a46321e13c0542a9e4d96fa05d73626f07b39f83a73a947d70ca706a9"},
-    {file = "google_api_python_client-1.12.11-py2.py3-none-any.whl", hash = "sha256:7e0a1a265c8d3088ee1987778c72683fcb376e32bada8d7767162bd9c503fd9b"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.21.0,<3dev", markers = "python_version >= \"3\""}
-google-auth = {version = ">=1.16.0,<3dev", markers = "python_version >= \"3\""}
-google-auth-httplib2 = ">=0.0.3"
-httplib2 = ">=0.15.0,<1dev"
-six = ">=1.13.0,<2dev"
-uritemplate = ">=3.0.0,<4dev"
-
 [[package]]
 name = "google-auth"
 version = "2.19.0"
 description = "Google Authentication Library"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -314,28 +206,10 @@ pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0dev)"]
 
-[[package]]
-name = "google-auth-httplib2"
-version = "0.1.0"
-description = "Google Authentication Library: httplib2 transport"
-category = "main"
-optional = false
-python-versions = "*"
-files = [
-    {file = "google-auth-httplib2-0.1.0.tar.gz", hash = "sha256:a07c39fd632becacd3f07718dfd6021bf396978f03ad3ce4321d060015cc30ac"},
-    {file = "google_auth_httplib2-0.1.0-py2.py3-none-any.whl", hash = "sha256:31e49c36c6b5643b57e82617cb3e021e3e1d2df9da63af67252c02fa9c1f4a10"},
-]
-
-[package.dependencies]
-google-auth = "*"
-httplib2 = ">=0.15.0"
-six = "*"
-
 [[package]]
 name = "google-cloud-bigquery"
 version = "2.30.0"
 description = "Google BigQuery API client library"
-category = "dev"
 optional = false
 python-versions = ">=3.6, <3.11"
 files = [
@@ -367,7 +241,6 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 name = "google-cloud-core"
 version = "2.3.2"
 description = "Google Cloud API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -376,7 +249,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.6,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
@@ -386,7 +259,6 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 name = "google-cloud-storage"
 version = "2.9.0"
 description = "Google Cloud Storage API client library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -395,7 +267,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 google-cloud-core = ">=2.3.0,<3.0dev"
 google-resumable-media = ">=2.3.2"
@@ -408,7 +280,6 @@ protobuf = ["protobuf (<5.0.0dev)"]
 name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -489,7 +360,6 @@ testing = ["pytest"]
 name = "google-resumable-media"
 version = "2.5.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
-category = "main"
 optional = false
 python-versions = ">= 3.7"
 files = [
@@ -508,7 +378,6 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 name = "googleapis-common-protos"
 version = "1.59.0"
 description = "Common protobufs used in Google APIs"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -526,7 +395,6 @@ grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
 name = "grpcio"
 version = "1.54.2"
 description = "HTTP/2-based RPC framework"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -584,7 +452,6 @@ protobuf = ["grpcio-tools (>=1.54.2)"]
 name = "grpcio-status"
 version = "1.48.2"
 description = "Status proto mapping for gRPC"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -597,26 +464,10 @@ googleapis-common-protos = ">=1.5.5"
 grpcio = ">=1.48.2"
 protobuf = ">=3.12.0"
 
-[[package]]
-name = "httplib2"
-version = "0.22.0"
-description = "A comprehensive HTTP client library."
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
-    {file = "httplib2-0.22.0-py3-none-any.whl", hash = "sha256:14ae0a53c1ba8f3d37e9e27cf37eabb0fb9980f435ba405d546948b009dd64dc"},
-    {file = "httplib2-0.22.0.tar.gz", hash = "sha256:d7a10bc5ef5ab08322488bde8c726eeee5c8618723fdb399597ec58f3d82df81"},
-]
-
-[package.dependencies]
-pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""}
-
 [[package]]
 name = "idna"
 version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -628,7 +479,6 @@ files = [
 name = "importlib-metadata"
 version = "6.6.0"
 description = "Read metadata from Python packages"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -645,30 +495,10 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker
 perf = ["ipython"]
 testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
 
-[[package]]
-name = "importlib-resources"
-version = "5.12.0"
-description = "Read resources from Python packages"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
-    {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
-]
-
-[package.dependencies]
-zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
-
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -676,79 +506,44 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
-[[package]]
-name = "jsonschema"
-version = "4.17.3"
-description = "An implementation of JSON Schema validation for Python"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "jsonschema-4.17.3-py3-none-any.whl", hash = "sha256:a870ad254da1a8ca84b6a2905cac29d265f805acc57af304784962a2aa6508f6"},
-    {file = "jsonschema-4.17.3.tar.gz", hash = "sha256:0f864437ab8b6076ba6707453ef8f98a6a0d512a80e93f8abdb676f737ecb60d"},
-]
-
-[package.dependencies]
-attrs = ">=17.4.0"
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
-importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
-pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
-pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
-typing-extensions = {version = "*", markers = "python_version < \"3.8\""}
-
-[package.extras]
-format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
-format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"]
-
 [[package]]
 name = "kfp"
-version = "1.8.21"
-description = "KubeFlow Pipelines SDK"
-category = "main"
+version = "2.0.1"
+description = "Kubeflow Pipelines SDK"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "kfp-1.8.21.tar.gz", hash = "sha256:038d77ec9145ccfade95ab3b4b53c32668ae498fede06647ed0425d093819b1c"},
+    {file = "kfp-2.0.1.tar.gz", hash = "sha256:4a65811778c3a45892d8d11c0f95ba5e410476157ed63cacb1dd82316f60cd4d"},
 ]
 
 [package.dependencies]
-absl-py = ">=0.9,<2"
-click = ">=7.1.2,<9"
-cloudpickle = ">=2.0.0,<3"
-Deprecated = ">=1.2.7,<2"
+click = ">=8.0.0,<9"
 docstring-parser = ">=0.7.3,<1"
-fire = ">=0.3.1,<1"
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
-google-api-python-client = ">=1.7.8,<2"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.6.1,<3"
-google-cloud-storage = ">=1.20.0,<3"
-jsonschema = ">=3.0.1,<5"
-kfp-pipeline-spec = ">=0.1.16,<0.2.0"
-kfp-server-api = ">=1.1.2,<2.0.0"
-kubernetes = ">=8.0.0,<26"
+google-cloud-storage = ">=2.2.1,<3"
+kfp-pipeline-spec = "0.2.2"
+kfp-server-api = ">=2.0.0,<2.1.0"
+kubernetes = ">=8.0.0,<27"
 protobuf = ">=3.13.0,<4"
-pydantic = ">=1.8.2,<2"
-PyYAML = ">=5.3,<6"
+PyYAML = ">=5.3,<7"
 requests-toolbelt = ">=0.8.0,<1"
-strip-hints = ">=0.1.8,<1"
 tabulate = ">=0.8.6,<1"
-typer = ">=0.3.2,<1.0"
 typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
-uritemplate = ">=3.0.1,<4"
-urllib3 = "<2"
+urllib3 = "<2.0.0"
 
 [package.extras]
-all = ["docker"]
+all = ["docker", "kfp-kubernetes (<2)"]
+kubernetes = ["kfp-kubernetes (<2)"]
 
 [[package]]
 name = "kfp-pipeline-spec"
-version = "0.1.16"
+version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
-    {file = "kfp_pipeline_spec-0.1.16-py3-none-any.whl", hash = "sha256:4cefae00ac50145cf862127202a8b8a783ed7504c773d7d7c517bd115283be25"},
+    {file = "kfp_pipeline_spec-0.2.2-py3-none-any.whl", hash = "sha256:e83b58ffed3f7ca154d62ab20e14dc9a1a3c9dad589e856dd2b421e226f3b8d0"},
 ]
 
 [package.dependencies]
@@ -756,13 +551,12 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "1.8.5"
+version = "2.0.0"
 description = "Kubeflow Pipelines API"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "kfp-server-api-1.8.5.tar.gz", hash = "sha256:482d71765ba57c003164dbb980a8cb1a18d234b578d064dc88dbeb3e4c7ab6de"},
+    {file = "kfp-server-api-2.0.0.tar.gz", hash = "sha256:c0462045244a69211bc82a8d6af6602ae8b4f716ee0ac0be5dc34b7ea76c7bd1"},
 ]
 
 [package.dependencies]
@@ -775,7 +569,6 @@ urllib3 = ">=1.15"
 name = "kubernetes"
 version = "25.3.0"
 description = "Kubernetes python client"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -793,7 +586,7 @@ requests-oauthlib = "*"
 setuptools = ">=21.0.0"
 six = ">=1.9.0"
 urllib3 = ">=1.24.2"
-websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.0 || >=0.43.0"
+websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
 
 [package.extras]
 adal = ["adal (>=1.0.2)"]
@@ -802,7 +595,6 @@ adal = ["adal (>=1.0.2)"]
 name = "oauthlib"
 version = "3.2.2"
 description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -819,7 +611,6 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -827,23 +618,10 @@ files = [
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
 ]
 
-[[package]]
-name = "pkgutil-resolve-name"
-version = "1.3.10"
-description = "Resolve a name to an object."
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "pkgutil_resolve_name-1.3.10-py3-none-any.whl", hash = "sha256:ca27cc078d25c5ad71a9de0a7a330146c4e014c2462d9af19c6b828280649c5e"},
-    {file = "pkgutil_resolve_name-1.3.10.tar.gz", hash = "sha256:357d6c9e6a755653cfd78893817c0853af365dd51ec97f3d358a819373bbd174"},
-]
-
 [[package]]
 name = "pluggy"
 version = "1.0.0"
 description = "plugin and hook calling mechanisms for python"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -862,7 +640,6 @@ testing = ["pytest", "pytest-benchmark"]
 name = "proto-plus"
 version = "1.22.2"
 description = "Beautiful, Pythonic protocol buffers."
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -880,7 +657,6 @@ testing = ["google-api-core[grpc] (>=1.31.5)"]
 name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -912,7 +688,6 @@ files = [
 name = "pyasn1"
 version = "0.5.0"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -924,7 +699,6 @@ files = [
 name = "pyasn1-modules"
 version = "0.3.0"
 description = "A collection of ASN.1-based protocols modules"
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -935,116 +709,10 @@ files = [
 [package.dependencies]
 pyasn1 = ">=0.4.6,<0.6.0"
 
-[[package]]
-name = "pydantic"
-version = "1.10.8"
-description = "Data validation and settings management using python type hints"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "pydantic-1.10.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1243d28e9b05003a89d72e7915fdb26ffd1d39bdd39b00b7dbe4afae4b557f9d"},
-    {file = "pydantic-1.10.8-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c0ab53b609c11dfc0c060d94335993cc2b95b2150e25583bec37a49b2d6c6c3f"},
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 python-versions = ">=3.7"
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@@ -1068,7 +736,6 @@ testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "no
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@@ -1083,7 +750,6 @@ six = ">=1.5"
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@@ -1122,7 +788,6 @@ files = [
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 python-versions = ">=3.7"
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@@ -1144,7 +809,6 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
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@@ -1308,23 +914,10 @@ files = [
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 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
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@@ -1341,7 +934,6 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
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@@ -1354,111 +946,10 @@ docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
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-]
-
 [[package]]
 name = "zipp"
 version = "3.15.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1473,4 +964,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.7,<3.11"
-content-hash = "d7bc7cb1b7d234cc70d56b33a1253a6a52b0f6d9ab3114fd47ab47dbfcdadfa0"
+content-hash = "6f7ca2171a974f20e9e0c7d38859b0570337711f678f0fed05a9560ce299f0e0"
diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index ee3e0477..9d6cd0db 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -12,7 +12,7 @@ classifiers = [
 
 [tool.poetry.dependencies]
 python = ">=3.7,<3.11"
-kfp = "==1.8.21"
+kfp = "^2.0.1"
 
 [tool.poetry.group.dev.dependencies]
 google-cloud-bigquery = "2.30.0"
diff --git a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py b/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
index 3effe09a..4846e448 100644
--- a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
+++ b/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from kfp.v2.dsl import Dataset, Output, component
+from kfp.dsl import Dataset, Output, component
 
 
 @component(
diff --git a/components/bigquery-components/tests/test_extract_bq_to_dataset.py b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
index be3084e6..dec9f1eb 100644
--- a/components/bigquery-components/tests/test_extract_bq_to_dataset.py
+++ b/components/bigquery-components/tests/test_extract_bq_to_dataset.py
@@ -1,5 +1,5 @@
 import google.cloud.bigquery  # noqa
-from kfp.v2.dsl import Dataset
+from kfp.dsl import Dataset
 from unittest import mock
 
 import bigquery_components
diff --git a/components/vertex-components/poetry.lock b/components/vertex-components/poetry.lock
index ca09c083..c03e62bb 100644
--- a/components/vertex-components/poetry.lock
+++ b/components/vertex-components/poetry.lock
@@ -1,44 +1,9 @@
-# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
-
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-version = "1.4.0"
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-
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-description = "Classes Without Boilerplate"
-category = "main"
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-
-[package.dependencies]
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
-
-[package.extras]
-cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
-tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
 
 [[package]]
 name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -50,7 +15,6 @@ files = [
 name = "certifi"
 version = "2023.5.7"
 description = "Python package for providing Mozilla's CA Bundle."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -62,7 +26,6 @@ files = [
 name = "charset-normalizer"
 version = "3.1.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -147,7 +110,6 @@ files = [
 name = "click"
 version = "8.1.3"
 description = "Composable command line interface toolkit"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -159,23 +121,10 @@ files = [
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
-[[package]]
-name = "cloudpickle"
-version = "2.2.1"
-description = "Extended pickling support for Python objects"
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "cloudpickle-2.2.1-py3-none-any.whl", hash = "sha256:61f594d1f4c295fa5cd9014ceb3a1fc4a70b0de1164b94fbc2d854ccba056f9f"},
-    {file = "cloudpickle-2.2.1.tar.gz", hash = "sha256:d89684b8de9e34a2a43b3460fbca07d09d6e25ce858df4d5a44240403b6178f5"},
-]
-
 [[package]]
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -183,29 +132,10 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
-[[package]]
-name = "deprecated"
-version = "1.2.14"
-description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
-    {file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
-    {file = "Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3"},
-]
-
-[package.dependencies]
-wrapt = ">=1.10,<2"
-
-[package.extras]
-dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
-
 [[package]]
 name = "docstring-parser"
 version = "0.15"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
-category = "main"
 optional = false
 python-versions = ">=3.6,<4.0"
 files = [
@@ -217,7 +147,6 @@ files = [
 name = "exceptiongroup"
 version = "1.1.1"
 description = "Backport of PEP 654 (exception groups)"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -228,26 +157,10 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
-[[package]]
-name = "fire"
-version = "0.5.0"
-description = "A library for automatically generating command line interfaces."
-category = "main"
-optional = false
-python-versions = "*"
-files = [
-    {file = "fire-0.5.0.tar.gz", hash = "sha256:a6b0d49e98c8963910021f92bba66f65ab440da2982b78eb1bbf95a0a34aacc6"},
-]
-
-[package.dependencies]
-six = "*"
-termcolor = "*"
-
 [[package]]
 name = "google-api-core"
 version = "2.11.0"
 description = "Google API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -268,31 +181,10 @@ grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status
 grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
 grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
 
-[[package]]
-name = "google-api-python-client"
-version = "1.12.11"
-description = "Google API Client Library for Python"
-category = "main"
-optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*"
-files = [
-    {file = "google-api-python-client-1.12.11.tar.gz", hash = "sha256:1b4bd42a46321e13c0542a9e4d96fa05d73626f07b39f83a73a947d70ca706a9"},
-    {file = "google_api_python_client-1.12.11-py2.py3-none-any.whl", hash = "sha256:7e0a1a265c8d3088ee1987778c72683fcb376e32bada8d7767162bd9c503fd9b"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.21.0,<3dev", markers = "python_version >= \"3\""}
-google-auth = {version = ">=1.16.0,<3dev", markers = "python_version >= \"3\""}
-google-auth-httplib2 = ">=0.0.3"
-httplib2 = ">=0.15.0,<1dev"
-six = ">=1.13.0,<2dev"
-uritemplate = ">=3.0.0,<4dev"
-
 [[package]]
 name = "google-auth"
 version = "2.19.0"
 description = "Google Authentication Library"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -314,28 +206,10 @@ pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0dev)"]
 
-[[package]]
-name = "google-auth-httplib2"
-version = "0.1.0"
-description = "Google Authentication Library: httplib2 transport"
-category = "main"
-optional = false
-python-versions = "*"
-files = [
-    {file = "google-auth-httplib2-0.1.0.tar.gz", hash = "sha256:a07c39fd632becacd3f07718dfd6021bf396978f03ad3ce4321d060015cc30ac"},
-    {file = "google_auth_httplib2-0.1.0-py2.py3-none-any.whl", hash = "sha256:31e49c36c6b5643b57e82617cb3e021e3e1d2df9da63af67252c02fa9c1f4a10"},
-]
-
-[package.dependencies]
-google-auth = "*"
-httplib2 = ">=0.15.0"
-six = "*"
-
 [[package]]
 name = "google-cloud-aiplatform"
 version = "1.24.1"
 description = "Vertex AI API client library"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -344,7 +218,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.32.0,<2.0.0 || >=2.8.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.32.0,<2.0.dev0 || >=2.8.dev0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-bigquery = ">=1.15.0,<4.0.0dev"
 google-cloud-resource-manager = ">=1.3.3,<3.0.0dev"
 google-cloud-storage = ">=1.32.0,<3.0.0dev"
@@ -373,7 +247,6 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 name = "google-cloud-bigquery"
 version = "3.10.0"
 description = "Google BigQuery API client library"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -382,7 +255,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-core = ">=1.6.0,<3.0.0dev"
 google-resumable-media = ">=0.6.0,<3.0dev"
 grpcio = ">=1.47.0,<2.0dev"
@@ -406,7 +279,6 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 name = "google-cloud-core"
 version = "2.3.2"
 description = "Google Cloud API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -415,59 +287,35 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.6,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
 grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
-[[package]]
-name = "google-cloud-notebooks"
-version = "1.7.0"
-description = "Google Cloud Notebooks API client library"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "google-cloud-notebooks-1.7.0.tar.gz", hash = "sha256:dac73a5cd983a4344d1fa96f9a8e5849b0ff75d7a5fdde921023a2ef4566e75e"},
-    {file = "google_cloud_notebooks-1.7.0-py2.py3-none-any.whl", hash = "sha256:8fbffb7ba535fc02c61f135d8863324a5a2d20dd58cafaae592f0b0172d6bdab"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]}
-grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
-proto-plus = ">=1.22.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "1.0.42"
+version = "2.0.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
-category = "dev"
 optional = false
-python-versions = "*"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "google_cloud_pipeline_components-1.0.42-py3-none-any.whl", hash = "sha256:bf833f325d1b4a89f1db9627d3f3e75d1bffc7b7725d4eb739488a68808fa623"},
+    {file = "google_cloud_pipeline_components-2.0.0-py3-none-any.whl", hash = "sha256:4a3708dda8d68989f37d6b4e184e783ab3dc2ff8f0ddf69f5cd4a160603ce252"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.0 || >=2.8.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-cloud-aiplatform = ">=1.14.0,<2"
-google-cloud-notebooks = ">=0.4.0"
-google-cloud-storage = ">=2.2.1,<3"
-googleapis-common-protos = ">=1.56.2,<2.0dev"
-grpcio-status = "<=1.47.0"
-kfp = ">=1.8.9,<2.0.0"
-protobuf = ">=3.19.0,<4.0.0dev"
+kfp = ">=2.0.0b10,<3.0.0"
 
 [package.extras]
-tests = ["flake8 (>=3.0.0)", "google-api-core (>=1.31.5,<2.0.0 || >=2.8.0,<3.0.0dev)", "google-cloud-aiplatform (>=1.14.0,<2)", "google-cloud-notebooks (>=0.4.0)", "google-cloud-storage (>=2.2.1,<3)", "googleapis-common-protos (>=1.56.2,<2.0dev)", "grpcio-status (<=1.47.0)", "kfp (>=1.8.9,<2.0.0)", "mock (>=4.0.0)", "protobuf (>=3.19.0,<4.0.0dev)", "pytest (>=6.0.0)"]
+docs = ["autodocsumm (==0.2.9)", "grpcio-status (<=1.47.0)", "m2r2 (==0.3.2)", "protobuf (>=3.19.0,<4.0.0dev)", "sphinx (==5.0.2)", "sphinx-immaterial (==0.9.0)", "sphinx-notfound-page (==0.8.3)", "sphinx-rtd-theme (==1.0.0)"]
+tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
 version = "1.10.1"
 description = "Google Cloud Resource Manager API client library"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -476,7 +324,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
 proto-plus = ">=1.22.0,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
@@ -485,7 +333,6 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 name = "google-cloud-storage"
 version = "2.9.0"
 description = "Google Cloud Storage API client library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -494,7 +341,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 google-cloud-core = ">=2.3.0,<3.0dev"
 google-resumable-media = ">=2.3.2"
@@ -507,7 +354,6 @@ protobuf = ["protobuf (<5.0.0dev)"]
 name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -588,7 +434,6 @@ testing = ["pytest"]
 name = "google-resumable-media"
 version = "2.5.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
-category = "main"
 optional = false
 python-versions = ">= 3.7"
 files = [
@@ -607,7 +452,6 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 name = "googleapis-common-protos"
 version = "1.59.0"
 description = "Common protobufs used in Google APIs"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -626,7 +470,6 @@ grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
 name = "grpc-google-iam-v1"
 version = "0.12.6"
 description = "IAM API client library"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -643,7 +486,6 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 name = "grpcio"
 version = "1.54.2"
 description = "HTTP/2-based RPC framework"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -701,7 +543,6 @@ protobuf = ["grpcio-tools (>=1.54.2)"]
 name = "grpcio-status"
 version = "1.47.0"
 description = "Status proto mapping for gRPC"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -714,26 +555,10 @@ googleapis-common-protos = ">=1.5.5"
 grpcio = ">=1.47.0"
 protobuf = ">=3.12.0"
 
-[[package]]
-name = "httplib2"
-version = "0.22.0"
-description = "A comprehensive HTTP client library."
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
-    {file = "httplib2-0.22.0-py3-none-any.whl", hash = "sha256:14ae0a53c1ba8f3d37e9e27cf37eabb0fb9980f435ba405d546948b009dd64dc"},
-    {file = "httplib2-0.22.0.tar.gz", hash = "sha256:d7a10bc5ef5ab08322488bde8c726eeee5c8618723fdb399597ec58f3d82df81"},
-]
-
-[package.dependencies]
-pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""}
-
 [[package]]
 name = "idna"
 version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -745,7 +570,6 @@ files = [
 name = "importlib-metadata"
 version = "6.6.0"
 description = "Read metadata from Python packages"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -762,30 +586,10 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker
 perf = ["ipython"]
 testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
 
-[[package]]
-name = "importlib-resources"
-version = "5.12.0"
-description = "Read resources from Python packages"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
-    {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
-]
-
-[package.dependencies]
-zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
-
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -793,79 +597,44 @@ files = [
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
 ]
 
-[[package]]
-name = "jsonschema"
-version = "4.17.3"
-description = "An implementation of JSON Schema validation for Python"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "jsonschema-4.17.3-py3-none-any.whl", hash = "sha256:a870ad254da1a8ca84b6a2905cac29d265f805acc57af304784962a2aa6508f6"},
-    {file = "jsonschema-4.17.3.tar.gz", hash = "sha256:0f864437ab8b6076ba6707453ef8f98a6a0d512a80e93f8abdb676f737ecb60d"},
-]
-
-[package.dependencies]
-attrs = ">=17.4.0"
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
-importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
-pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
-pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
-typing-extensions = {version = "*", markers = "python_version < \"3.8\""}
-
-[package.extras]
-format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
-format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"]
-
 [[package]]
 name = "kfp"
-version = "1.8.21"
-description = "KubeFlow Pipelines SDK"
-category = "main"
+version = "2.0.1"
+description = "Kubeflow Pipelines SDK"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
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-click = ">=7.1.2,<9"
-cloudpickle = ">=2.0.0,<3"
-Deprecated = ">=1.2.7,<2"
+click = ">=8.0.0,<9"
 docstring-parser = ">=0.7.3,<1"
-fire = ">=0.3.1,<1"
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
-google-api-python-client = ">=1.7.8,<2"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.6.1,<3"
-google-cloud-storage = ">=1.20.0,<3"
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-kfp-server-api = ">=1.1.2,<2.0.0"
-kubernetes = ">=8.0.0,<26"
+google-cloud-storage = ">=2.2.1,<3"
+kfp-pipeline-spec = "0.2.2"
+kfp-server-api = ">=2.0.0,<2.1.0"
+kubernetes = ">=8.0.0,<27"
 protobuf = ">=3.13.0,<4"
-pydantic = ">=1.8.2,<2"
-PyYAML = ">=5.3,<6"
+PyYAML = ">=5.3,<7"
 requests-toolbelt = ">=0.8.0,<1"
-strip-hints = ">=0.1.8,<1"
 tabulate = ">=0.8.6,<1"
-typer = ">=0.3.2,<1.0"
 typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
-uritemplate = ">=3.0.1,<4"
-urllib3 = "<2"
+urllib3 = "<2.0.0"
 
 [package.extras]
-all = ["docker"]
+all = ["docker", "kfp-kubernetes (<2)"]
+kubernetes = ["kfp-kubernetes (<2)"]
 
 [[package]]
 name = "kfp-pipeline-spec"
-version = "0.1.16"
+version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -873,13 +642,12 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "1.8.5"
+version = "2.0.0"
 description = "Kubeflow Pipelines API"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
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+    {file = "kfp-server-api-2.0.0.tar.gz", hash = "sha256:c0462045244a69211bc82a8d6af6602ae8b4f716ee0ac0be5dc34b7ea76c7bd1"},
 ]
 
 [package.dependencies]
@@ -892,7 +660,6 @@ urllib3 = ">=1.15"
 name = "kubernetes"
 version = "25.3.0"
 description = "Kubernetes python client"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -910,7 +677,7 @@ requests-oauthlib = "*"
 setuptools = ">=21.0.0"
 six = ">=1.9.0"
 urllib3 = ">=1.24.2"
-websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.0 || >=0.43.0"
+websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
 
 [package.extras]
 adal = ["adal (>=1.0.2)"]
@@ -919,7 +686,6 @@ adal = ["adal (>=1.0.2)"]
 name = "oauthlib"
 version = "3.2.2"
 description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -936,7 +702,6 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -944,23 +709,10 @@ files = [
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 ]
 
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-category = "main"
-optional = false
-python-versions = ">=3.6"
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-
 [[package]]
 name = "pluggy"
 version = "1.0.0"
 description = "plugin and hook calling mechanisms for python"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -979,7 +731,6 @@ testing = ["pytest", "pytest-benchmark"]
 name = "proto-plus"
 version = "1.22.2"
 description = "Beautiful, Pythonic protocol buffers."
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -997,7 +748,6 @@ testing = ["google-api-core[grpc] (>=1.31.5)"]
 name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1029,7 +779,6 @@ files = [
 name = "pyasn1"
 version = "0.5.0"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -1041,7 +790,6 @@ files = [
 name = "pyasn1-modules"
 version = "0.3.0"
 description = "A collection of ASN.1-based protocols modules"
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -1052,116 +800,10 @@ files = [
 [package.dependencies]
 pyasn1 = ">=0.4.6,<0.6.0"
 
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 optional = false
 python-versions = ">=3.7"
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@@ -1185,7 +827,6 @@ testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "no
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@@ -1200,7 +841,6 @@ six = ">=1.5"
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 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
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@@ -1239,7 +879,6 @@ files = [
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 description = "Python HTTP for Humans."
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 optional = false
 python-versions = ">=3.7"
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@@ -1261,7 +900,6 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
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@@ -1310,7 +946,6 @@ pyasn1 = ">=0.1.3"
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@@ -1327,7 +962,6 @@ testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (
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@@ -1528,111 +1093,10 @@ docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
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-    {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
-]
-
 [[package]]
 name = "zipp"
 version = "3.15.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1647,4 +1111,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.7,<3.11"
-content-hash = "9ab64756b47c22efb2437659a3a7b8ca9a5b5c019f86217a03bdfbfb620d83ee"
+content-hash = "60358af42655b9cff7889a1d3d0fbcf4ca40982c4dd4d29784544c511a63cb96"
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index f608436f..9e628dc1 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -12,12 +12,12 @@ classifiers = [
 
 [tool.poetry.dependencies]
 python = ">=3.7,<3.11"
-kfp = "==1.8.21"
+kfp = ">=2.0.1,<3.0.0"
 
 [tool.poetry.group.dev.dependencies]
 google-cloud-aiplatform = "1.24.1"
-google-cloud-pipeline-components = "1.0.42"
 pytest = ">=7.3.1,<8.0.0"
+google-cloud-pipeline-components = "^2.0.0"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
diff --git a/components/vertex-components/src/vertex_components/custom_train_job.py b/components/vertex-components/src/vertex_components/custom_train_job.py
index 9cc51b17..8e2f220a 100644
--- a/components/vertex-components/src/vertex_components/custom_train_job.py
+++ b/components/vertex-components/src/vertex_components/custom_train_job.py
@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from kfp.v2.dsl import Input, component, Metrics, Output, Artifact, Dataset
+from kfp.dsl import Input, component, Metrics, Output, Artifact, Dataset
 
 
 @component(
diff --git a/components/vertex-components/src/vertex_components/import_model_evaluation.py b/components/vertex-components/src/vertex_components/import_model_evaluation.py
index b7a2913e..acfec517 100644
--- a/components/vertex-components/src/vertex_components/import_model_evaluation.py
+++ b/components/vertex-components/src/vertex_components/import_model_evaluation.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from kfp.v2.dsl import Input, Model, Metrics, component, Dataset
+from kfp.dsl import Input, Model, Metrics, component, Dataset
 from typing import NamedTuple
 
 
diff --git a/components/vertex-components/src/vertex_components/lookup_model.py b/components/vertex-components/src/vertex_components/lookup_model.py
index c235b373..a4d6f3db 100644
--- a/components/vertex-components/src/vertex_components/lookup_model.py
+++ b/components/vertex-components/src/vertex_components/lookup_model.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from kfp.v2.dsl import component, Output, Model
+from kfp.dsl import component, Output, Model
 from typing import NamedTuple
 
 
diff --git a/components/vertex-components/src/vertex_components/model_batch_predict.py b/components/vertex-components/src/vertex_components/model_batch_predict.py
index 849ebd28..36916ec4 100644
--- a/components/vertex-components/src/vertex_components/model_batch_predict.py
+++ b/components/vertex-components/src/vertex_components/model_batch_predict.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from kfp.v2.dsl import Input, Model, component
+from kfp.dsl import Input, Model, component
 from typing import List, NamedTuple
 
 
diff --git a/components/vertex-components/src/vertex_components/update_best_model.py b/components/vertex-components/src/vertex_components/update_best_model.py
index eeb45461..9ec4ff9b 100644
--- a/components/vertex-components/src/vertex_components/update_best_model.py
+++ b/components/vertex-components/src/vertex_components/update_best_model.py
@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from kfp.v2.dsl import Input, Model, component
+from kfp.dsl import Input, Model, component
 
 
 @component(
diff --git a/components/vertex-components/tests/test_custom_training_job.py b/components/vertex-components/tests/test_custom_training_job.py
index ac7675c4..3cd43b6e 100644
--- a/components/vertex-components/tests/test_custom_training_job.py
+++ b/components/vertex-components/tests/test_custom_training_job.py
@@ -1,5 +1,5 @@
 import google.cloud.aiplatform as aip  # noqa
-from kfp.v2.dsl import Dataset, Metrics, Artifact
+from kfp.dsl import Dataset, Metrics, Artifact
 from unittest import mock
 import pytest
 import json
diff --git a/components/vertex-components/tests/test_import_model_evaluation.py b/components/vertex-components/tests/test_import_model_evaluation.py
index 56cdf8bd..cfe8c5ab 100644
--- a/components/vertex-components/tests/test_import_model_evaluation.py
+++ b/components/vertex-components/tests/test_import_model_evaluation.py
@@ -1,5 +1,5 @@
 from unittest import mock
-from kfp.v2.dsl import Model, Metrics, Dataset
+from kfp.dsl import Model, Metrics, Dataset
 
 import vertex_components
 from google.cloud.aiplatform_v1 import ModelEvaluation
diff --git a/components/vertex-components/tests/test_lookup_model.py b/components/vertex-components/tests/test_lookup_model.py
index 6950dd1b..a869f7cd 100644
--- a/components/vertex-components/tests/test_lookup_model.py
+++ b/components/vertex-components/tests/test_lookup_model.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import google.cloud.aiplatform  # noqa
-from kfp.v2.dsl import Model
+from kfp.dsl import Model
 from unittest import mock
 import pytest
 
diff --git a/components/vertex-components/tests/test_model_batch_predict.py b/components/vertex-components/tests/test_model_batch_predict.py
index 76bca67d..8131794d 100644
--- a/components/vertex-components/tests/test_model_batch_predict.py
+++ b/components/vertex-components/tests/test_model_batch_predict.py
@@ -14,7 +14,7 @@
 import json
 import pytest
 from unittest import mock
-from kfp.v2.dsl import Model
+from kfp.dsl import Model
 from google.cloud.aiplatform_v1beta1.types.job_state import JobState
 
 
diff --git a/components/vertex-components/tests/test_update_best_model.py b/components/vertex-components/tests/test_update_best_model.py
index 4ef6ba21..481cd605 100644
--- a/components/vertex-components/tests/test_update_best_model.py
+++ b/components/vertex-components/tests/test_update_best_model.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 from unittest import mock
 
-from kfp.v2.dsl import Model
+from kfp.dsl import Model
 
 
 import vertex_components
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index e8388b8a..5fc4247c 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -1,51 +1,16 @@
-# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
-
-[[package]]
-name = "absl-py"
-version = "1.4.0"
-description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "absl-py-1.4.0.tar.gz", hash = "sha256:d2c244d01048ba476e7c080bd2c6df5e141d211de80223460d5b3b8a2a58433d"},
-    {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"},
-]
-
-[[package]]
-name = "attrs"
-version = "23.1.0"
-description = "Classes Without Boilerplate"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
-    {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
-]
-
-[package.dependencies]
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
-
-[package.extras]
-cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
-tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
 
 [[package]]
 name = "bigquery-components"
 version = "0.1.0"
 description = "KubeFlow components for BigQuery"
-category = "main"
 optional = false
 python-versions = ">=3.7,<3.11"
 files = []
 develop = true
 
 [package.dependencies]
-kfp = "==1.8.21"
+kfp = "^2.0.1"
 
 [package.source]
 type = "directory"
@@ -55,7 +20,6 @@ url = "../components/bigquery-components"
 name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -67,7 +31,6 @@ files = [
 name = "certifi"
 version = "2023.5.7"
 description = "Python package for providing Mozilla's CA Bundle."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -79,7 +42,6 @@ files = [
 name = "cfgv"
 version = "3.3.1"
 description = "Validate configuration and produce human readable error messages."
-category = "dev"
 optional = false
 python-versions = ">=3.6.1"
 files = [
@@ -91,7 +53,6 @@ files = [
 name = "charset-normalizer"
 version = "3.1.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -176,7 +137,6 @@ files = [
 name = "click"
 version = "8.1.3"
 description = "Composable command line interface toolkit"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -188,23 +148,10 @@ files = [
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
 importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
-[[package]]
-name = "cloudpickle"
-version = "2.2.1"
-description = "Extended pickling support for Python objects"
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "cloudpickle-2.2.1-py3-none-any.whl", hash = "sha256:61f594d1f4c295fa5cd9014ceb3a1fc4a70b0de1164b94fbc2d854ccba056f9f"},
-    {file = "cloudpickle-2.2.1.tar.gz", hash = "sha256:d89684b8de9e34a2a43b3460fbca07d09d6e25ce858df4d5a44240403b6178f5"},
-]
-
 [[package]]
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -216,7 +163,6 @@ files = [
 name = "coverage"
 version = "7.2.5"
 description = "Code coverage measurement for Python"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -276,29 +222,10 @@ files = [
 [package.extras]
 toml = ["tomli"]
 
-[[package]]
-name = "deprecated"
-version = "1.2.14"
-description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
-    {file = "Deprecated-1.2.14-py2.py3-none-any.whl", hash = "sha256:6fac8b097794a90302bdbb17b9b815e732d3c4720583ff1b198499d78470466c"},
-    {file = "Deprecated-1.2.14.tar.gz", hash = "sha256:e5323eb936458dccc2582dc6f9c322c852a775a27065ff2b0c4970b9d53d01b3"},
-]
-
-[package.dependencies]
-wrapt = ">=1.10,<2"
-
-[package.extras]
-dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
-
 [[package]]
 name = "distlib"
 version = "0.3.6"
 description = "Distribution utilities"
-category = "dev"
 optional = false
 python-versions = "*"
 files = [
@@ -310,7 +237,6 @@ files = [
 name = "docstring-parser"
 version = "0.15"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
-category = "main"
 optional = false
 python-versions = ">=3.6,<4.0"
 files = [
@@ -322,7 +248,6 @@ files = [
 name = "exceptiongroup"
 version = "1.1.1"
 description = "Backport of PEP 654 (exception groups)"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -337,7 +262,6 @@ test = ["pytest (>=6)"]
 name = "filelock"
 version = "3.12.0"
 description = "A platform independent file lock."
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -349,26 +273,10 @@ files = [
 docs = ["furo (>=2023.3.27)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
 testing = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
 
-[[package]]
-name = "fire"
-version = "0.5.0"
-description = "A library for automatically generating command line interfaces."
-category = "main"
-optional = false
-python-versions = "*"
-files = [
-    {file = "fire-0.5.0.tar.gz", hash = "sha256:a6b0d49e98c8963910021f92bba66f65ab440da2982b78eb1bbf95a0a34aacc6"},
-]
-
-[package.dependencies]
-six = "*"
-termcolor = "*"
-
 [[package]]
 name = "google-api-core"
 version = "2.11.0"
 description = "Google API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -389,31 +297,10 @@ grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status
 grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
 grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
 
-[[package]]
-name = "google-api-python-client"
-version = "1.12.11"
-description = "Google API Client Library for Python"
-category = "main"
-optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*"
-files = [
-    {file = "google-api-python-client-1.12.11.tar.gz", hash = "sha256:1b4bd42a46321e13c0542a9e4d96fa05d73626f07b39f83a73a947d70ca706a9"},
-    {file = "google_api_python_client-1.12.11-py2.py3-none-any.whl", hash = "sha256:7e0a1a265c8d3088ee1987778c72683fcb376e32bada8d7767162bd9c503fd9b"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.21.0,<3dev", markers = "python_version >= \"3\""}
-google-auth = {version = ">=1.16.0,<3dev", markers = "python_version >= \"3\""}
-google-auth-httplib2 = ">=0.0.3"
-httplib2 = ">=0.15.0,<1dev"
-six = ">=1.13.0,<2dev"
-uritemplate = ">=3.0.0,<4dev"
-
 [[package]]
 name = "google-auth"
 version = "2.19.1"
 description = "Google Authentication Library"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -435,28 +322,10 @@ pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0dev)"]
 
-[[package]]
-name = "google-auth-httplib2"
-version = "0.1.0"
-description = "Google Authentication Library: httplib2 transport"
-category = "main"
-optional = false
-python-versions = "*"
-files = [
-    {file = "google-auth-httplib2-0.1.0.tar.gz", hash = "sha256:a07c39fd632becacd3f07718dfd6021bf396978f03ad3ce4321d060015cc30ac"},
-    {file = "google_auth_httplib2-0.1.0-py2.py3-none-any.whl", hash = "sha256:31e49c36c6b5643b57e82617cb3e021e3e1d2df9da63af67252c02fa9c1f4a10"},
-]
-
-[package.dependencies]
-google-auth = "*"
-httplib2 = ">=0.15.0"
-six = "*"
-
 [[package]]
 name = "google-cloud-aiplatform"
 version = "1.24.1"
 description = "Vertex AI API client library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -465,7 +334,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.32.0,<2.0.0 || >=2.8.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.32.0,<2.0.dev0 || >=2.8.dev0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-bigquery = ">=1.15.0,<4.0.0dev"
 google-cloud-resource-manager = ">=1.3.3,<3.0.0dev"
 google-cloud-storage = ">=1.32.0,<3.0.0dev"
@@ -494,7 +363,6 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 name = "google-cloud-bigquery"
 version = "3.11.0"
 description = "Google BigQuery API client library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -503,7 +371,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-core = ">=1.6.0,<3.0.0dev"
 google-resumable-media = ">=0.6.0,<3.0dev"
 grpcio = ">=1.47.0,<2.0dev"
@@ -527,7 +395,6 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 name = "google-cloud-core"
 version = "2.3.2"
 description = "Google Cloud API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -536,59 +403,35 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.6,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
 grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
-[[package]]
-name = "google-cloud-notebooks"
-version = "1.7.0"
-description = "Google Cloud Notebooks API client library"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "google-cloud-notebooks-1.7.0.tar.gz", hash = "sha256:dac73a5cd983a4344d1fa96f9a8e5849b0ff75d7a5fdde921023a2ef4566e75e"},
-    {file = "google_cloud_notebooks-1.7.0-py2.py3-none-any.whl", hash = "sha256:8fbffb7ba535fc02c61f135d8863324a5a2d20dd58cafaae592f0b0172d6bdab"},
-]
-
-[package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]}
-grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
-proto-plus = ">=1.22.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "1.0.42"
+version = "2.0.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
-category = "main"
 optional = false
-python-versions = "*"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "google_cloud_pipeline_components-1.0.42-py3-none-any.whl", hash = "sha256:bf833f325d1b4a89f1db9627d3f3e75d1bffc7b7725d4eb739488a68808fa623"},
+    {file = "google_cloud_pipeline_components-2.0.0-py3-none-any.whl", hash = "sha256:4a3708dda8d68989f37d6b4e184e783ab3dc2ff8f0ddf69f5cd4a160603ce252"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.0 || >=2.8.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-cloud-aiplatform = ">=1.14.0,<2"
-google-cloud-notebooks = ">=0.4.0"
-google-cloud-storage = ">=2.2.1,<3"
-googleapis-common-protos = ">=1.56.2,<2.0dev"
-grpcio-status = "<=1.47.0"
-kfp = ">=1.8.9,<2.0.0"
-protobuf = ">=3.19.0,<4.0.0dev"
+kfp = ">=2.0.0b10,<3.0.0"
 
 [package.extras]
-tests = ["flake8 (>=3.0.0)", "google-api-core (>=1.31.5,<2.0.0 || >=2.8.0,<3.0.0dev)", "google-cloud-aiplatform (>=1.14.0,<2)", "google-cloud-notebooks (>=0.4.0)", "google-cloud-storage (>=2.2.1,<3)", "googleapis-common-protos (>=1.56.2,<2.0dev)", "grpcio-status (<=1.47.0)", "kfp (>=1.8.9,<2.0.0)", "mock (>=4.0.0)", "protobuf (>=3.19.0,<4.0.0dev)", "pytest (>=6.0.0)"]
+docs = ["autodocsumm (==0.2.9)", "grpcio-status (<=1.47.0)", "m2r2 (==0.3.2)", "protobuf (>=3.19.0,<4.0.0dev)", "sphinx (==5.0.2)", "sphinx-immaterial (==0.9.0)", "sphinx-notfound-page (==0.8.3)", "sphinx-rtd-theme (==1.0.0)"]
+tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
 version = "1.10.1"
 description = "Google Cloud Resource Manager API client library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -597,7 +440,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
 proto-plus = ">=1.22.0,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
@@ -606,7 +449,6 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 name = "google-cloud-storage"
 version = "2.9.0"
 description = "Google Cloud Storage API client library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -615,7 +457,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 google-cloud-core = ">=2.3.0,<3.0dev"
 google-resumable-media = ">=2.3.2"
@@ -628,7 +470,6 @@ protobuf = ["protobuf (<5.0.0dev)"]
 name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -709,7 +550,6 @@ testing = ["pytest"]
 name = "google-resumable-media"
 version = "2.5.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
-category = "main"
 optional = false
 python-versions = ">= 3.7"
 files = [
@@ -728,7 +568,6 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 name = "googleapis-common-protos"
 version = "1.59.0"
 description = "Common protobufs used in Google APIs"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -747,7 +586,6 @@ grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
 name = "grpc-google-iam-v1"
 version = "0.12.6"
 description = "IAM API client library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -764,7 +602,6 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 name = "grpcio"
 version = "1.54.2"
 description = "HTTP/2-based RPC framework"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -822,7 +659,6 @@ protobuf = ["grpcio-tools (>=1.54.2)"]
 name = "grpcio-status"
 version = "1.47.0"
 description = "Status proto mapping for gRPC"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -835,26 +671,10 @@ googleapis-common-protos = ">=1.5.5"
 grpcio = ">=1.47.0"
 protobuf = ">=3.12.0"
 
-[[package]]
-name = "httplib2"
-version = "0.22.0"
-description = "A comprehensive HTTP client library."
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
-    {file = "httplib2-0.22.0-py3-none-any.whl", hash = "sha256:14ae0a53c1ba8f3d37e9e27cf37eabb0fb9980f435ba405d546948b009dd64dc"},
-    {file = "httplib2-0.22.0.tar.gz", hash = "sha256:d7a10bc5ef5ab08322488bde8c726eeee5c8618723fdb399597ec58f3d82df81"},
-]
-
-[package.dependencies]
-pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""}
-
 [[package]]
 name = "identify"
 version = "2.5.24"
 description = "File identification library for Python"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -869,7 +689,6 @@ license = ["ukkonen"]
 name = "idna"
 version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -881,7 +700,6 @@ files = [
 name = "importlib-metadata"
 version = "6.6.0"
 description = "Read metadata from Python packages"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -898,30 +716,10 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker
 perf = ["ipython"]
 testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
 
-[[package]]
-name = "importlib-resources"
-version = "5.12.0"
-description = "Read resources from Python packages"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "importlib_resources-5.12.0-py3-none-any.whl", hash = "sha256:7b1deeebbf351c7578e09bf2f63fa2ce8b5ffec296e0d349139d43cca061a81a"},
-    {file = "importlib_resources-5.12.0.tar.gz", hash = "sha256:4be82589bf5c1d7999aedf2a45159d10cb3ca4f19b2271f8792bc8e6da7b22f6"},
-]
-
-[package.dependencies]
-zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""}
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["flake8 (<5)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
-
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -933,7 +731,6 @@ files = [
 name = "jinja2"
 version = "3.1.2"
 description = "A very fast and expressive template engine."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -947,79 +744,44 @@ MarkupSafe = ">=2.0"
 [package.extras]
 i18n = ["Babel (>=2.7)"]
 
-[[package]]
-name = "jsonschema"
-version = "4.17.3"
-description = "An implementation of JSON Schema validation for Python"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "jsonschema-4.17.3-py3-none-any.whl", hash = "sha256:a870ad254da1a8ca84b6a2905cac29d265f805acc57af304784962a2aa6508f6"},
-    {file = "jsonschema-4.17.3.tar.gz", hash = "sha256:0f864437ab8b6076ba6707453ef8f98a6a0d512a80e93f8abdb676f737ecb60d"},
-]
-
-[package.dependencies]
-attrs = ">=17.4.0"
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
-importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
-pkgutil-resolve-name = {version = ">=1.3.10", markers = "python_version < \"3.9\""}
-pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2"
-typing-extensions = {version = "*", markers = "python_version < \"3.8\""}
-
-[package.extras]
-format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
-format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"]
-
 [[package]]
 name = "kfp"
-version = "1.8.21"
-description = "KubeFlow Pipelines SDK"
-category = "main"
+version = "2.0.1"
+description = "Kubeflow Pipelines SDK"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "kfp-1.8.21.tar.gz", hash = "sha256:038d77ec9145ccfade95ab3b4b53c32668ae498fede06647ed0425d093819b1c"},
+    {file = "kfp-2.0.1.tar.gz", hash = "sha256:4a65811778c3a45892d8d11c0f95ba5e410476157ed63cacb1dd82316f60cd4d"},
 ]
 
 [package.dependencies]
-absl-py = ">=0.9,<2"
-click = ">=7.1.2,<9"
-cloudpickle = ">=2.0.0,<3"
-Deprecated = ">=1.2.7,<2"
+click = ">=8.0.0,<9"
 docstring-parser = ">=0.7.3,<1"
-fire = ">=0.3.1,<1"
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
-google-api-python-client = ">=1.7.8,<2"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.6.1,<3"
-google-cloud-storage = ">=1.20.0,<3"
-jsonschema = ">=3.0.1,<5"
-kfp-pipeline-spec = ">=0.1.16,<0.2.0"
-kfp-server-api = ">=1.1.2,<2.0.0"
-kubernetes = ">=8.0.0,<26"
+google-cloud-storage = ">=2.2.1,<3"
+kfp-pipeline-spec = "0.2.2"
+kfp-server-api = ">=2.0.0,<2.1.0"
+kubernetes = ">=8.0.0,<27"
 protobuf = ">=3.13.0,<4"
-pydantic = ">=1.8.2,<2"
-PyYAML = ">=5.3,<6"
+PyYAML = ">=5.3,<7"
 requests-toolbelt = ">=0.8.0,<1"
-strip-hints = ">=0.1.8,<1"
 tabulate = ">=0.8.6,<1"
-typer = ">=0.3.2,<1.0"
 typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
-uritemplate = ">=3.0.1,<4"
-urllib3 = "<2"
+urllib3 = "<2.0.0"
 
 [package.extras]
-all = ["docker"]
+all = ["docker", "kfp-kubernetes (<2)"]
+kubernetes = ["kfp-kubernetes (<2)"]
 
 [[package]]
 name = "kfp-pipeline-spec"
-version = "0.1.16"
+version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
-    {file = "kfp_pipeline_spec-0.1.16-py3-none-any.whl", hash = "sha256:4cefae00ac50145cf862127202a8b8a783ed7504c773d7d7c517bd115283be25"},
+    {file = "kfp_pipeline_spec-0.2.2-py3-none-any.whl", hash = "sha256:e83b58ffed3f7ca154d62ab20e14dc9a1a3c9dad589e856dd2b421e226f3b8d0"},
 ]
 
 [package.dependencies]
@@ -1027,13 +789,12 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "1.8.5"
+version = "2.0.0"
 description = "Kubeflow Pipelines API"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "kfp-server-api-1.8.5.tar.gz", hash = "sha256:482d71765ba57c003164dbb980a8cb1a18d234b578d064dc88dbeb3e4c7ab6de"},
+    {file = "kfp-server-api-2.0.0.tar.gz", hash = "sha256:c0462045244a69211bc82a8d6af6602ae8b4f716ee0ac0be5dc34b7ea76c7bd1"},
 ]
 
 [package.dependencies]
@@ -1046,7 +807,6 @@ urllib3 = ">=1.15"
 name = "kubernetes"
 version = "25.3.0"
 description = "Kubernetes python client"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1064,7 +824,7 @@ requests-oauthlib = "*"
 setuptools = ">=21.0.0"
 six = ">=1.9.0"
 urllib3 = ">=1.24.2"
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 [package.extras]
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@@ -1133,7 +892,6 @@ files = [
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 python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
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@@ -1148,7 +906,6 @@ setuptools = "*"
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@@ -1165,7 +922,6 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
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 python-versions = ">=3.7"
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@@ -1173,23 +929,10 @@ files = [
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@@ -1208,7 +951,6 @@ test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.3.1)", "pytest-
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@@ -1227,7 +969,6 @@ testing = ["pytest", "pytest-benchmark"]
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 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
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@@ -1320,116 +1057,10 @@ files = [
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 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -1548,7 +1175,6 @@ rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 name = "requests-toolbelt"
 version = "0.10.1"
 description = "A utility belt for advanced users of python-requests"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -1563,7 +1189,6 @@ requests = ">=2.0.1,<3.0.0"
 name = "rsa"
 version = "4.9"
 description = "Pure-Python RSA implementation"
-category = "main"
 optional = false
 python-versions = ">=3.6,<4"
 files = [
@@ -1578,7 +1203,6 @@ pyasn1 = ">=0.1.3"
 name = "setuptools"
 version = "67.8.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1595,7 +1219,6 @@ testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (
 name = "shapely"
 version = "1.8.5.post1"
 description = "Geometric objects, predicates, and operations"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1652,7 +1275,6 @@ vectorized = ["numpy"]
 name = "six"
 version = "1.16.0"
 description = "Python 2 and 3 compatibility utilities"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
@@ -1660,25 +1282,10 @@ files = [
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 ]
 
-[[package]]
-name = "strip-hints"
-version = "0.1.10"
-description = "Function and command-line program to strip Python type hints."
-category = "main"
-optional = false
-python-versions = "*"
-files = [
-    {file = "strip-hints-0.1.10.tar.gz", hash = "sha256:307c2bd147cd35997c8ed2e9a3bdca48ad9c9617e04ea46599095201b4ce998f"},
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-
-[package.dependencies]
-wheel = "*"
-
 [[package]]
 name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1689,26 +1296,10 @@ files = [
 [package.extras]
 widechars = ["wcwidth"]
 
-[[package]]
-name = "termcolor"
-version = "2.3.0"
-description = "ANSI color formatting for output in terminal"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
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-
-[package.extras]
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-
 [[package]]
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1716,33 +1307,10 @@ files = [
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-version = "0.9.0"
-description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
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-
-[package.dependencies]
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-typing-extensions = ">=3.7.4.3"
-
-[package.extras]
-all = ["colorama (>=0.4.3,<0.5.0)", "rich (>=10.11.0,<14.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
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-
 [[package]]
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 version = "4.6.3"
 description = "Backported and Experimental Type Hints for Python 3.7+"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1750,23 +1318,10 @@ files = [
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 ]
 
-[[package]]
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-version = "3.0.1"
-description = "URI templates"
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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-
 [[package]]
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 description = "HTTP library with thread-safe connection pooling, file post, and more."
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
@@ -1783,14 +1338,13 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 name = "vertex-components"
 version = "0.1.0"
 description = "KubeFlow components for Vertex AI"
-category = "main"
 optional = false
 python-versions = ">=3.7,<3.11"
 files = []
 develop = true
 
 [package.dependencies]
-kfp = "==1.8.21"
+kfp = ">=2.0.1,<3.0.0"
 
 [package.source]
 type = "directory"
@@ -1800,7 +1354,6 @@ url = "../components/vertex-components"
 name = "virtualenv"
 version = "20.23.0"
 description = "Virtual Python Environment builder"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1822,7 +1375,6 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "coverage-enable-subprocess
 name = "websocket-client"
 version = "1.5.2"
 description = "WebSocket client for Python with low level API options"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1835,111 +1387,10 @@ docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
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-version = "0.40.0"
-description = "A built-package format for Python"
-category = "main"
-optional = false
-python-versions = ">=3.7"
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-
-[package.extras]
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-
-[[package]]
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-    {file = "wrapt-1.15.0.tar.gz", hash = "sha256:d06730c6aed78cee4126234cf2d071e01b44b915e725a6cb439a879ec9754a3a"},
-]
-
 [[package]]
 name = "zipp"
 version = "3.15.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1954,4 +1405,4 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.7,<3.11"
-content-hash = "60130a208e8b1b38937ed8c91f1aa32e75c3c86be061ca321457ebc6f3a7d72c"
+content-hash = "6360ac432e14023430d2290fcbd782c7693b0365570fd50f4ecc865d04a5718d"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 9548d91c..eb468200 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -17,9 +17,10 @@ packages = [
 python = ">=3.7,<3.11"
 Jinja2 = ">=3.0.1,<4.0.0"
 google-cloud-aiplatform = "1.24.1"
-google-cloud-pipeline-components = "1.0.42"
+google-cloud-pipeline-components = "^2.0.0"
 bigquery-components = { path = "../components/bigquery-components", develop = true }
 vertex-components = { path = "../components/vertex-components", develop = true }
+kfp = "^2.0.1"
 
 [tool.poetry.group.dev.dependencies]
 pytest = ">=7.3.1,<8.0.0"
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index ff25c119..20deca08 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -16,7 +16,7 @@
 import pathlib
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp.v2 import compiler, dsl
+from kfp import compiler, dsl
 
 from pipelines import generate_query
 from vertex_components import lookup_model, model_batch_predict
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 371928f5..13ccb817 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -16,7 +16,7 @@
 import pathlib
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp.v2 import compiler, dsl
+from kfp import compiler, dsl
 from pipelines import generate_query
 from bigquery_components import extract_bq_to_dataset
 from vertex_components import (
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index f077d32c..c7225e10 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -16,7 +16,7 @@
 import pathlib
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp.v2 import compiler, dsl
+from kfp import compiler, dsl
 
 from pipelines import generate_query
 from vertex_components import lookup_model, model_batch_predict
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 7db36231..411bc69e 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -16,7 +16,7 @@
 import pathlib
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp.v2 import compiler, dsl
+from kfp import compiler, dsl
 from pipelines import generate_query
 from bigquery_components import extract_bq_to_dataset
 from vertex_components import (
diff --git a/pipelines/tests/e2e/test_e2e.py b/pipelines/tests/e2e/test_e2e.py
index d4c70393..c7b8081c 100644
--- a/pipelines/tests/e2e/test_e2e.py
+++ b/pipelines/tests/e2e/test_e2e.py
@@ -18,7 +18,7 @@
 import pytest
 import os
 from google.cloud import storage
-from kfp.v2 import compiler
+from kfp import compiler
 
 from pipelines.trigger.main import trigger_pipeline_from_payload
 

From bfa29041301cb72a5d31edb44fad5a22d7f0c711 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Wed, 19 Jul 2023 22:34:34 +0100
Subject: [PATCH 125/238] feat: upgrade to kfp v2 and Python 3.9

---
 .pre-commit-config.yaml                       |   2 +-
 .python-version                               |   2 +-
 Makefile                                      |   6 +
 cloudbuild/e2e-test.yaml                      |   2 +-
 cloudbuild/pr-checks.yaml                     |   2 +-
 cloudbuild/release.yaml                       |   2 +-
 cloudbuild/trigger-tests.yaml                 |   2 +-
 .../bigquery-components/.python-version       |   2 +-
 components/bigquery-components/poetry.lock    |  62 ++--
 components/bigquery-components/pyproject.toml |   4 +-
 .../extract_bq_to_dataset.py                  |   2 +-
 components/vertex-components/.python-version  |   2 +-
 components/vertex-components/poetry.lock      |  72 ++---
 components/vertex-components/pyproject.toml   |   4 +-
 .../src/vertex_components/__init__.py         |   2 +
 .../src/vertex_components/custom_train_job.py | 160 ----------
 .../import_model_evaluation.py                |  86 ------
 .../src/vertex_components/lookup_model.py     |  99 ------
 .../vertex_components/model_batch_predict.py  |   2 +-
 .../vertex_components/update_best_model.py    |  87 ------
 .../src/vertex_components/upload_model.py     | 216 +++++++++++++
 env.sh.example                                |   1 +
 pipelines/.python-version                     |   2 +-
 pipelines/poetry.lock                         |  71 +----
 pipelines/pyproject.toml                      |   6 +-
 .../pipelines/xgboost/training/pipeline.py    |  95 +++---
 terraform/modules/vertex_deployment/main.tf   |  10 +
 training/.gitignore                           |   1 +
 training/Dockerfile                           |   8 +
 training/main.py                              | 147 +++++++++
 training/poetry.lock                          | 283 ++++++++++++++++++
 training/pyproject.toml                       |  17 ++
 32 files changed, 833 insertions(+), 626 deletions(-)
 delete mode 100644 components/vertex-components/src/vertex_components/custom_train_job.py
 delete mode 100644 components/vertex-components/src/vertex_components/import_model_evaluation.py
 delete mode 100644 components/vertex-components/src/vertex_components/lookup_model.py
 delete mode 100644 components/vertex-components/src/vertex_components/update_best_model.py
 create mode 100644 components/vertex-components/src/vertex_components/upload_model.py
 create mode 100644 training/.gitignore
 create mode 100644 training/Dockerfile
 create mode 100644 training/main.py
 create mode 100644 training/poetry.lock
 create mode 100644 training/pyproject.toml

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 3bd0bc1e..66dc32d3 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -14,7 +14,7 @@
 
 ---
 default_language_version:
-  python: python3.7
+  python: python3.9
 
 repos:
   - repo: https://github.com/gruntwork-io/pre-commit
diff --git a/.python-version b/.python-version
index 8a433dd7..7a72691a 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.7.12 
+3.9.16 
diff --git a/Makefile b/Makefile
index 2ce9ca3b..d441b7f7 100644
--- a/Makefile
+++ b/Makefile
@@ -105,3 +105,9 @@ destroy-infra: ## DESTROY the Terraform infrastructure in your project. Requires
 	@ cd terraform/envs/$(env) && \
 	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
 	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
+
+build-training-container: ## Build and push training container image using Docker
+	@ cd training && \
+	poetry export -f requirements.txt -o requirements.txt && \
+	docker build -t ${TRAINING_CONTAINER_IMAGE} . && \
+	docker push ${TRAINING_CONTAINER_IMAGE}
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index b71430d2..b3d054da 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -28,7 +28,7 @@ steps:
 
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 9f0f4347..969e7bbf 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -17,7 +17,7 @@ steps:
   # Install poetry and deps, run pre-commit and unit tests
   # Then compile pipelines (to make sure they can compile)
   # need to run "git init" for pre-commit checks to work
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index d5903468..0c22abdb 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -15,7 +15,7 @@
 steps:
 
   # Install poetry, install deps, compile pipelines
-  - name: python:3.7
+  - name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
diff --git a/cloudbuild/trigger-tests.yaml b/cloudbuild/trigger-tests.yaml
index a3387438..295e2c50 100644
--- a/cloudbuild/trigger-tests.yaml
+++ b/cloudbuild/trigger-tests.yaml
@@ -13,7 +13,7 @@
 # limitations under the License.
 ---
 steps:
-  - name: 'python:3.7'
+  - name: 'python:3.9'
     args:
       - '-c'
       - |
diff --git a/components/bigquery-components/.python-version b/components/bigquery-components/.python-version
index f7e5aa84..9f3d4c17 100644
--- a/components/bigquery-components/.python-version
+++ b/components/bigquery-components/.python-version
@@ -1 +1 @@
-3.7.12
+3.9.16
diff --git a/components/bigquery-components/poetry.lock b/components/bigquery-components/poetry.lock
index 7fa1ecb4..d2a3ec40 100644
--- a/components/bigquery-components/poetry.lock
+++ b/components/bigquery-components/poetry.lock
@@ -5,7 +5,7 @@ name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
     {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
@@ -27,7 +27,7 @@ name = "charset-normalizer"
 version = "3.1.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
-python-versions = ">=3.7.0"
+python-versions = ">=3.9.0"
 files = [
     {file = "charset-normalizer-3.1.0.tar.gz", hash = "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5"},
     {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e0ac8959c929593fee38da1c2b64ee9778733cdf03c482c9ff1d508b6b593b2b"},
@@ -111,7 +111,7 @@ name = "click"
 version = "8.1.3"
 description = "Composable command line interface toolkit"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "click-8.1.3-py3-none-any.whl", hash = "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"},
     {file = "click-8.1.3.tar.gz", hash = "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e"},
@@ -148,7 +148,7 @@ name = "exceptiongroup"
 version = "1.1.1"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "exceptiongroup-1.1.1-py3-none-any.whl", hash = "sha256:232c37c63e4f682982c8b6459f33a8981039e5fb8756b2074364e5055c498c9e"},
     {file = "exceptiongroup-1.1.1.tar.gz", hash = "sha256:d484c3090ba2889ae2928419117447a14daf3c1231d5e30d0aae34f354f01785"},
@@ -162,7 +162,7 @@ name = "google-api-core"
 version = "2.11.0"
 description = "Google API client core library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-api-core-2.11.0.tar.gz", hash = "sha256:4b9bb5d5a380a0befa0573b302651b8a9a89262c1730e37bf423cec511804c22"},
     {file = "google_api_core-2.11.0-py3-none-any.whl", hash = "sha256:ce222e27b0de0d7bc63eb043b956996d6dccab14cc3b690aaea91c9cc99dc16e"},
@@ -242,7 +242,7 @@ name = "google-cloud-core"
 version = "2.3.2"
 description = "Google Cloud API client core library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-cloud-core-2.3.2.tar.gz", hash = "sha256:b9529ee7047fd8d4bf4a2182de619154240df17fbe60ead399078c1ae152af9a"},
     {file = "google_cloud_core-2.3.2-py2.py3-none-any.whl", hash = "sha256:8417acf6466be2fa85123441696c4badda48db314c607cf1e5d543fa8bdc22fe"},
@@ -260,7 +260,7 @@ name = "google-cloud-storage"
 version = "2.9.0"
 description = "Google Cloud Storage API client library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-cloud-storage-2.9.0.tar.gz", hash = "sha256:9b6ae7b509fc294bdacb84d0f3ea8e20e2c54a8b4bbe39c5707635fec214eff3"},
     {file = "google_cloud_storage-2.9.0-py2.py3-none-any.whl", hash = "sha256:83a90447f23d5edd045e0037982c270302e3aeb45fc1288d2c2ca713d27bad94"},
@@ -281,7 +281,7 @@ name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-crc32c-1.5.0.tar.gz", hash = "sha256:89284716bc6a5a415d4eaa11b1726d2d60a0cd12aadf5439828353662ede9dd7"},
     {file = "google_crc32c-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:596d1f98fc70232fcb6590c439f43b350cb762fb5d61ce7b0e9db4539654cc13"},
@@ -361,7 +361,7 @@ name = "google-resumable-media"
 version = "2.5.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
 optional = false
-python-versions = ">= 3.7"
+python-versions = ">= 3.9"
 files = [
     {file = "google-resumable-media-2.5.0.tar.gz", hash = "sha256:218931e8e2b2a73a58eb354a288e03a0fd5fb1c4583261ac6e4c078666468c93"},
     {file = "google_resumable_media-2.5.0-py2.py3-none-any.whl", hash = "sha256:da1bd943e2e114a56d85d6848497ebf9be6a14d3db23e9fc57581e7c3e8170ec"},
@@ -379,7 +379,7 @@ name = "googleapis-common-protos"
 version = "1.59.0"
 description = "Common protobufs used in Google APIs"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "googleapis-common-protos-1.59.0.tar.gz", hash = "sha256:4168fcb568a826a52f23510412da405abd93f4d23ba544bb68d943b14ba3cb44"},
     {file = "googleapis_common_protos-1.59.0-py2.py3-none-any.whl", hash = "sha256:b287dc48449d1d41af0c69f4ea26242b5ae4c3d7249a38b0984c86a4caffff1f"},
@@ -396,7 +396,7 @@ name = "grpcio"
 version = "1.54.2"
 description = "HTTP/2-based RPC framework"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "grpcio-1.54.2-cp310-cp310-linux_armv7l.whl", hash = "sha256:40e1cbf69d6741b40f750f3cccc64326f927ac6145a9914d33879e586002350c"},
     {file = "grpcio-1.54.2-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:2288d76e4d4aa7ef3fe7a73c1c470b66ea68e7969930e746a8cd8eca6ef2a2ea"},
@@ -480,7 +480,7 @@ name = "importlib-metadata"
 version = "6.6.0"
 description = "Read metadata from Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "importlib_metadata-6.6.0-py3-none-any.whl", hash = "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed"},
     {file = "importlib_metadata-6.6.0.tar.gz", hash = "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"},
@@ -493,14 +493,14 @@ zipp = ">=0.5"
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
-testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
+testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
 
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
@@ -511,7 +511,7 @@ name = "kfp"
 version = "2.0.1"
 description = "Kubeflow Pipelines SDK"
 optional = false
-python-versions = ">=3.7.0,<3.12.0"
+python-versions = ">=3.9.0,<3.12.0"
 files = [
     {file = "kfp-2.0.1.tar.gz", hash = "sha256:4a65811778c3a45892d8d11c0f95ba5e410476157ed63cacb1dd82316f60cd4d"},
 ]
@@ -529,7 +529,7 @@ protobuf = ">=3.13.0,<4"
 PyYAML = ">=5.3,<7"
 requests-toolbelt = ">=0.8.0,<1"
 tabulate = ">=0.8.6,<1"
-typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
+typing-extensions = {version = ">=3.9.4,<5", markers = "python_version < \"3.9\""}
 urllib3 = "<2.0.0"
 
 [package.extras]
@@ -541,7 +541,7 @@ name = "kfp-pipeline-spec"
 version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
 optional = false
-python-versions = ">=3.7.0"
+python-versions = ">=3.9.0"
 files = [
     {file = "kfp_pipeline_spec-0.2.2-py3-none-any.whl", hash = "sha256:e83b58ffed3f7ca154d62ab20e14dc9a1a3c9dad589e856dd2b421e226f3b8d0"},
 ]
@@ -612,7 +612,7 @@ name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "packaging-23.1-py3-none-any.whl", hash = "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61"},
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
@@ -658,7 +658,7 @@ name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "protobuf-3.20.3-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:f4bd856d702e5b0d96a00ec6b307b0f51c1982c2bf9c0052cf9019e9a544ba99"},
     {file = "protobuf-3.20.3-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:9aae4406ea63d825636cc11ffb34ad3379335803216ee3a856787bcf5ccc751e"},
@@ -714,7 +714,7 @@ name = "pytest"
 version = "7.3.1"
 description = "pytest: simple powerful testing with Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "pytest-7.3.1-py3-none-any.whl", hash = "sha256:3799fa815351fea3a5e96ac7e503a96fa51cc9942c3753cda7651b93c1cfa362"},
     {file = "pytest-7.3.1.tar.gz", hash = "sha256:434afafd78b1d78ed0addf160ad2b77a30d35d4bdf8af234fe621919d9ed15e3"},
@@ -789,7 +789,7 @@ name = "requests"
 version = "2.31.0"
 description = "Python HTTP for Humans."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
     {file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
@@ -856,7 +856,7 @@ name = "setuptools"
 version = "67.8.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "setuptools-67.8.0-py3-none-any.whl", hash = "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f"},
     {file = "setuptools-67.8.0.tar.gz", hash = "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"},
@@ -864,7 +864,7 @@ files = [
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
@@ -883,7 +883,7 @@ name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"},
     {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"},
@@ -897,7 +897,7 @@ name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
     {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
@@ -906,9 +906,9 @@ files = [
 [[package]]
 name = "typing-extensions"
 version = "4.6.2"
-description = "Backported and Experimental Type Hints for Python 3.7+"
+description = "Backported and Experimental Type Hints for Python 3.9+"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "typing_extensions-4.6.2-py3-none-any.whl", hash = "sha256:3a8b36f13dd5fdc5d1b16fe317f5668545de77fa0b8e02006381fd49d731ab98"},
     {file = "typing_extensions-4.6.2.tar.gz", hash = "sha256:06006244c70ac8ee83fa8282cb188f697b8db25bc8b4df07be1873c43897060c"},
@@ -935,7 +935,7 @@ name = "websocket-client"
 version = "1.5.2"
 description = "WebSocket client for Python with low level API options"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "websocket-client-1.5.2.tar.gz", hash = "sha256:c7d67c13b928645f259d9b847ab5b57fd2d127213ca41ebd880de1f553b7c23b"},
     {file = "websocket_client-1.5.2-py3-none-any.whl", hash = "sha256:f8c64e28cd700e7ba1f04350d66422b6833b82a796b525a51e740b8cc8dab4b1"},
@@ -951,7 +951,7 @@ name = "zipp"
 version = "3.15.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
     {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
@@ -959,9 +959,9 @@ files = [
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.7,<3.11"
+python-versions = ">=3.9,<3.11"
 content-hash = "6f7ca2171a974f20e9e0c7d38859b0570337711f678f0fed05a9560ce299f0e0"
diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index 9d6cd0db..36d55a21 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -7,11 +7,11 @@ readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.7",
+    "Programming Language :: Python :: 3.9",
 ]
 
 [tool.poetry.dependencies]
-python = ">=3.7,<3.11"
+python = ">=3.9,<3.11"
 kfp = "^2.0.1"
 
 [tool.poetry.group.dev.dependencies]
diff --git a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py b/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
index 4846e448..7039b022 100644
--- a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
+++ b/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
@@ -16,7 +16,7 @@
 
 
 @component(
-    base_image="python:3.7",
+    base_image="python:3.9",
     packages_to_install=["google-cloud-bigquery==2.30.0"],
 )
 def extract_bq_to_dataset(
diff --git a/components/vertex-components/.python-version b/components/vertex-components/.python-version
index f7e5aa84..9f3d4c17 100644
--- a/components/vertex-components/.python-version
+++ b/components/vertex-components/.python-version
@@ -1 +1 @@
-3.7.12
+3.9.16
diff --git a/components/vertex-components/poetry.lock b/components/vertex-components/poetry.lock
index c03e62bb..c5e25a3e 100644
--- a/components/vertex-components/poetry.lock
+++ b/components/vertex-components/poetry.lock
@@ -5,7 +5,7 @@ name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
     {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
@@ -27,7 +27,7 @@ name = "charset-normalizer"
 version = "3.1.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
-python-versions = ">=3.7.0"
+python-versions = ">=3.9.0"
 files = [
     {file = "charset-normalizer-3.1.0.tar.gz", hash = "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5"},
     {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e0ac8959c929593fee38da1c2b64ee9778733cdf03c482c9ff1d508b6b593b2b"},
@@ -111,7 +111,7 @@ name = "click"
 version = "8.1.3"
 description = "Composable command line interface toolkit"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "click-8.1.3-py3-none-any.whl", hash = "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"},
     {file = "click-8.1.3.tar.gz", hash = "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e"},
@@ -148,7 +148,7 @@ name = "exceptiongroup"
 version = "1.1.1"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "exceptiongroup-1.1.1-py3-none-any.whl", hash = "sha256:232c37c63e4f682982c8b6459f33a8981039e5fb8756b2074364e5055c498c9e"},
     {file = "exceptiongroup-1.1.1.tar.gz", hash = "sha256:d484c3090ba2889ae2928419117447a14daf3c1231d5e30d0aae34f354f01785"},
@@ -162,7 +162,7 @@ name = "google-api-core"
 version = "2.11.0"
 description = "Google API client core library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-api-core-2.11.0.tar.gz", hash = "sha256:4b9bb5d5a380a0befa0573b302651b8a9a89262c1730e37bf423cec511804c22"},
     {file = "google_api_core-2.11.0-py3-none-any.whl", hash = "sha256:ce222e27b0de0d7bc63eb043b956996d6dccab14cc3b690aaea91c9cc99dc16e"},
@@ -211,7 +211,7 @@ name = "google-cloud-aiplatform"
 version = "1.24.1"
 description = "Vertex AI API client library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-cloud-aiplatform-1.24.1.tar.gz", hash = "sha256:0ce9e97bf5c977397e52b3b7c4dc78610c135fbde11a60a6c0b77a4fdf776400"},
     {file = "google_cloud_aiplatform-1.24.1-py2.py3-none-any.whl", hash = "sha256:942765a6bad97e46e262dd6599dc5f171663ce952130e0b0b2eb97e0b1b98bfd"},
@@ -248,7 +248,7 @@ name = "google-cloud-bigquery"
 version = "3.10.0"
 description = "Google BigQuery API client library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-cloud-bigquery-3.10.0.tar.gz", hash = "sha256:4b02def076e2db8cec66f65fb627d13904a9fc3cf4fee315ede43dcb7038a8df"},
     {file = "google_cloud_bigquery-3.10.0-py2.py3-none-any.whl", hash = "sha256:848a3cbce0ba7d4f1e9551400a7c99aa0eab72290d5a1bbbe69f18a24a10bd3a"},
@@ -280,7 +280,7 @@ name = "google-cloud-core"
 version = "2.3.2"
 description = "Google Cloud API client core library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-cloud-core-2.3.2.tar.gz", hash = "sha256:b9529ee7047fd8d4bf4a2182de619154240df17fbe60ead399078c1ae152af9a"},
     {file = "google_cloud_core-2.3.2-py2.py3-none-any.whl", hash = "sha256:8417acf6466be2fa85123441696c4badda48db314c607cf1e5d543fa8bdc22fe"},
@@ -298,7 +298,7 @@ name = "google-cloud-pipeline-components"
 version = "2.0.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
 optional = false
-python-versions = ">=3.7.0,<3.12.0"
+python-versions = ">=3.9.0,<3.12.0"
 files = [
     {file = "google_cloud_pipeline_components-2.0.0-py3-none-any.whl", hash = "sha256:4a3708dda8d68989f37d6b4e184e783ab3dc2ff8f0ddf69f5cd4a160603ce252"},
 ]
@@ -317,7 +317,7 @@ name = "google-cloud-resource-manager"
 version = "1.10.1"
 description = "Google Cloud Resource Manager API client library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-cloud-resource-manager-1.10.1.tar.gz", hash = "sha256:c974fb6f9810476cf7b63ea89394c1a8df47f7f2dc2303e728bb74b500bcde67"},
     {file = "google_cloud_resource_manager-1.10.1-py2.py3-none-any.whl", hash = "sha256:41a2204532f084c707fde0bc1a9bc95c7e0b739d7072dd0b8a25106667a56184"},
@@ -334,7 +334,7 @@ name = "google-cloud-storage"
 version = "2.9.0"
 description = "Google Cloud Storage API client library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-cloud-storage-2.9.0.tar.gz", hash = "sha256:9b6ae7b509fc294bdacb84d0f3ea8e20e2c54a8b4bbe39c5707635fec214eff3"},
     {file = "google_cloud_storage-2.9.0-py2.py3-none-any.whl", hash = "sha256:83a90447f23d5edd045e0037982c270302e3aeb45fc1288d2c2ca713d27bad94"},
@@ -355,7 +355,7 @@ name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "google-crc32c-1.5.0.tar.gz", hash = "sha256:89284716bc6a5a415d4eaa11b1726d2d60a0cd12aadf5439828353662ede9dd7"},
     {file = "google_crc32c-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:596d1f98fc70232fcb6590c439f43b350cb762fb5d61ce7b0e9db4539654cc13"},
@@ -435,7 +435,7 @@ name = "google-resumable-media"
 version = "2.5.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
 optional = false
-python-versions = ">= 3.7"
+python-versions = ">= 3.9"
 files = [
     {file = "google-resumable-media-2.5.0.tar.gz", hash = "sha256:218931e8e2b2a73a58eb354a288e03a0fd5fb1c4583261ac6e4c078666468c93"},
     {file = "google_resumable_media-2.5.0-py2.py3-none-any.whl", hash = "sha256:da1bd943e2e114a56d85d6848497ebf9be6a14d3db23e9fc57581e7c3e8170ec"},
@@ -453,7 +453,7 @@ name = "googleapis-common-protos"
 version = "1.59.0"
 description = "Common protobufs used in Google APIs"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "googleapis-common-protos-1.59.0.tar.gz", hash = "sha256:4168fcb568a826a52f23510412da405abd93f4d23ba544bb68d943b14ba3cb44"},
     {file = "googleapis_common_protos-1.59.0-py2.py3-none-any.whl", hash = "sha256:b287dc48449d1d41af0c69f4ea26242b5ae4c3d7249a38b0984c86a4caffff1f"},
@@ -471,7 +471,7 @@ name = "grpc-google-iam-v1"
 version = "0.12.6"
 description = "IAM API client library"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "grpc-google-iam-v1-0.12.6.tar.gz", hash = "sha256:2bc4b8fdf22115a65d751c9317329322602c39b7c86a289c9b72d228d960ef5f"},
     {file = "grpc_google_iam_v1-0.12.6-py2.py3-none-any.whl", hash = "sha256:5c10f3d8dc2d88678ab1a9b0cb5482735c5efee71e6c0cd59f872eef22913f5c"},
@@ -487,7 +487,7 @@ name = "grpcio"
 version = "1.54.2"
 description = "HTTP/2-based RPC framework"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "grpcio-1.54.2-cp310-cp310-linux_armv7l.whl", hash = "sha256:40e1cbf69d6741b40f750f3cccc64326f927ac6145a9914d33879e586002350c"},
     {file = "grpcio-1.54.2-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:2288d76e4d4aa7ef3fe7a73c1c470b66ea68e7969930e746a8cd8eca6ef2a2ea"},
@@ -571,7 +571,7 @@ name = "importlib-metadata"
 version = "6.6.0"
 description = "Read metadata from Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "importlib_metadata-6.6.0-py3-none-any.whl", hash = "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed"},
     {file = "importlib_metadata-6.6.0.tar.gz", hash = "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"},
@@ -584,14 +584,14 @@ zipp = ">=0.5"
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
-testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
+testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
 
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
@@ -602,7 +602,7 @@ name = "kfp"
 version = "2.0.1"
 description = "Kubeflow Pipelines SDK"
 optional = false
-python-versions = ">=3.7.0,<3.12.0"
+python-versions = ">=3.9.0,<3.12.0"
 files = [
     {file = "kfp-2.0.1.tar.gz", hash = "sha256:4a65811778c3a45892d8d11c0f95ba5e410476157ed63cacb1dd82316f60cd4d"},
 ]
@@ -620,7 +620,7 @@ protobuf = ">=3.13.0,<4"
 PyYAML = ">=5.3,<7"
 requests-toolbelt = ">=0.8.0,<1"
 tabulate = ">=0.8.6,<1"
-typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
+typing-extensions = {version = ">=3.9.4,<5", markers = "python_version < \"3.9\""}
 urllib3 = "<2.0.0"
 
 [package.extras]
@@ -632,7 +632,7 @@ name = "kfp-pipeline-spec"
 version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
 optional = false
-python-versions = ">=3.7.0"
+python-versions = ">=3.9.0"
 files = [
     {file = "kfp_pipeline_spec-0.2.2-py3-none-any.whl", hash = "sha256:e83b58ffed3f7ca154d62ab20e14dc9a1a3c9dad589e856dd2b421e226f3b8d0"},
 ]
@@ -703,7 +703,7 @@ name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "packaging-23.1-py3-none-any.whl", hash = "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61"},
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
@@ -749,7 +749,7 @@ name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "protobuf-3.20.3-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:f4bd856d702e5b0d96a00ec6b307b0f51c1982c2bf9c0052cf9019e9a544ba99"},
     {file = "protobuf-3.20.3-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:9aae4406ea63d825636cc11ffb34ad3379335803216ee3a856787bcf5ccc751e"},
@@ -805,7 +805,7 @@ name = "pytest"
 version = "7.3.1"
 description = "pytest: simple powerful testing with Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "pytest-7.3.1-py3-none-any.whl", hash = "sha256:3799fa815351fea3a5e96ac7e503a96fa51cc9942c3753cda7651b93c1cfa362"},
     {file = "pytest-7.3.1.tar.gz", hash = "sha256:434afafd78b1d78ed0addf160ad2b77a30d35d4bdf8af234fe621919d9ed15e3"},
@@ -880,7 +880,7 @@ name = "requests"
 version = "2.31.0"
 description = "Python HTTP for Humans."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
     {file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
@@ -947,7 +947,7 @@ name = "setuptools"
 version = "67.8.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "setuptools-67.8.0-py3-none-any.whl", hash = "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f"},
     {file = "setuptools-67.8.0.tar.gz", hash = "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"},
@@ -955,7 +955,7 @@ files = [
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
@@ -1030,7 +1030,7 @@ name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"},
     {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"},
@@ -1044,7 +1044,7 @@ name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
     {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
@@ -1053,9 +1053,9 @@ files = [
 [[package]]
 name = "typing-extensions"
 version = "4.6.2"
-description = "Backported and Experimental Type Hints for Python 3.7+"
+description = "Backported and Experimental Type Hints for Python 3.9+"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "typing_extensions-4.6.2-py3-none-any.whl", hash = "sha256:3a8b36f13dd5fdc5d1b16fe317f5668545de77fa0b8e02006381fd49d731ab98"},
     {file = "typing_extensions-4.6.2.tar.gz", hash = "sha256:06006244c70ac8ee83fa8282cb188f697b8db25bc8b4df07be1873c43897060c"},
@@ -1082,7 +1082,7 @@ name = "websocket-client"
 version = "1.5.2"
 description = "WebSocket client for Python with low level API options"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "websocket-client-1.5.2.tar.gz", hash = "sha256:c7d67c13b928645f259d9b847ab5b57fd2d127213ca41ebd880de1f553b7c23b"},
     {file = "websocket_client-1.5.2-py3-none-any.whl", hash = "sha256:f8c64e28cd700e7ba1f04350d66422b6833b82a796b525a51e740b8cc8dab4b1"},
@@ -1098,7 +1098,7 @@ name = "zipp"
 version = "3.15.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 files = [
     {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
     {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
@@ -1106,9 +1106,9 @@ files = [
 
 [package.extras]
 docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
+testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
 
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.7,<3.11"
+python-versions = ">=3.9,<3.11"
 content-hash = "60358af42655b9cff7889a1d3d0fbcf4ca40982c4dd4d29784544c511a63cb96"
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index 9e628dc1..a12e1fdc 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -7,11 +7,11 @@ readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.7",
+    "Programming Language :: Python :: 3.9",
 ]
 
 [tool.poetry.dependencies]
-python = ">=3.7,<3.11"
+python = ">=3.9,<3.11"
 kfp = ">=2.0.1,<3.0.0"
 
 [tool.poetry.group.dev.dependencies]
diff --git a/components/vertex-components/src/vertex_components/__init__.py b/components/vertex-components/src/vertex_components/__init__.py
index 22ca7d04..4175abff 100644
--- a/components/vertex-components/src/vertex_components/__init__.py
+++ b/components/vertex-components/src/vertex_components/__init__.py
@@ -3,6 +3,7 @@
 from .lookup_model import lookup_model
 from .model_batch_predict import model_batch_predict
 from .update_best_model import update_best_model
+from .upload_model import upload_model
 
 
 __version__ = "0.0.1"
@@ -12,4 +13,5 @@
     "lookup_model",
     "model_batch_predict",
     "update_best_model",
+    "upload_model",
 ]
diff --git a/components/vertex-components/src/vertex_components/custom_train_job.py b/components/vertex-components/src/vertex_components/custom_train_job.py
deleted file mode 100644
index 8e2f220a..00000000
--- a/components/vertex-components/src/vertex_components/custom_train_job.py
+++ /dev/null
@@ -1,160 +0,0 @@
-# Copyright 2022 Google LLC
-from typing import List, Dict, NamedTuple
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from kfp.dsl import Input, component, Metrics, Output, Artifact, Dataset
-
-
-@component(
-    base_image="python:3.7",
-    packages_to_install=[
-        "google-cloud-aiplatform==1.24.1",
-        "google-cloud-pipeline-components==1.0.42",
-    ],
-)
-def custom_train_job(
-    train_script_uri: str,
-    train_data: Input[Dataset],
-    valid_data: Input[Dataset],
-    test_data: Input[Dataset],
-    project_id: str,
-    project_location: str,
-    model_display_name: str,
-    train_container_uri: str,
-    serving_container_uri: str,
-    model: Output[Artifact],
-    metrics: Output[Metrics],
-    staging_bucket: str,
-    requirements: List[str] = None,
-    job_name: str = None,
-    hparams: Dict[str, str] = None,
-    replica_count: int = 1,
-    machine_type: str = "n1-standard-4",
-    accelerator_type: str = "ACCELERATOR_TYPE_UNSPECIFIED",
-    accelerator_count: int = 0,
-    parent_model: str = None,
-) -> NamedTuple("Outputs", [("gcp_resources", str)]):
-    """Run a custom training job using a training script.
-
-    The provided script will be invoked by passing the following command-line arguments:
-
-    ```
-    train.py \
-        --train_data <train_data.path> \
-        --valid_data <valid_data.path> \
-        --test_data <test_data.path> \
-        --metrics <metrics.path> \
-        --hparams json.dumps(<hparams>)
-    ```
-
-    Ensure that your train script can read these arguments and outputs metrics
-    to the provided path and the model to the correct path based on:
-    https://cloud.google.com/vertex-ai/docs/training/code-requirements.
-
-    Args:
-        train_script_uri (str): gs:// uri to python train script. See:
-            https://cloud.google.com/vertex-ai/docs/training/code-requirements.
-        train_data (Dataset): Training data (passed as an argument to train script)
-        valid_data (Dataset): Validation data (passed as an argument to train script)
-        test_data (Dataset): Test data (passed as an argument to train script).
-        staging_bucket (str): Staging bucket for CustomTrainingJob.
-        project_location (str): location of the Google Cloud project.
-        project_id (str): project id of the Google Cloud project.
-        model_display_name (str): Name of the new trained model version.
-        train_container_uri (str): Container URI for running train script.
-        serving_container_uri (str): Container URI for deploying the output model.
-        model (Model): Trained model output.
-        metrics (Metrics): Output metrics of trained model.
-        requirements (List[str]): Additional python dependencies for training script.
-        job_name (str): Name of training job.
-        hparams (Dict[str, str]): Hyperparameters (passed as a JSON serialised argument
-            to train script)
-        replica_count (int): Number of replicas (increase for distributed training).
-        machine_type (str): Machine type of compute.
-        accelerator_type (str): Accelerator type (change for GPU support).
-        accelerator_count (str): Accelerator count (increase for GPU cores).
-        parent_model (str): Resource URI of existing parent model (optional). If `None`,
-            a new model will be uploaded. Otherwise, a new model version for the parent
-            model will be uploaded.
-    Returns:
-        parent_model (str): Resource URI of the parent model (empty string if the
-            trained model is the first model version of its kind).
-        NamedTuple: gcp_resources for Vertex AI UI integration.
-    """
-    import json
-    import logging
-    import os.path
-    import time
-    import google.cloud.aiplatform as aip
-    from google_cloud_pipeline_components.proto.gcp_resources_pb2 import GcpResources
-    from google.protobuf.json_format import MessageToJson
-
-    logging.info(f"Using train script: {train_script_uri}")
-    script_path = "/gcs/" + train_script_uri[5:]
-    if not os.path.exists(script_path):
-        raise ValueError(
-            "Train script was not found. "
-            f"Check if the path is correct: {train_script_uri}"
-        )
-
-    job = aip.CustomTrainingJob(
-        project=project_id,
-        location=project_location,
-        staging_bucket=staging_bucket,
-        display_name=job_name if job_name else f"Custom job {int(time.time())}",
-        script_path=script_path,
-        container_uri=train_container_uri,
-        requirements=requirements,
-        model_serving_container_image_uri=serving_container_uri,
-    )
-    cmd_args = [
-        f"--train_data={train_data.path}",
-        f"--valid_data={valid_data.path}",
-        f"--test_data={test_data.path}",
-        f"--metrics={metrics.path}",
-        f"--hparams={json.dumps(hparams if hparams else {})}",
-    ]
-    uploaded_model = job.run(
-        model_display_name=model_display_name,
-        parent_model=parent_model,
-        is_default_version=(not parent_model),
-        args=cmd_args,
-        replica_count=replica_count,
-        machine_type=machine_type,
-        accelerator_type=accelerator_type,
-        accelerator_count=accelerator_count,
-    )
-
-    resource_name = f"{uploaded_model.resource_name}@{uploaded_model.version_id}"
-    model.metadata["resourceName"] = resource_name
-    model.metadata["containerSpec"] = {"imageUri": serving_container_uri}
-    model.uri = uploaded_model.uri
-    model.TYPE_NAME = "google.VertexModel"
-
-    with open(metrics.path, "r") as fp:
-        parsed_metrics = json.load(fp)
-
-    logging.info(parsed_metrics)
-    for k, v in parsed_metrics.items():
-        if type(v) is float:
-            metrics.log_metric(k, v)
-
-    # return GCP resource for Vertex AI UI integration
-    custom_job_name = job.to_dict()["trainingTaskMetadata"]["backingCustomJob"]
-    custom_train_job_resources = GcpResources()
-    ctr = custom_train_job_resources.resources.add()
-    ctr.resource_type = "CustomJob"
-    ctr.resource_uri = custom_job_name
-    gcp_resources = MessageToJson(custom_train_job_resources)
-    return (gcp_resources,)
diff --git a/components/vertex-components/src/vertex_components/import_model_evaluation.py b/components/vertex-components/src/vertex_components/import_model_evaluation.py
deleted file mode 100644
index acfec517..00000000
--- a/components/vertex-components/src/vertex_components/import_model_evaluation.py
+++ /dev/null
@@ -1,86 +0,0 @@
-# Copyright 2022 Google LLC
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from kfp.dsl import Input, Model, Metrics, component, Dataset
-from typing import NamedTuple
-
-
-@component(
-    base_image="python:3.7",
-    packages_to_install=[
-        "google-cloud-aiplatform==1.24.1",
-    ],
-)
-def import_model_evaluation(
-    model: Input[Model],
-    metrics: Input[Metrics],
-    test_dataset: Input[Dataset],
-    pipeline_job_id: str,
-    project_location: str,
-    evaluation_name: str = "Imported evaluation",
-) -> NamedTuple("Outputs", [("model_evaluation", str)]):
-    """Import an evaluation result for a model version.
-
-    Args:
-        model (Model): Input model version.
-        metrics (Metrics): Input metrics. The contents of the artifact are expected
-            to follow the evaluation schema linked in the docs:
-            https://cloud.google.com/vertex-ai/docs/evaluation/introduction#features.
-        test_dataset (Dataset): Input test dataset which will be linked to evaluation.
-        pipeline_job_id (str): Pipeline job id which will be linked to evaluation.
-        project_location (str): Location of the Google Cloud project.
-        evaluation_name (str): Display name of model evaluation.
-    Returns:
-        model_evaluation (str): Resource URI of imported model evaluation.
-    """
-    import json
-    import logging
-    from google.cloud.aiplatform_v1 import ModelEvaluation, ModelServiceClient
-    from google.protobuf.json_format import ParseDict
-
-    logging.info(f"Read metrics from: {metrics.path}")
-    with open(metrics.path) as fp:
-        parsed_metrics = json.load(fp)
-    logging.info(f"Parsed metrics: {parsed_metrics}")
-
-    schema_template = (
-        "gs://google-cloud-aiplatform/schema/modelevaluation/%s_metrics_1.0.0.yaml"
-    )
-    schema = schema_template % parsed_metrics.pop("problemType")
-    evaluation = {
-        "displayName": evaluation_name,
-        "metricsSchemaUri": schema,
-        "metrics": parsed_metrics,
-        "metadata": {
-            "pipeline_job_id": pipeline_job_id,
-            "evaluation_dataset_type": "gcs",
-            "evaluation_dataset_path": [test_dataset.uri],
-        },
-    }
-
-    request = ParseDict(evaluation, ModelEvaluation()._pb)
-    logging.info(f"Request: {request}")
-
-    model_name = model.metadata["resourceName"]
-    logging.info(model_name)
-
-    client = ModelServiceClient(
-        client_options={"api_endpoint": project_location + "-aiplatform.googleapis.com"}
-    )
-    response = client.import_model_evaluation(
-        parent=model_name,
-        model_evaluation=request,
-    )
-    logging.info(f"Response: {response}")
-    return (response.name,)
diff --git a/components/vertex-components/src/vertex_components/lookup_model.py b/components/vertex-components/src/vertex_components/lookup_model.py
deleted file mode 100644
index a4d6f3db..00000000
--- a/components/vertex-components/src/vertex_components/lookup_model.py
+++ /dev/null
@@ -1,99 +0,0 @@
-# Copyright 2022 Google LLC
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from kfp.dsl import component, Output, Model
-from typing import NamedTuple
-
-
-@component(
-    base_image="python:3.7",
-    packages_to_install=["google-cloud-aiplatform==1.24.1"],
-)
-def lookup_model(
-    model_name: str,
-    project_location: str,
-    project_id: str,
-    model: Output[Model],
-    order_models_by: str = "create_time desc",
-    fail_on_model_not_found: bool = False,
-) -> NamedTuple("Outputs", [("model_resource_name", str), ("training_dataset", dict)]):
-    """
-    Fetch a model given a model name (display name) and export to GCS.
-
-    Args:
-        model_name (str): display name of the model
-        project_location (str): location of the Google Cloud project
-        project_id (str): project id of the Google Cloud project
-        model (Output[Model]): a Vertex AI model
-        order_models_by (str): if multiple models are found based on the display name,
-            use a filter clause:
-            A comma-separated list of fields to order by, sorted in
-            ascending order. Use "desc" after a field name for descending.
-            Supported fields: `display_name`, `create_time`, `update_time`
-            Defaults to "create_time desc".
-        fail_on_model_not_found (bool): if set to True, raise runtime error if
-            model is not found
-
-    Returns:
-        str: Resource name of the found model. Empty string if model not found.
-    """
-
-    import json
-    import logging
-    import os
-    from pathlib import Path
-    from google.cloud.aiplatform import Model
-
-    TRAINING_DATASET_INFO = "training_dataset.json"
-
-    logging.info(f"listing models with display name {model_name}")
-    models = Model.list(
-        filter=f'display_name="{model_name}"',
-        order_by=order_models_by,
-        location=project_location,
-        project=project_id,
-    )
-    logging.info(f"found {len(models)} models")
-
-    training_dataset = {}
-    model_resource_name = ""
-    if len(models) == 0:
-        logging.error(
-            f"No model found with name {model_name}"
-            + f"(project: {project_id} location: {project_location})"
-        )
-        if fail_on_model_not_found:
-            raise RuntimeError(f"Failed as model was not found")
-    elif len(models) == 1:
-        target_model = models[0]
-        model_resource_name = target_model.resource_name
-        logging.info(f"choosing model by order ({order_models_by})")
-        logging.info(f"model display name: {target_model.display_name}")
-        logging.info(f"model resource name: {target_model.resource_name}")
-        logging.info(f"model uri: {target_model.uri}")
-        model.uri = target_model.uri
-        model.metadata["resourceName"] = target_model.resource_name
-
-        path = Path(model.path) / TRAINING_DATASET_INFO
-        logging.info(f"Reading training dataset metadata: {path}")
-
-        if os.path.exists(path):
-            with open(path, "r") as fp:
-                training_dataset = json.load(fp)
-        else:
-            logging.warning("Training dataset metadata doesn't exist!")
-    else:
-        raise RuntimeError(f"Multiple models with name {model_name} were found.")
-
-    return model_resource_name, training_dataset
diff --git a/components/vertex-components/src/vertex_components/model_batch_predict.py b/components/vertex-components/src/vertex_components/model_batch_predict.py
index 36916ec4..80605a32 100644
--- a/components/vertex-components/src/vertex_components/model_batch_predict.py
+++ b/components/vertex-components/src/vertex_components/model_batch_predict.py
@@ -17,7 +17,7 @@
 
 
 @component(
-    base_image="python:3.7",
+    base_image="python:3.9",
     packages_to_install=[
         "google-cloud-aiplatform==1.24.1",
         "google-cloud-pipeline-components==1.0.33",
diff --git a/components/vertex-components/src/vertex_components/update_best_model.py b/components/vertex-components/src/vertex_components/update_best_model.py
deleted file mode 100644
index 9ec4ff9b..00000000
--- a/components/vertex-components/src/vertex_components/update_best_model.py
+++ /dev/null
@@ -1,87 +0,0 @@
-# Copyright 2022 Google LLC
-from typing import NamedTuple
-
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from kfp.dsl import Input, Model, component
-
-
-@component(
-    base_image="python:3.7",
-    packages_to_install=["google-cloud-aiplatform==1.24.1"],
-)
-def update_best_model(
-    challenger: Input[Model],
-    challenger_evaluation: str,
-    parent_model: str,
-    project_id: str,
-    project_location: str,
-    eval_metric: str,
-    eval_lower_is_better: bool,
-    model_alias: str = "default",
-) -> NamedTuple("Outputs", [("challenger_wins", bool)]):
-    """
-    Args:
-        challenger (Model): Challenger model.
-        challenger_evaluation (str): Resource URI of challenger model evaluation e.g.
-            `projects/.../locations/.../models/.../evaluations/...`
-        parent_model (str): Resource URI of parent model.
-        eval_metric (str): Metric to compare champion and challenger on.
-        eval_lower_is_better (bool): Usually True for losses and
-            False for classification metrics.
-        project_id (str): project id of the Google Cloud project.
-        project_location (str): location of the Google Cloud project.
-        model_alias (str): alias of the parent model.
-    """
-
-    import logging
-    import google.cloud.aiplatform as aip
-    from google.cloud.aiplatform.models import ModelRegistry
-    from google.protobuf.json_format import MessageToDict
-
-    logging.info("Get models...")
-    if model_alias:
-        parent_model += "@" + model_alias
-    champion = aip.Model(parent_model)
-    challenger = aip.Model(challenger.metadata["resourceName"])
-    logging.info(
-        f"Model default version {champion.version_id} "
-        f"is being challenged by version {challenger.version_id}!"
-    )
-
-    eval_champion = challenger.get_model_evaluation()
-    eval_challenger = aip.model_evaluation.ModelEvaluation(challenger_evaluation)
-    metrics_champion = MessageToDict(eval_champion._gca_resource._pb)["metrics"]
-    metrics_challenger = MessageToDict(eval_challenger._gca_resource._pb)["metrics"]
-
-    logging.info(f"Comparing {eval_metric} of models")
-    logging.debug(f"Champion metrics: {metrics_champion}")
-    logging.debug(f"Challenger metrics: {metrics_challenger}")
-
-    m_champ = metrics_champion[eval_metric]
-    m_chall = metrics_challenger[eval_metric]
-    logging.info(f"Champion={m_champ} Challenger={m_chall}")
-
-    challenger_wins = (
-        (m_chall < m_champ) if eval_lower_is_better else (m_chall > m_champ)
-    )
-    if challenger_wins:
-        logging.info(f"Updating champion to version: {challenger.version_id}")
-        model_registry = ModelRegistry(
-            model=champion, project=project_id, location=project_location
-        )
-        model_registry.add_version_aliases(["default"], challenger.version_id)
-        return (True,)
-
-    logging.info(f"Keeping current champion!")
-    return (False,)
diff --git a/components/vertex-components/src/vertex_components/upload_model.py b/components/vertex-components/src/vertex_components/upload_model.py
new file mode 100644
index 00000000..be65b866
--- /dev/null
+++ b/components/vertex-components/src/vertex_components/upload_model.py
@@ -0,0 +1,216 @@
+# Copyright 2022 Google LLC
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+#     https://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from kfp.dsl import Dataset, Input, Metrics, Model, Output, component
+from google_cloud_pipeline_components.types import artifact_types
+
+
+@component(
+    base_image="python:3.9",
+    packages_to_install=[
+        "google-cloud-aiplatform==1.28.1",
+        "google-cloud-pipeline-components==2.1.0",
+    ],
+)
+def upload_model(
+    model: Input[Model],
+    serving_container_image: str,
+    vertex_model: Output[artifact_types.VertexModel],
+    project: str,
+    location: str,
+    model_evaluation: Input[Metrics],
+    eval_metric: str,
+    eval_lower_is_better: bool,
+    model_name: str,
+    pipeline_job_id: str,
+    test_dataset: Input[Dataset],
+    evaluation_name: str = "Imported evaluation",
+    order_models_by: str = "create_time desc",
+) -> None:
+    """
+    Args:
+        challenger (Model): Challenger model.
+        challenger_evaluation (str): Resource URI of challenger model evaluation e.g.
+            `projects/.../locations/.../models/.../evaluations/...`
+        parent_model (str): Resource URI of parent model.
+        eval_metric (str): Metric to compare champion and challenger on.
+        eval_lower_is_better (bool): Usually True for losses and
+            False for classification metrics.
+        project_id (str): project id of the Google Cloud project.
+        project_location (str): location of the Google Cloud project.
+        model_alias (str): alias of the parent model.
+    """
+
+    import json
+    import logging
+    import google.cloud.aiplatform as aip
+    from google.protobuf.json_format import MessageToDict
+
+    def lookup_model(
+        order_models_by: str,
+        location: str,
+        project: str,
+        model_name: str,
+    ) -> aip.Model:
+
+        logging.info(f"listing models with display name {model_name}")
+        logging.info(f"choosing model by order ({order_models_by})")
+        models = aip.Model.list(
+            filter=f'display_name="{model_name}"',
+            order_by=order_models_by,
+            location=location,
+            project=project,
+        )
+        logging.info(f"found {len(models)} models")
+
+        if len(models) == 0:
+            logging.info(
+                f"No model found with name {model_name}"
+                + f"(project: {project} location: {location})"
+            )
+            return None
+        elif len(models) == 1:
+            return models[0]
+        else:
+            raise RuntimeError(f"Multiple models with name {model_name} were found.")
+
+    def compare_models(
+        champion_metrics: dict,
+        challenger_metrics: dict,
+        eval_metric: str,
+        eval_lower_is_better,
+    ) -> bool:
+
+        logging.info(f"Comparing {eval_metric} of models")
+        logging.debug(f"Champion metrics: {champion_metrics}")
+        logging.debug(f"Challenger metrics: {challenger_metrics}")
+
+        m_champ = champion_metrics[eval_metric]
+        m_chall = challenger_metrics[eval_metric]
+        logging.info(f"Champion={m_champ} Challenger={m_chall}")
+
+        challenger_wins = (
+            (m_chall < m_champ) if eval_lower_is_better else (m_chall > m_champ)
+        )
+
+        if challenger_wins:
+            logging.info("Challenger wins!")
+        else:
+            logging.info("Champion wins!")
+
+        return challenger_wins
+
+    def import_evaluation(
+        parsed_metrics: dict,
+        challenger_model: aip.Model,
+        location: str,
+        evaluation_name: str = "Imported evaluation",
+    ):
+        from google.cloud.aiplatform_v1 import ModelEvaluation, ModelServiceClient
+        from google.protobuf.json_format import ParseDict
+
+        logging.info(f"Parsed metrics: {parsed_metrics}")
+
+        schema_template = (
+            "gs://google-cloud-aiplatform/schema/modelevaluation/%s_metrics_1.0.0.yaml"
+        )
+        schema = schema_template % parsed_metrics.pop("problemType")
+        evaluation = {
+            "displayName": evaluation_name,
+            "metricsSchemaUri": schema,
+            "metrics": parsed_metrics,
+            "metadata": {
+                "pipeline_job_id": pipeline_job_id,
+                "evaluation_dataset_type": "gcs",
+                "evaluation_dataset_path": [test_dataset.uri],
+            },
+        }
+
+        request = ParseDict(evaluation, ModelEvaluation()._pb)
+        logging.info(f"Request: {request}")
+
+        model_name = challenger_model.versioned_resource_name
+        logging.info(model_name)
+
+        client = ModelServiceClient(
+            client_options={"api_endpoint": location + "-aiplatform.googleapis.com"}
+        )
+        response = client.import_model_evaluation(
+            parent=model_name,
+            model_evaluation=request,
+        )
+        logging.info(f"Response: {response}")
+        return (response.name,)
+
+    # Parse metrics to dict
+    with open(model_evaluation.path, "r") as f:
+        metrics = json.load(f)
+
+    champion_model = lookup_model(
+        order_models_by=order_models_by,
+        location=location,
+        project=project,
+        model_name=model_name,
+    )
+
+    if champion_model is not None:
+        # Compare models
+        logging.info(
+            f"Model default version {champion_model.version_id} "
+            "is being challenged by new model."
+        )
+        # Look up Vertex model evaluation for champion model
+        eval_champion = champion_model.get_model_evaluation()
+        champion_metrics = MessageToDict(eval_champion._gca_resource._pb)["metrics"]
+
+        # Take challenger metrics as input to this component
+        challenger_metrics = metrics
+
+        challenger_wins = compare_models(
+            champion_metrics=champion_metrics,
+            challenger_metrics=challenger_metrics,
+            eval_metric=eval_metric,
+            eval_lower_is_better=eval_lower_is_better,
+        )
+
+    else:
+        logging.info("No champion model found, uploading new model.")
+        challenger_wins = True
+
+    # Upload model to registry
+    uploaded_model = aip.Model.upload(
+        display_name=model_name,
+        artifact_uri=model.uri,
+        serving_container_image_uri=serving_container_image,
+        parent_model=(
+            champion_model.resource_name if champion_model is not None else None
+        ),
+        is_default_version=challenger_wins,
+        # TODO more model options
+    )
+
+    # Output google.VertexModel artifact
+    vertex_model.uri = (
+        f"https://{location}-aiplatform.googleapis.com/v1/"
+        f"{uploaded_model.versioned_resource_name}"
+    )
+    vertex_model.metadata["resourceName"] = uploaded_model.versioned_resource_name
+
+    # Import evaluation to model registry
+    import_evaluation(
+        location=location,
+        parsed_metrics=metrics,
+        challenger_model=uploaded_model,
+        evaluation_name=evaluation_name,
+    )
diff --git a/env.sh.example b/env.sh.example
index 3e747dfe..e57c7dbb 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -28,3 +28,4 @@ export RESOURCE_SUFFIX=default
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
 export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/${RESOURCE_SUFFIX}
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
+export TRAINING_CONTAINER_IMAGE=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images/training:${RESOURCE_SUFFIX}
diff --git a/pipelines/.python-version b/pipelines/.python-version
index f7e5aa84..9f3d4c17 100644
--- a/pipelines/.python-version
+++ b/pipelines/.python-version
@@ -1 +1 @@
-3.7.12
+3.9.16
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index 5fc4247c..50d59be0 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -1,11 +1,11 @@
-# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
 
 [[package]]
 name = "bigquery-components"
 version = "0.1.0"
 description = "KubeFlow components for BigQuery"
 optional = false
-python-versions = ">=3.7,<3.11"
+python-versions = ">=3.9,<3.11"
 files = []
 develop = true
 
@@ -146,7 +146,6 @@ files = [
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
 [[package]]
 name = "colorama"
@@ -411,12 +410,12 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "2.0.0"
+version = "2.1.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "google_cloud_pipeline_components-2.0.0-py3-none-any.whl", hash = "sha256:4a3708dda8d68989f37d6b4e184e783ab3dc2ff8f0ddf69f5cd4a160603ce252"},
+    {file = "google_cloud_pipeline_components-2.1.0-py3-none-any.whl", hash = "sha256:ddd6afd8e1ab302a3176d60934f289fb609faeacea09292f62d7eb3576e3e321"},
 ]
 
 [package.dependencies]
@@ -696,26 +695,6 @@ files = [
     {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
 ]
 
-[[package]]
-name = "importlib-metadata"
-version = "6.6.0"
-description = "Read metadata from Python packages"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "importlib_metadata-6.6.0-py3-none-any.whl", hash = "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed"},
-    {file = "importlib_metadata-6.6.0.tar.gz", hash = "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"},
-]
-
-[package.dependencies]
-typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
-zipp = ">=0.5"
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-perf = ["ipython"]
-testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
-
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -767,7 +746,6 @@ protobuf = ">=3.13.0,<4"
 PyYAML = ">=5.3,<7"
 requests-toolbelt = ">=0.8.0,<1"
 tabulate = ">=0.8.6,<1"
-typing-extensions = {version = ">=3.7.4,<5", markers = "python_version < \"3.9\""}
 urllib3 = "<2.0.0"
 
 [package.extras]
@@ -940,9 +918,6 @@ files = [
     {file = "platformdirs-3.5.1.tar.gz", hash = "sha256:412dae91f52a6f84830f39a8078cecd0e866cb72294a5c66808e74d5e88d251f"},
 ]
 
-[package.dependencies]
-typing-extensions = {version = ">=4.5", markers = "python_version < \"3.8\""}
-
 [package.extras]
 docs = ["furo (>=2023.3.27)", "proselint (>=0.13)", "sphinx (>=6.2.1)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.3.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"]
@@ -958,9 +933,6 @@ files = [
     {file = "pluggy-1.0.0.tar.gz", hash = "sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159"},
 ]
 
-[package.dependencies]
-importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
-
 [package.extras]
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
@@ -979,7 +951,6 @@ files = [
 [package.dependencies]
 cfgv = ">=2.0.0"
 identify = ">=1.0.0"
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 nodeenv = ">=0.11.1"
 pyyaml = ">=5.1"
 virtualenv = ">=20.10.0"
@@ -1071,7 +1042,6 @@ files = [
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
 exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
-importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
 iniconfig = "*"
 packaging = "*"
 pluggy = ">=0.12,<2.0"
@@ -1307,17 +1277,6 @@ files = [
     {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
 ]
 
-[[package]]
-name = "typing-extensions"
-version = "4.6.3"
-description = "Backported and Experimental Type Hints for Python 3.7+"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "typing_extensions-4.6.3-py3-none-any.whl", hash = "sha256:88a4153d8505aabbb4e13aacb7c486c2b4a33ca3b3f807914a9b4c844c471c26"},
-    {file = "typing_extensions-4.6.3.tar.gz", hash = "sha256:d91d5919357fe7f681a9f2b5b4cb2a5f1ef0a1e9f59c4d8ff0d3491e05c0ffd5"},
-]
-
 [[package]]
 name = "urllib3"
 version = "1.26.16"
@@ -1339,7 +1298,7 @@ name = "vertex-components"
 version = "0.1.0"
 description = "KubeFlow components for Vertex AI"
 optional = false
-python-versions = ">=3.7,<3.11"
+python-versions = ">=3.9,<3.11"
 files = []
 develop = true
 
@@ -1364,7 +1323,6 @@ files = [
 [package.dependencies]
 distlib = ">=0.3.6,<1"
 filelock = ">=3.11,<4"
-importlib-metadata = {version = ">=6.4.1", markers = "python_version < \"3.8\""}
 platformdirs = ">=3.2,<4"
 
 [package.extras]
@@ -1387,22 +1345,7 @@ docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
-[[package]]
-name = "zipp"
-version = "3.15.0"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
-    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
-]
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
-
 [metadata]
 lock-version = "2.0"
-python-versions = ">=3.7,<3.11"
-content-hash = "6360ac432e14023430d2290fcbd782c7693b0365570fd50f4ecc865d04a5718d"
+python-versions = ">=3.9,<3.11"
+content-hash = "8430eb49df1dcdfd43c734f1850e97657a2f1b346cb7407778cf7f4cf1be46a0"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index eb468200..08c07fad 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -7,17 +7,17 @@ readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.7",
+    "Programming Language :: Python :: 3.9",
 ]
 packages = [
     { include = "pipelines", from = "src" },
 ]
 
 [tool.poetry.dependencies]
-python = ">=3.7,<3.11"
+python = ">=3.9,<3.11"
 Jinja2 = ">=3.0.1,<4.0.0"
 google-cloud-aiplatform = "1.24.1"
-google-cloud-pipeline-components = "^2.0.0"
+google-cloud-pipeline-components = "^2.1.0"
 bigquery-components = { path = "../components/bigquery-components", develop = true }
 vertex-components = { path = "../components/vertex-components", develop = true }
 kfp = "^2.0.1"
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 411bc69e..228d7afa 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -17,14 +17,45 @@
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
 from kfp import compiler, dsl
+from kfp.dsl import Dataset, Input, Metrics, Model, Output, OutputPath
 from pipelines import generate_query
 from bigquery_components import extract_bq_to_dataset
-from vertex_components import (
-    lookup_model,
-    custom_train_job,
-    import_model_evaluation,
-    update_best_model,
-)
+from vertex_components import upload_model
+
+IMAGE = os.environ.get("TRAINING_CONTAINER_IMAGE")
+
+
+@dsl.container_component
+def train(
+    train_data: Input[Dataset],
+    valid_data: Input[Dataset],
+    test_data: Input[Dataset],
+    model: Output[Model],
+    model_output_uri: OutputPath(str),
+    metrics: Output[Metrics],  # TODO could be a more specific type of metrics object
+    hparams: dict,
+):
+    return dsl.ContainerSpec(
+        image=IMAGE,
+        command=["python"],
+        args=[
+            "main.py",
+            "--train-data",
+            train_data.path,
+            "--valid-data",
+            valid_data.path,
+            "--test-data",
+            test_data.path,
+            "--model",
+            model.path,
+            "--model-output-uri",
+            model_output_uri,
+            "--metrics",
+            metrics.path,
+            "--hparams",
+            hparams,
+        ],
+    )
 
 
 @dsl.pipeline(name="xgboost-train-pipeline")
@@ -81,7 +112,6 @@ def xgboost_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
-    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_xgb_model.py"
     hparams = dict(
         n_estimators=200,
         early_stopping_rounds=10,
@@ -157,52 +187,27 @@ def xgboost_pipeline(
         .set_caching_options(False)
     ).outputs["dataset"]
 
-    existing_model = (
-        lookup_model(
-            model_name=model_name,
-            project_location=project_location,
-            project_id=project_id,
-            fail_on_model_not_found=False,
-        )
-        .set_display_name("Lookup past model")
-        .set_caching_options(False)
-        .outputs["model_resource_name"]
-    )
-
-    train_model = custom_train_job(
-        train_script_uri=train_script_uri,
+    train_model = train(
         train_data=train_dataset,
         valid_data=valid_dataset,
         test_data=test_dataset,
-        project_id=project_id,
-        project_location=project_location,
-        model_display_name=model_name,
-        train_container_uri="europe-docker.pkg.dev/vertex-ai/training/scikit-learn-cpu.0-23:latest",  # noqa: E501
-        serving_container_uri="europe-docker.pkg.dev/vertex-ai/prediction/sklearn-cpu.0-24:latest",  # noqa: E501
         hparams=hparams,
-        requirements=["scikit-learn==0.24.0"],
-        staging_bucket=staging_bucket,
-        parent_model=existing_model,
     ).set_display_name("Train model")
 
-    evaluation = import_model_evaluation(
+    upload_model_op = upload_model(
+        project=project_id,
+        location=project_location,
+        model_evaluation=train_model.outputs["metrics"],
+        eval_metric=primary_metric,
+        eval_lower_is_better=True,
         model=train_model.outputs["model"],
-        metrics=train_model.outputs["metrics"],
-        test_dataset=test_dataset,
+        serving_container_image=(
+            "europe-docker.pkg.dev/vertex-ai/prediction/sklearn-cpu.0-24:latest"
+        ),
+        model_name=model_name,
         pipeline_job_id="{{$.pipeline_job_name}}",
-        project_location=project_location,
-    ).set_display_name("Import evaluation")
-
-    with dsl.Condition(existing_model != "", "champion-exists"):
-        update_best_model(
-            challenger=train_model.outputs["model"],
-            challenger_evaluation=evaluation.outputs["model_evaluation"],
-            parent_model=existing_model,
-            eval_metric=primary_metric,
-            eval_lower_is_better=True,
-            project_id=project_id,
-            project_location=project_location,
-        ).set_display_name("Update best model")
+        test_dataset=test_dataset,
+    ).set_display_name("Upload model")
 
 
 if __name__ == "__main__":
diff --git a/terraform/modules/vertex_deployment/main.tf b/terraform/modules/vertex_deployment/main.tf
index 35498a20..b0a808ee 100644
--- a/terraform/modules/vertex_deployment/main.tf
+++ b/terraform/modules/vertex_deployment/main.tf
@@ -122,3 +122,13 @@ resource "google_vertex_ai_metadata_store" "default_metadata_store" {
   region      = var.region
   depends_on  = [google_project_service.gcp_services]
 }
+
+## Artifact Registry ##
+resource "google_artifact_registry_repository" "vertex-images" {
+  repository_id = "vertex-images"
+  description   = "Container image repository for training container images"
+  project       = var.project_id
+  location      = var.region
+  format        = "DOCKER"
+  depends_on    = [google_project_service.gcp_services]
+}
diff --git a/training/.gitignore b/training/.gitignore
new file mode 100644
index 00000000..4414fc1e
--- /dev/null
+++ b/training/.gitignore
@@ -0,0 +1 @@
+requirements.txt
diff --git a/training/Dockerfile b/training/Dockerfile
new file mode 100644
index 00000000..bf4587f2
--- /dev/null
+++ b/training/Dockerfile
@@ -0,0 +1,8 @@
+FROM python:3.9.16-slim
+ENV PIP_NO_CACHE_DIR=off \
+    PIP_DISABLE_PIP_VERSION_CHECK=on \
+    PIP_DEFAULT_TIMEOUT=100
+
+COPY requirements.txt requirements.txt
+RUN pip install -r requirements.txt
+COPY main.py main.py
diff --git a/training/main.py b/training/main.py
new file mode 100644
index 00000000..18486e2d
--- /dev/null
+++ b/training/main.py
@@ -0,0 +1,147 @@
+import argparse
+from pathlib import Path
+
+import joblib
+import json
+import os
+import logging
+
+import numpy as np
+import pandas as pd
+from sklearn import metrics
+from sklearn.compose import ColumnTransformer
+from sklearn.pipeline import Pipeline
+from sklearn.preprocessing import StandardScaler, OrdinalEncoder, OneHotEncoder
+from xgboost import XGBRegressor
+
+logging.basicConfig(level=logging.DEBUG)
+
+# used for monitoring during prediction time
+TRAINING_DATASET_INFO = "training_dataset.json"
+# numeric/categorical features in Chicago trips dataset to be preprocessed
+NUM_COLS = ["dayofweek", "hourofday", "trip_distance", "trip_miles", "trip_seconds"]
+ORD_COLS = ["company"]
+OHE_COLS = ["payment_type"]
+
+
+def split_xy(df: pd.DataFrame, label: str) -> (pd.DataFrame, pd.Series):
+    """Split dataframe into X and y."""
+    return df.drop(columns=[label]), df[label]
+
+
+def indices_in_list(elements: list, base_list: list) -> list:
+    """Get indices of specific elements in a base list"""
+    return [idx for idx, elem in enumerate(base_list) if elem in elements]
+
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--train-data", type=str, required=True)
+parser.add_argument("--valid-data", type=str, required=True)
+parser.add_argument("--test-data", type=str, required=True)
+parser.add_argument("--model", default=os.getenv("AIP_MODEL_DIR"), type=str, help="")
+parser.add_argument("--model-output-uri", type=str)
+parser.add_argument("--metrics", type=str, required=True)
+parser.add_argument("--hparams", default={}, type=json.loads)
+args = parser.parse_args()
+
+if args.model.startswith("gs://"):
+    args.model = "/gcs/" + args.model[5:]
+
+logging.info("Read csv files into dataframes")
+df_train = pd.read_csv(args.train_data)
+df_valid = pd.read_csv(args.valid_data)
+df_test = pd.read_csv(args.test_data)
+
+logging.info("Split dataframes")
+label = args.hparams["label"]
+X_train, y_train = split_xy(df_train, label)
+X_valid, y_valid = split_xy(df_valid, label)
+X_test, y_test = split_xy(df_test, label)
+
+logging.info("Get the number of unique categories for ordinal encoded columns")
+ordinal_columns = X_train[ORD_COLS]
+n_unique_cat = ordinal_columns.nunique()
+
+logging.info("Get indices of columns in base data")
+col_list = X_train.columns.tolist()
+num_indices = indices_in_list(NUM_COLS, col_list)
+cat_indices_onehot = indices_in_list(OHE_COLS, col_list)
+cat_indices_ordinal = indices_in_list(ORD_COLS, col_list)
+
+ordinal_transformers = [
+    (
+        f"ordinal encoding for {ord_col}",
+        OrdinalEncoder(
+            handle_unknown="use_encoded_value", unknown_value=n_unique_cat[ord_col]
+        ),
+        [ord_index],
+    )
+    for ord_col in ORD_COLS
+    for ord_index in cat_indices_ordinal
+]
+all_transformers = [
+    ("numeric_scaling", StandardScaler(), num_indices),
+    (
+        "one_hot_encoding",
+        OneHotEncoder(handle_unknown="ignore"),
+        cat_indices_onehot,
+    ),
+] + ordinal_transformers
+
+logging.info("Build sklearn preprocessing steps")
+preprocesser = ColumnTransformer(transformers=all_transformers)
+logging.info("Build sklearn pipeline with XGBoost model")
+xgb_model = XGBRegressor(**args.hparams)
+
+pipeline = Pipeline(
+    steps=[("feature_engineering", preprocesser), ("train_model", xgb_model)]
+)
+
+logging.info("Transform validation data")
+valid_preprocesser = preprocesser.fit(X_train)
+X_valid_transformed = valid_preprocesser.transform(X_valid)
+
+logging.info("Fit model")
+pipeline.fit(X_train, y_train, train_model__eval_set=[(X_valid_transformed, y_valid)])
+
+logging.info("Predict test data")
+y_pred = pipeline.predict(X_test)
+y_pred = y_pred.clip(0)
+
+metrics = {
+    "problemType": "regression",
+    "rootMeanSquaredError": np.sqrt(metrics.mean_squared_error(y_test, y_pred)),
+    "meanAbsoluteError": metrics.mean_absolute_error(y_test, y_pred),
+    "meanAbsolutePercentageError": metrics.mean_absolute_percentage_error(
+        y_test, y_pred
+    ),
+    "rSquared": metrics.r2_score(y_test, y_pred),
+    "rootMeanSquaredLogError": np.sqrt(metrics.mean_squared_log_error(y_test, y_pred)),
+}
+
+logging.info(f"Save model to: {args.model}")
+Path(args.model).mkdir(parents=True)
+joblib.dump(pipeline, f"{args.model}/model.joblib")
+
+model_uri = "gs://" + args.model[5:]
+with open(args.model_output_uri, "w") as f:
+    f.write(model_uri)
+
+logging.info(f"Metrics: {metrics}")
+with open(args.metrics, "w") as fp:
+    json.dump(metrics, fp)
+
+# Persist URIs of training file(s) for model monitoring in batch predictions
+# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
+# for the expected schema.
+path = f"{args.model}/{TRAINING_DATASET_INFO}"
+training_dataset_for_monitoring = {
+    "gcsSource": {"uris": [args.train_data]},
+    "dataFormat": "csv",
+    "targetField": label,
+}
+logging.info(f"Training dataset info: {training_dataset_for_monitoring}")
+
+with open(path, "w") as fp:
+    logging.info(f"Save training dataset info for model monitoring: {path}")
+    json.dump(training_dataset_for_monitoring, fp)
diff --git a/training/poetry.lock b/training/poetry.lock
new file mode 100644
index 00000000..611c8c73
--- /dev/null
+++ b/training/poetry.lock
@@ -0,0 +1,283 @@
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+
+[[package]]
+name = "joblib"
+version = "1.3.1"
+description = "Lightweight pipelining with Python functions"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "joblib-1.3.1-py3-none-any.whl", hash = "sha256:89cf0529520e01b3de7ac7b74a8102c90d16d54c64b5dd98cafcd14307fdf915"},
+    {file = "joblib-1.3.1.tar.gz", hash = "sha256:1f937906df65329ba98013dc9692fe22a4c5e4a648112de500508b18a21b41e3"},
+]
+
+[[package]]
+name = "numpy"
+version = "1.25.1"
+description = "Fundamental package for array computing in Python"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "numpy-1.25.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:77d339465dff3eb33c701430bcb9c325b60354698340229e1dff97745e6b3efa"},
+    {file = "numpy-1.25.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d736b75c3f2cb96843a5c7f8d8ccc414768d34b0a75f466c05f3a739b406f10b"},
+    {file = "numpy-1.25.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4a90725800caeaa160732d6b31f3f843ebd45d6b5f3eec9e8cc287e30f2805bf"},
+    {file = "numpy-1.25.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c6c9261d21e617c6dc5eacba35cb68ec36bb72adcff0dee63f8fbc899362588"},
+    {file = "numpy-1.25.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0def91f8af6ec4bb94c370e38c575855bf1d0be8a8fbfba42ef9c073faf2cf19"},
+    {file = "numpy-1.25.1-cp310-cp310-win32.whl", hash = "sha256:fd67b306320dcadea700a8f79b9e671e607f8696e98ec255915c0c6d6b818503"},
+    {file = "numpy-1.25.1-cp310-cp310-win_amd64.whl", hash = "sha256:c1516db588987450b85595586605742879e50dcce923e8973f79529651545b57"},
+    {file = "numpy-1.25.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6b82655dd8efeea69dbf85d00fca40013d7f503212bc5259056244961268b66e"},
+    {file = "numpy-1.25.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:e8f6049c4878cb16960fbbfb22105e49d13d752d4d8371b55110941fb3b17800"},
+    {file = "numpy-1.25.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:41a56b70e8139884eccb2f733c2f7378af06c82304959e174f8e7370af112e09"},
+    {file = "numpy-1.25.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d5154b1a25ec796b1aee12ac1b22f414f94752c5f94832f14d8d6c9ac40bcca6"},
+    {file = "numpy-1.25.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:38eb6548bb91c421261b4805dc44def9ca1a6eef6444ce35ad1669c0f1a3fc5d"},
+    {file = "numpy-1.25.1-cp311-cp311-win32.whl", hash = "sha256:791f409064d0a69dd20579345d852c59822c6aa087f23b07b1b4e28ff5880fcb"},
+    {file = "numpy-1.25.1-cp311-cp311-win_amd64.whl", hash = "sha256:c40571fe966393b212689aa17e32ed905924120737194b5d5c1b20b9ed0fb171"},
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+    {file = "scipy-1.9.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:5a04cd7d0d3eff6ea4719371cbc44df31411862b9646db617c99718ff68d4840"},
+    {file = "scipy-1.9.3-cp38-cp38-macosx_12_0_arm64.whl", hash = "sha256:545c83ffb518094d8c9d83cce216c0c32f8c04aaf28b92cc8283eda0685162d5"},
+    {file = "scipy-1.9.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0d54222d7a3ba6022fdf5773931b5d7c56efe41ede7f7128c7b1637700409108"},
+    {file = "scipy-1.9.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cff3a5295234037e39500d35316a4c5794739433528310e117b8a9a0c76d20fc"},
+    {file = "scipy-1.9.3-cp38-cp38-win_amd64.whl", hash = "sha256:2318bef588acc7a574f5bfdff9c172d0b1bf2c8143d9582e05f878e580a3781e"},
+    {file = "scipy-1.9.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:d644a64e174c16cb4b2e41dfea6af722053e83d066da7343f333a54dae9bc31c"},
+    {file = "scipy-1.9.3-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:da8245491d73ed0a994ed9c2e380fd058ce2fa8a18da204681f2fe1f57f98f95"},
+    {file = "scipy-1.9.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4db5b30849606a95dcf519763dd3ab6fe9bd91df49eba517359e450a7d80ce2e"},
+    {file = "scipy-1.9.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c68db6b290cbd4049012990d7fe71a2abd9ffbe82c0056ebe0f01df8be5436b0"},
+    {file = "scipy-1.9.3-cp39-cp39-win_amd64.whl", hash = "sha256:5b88e6d91ad9d59478fafe92a7c757d00c59e3bdc3331be8ada76a4f8d683f58"},
+    {file = "scipy-1.9.3.tar.gz", hash = "sha256:fbc5c05c85c1a02be77b1ff591087c83bc44579c6d2bd9fb798bb64ea5e1a027"},
+]
+
+[package.dependencies]
+numpy = ">=1.18.5,<1.26.0"
+
+[package.extras]
+dev = ["flake8", "mypy", "pycodestyle", "typing_extensions"]
+doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-panels (>=0.5.2)", "sphinx-tabs"]
+test = ["asv", "gmpy2", "mpmath", "pytest", "pytest-cov", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
+
+[[package]]
+name = "six"
+version = "1.16.0"
+description = "Python 2 and 3 compatibility utilities"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
+    {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
+    {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
+]
+
+[[package]]
+name = "threadpoolctl"
+version = "3.1.0"
+description = "threadpoolctl"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "threadpoolctl-3.1.0-py3-none-any.whl", hash = "sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b"},
+    {file = "threadpoolctl-3.1.0.tar.gz", hash = "sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380"},
+]
+
+[[package]]
+name = "tzdata"
+version = "2023.3"
+description = "Provider of IANA time zone data"
+optional = false
+python-versions = ">=2"
+files = [
+    {file = "tzdata-2023.3-py2.py3-none-any.whl", hash = "sha256:7e65763eef3120314099b6939b5546db7adce1e7d6f2e179e3df563c70511eda"},
+    {file = "tzdata-2023.3.tar.gz", hash = "sha256:11ef1e08e54acb0d4f95bdb1be05da659673de4acbd21bf9c69e94cc5e907a3a"},
+]
+
+[[package]]
+name = "xgboost"
+version = "1.7.6"
+description = "XGBoost Python Package"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "xgboost-1.7.6-py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.macosx_12_0_x86_64.whl", hash = "sha256:4c34675b4d2678c624ddde5d45361e7e16046923e362e4e609b88353e6b87124"},
+    {file = "xgboost-1.7.6-py3-none-macosx_12_0_arm64.whl", hash = "sha256:59b4b366d2cafc7f645e87d897983a5b59be02876194b1d213bd8d8b811d8ce8"},
+    {file = "xgboost-1.7.6-py3-none-manylinux2014_aarch64.whl", hash = "sha256:281c3c6f4fbed2d36bf95cd02a641afa95e72e9abde70064056da5e76233e8df"},
+    {file = "xgboost-1.7.6-py3-none-manylinux2014_x86_64.whl", hash = "sha256:b1d5db49b199152d62bd9217c98760207d3de86d2b9d243260c573ffe638f80a"},
+    {file = "xgboost-1.7.6-py3-none-win_amd64.whl", hash = "sha256:127cf1f5e2ec25cd41429394c6719b87af1456ce583e89f0bffd35d02ad18bcb"},
+    {file = "xgboost-1.7.6.tar.gz", hash = "sha256:1c527554a400445e0c38186039ba1a00425dcdb4e40b37eed0e74cb39a159c47"},
+]
+
+[package.dependencies]
+numpy = "*"
+scipy = "*"
+
+[package.extras]
+dask = ["dask", "distributed", "pandas"]
+datatable = ["datatable"]
+pandas = ["pandas"]
+plotting = ["graphviz", "matplotlib"]
+pyspark = ["cloudpickle", "pyspark", "scikit-learn"]
+scikit-learn = ["scikit-learn"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.9"
+content-hash = "5bcbe70fcb0085df96641192352231b73948cafcdaa211acffd4b4091e70c874"
diff --git a/training/pyproject.toml b/training/pyproject.toml
new file mode 100644
index 00000000..ad6df515
--- /dev/null
+++ b/training/pyproject.toml
@@ -0,0 +1,17 @@
+[tool.poetry]
+name = "training"
+version = "0.1.0"
+description = ""
+authors = ["Your Name <you@example.com>"]
+readme = "README.md"
+
+[tool.poetry.dependencies]
+python = "^3.9"
+scikit-learn = "^1.3.0"
+xgboost = "^1.7.6"
+pandas = "^2.0.3"
+
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

From 0a2ffebdf120edb2ea1c283757fe9d35f33dc512 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 25 Jul 2023 13:42:36 +0100
Subject: [PATCH 126/238] feat: replace docker build with gcloud build

---
 Makefile                                       | 7 +++++--
 terraform/modules/vertex_deployment/main.tf    | 8 ++++----
 terraform/modules/vertex_deployment/outputs.tf | 4 ++--
 training/.gcloudignore                         | 2 ++
 4 files changed, 13 insertions(+), 8 deletions(-)
 create mode 100644 training/.gcloudignore

diff --git a/Makefile b/Makefile
index d441b7f7..eb62931e 100644
--- a/Makefile
+++ b/Makefile
@@ -109,5 +109,8 @@ destroy-infra: ## DESTROY the Terraform infrastructure in your project. Requires
 build-training-container: ## Build and push training container image using Docker
 	@ cd training && \
 	poetry export -f requirements.txt -o requirements.txt && \
-	docker build -t ${TRAINING_CONTAINER_IMAGE} . && \
-	docker push ${TRAINING_CONTAINER_IMAGE}
+	gcloud builds submit . \
+	--tag=${TRAINING_CONTAINER_IMAGE} \
+	--region=${VERTEX_LOCATION} \
+	--project=${VERTEX_PROJECT_ID} \
+	--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source
diff --git a/terraform/modules/vertex_deployment/main.tf b/terraform/modules/vertex_deployment/main.tf
index b0a808ee..335ca64f 100644
--- a/terraform/modules/vertex_deployment/main.tf
+++ b/terraform/modules/vertex_deployment/main.tf
@@ -75,9 +75,9 @@ resource "google_pubsub_topic" "pipeline_trigger_topic" {
   depends_on = [google_project_service.gcp_services]
 }
 
-# Cloud Function staging bucket
-resource "google_storage_bucket" "cf_staging_bucket" {
-  name                        = "${var.project_id}-cf-staging"
+# Cloud Function / Cloud Build staging bucket
+resource "google_storage_bucket" "staging_bucket" {
+  name                        = "${var.project_id}-staging"
   location                    = local.cloudfunction_region
   project                     = var.project_id
   uniform_bucket_level_access = true
@@ -93,7 +93,7 @@ module "cloudfunction" {
   function_name                 = var.cloudfunction_name
   description                   = var.cloudfunction_description
   source_dir                    = "../../../pipelines/src/pipelines/trigger"
-  source_code_bucket_name       = google_storage_bucket.cf_staging_bucket.name
+  source_code_bucket_name       = google_storage_bucket.staging_bucket.name
   runtime                       = "python39"
   entry_point                   = "cf_handler"
   cf_service_account            = google_service_account.vertex_cloudfunction_sa.email
diff --git a/terraform/modules/vertex_deployment/outputs.tf b/terraform/modules/vertex_deployment/outputs.tf
index 80bd3462..608e9bcc 100644
--- a/terraform/modules/vertex_deployment/outputs.tf
+++ b/terraform/modules/vertex_deployment/outputs.tf
@@ -18,8 +18,8 @@ output "pubsub_topic_id" {
   value = google_pubsub_topic.pipeline_trigger_topic.id
 }
 
-output "cf_staging_bucket_name" {
-  value = google_storage_bucket.cf_staging_bucket.name
+output "staging_bucket_name" {
+  value = google_storage_bucket.staging_bucket.name
 }
 
 output "pipeline_root_bucket_name" {
diff --git a/training/.gcloudignore b/training/.gcloudignore
new file mode 100644
index 00000000..510bf9ce
--- /dev/null
+++ b/training/.gcloudignore
@@ -0,0 +1,2 @@
+.venv
+.DS_Store

From e612b31d8f0db7876e73c5d9fe377f0acc394f18 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 25 Jul 2023 17:27:11 +0100
Subject: [PATCH 127/238] feat: replace GCS buckets with KFP AR for compiled
 pipelines and remove assets bucket

---
 .gitignore                                    |   1 +
 CONTRIBUTING.md                               |   9 -
 Makefile                                      |  29 +-
 README.md                                     |  25 +-
 cloudbuild/README.md                          |   8 +-
 cloudbuild/e2e-test.yaml                      |  17 +-
 cloudbuild/release.yaml                       |  32 +-
 components/vertex-components/README.md        |   7 +-
 .../src/vertex_components/__init__.py         |   8 -
 .../src/vertex_components/upload_model.py     |   1 -
 .../tests/test_custom_training_job.py         | 103 ------
 docs/PRODUCTION.md                            |  34 +-
 docs/TESTING_SETUP.md                         |  17 +-
 docs/images/cf_view.png                       | Bin 79756 -> 80012 bytes
 env.sh.example                                |   1 -
 pipelines/assets/.gitkeep                     |   0
 pipelines/assets/train_tf_model.py            | 299 ------------------
 pipelines/assets/train_xgb_model.py           | 142 ---------
 .../tensorflow/prediction/pipeline.py         |  12 +-
 .../pipelines/tensorflow/training/pipeline.py |  15 +-
 .../src/pipelines/utils/upload_pipeline.py    |  19 ++
 .../pipelines/xgboost/prediction/pipeline.py  |  12 +-
 .../pipelines/xgboost/training/pipeline.py    |  18 +-
 .../scheduled_jobs.auto.tfvars.example        |  20 +-
 terraform/modules/vertex_deployment/iam.tf    |  22 --
 terraform/modules/vertex_deployment/main.tf   |  21 +-
 .../modules/vertex_deployment/outputs.tf      |   4 -
 27 files changed, 97 insertions(+), 779 deletions(-)
 delete mode 100644 components/vertex-components/tests/test_custom_training_job.py
 delete mode 100644 pipelines/assets/.gitkeep
 delete mode 100644 pipelines/assets/train_tf_model.py
 delete mode 100644 pipelines/assets/train_xgb_model.py
 create mode 100644 pipelines/src/pipelines/utils/upload_pipeline.py

diff --git a/.gitignore b/.gitignore
index 930b7889..e879a6d6 100644
--- a/.gitignore
+++ b/.gitignore
@@ -165,3 +165,4 @@ env.sh
 
 # Compiled pipelines
 **/*pipeline.json
+**/*pipeline.yaml
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 39ee273e..905de864 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -271,12 +271,3 @@ make help
 Some of these rules use the environment variables specified in [`env.sh`](env.sh).
 
 **It is not expected that you will need to change the Makefile or create a new one.**
-
-## Assets folder
-
-For a brief description of the Assets folder, please refer to our [general documentation](README.md#Assets). 
-To make sure that assets are available while running the ML pipelines, `make run` ensure that these will be uploaded automatically to the respective Google Cloud Storage locations.
-
-### Common assets
-
-Within the [assets](./assets/) folder, there are common files stored which need to be uploaded to Google Cloud Storage so that the pipelines running Vertex AI can consume such assets, namely:
diff --git a/Makefile b/Makefile
index eb62931e..179d929c 100644
--- a/Makefile
+++ b/Makefile
@@ -33,9 +33,9 @@ test-trigger: ## Runs unit tests for the pipeline trigger code
 	@cd pipelines && \
 	poetry run python -m pytest tests/trigger
 
-compile-pipeline: ## Compile the pipeline to training.json or prediction.json. Must specify pipeline=<training|prediction>
+compile-pipeline: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
 	@cd pipelines/src && \
-	poetry run python -m pipelines.${PIPELINE_TEMPLATE}.${pipeline}.pipeline
+	poetry run kfp dsl compile --py pipelines/${PIPELINE_TEMPLATE}/${pipeline}/pipeline.py --output pipelines/${PIPELINE_TEMPLATE}/${pipeline}/pipeline.yaml --function pipeline
 
 setup-components: ## Run unit tests for a component group
 	@cd "components/${GROUP}" && \
@@ -71,28 +71,13 @@ test-all-components-coverage: ## Run tests with coverage
 		$(MAKE) test-components-coverage GROUP=$$(basename $$component_group) ; \
 	done
 
-sync-assets: ## Sync assets folder to GCS.
-	@if [ -d "./pipelines/assets/" ]; then \
-		echo "Syncing assets to GCS"; \
-		gsutil -m rsync -r -d ./pipelines/assets $(PIPELINE_FILES_GCS_PATH)/assets ; \
-	else \
-		echo "No assets folder found"; \
-	fi;
-
-run: ## Compile pipeline, copy assets to GCS, and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
+run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
 	@ $(MAKE) compile-pipeline && \
-	$(MAKE) sync-assets && \
 	cd pipelines/src && \
-	poetry run python -m pipelines.trigger --template_path=./$(pipeline).json --enable_caching=$(enable_pipeline_caching)
-
-sync_assets ?= true
-e2e-tests: ## (Optionally) copy assets to GCS, and perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour). Optionally specify sync_assets=<true|false> (defaults to true)
-	@if [ $$sync_assets = true ] ; then \
-        $(MAKE) sync-assets; \
-	else \
-		echo "Skipping syncing assets to GCS"; \
-    fi && \
-	cd pipelines && \
+	poetry run python -m pipelines.trigger --template_path=pipelines/${PIPELINE_TEMPLATE}/${pipeline}/pipeline.yaml --enable_caching=$(enable_pipeline_caching)
+
+e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour).
+	@ cd pipelines && \
 	poetry run pytest --log-cli-level=INFO tests/${PIPELINE_TEMPLATE}/$(pipeline) --enable_caching=$(enable_pipeline_caching)
 
 env ?= dev
diff --git a/README.md b/README.md
index 6fcd6069..efc9196c 100644
--- a/README.md
+++ b/README.md
@@ -74,7 +74,7 @@ The cloud infrastructure is managed using Terraform and is defined in the [`terr
 
 - `cloudfunction` - deploys a (Pub/Sub-triggered) Cloud Function from local source code
 - `scheduled_pipelines` - deploys Cloud Scheduler jobs that will trigger Vertex Pipeline runs (via the above Cloud Function)
-- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, service accounts, and IAM permissions.
+- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, Artifact Registry repos, service accounts, and IAM permissions.
 
 There is a Terraform configuration for each environment (dev/test/prod) under [`terraform/envs`](terraform/envs/).
 
@@ -158,6 +158,14 @@ bq mk --transfer_config \
   --params='{"source_dataset_id":"'"chicago_taxi_trips"'","source_project_id":"'"bigquery-public-data"'"}'
 ```
 
+#### Building the training container image
+
+Build the container image and push it to Artifact Registry with:
+
+```bash
+make build-training-container
+```
+
 #### Running Pipelines
 
 You can run the XGBoost training pipeline (for example) with:
@@ -175,7 +183,6 @@ make run pipeline=<training|prediction>
 This will execute the pipeline using the chosen template on Vertex AI, namely it will:
 
 1. Compile the pipeline using the Kubeflow Pipelines SDK
-1. Copy the `assets` folders to Cloud Storage
 1. Trigger the pipeline with the help of `pipelines/trigger/main.py`
 
 To avoid resource conflicts when running pipelines concurrently in the same Google Cloud project with multiple developers, populate the `RESOURCE_SUFFIX` environment variable in your `env.sh` file. This will append your defined suffix to Google resources and ensure each developer's resources remain unique and separate, preventing unintentional overwriting.
@@ -186,12 +193,6 @@ The ML pipelines have input parameters. As you can see in the pipeline definitio
 
 When triggering ad hoc runs in your dev/sandbox environment, or when running the E2E tests in CI, these default values are used. For the test and production deployments, the pipeline parameters are defined in the Terraform code for the Cloud Scheduler jobs (`terraform/envs/<test|prod>/variables.auto.tfvars`).
 
-### Assets
-
-The folder `pipelines/assets/` can be used for any additional files that may be needed during execution of the pipelines. 
-Most importantly this can include your training scripts.
-This directory is rsync'd to Google Cloud Storage when running a pipeline in the sandbox environment or as part of the CD pipeline (see [CI/CD setup](cloudbuild/README.md)).
-
 ## Testing
 
 Unit tests and end-to-end (E2E) pipeline tests are performed using [pytest](https://docs.pytest.org). 
@@ -211,7 +212,7 @@ make test-components GROUP=vertex-components
 To run end-to-end tests of a single pipeline, you can use:
 
 ```
-make e2e-tests pipeline=<training|prediction> [ enable_caching=<true|false> ] [ sync_assets=<true|false> ]
+make e2e-tests pipeline=<training|prediction> [ enable_caching=<true|false> ]
 ```
 
 There are also unit tests for the pipeline triggering code. 
@@ -245,8 +246,8 @@ To schedule pipelines into an environment, you will need to provide the `cloud_s
 There are five CI/CD pipelines located under the [cloudbuild](cloudbuild) directory:
 
 1. `pr-checks.yaml` - runs pre-commit checks and unit tests on the custom KFP components, and checks that the ML pipelines (training and prediction) can compile.
-2. `e2e-test.yaml` - copies the "assets" folders to the chosen GCS destination (versioned by git commit hash - see below) and runs end-to-end tests of the training and prediction pipeline.
-3. `release.yaml` - Compiles the training and prediction pipelines, and copies the compiled pipelines, along with their respective `assets` directories, to Google Cloud Storage in the build / CI/CD environment. The Google Cloud Storage destination is namespaced using the git tag (see below). Following this, the E2E tests are run on the new compiled pipelines.
+2. `e2e-test.yaml` - runs end-to-end tests of the training and prediction pipeline.
+3. `release.yaml` - Compiles the training and prediction pipelines, and copies the compiled pipelines to Google Cloud Storage in the build / CI/CD environment. The Google Cloud Storage destination is namespaced using the git tag (see below). Following this, the E2E tests are run on the new compiled pipelines.
 
 Below is a diagram of how the files are published in each environment in the `e2e-test.yaml` and `release.yaml` pipelines:
 
@@ -255,8 +256,6 @@ Below is a diagram of how the files are published in each environment in the `e2
 └── TAG_NAME or GIT COMMIT HASH <-- Git tag used for the release (release.yaml) OR git commit hash (e2e-test.yaml)
     ├── training.json
     ├── prediction.json
-    ├── assets
-    │   └── some_useful_file.json
 ```
 
 4. `terraform-plan.yaml` - Checks the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`), and produces a summary of any proposed changes that will be applied on merge to the main branch.
diff --git a/cloudbuild/README.md b/cloudbuild/README.md
index d541b034..7adc610f 100644
--- a/cloudbuild/README.md
+++ b/cloudbuild/README.md
@@ -21,8 +21,8 @@ limitations under the License.
 There are five CI/CD pipelines
 
 1. `pr-checks.yaml` - runs pre-commit checks and unit tests on the custom KFP components, and checks that the ML pipelines (training and prediction) can compile.
-1. `e2e-test.yaml` - copies the "assets" folder to the chosen GCS destination (versioned by git commit hash) and runs end-to-end tests of the training and prediction pipeline.
-1. `release.yaml` - compiles training and prediction pipelines, then copies the compiled pipelines and "assets" folder to the chosen GCS destination (versioned by git tag).
+1. `e2e-test.yaml` - runs end-to-end tests of the training and prediction pipeline.
+1. `release.yaml` - compiles training and prediction pipelines, then copies the compiled pipelines to the chosen GCS destination (versioned by git tag).
 1. `terraform-plan.yaml` - Checks the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`), and produces a summary of any proposed changes that will be applied on merge to the main branch.
 1. `terraform-apply.yaml` - Applies the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`).
 
@@ -61,7 +61,6 @@ Set up a trigger for the `e2e-test.yaml` pipeline, and provide substitution valu
 
 | Variable | Description | Suggested value |
 |---|---|---|
-| `_PIPELINE_PUBLISH_GCS_PATH` | The GCS folder (i.e. path prefix) where the pipeline files will be copied to. See the [Assets](../README.md#assets) section of the main README for more information. | `gs://<Project ID for dev environment>-pl-assets/e2e-tests` |
 | `_PIPELINE_TEMPLATE` | The set of pipelines in the repo that you would like to use - i.e. the subfolder under `pipelines` where your pipelines live. | Currently, can be either `xgboost` or `tensorflow`. |
 | `_TEST_VERTEX_CMEK_IDENTIFIER` | Optional. ID of the CMEK (Customer Managed Encryption Key) that you want to use for the ML pipeline runs in the E2E tests as part of the CI/CD pipeline with the format `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key` | Leave blank |
 | `_TEST_VERTEX_LOCATION` | The Google Cloud region where you want to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | Your chosen Google Cloud region |
@@ -69,7 +68,6 @@ Set up a trigger for the `e2e-test.yaml` pipeline, and provide substitution valu
 | `_TEST_VERTEX_PIPELINE_ROOT` | The GCS folder (i.e. path prefix) that you want to use for the pipeline artifacts and for passing data between stages in the pipeline. Used during the pipeline runs in the E2E tests as part of the CI/CD pipeline. | `gs://<Project ID for dev environment>-pl-root` |
 | `_TEST_VERTEX_PROJECT_ID` | Google Cloud project ID in which you want to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | Project ID for the dev environment |
 | `_TEST_VERTEX_SA_EMAIL` | Email address of the service account you want to use to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | `vertex-pipelines@<Project ID for dev environment>.iam.gserviceaccount.com` |
-| `_TEST_TRAIN_STATS_GCS_PATH` | GCS path to use for storing the statistics computed about the training dataset used in the training pipeline. | `gs://<Project ID for dev environment>-pl-root/train_stats/train.stats` |
 | `_TEST_ENABLE_PIPELINE_CACHING` | Override the default caching behaviour of the ML pipelines. Leave blank to use the default caching behaviour. | `False` |
 
 We recommend to enable comment control for this trigger (select `Required` under `Comment Control`). This will mean that the end-to-end tests will only run once a repository collaborator or owner comments `/gcbrun` on the pull request.
@@ -89,7 +87,7 @@ Set up a trigger for the `release.yaml` pipeline, and provide substitution value
 
 | Variable | Description | Suggested value |
 |---|---|---|
-| `_PIPELINE_PUBLISH_GCS_PATHS` | The (space separated) GCS folders (plural!) where the pipeline files (compiled pipelines + pipeline assets) will be copied to. See the [Assets](../README.md#assets) section of the main README for more information. | `gs://<Project ID for dev environment>-pl-assets gs://<Project ID for test environment>-pl-assets gs://<Project ID for prod environment>-pl-assets` |
+| `_PIPELINE_PUBLISH_AR_PATHS` | The (space separated) Artifact Registry repositories (plural!) where the compiled pipelines will be copied to. | `gs://europe-west2-kfp.pkg.dev/<Project ID for dev environment>/vertex-pipelines gs://europe-west2-kfp.pkg.dev/<Project ID for test environment>/vertex-pipelines gs://europe-west2-kfp.pkg.dev/<Project ID for prod environment>/vertex-pipelines` |
 | `_PIPELINE_TEMPLATE` | The set of pipelines in the repo that you would like to use - i.e. the subfolder under `pipelines` where your pipelines live. | Currently, can be either `xgboost` or `tensorflow`. |
 
 ### On merge to `main` / `master` branch
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index b3d054da..2a9af102 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -14,18 +14,6 @@
 ---
 steps:
 
-  # Copy assets files to a new directory in GCS
-  # (via a new local directory)
-  # Directory name = git commit hash
-  - name: gcr.io/cloud-builders/gsutil
-    entrypoint: bash
-    args:
-      - -c
-      - |
-        mkdir -p ${COMMIT_SHA}/assets && \
-        cp -r pipelines/assets ${COMMIT_SHA} && \
-        gsutil cp -r ${COMMIT_SHA} ${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
-
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
   - name: python:3.9
@@ -34,8 +22,8 @@ steps:
       - -c
       - |
         make setup && \
-        make e2e-tests pipeline=training enable_pipeline_caching=False sync_assets=false && \
-        make e2e-tests pipeline=prediction enable_pipeline_caching=False sync_assets=false
+        make e2e-tests pipeline=training enable_pipeline_caching=False && \
+        make e2e-tests pipeline=prediction enable_pipeline_caching=False
     env:
       - VERTEX_LOCATION=${_TEST_VERTEX_LOCATION}
       - VERTEX_PROJECT_ID=${_TEST_VERTEX_PROJECT_ID}
@@ -44,7 +32,6 @@ steps:
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
-      - PIPELINE_FILES_GCS_PATH=${_PIPELINE_PUBLISH_GCS_PATH}/${COMMIT_SHA}
       - RESOURCE_SUFFIX=${COMMIT_SHA}
 
 options:
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 0c22abdb..f2ac361c 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -22,26 +22,24 @@ steps:
       - |
         make setup && \
         make compile-pipeline pipeline=training && \
-        make compile-pipeline pipeline=prediction
+        make compile-pipeline pipeline=prediction && \
+        cd pipelines && \
+        for dest in ${_PIPELINE_PUBLISH_AR_PATHS} ; do \
+          poetry run python -m pipelines.utils.upload_pipeline \
+          --dest=$$dest \
+          --yaml=src/pipelines/${_PIPELINE_TEMPLATE}/training/pipeline.yaml \
+          --tag=latest \
+          --tag=${TAG_NAME} && \
+          poetry run python -m pipelines.utils.upload_pipeline \
+          --dest=$$dest \
+          --yaml=src/pipelines/${_PIPELINE_TEMPLATE}/prediction/pipeline.yaml \
+          --tag=latest \
+          --tag=${TAG_NAME}; \
+        done
+
     env:
       - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
 
-  # Copy pipelines and files to a new directory in GCS
-  # (via a new local directory)
-  # Directory name = git commit hash
-  - name: gcr.io/cloud-builders/gsutil
-    entrypoint: bash
-    args:
-      - -c
-      - |
-        mkdir -p ${TAG_NAME}/assets && \
-        cp pipelines/src/training.json ${TAG_NAME}/training.json && \
-        cp pipelines/src/prediction.json ${TAG_NAME}/prediction.json && \
-        cp -r pipelines/assets/* ${TAG_NAME}/assets/ && \
-        for dest in ${_PIPELINE_PUBLISH_GCS_PATHS} ; do \
-          gsutil cp -r ${TAG_NAME} $$dest ; \
-        done
-
 options:
   logging: CLOUD_LOGGING_ONLY
 
diff --git a/components/vertex-components/README.md b/components/vertex-components/README.md
index bd674ccc..8252c9f0 100644
--- a/components/vertex-components/README.md
+++ b/components/vertex-components/README.md
@@ -16,13 +16,10 @@ limitations under the License.
 
 # Vertex Components
 
-A python package which provides common KubeFlow components for interacting with Vertex AI.
+A Python package which provides common KubeFlow components for interacting with Vertex AI.
 Currently, the following components are implemented:
 
-- `custom_train_job`: Train a model in a [Custom Training Job](https://cloud.google.com/vertex-ai/docs/training/create-custom-job).
-- `import_model_evaluation`: Import model evaluation results to a model in the model registry.
-- `lookup_model`: Look up a model which was previously uploaded to the model registry.
+- `upload_model`: Uploads a new model version to the Vertex Model Registry, importing a model evaluation, and updating the "default" tag on the model if the new version (challenger) is superior to the previous (champion) model.
 - `model_batch_predict`: Run a [Batch Prediction Job](https://cloud.google.com/ai-platform/prediction/docs/batch-predict).
-- `update_best_model`: Using two model evaluations and a comparison metric, update the better model to the default model.
 
 These components either augment, extend, or add new functionalities that aren't found in [Google Cloud Pipeline Components list](https://cloud.google.com/vertex-ai/docs/pipelines/gcpc-list).
diff --git a/components/vertex-components/src/vertex_components/__init__.py b/components/vertex-components/src/vertex_components/__init__.py
index 4175abff..040039b3 100644
--- a/components/vertex-components/src/vertex_components/__init__.py
+++ b/components/vertex-components/src/vertex_components/__init__.py
@@ -1,17 +1,9 @@
-from .custom_train_job import custom_train_job
-from .import_model_evaluation import import_model_evaluation
-from .lookup_model import lookup_model
 from .model_batch_predict import model_batch_predict
-from .update_best_model import update_best_model
 from .upload_model import upload_model
 
 
 __version__ = "0.0.1"
 __all__ = [
-    "custom_train_job",
-    "import_model_evaluation",
-    "lookup_model",
     "model_batch_predict",
-    "update_best_model",
     "upload_model",
 ]
diff --git a/components/vertex-components/src/vertex_components/upload_model.py b/components/vertex-components/src/vertex_components/upload_model.py
index be65b866..59838d37 100644
--- a/components/vertex-components/src/vertex_components/upload_model.py
+++ b/components/vertex-components/src/vertex_components/upload_model.py
@@ -197,7 +197,6 @@ def import_evaluation(
             champion_model.resource_name if champion_model is not None else None
         ),
         is_default_version=challenger_wins,
-        # TODO more model options
     )
 
     # Output google.VertexModel artifact
diff --git a/components/vertex-components/tests/test_custom_training_job.py b/components/vertex-components/tests/test_custom_training_job.py
deleted file mode 100644
index 3cd43b6e..00000000
--- a/components/vertex-components/tests/test_custom_training_job.py
+++ /dev/null
@@ -1,103 +0,0 @@
-import google.cloud.aiplatform as aip  # noqa
-from kfp.dsl import Dataset, Metrics, Artifact
-from unittest import mock
-import pytest
-import json
-
-import vertex_components
-
-custom_train_job = vertex_components.custom_train_job.python_func
-
-
-@mock.patch("google.cloud.aiplatform.CustomTrainingJob")
-@mock.patch("os.path.exists")
-@mock.patch("builtins.open", new_callable=mock.mock_open, read_data="{}")
-def test_custom_train_job(mock_open, mock_exists, mock_job, tmpdir):
-    """
-    Checks that the custom job method is called
-    """
-    mock_exists.return_value = True
-
-    mock_train_data = Dataset(uri=tmpdir)
-    mock_valid_data = Dataset(uri=tmpdir)
-    mock_test_data = Dataset(uri=tmpdir)
-    mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
-    mock_metrics = Metrics(uri=tmpdir)
-
-    mock_job_instance = mock_job.return_value
-    mock_job_instance.to_dict.return_value = {
-        "trainingTaskMetadata": {"backingCustomJob": "mock_custom_job_name"}
-    }
-
-    (gcp_resources,) = custom_train_job(
-        train_script_uri="gs://my-bucket/train_script.py",
-        train_data=mock_train_data,
-        valid_data=mock_valid_data,
-        test_data=mock_test_data,
-        project_id="my-project-id",
-        project_location="europe-west4",
-        model_display_name="my-model",
-        train_container_uri="gcr.io/my-project/my-image:latest",
-        serving_container_uri="gcr.io/my-project/my-serving-image:latest",
-        model=mock_model,
-        metrics=mock_metrics,
-        staging_bucket="gs://my-bucket",
-        job_name="my-job",
-    )
-
-    mock_job.assert_called_once_with(
-        project="my-project-id",
-        location="europe-west4",
-        staging_bucket="gs://my-bucket",
-        display_name="my-job",
-        script_path="/gcs/my-bucket/train_script.py",
-        container_uri="gcr.io/my-project/my-image:latest",
-        requirements=None,
-        model_serving_container_image_uri="gcr.io/my-project/my-serving-image:latest",  # noqa: E501
-    )
-
-    # Assert metrics loading
-    mock_open.assert_called_once_with(tmpdir, "r")
-    # Assert gcp_resources contains the expected value
-    assert (
-        json.loads(gcp_resources)["resources"][0]["resourceUri"]
-        == "mock_custom_job_name"
-    )
-
-
-@mock.patch("google.cloud.aiplatform.CustomTrainingJob")
-@mock.patch("os.path.exists")
-@mock.patch("builtins.open", new_callable=mock.mock_open, read_data="{}")
-def test_custom_train_script_not_found(mock_open, mock_exists, mock_job, tmpdir):
-    """
-    Checks that when the training script is not found
-    the method fails
-    """
-    mock_exists.return_value = False
-
-    mock_train_data = Dataset(uri=tmpdir)
-    mock_valid_data = Dataset(uri=tmpdir)
-    mock_test_data = Dataset(uri=tmpdir)
-    mock_model = Artifact(uri=tmpdir, metadata={"resourceName": ""})
-    mock_metrics = Metrics(uri=tmpdir)
-
-    with pytest.raises(ValueError):
-        (gcp_resources,) = custom_train_job(
-            train_script_uri="gs://my-bucket/train_script.py",
-            train_data=mock_train_data,
-            valid_data=mock_valid_data,
-            test_data=mock_test_data,
-            project_id="my-project-id",
-            project_location="europe-west4",
-            model_display_name="my-model",
-            train_container_uri="gcr.io/my-project/my-image:latest",
-            serving_container_uri="gcr.io/my-project/my-serving-image:latest",
-            model=mock_model,
-            metrics=mock_metrics,
-            staging_bucket="gs://my-bucket",
-            job_name="my-job",
-        )
-
-    # Assert the custom training job is not executed
-    mock_job.assert_not_called()
-    mock_open.assert_not_called()
diff --git a/docs/PRODUCTION.md b/docs/PRODUCTION.md
index db4a0f5d..47fb4a7e 100644
--- a/docs/PRODUCTION.md
+++ b/docs/PRODUCTION.md
@@ -54,24 +54,14 @@ When the new tag is created, the `release.yaml` pipeline should be triggered. It
   - `_PIPELINE_PUBLISH_GCS_PATHS` = `gs://<Project ID of dev project>-pl-assets gs://<Project ID of test project>-pl-assets gs://<Project ID of prod project>-pl-assets`
 
 Assuming your end-to-end tests pass, your compiled training pipeline will be published to:
-- `gs://<Project ID of dev project>-pl-assets/v1.2/training/training.json`
-- `gs://<Project ID of test project>-pl-assets/v1.2/training/training.json`
-- `gs://<Project ID of prod project>-pl-assets/v1.2/training/training.json`
-
-The contents of your assets folder for your training pipeline will be published to:
-- `gs://<Project ID of dev project>-pl-assets/v1.2/training/assets/`
-- `gs://<Project ID of test project>-pl-assets/v1.2/training/assets/`
-- `gs://<Project ID of prod project>-pl-assets/v1.2/training/assets/`
+- `https://<GCP region>-kfp.pkg.dev/<Project ID of dev project>/vertex-pipelines/xgboost-train-pipeline/v1.2`
+- `https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/v1.2`
+- `https://<GCP region>-kfp.pkg.dev/<Project ID of prod project>/vertex-pipelines/xgboost-train-pipeline/v1.2`
 
 Similarly, your compiled prediction pipeline will be published in this location:
-- `gs://<Project ID of dev project>-pl-assets/v1.2/prediction/prediction.json`
-- `gs://<Project ID of test project>-pl-assets/v1.2/prediction/prediction.json`
-- `gs://<Project ID of prod project>-pl-assets/v1.2/prediction/prediction.json`
-
-The contents of your assets folder for your prediction pipeline will be published in this location:
-- `gs://<Project ID of dev project>-pl-assets/v1.2/prediction/assets/`
-- `gs://<Project ID of test project>-pl-assets/v1.2/prediction/assets/`
-- `gs://<Project ID of prod project>-pl-assets/v1.2/prediction/assets/`
+- `https://<GCP region>-kfp.pkg.dev/<Project ID of dev project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2`
+- `https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2`
+- `https://<GCP region>-kfp.pkg.dev/<Project ID of prod project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2`
 
 | :exclamation: IMPORTANT    |
 |:---------------------------|
@@ -79,7 +69,7 @@ The contents of your assets folder for your prediction pipeline will be publishe
 
 ## Deploying a release to the test environment
 
-Now that you have created a release, and the compiled pipelines (and their `assets` files) have been copied to the test and prod environments, you can now schedule your pipelines to run in those environments.
+Now that you have created a release, and the compiled pipelines have been copied to the test and prod environments, you can now schedule your pipelines to run in those environments.
 
 Of course, we will begin by scheduling the pipelines to run in the test environment.
 
@@ -97,17 +87,14 @@ cloud_schedulers_config = {
     description  = "Trigger my XGBoost training pipeline in Vertex"
     schedule     = "0 0 1 * *"
     time_zone    = "UTC"
-    template_path = "gs://<Project ID of test project>-pl-assets/v1.2/training/training.json"
+    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/<Git tag>"
     enable_caching = null
     pipeline_parameters = {
       project_id = <Project ID of test project>
       project_location = "europe-west2"
-      pipeline_files_gcs_path = "gs://<Project ID of test project>-pl-assets/v1.2/training/assets"
       ingestion_project_id = <Project ID of test project>
       model_name = "xgboost-with-preprocessing"
       model_label = "label_name"
-      tfdv_schema_filename = "tfdv_schema_training.pbtxt"
-      tfdv_train_stats_path = "gs://<Project ID of test project>-pl-root/train_stats/train.stats"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
@@ -120,17 +107,14 @@ cloud_schedulers_config = {
     description  = "Trigger my XGBoost prediction pipeline in Vertex"
     schedule     = "0 0 * * *"
     time_zone    = "UTC"
-    template_path = "gs://<Project ID of test project>-pl-assets/v1.2/prediction/prediction.json"
+    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/<Git tag>"
     enable_caching = null
     pipeline_parameters = {
       project_id = <Project ID of test project>
       project_location = "europe-west2"
-      pipeline_files_gcs_path = "gs://<Project ID of test project>-pl-assets/v1.2/prediction/assets"
       ingestion_project_id = <Project ID of test project>
       model_name = "xgboost-with-preprocessing"
       model_label = "label_name"
-      tfdv_schema_filename = "tfdv_schema_prediction.pbtxt"
-      tfdv_train_stats_path = "gs://<Project ID of test project>-pl-root/train_stats/train.stats"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
diff --git a/docs/TESTING_SETUP.md b/docs/TESTING_SETUP.md
index cdf9ca00..ef358f09 100644
--- a/docs/TESTING_SETUP.md
+++ b/docs/TESTING_SETUP.md
@@ -47,15 +47,6 @@ storage.googleapis.com \
 --project $GCP_PROJECT_ID
 ```
 
-### Google Cloud Storage buckets
-
-Two buckets will need to be created - one for publishing the compiled JSON pipelines (and any other files required for running the pipelines), and one for the pipeline root.
-
-```
-gsutil mb -l ${GCP_REGION} -p ${GCP_PROJECT_ID} gs://${GCP_PROJECT_ID}-pl-root
-gsutil mb -l ${GCP_REGION} -p ${GCP_PROJECT_ID} gs://${GCP_PROJECT_ID}-assets 
-```
-
 ### BigQuery 
 
 Create a new BigQuery dataset for the Chicago Taxi data:
@@ -137,15 +128,11 @@ gcloud projects add-iam-policy-binding $GCP_PROJECT_ID --member="serviceAccount:
 gcloud projects add-iam-policy-binding $GCP_PROJECT_ID --member="serviceAccount:vertex-pipelines@${GCP_PROJECT_ID}.iam.gserviceaccount.com" --role="roles/bigquery.jobUser" --condition=None
 ```
 
-The Vertex Pipelines service account requires read access to the assets bucket, read/write access to the pipeline root bucket, and access to list both buckets:
+The Vertex Pipelines service account requires read/write/list access to the pipeline root bucket:
 
 ```
-gsutil iam ch serviceAccount:vertex-pipelines@${GCP_PROJECT_ID}.iam.gserviceaccount.com:objectViewer gs://${GCP_PROJECT_ID}-assets
-
 gsutil iam ch serviceAccount:vertex-pipelines@${GCP_PROJECT_ID}.iam.gserviceaccount.com:objectAdmin gs://${GCP_PROJECT_ID}-pl-root
 
-gsutil iam ch serviceAccount:vertex-pipelines@${GCP_PROJECT_ID}.iam.gserviceaccount.com:legacyBucketReader gs://${GCP_PROJECT_ID}-assets
-
 gsutil iam ch serviceAccount:vertex-pipelines@${GCP_PROJECT_ID}.iam.gserviceaccount.com:legacyBucketReader gs://${GCP_PROJECT_ID}-pl-root
 ```
 
@@ -181,4 +168,4 @@ For each of the above, create a Cloud Build trigger with the following settings:
 | `pr-checks.yaml` (xgboost)    |  _PIPELINE_TEMPLATE = `xgboost`     |
 | `trigger-tests.yaml`          |                                     |
 | `e2e-test.yaml` (tensorflow)  |  _PIPELINE_TEMPLATE = `tensorflow`<br>_PIPELINE_PUBLISH_GCS_PATH = `gs://<GCP PROJECT ID>-assets/e2e-test-tensorflow`<br>_TEST_ENABLE_PIPELINE_CACHING = `False`<br>_TEST_TRAIN_STATS_GCS_PATH = `gs://<GCP PROJECT ID>-pl-root/e2e-test-tensorflow/train-stats/train.stats`<br>_TEST_VERTEX_LOCATION = `<GCP REGION (same as buckets etc above)>`<br>_TEST_VERTEX_PIPELINE_ROOT = `gs://<GCP PROJECT ID>-pl-root`<br>_TEST_VERTEX_PROJECT_ID = `<GCP PROJECT ID>`<br>_TEST_VERTEX_SA_EMAIL = `vertex-pipelines@<GCP PROJECT ID>.iam.gserviceaccount.com`  |
-| `e2e-test.yaml` (xgboost)  |  _PIPELINE_TEMPLATE = `xgboost`<br>_PIPELINE_PUBLISH_GCS_PATH = `gs://<GCP PROJECT ID>-assets/e2e-test-xgboost`<br>_TEST_ENABLE_PIPELINE_CACHING = `False`<br>_TEST_TRAIN_STATS_GCS_PATH = `gs://<GCP PROJECT ID>-pl-root/e2e-test-xgboost/train-stats/train.stats`<br>_TEST_VERTEX_LOCATION = `<GCP REGION (same as buckets etc above)>`<br>_TEST_VERTEX_PIPELINE_ROOT = `gs://<GCP PROJECT ID>-pl-root`<br>_TEST_VERTEX_PROJECT_ID = `<GCP PROJECT ID>`<br>_TEST_VERTEX_SA_EMAIL = `vertex-pipelines@<GCP PROJECT ID>.iam.gserviceaccount.com`  |
+| `e2e-test.yaml` (xgboost)  |  _PIPELINE_TEMPLATE = `xgboost`<br>_TEST_ENABLE_PIPELINE_CACHING = `False`<br>_TEST_VERTEX_LOCATION = `<GCP REGION (same as buckets etc above)>`<br>_TEST_VERTEX_PIPELINE_ROOT = `gs://<GCP PROJECT ID>-pl-root`<br>_TEST_VERTEX_PROJECT_ID = `<GCP PROJECT ID>`<br>_TEST_VERTEX_SA_EMAIL = `vertex-pipelines@<GCP PROJECT ID>.iam.gserviceaccount.com`  |
diff --git a/docs/images/cf_view.png b/docs/images/cf_view.png
index 7a81234d9a3045e3860fc5360ec008b3659c42e6..06ba46262b680a84e636064cb049736f0f0c9c43 100644
GIT binary patch
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diff --git a/env.sh.example b/env.sh.example
index e57c7dbb..3a84eb80 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -26,6 +26,5 @@ export RESOURCE_SUFFIX=default
 
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export PIPELINE_FILES_GCS_PATH=gs://${VERTEX_PROJECT_ID}-pl-assets/${RESOURCE_SUFFIX}
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
 export TRAINING_CONTAINER_IMAGE=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images/training:${RESOURCE_SUFFIX}
diff --git a/pipelines/assets/.gitkeep b/pipelines/assets/.gitkeep
deleted file mode 100644
index e69de29b..00000000
diff --git a/pipelines/assets/train_tf_model.py b/pipelines/assets/train_tf_model.py
deleted file mode 100644
index 5d164ae7..00000000
--- a/pipelines/assets/train_tf_model.py
+++ /dev/null
@@ -1,299 +0,0 @@
-import argparse
-import os
-import json
-import logging
-import sys
-
-import tensorflow as tf
-from pathlib import Path
-from tensorflow.data import Dataset
-from tensorflow.keras import Input, Model, optimizers
-from tensorflow.keras.layers import Dense, Normalization, StringLookup, Concatenate
-
-# used for monitoring during prediction time
-TRAINING_DATASET_INFO = "training_dataset.json"
-# numeric/categorical features in Chicago trips dataset to be preprocessed
-NUM_COLS = ["dayofweek", "hourofday", "trip_distance", "trip_miles", "trip_seconds"]
-ORD_COLS = ["company"]
-OHE_COLS = ["payment_type"]
-DEFAULT_HPARAMS = dict(
-    batch_size=100,
-    epochs=1,
-    loss_fn="MeanSquaredError",
-    optimizer="Adam",
-    learning_rate=0.001,
-    metrics=[
-        "RootMeanSquaredError",
-        "MeanAbsoluteError",
-        "MeanAbsolutePercentageError",
-        "MeanSquaredLogarithmicError",
-    ],
-    hidden_units=[(10, "relu")],
-    distribute_strategy="single",
-    early_stopping_epochs=5,
-    label="total_fare",
-)
-
-logging.getLogger().setLevel(logging.INFO)
-
-
-def create_dataset(input_data: Path, label_name: str, model_params: dict) -> Dataset:
-    """Create a TF Dataset from input csv files.
-    Args:
-        input_data (Input[Dataset]): Train/Valid data in CSV format
-        label_name (str): Name of column containing the labels
-        model_params (dict): model parameters
-        file_pattern (str): Read data from one or more files. If empty, then
-            training and validation data is read from single file respectively.
-            For multiple files, use a pattern e.g. "files-*.csv".
-    Returns:
-        dataset (TF Dataset): TF dataset where each element is a (features, labels)
-            tuple that corresponds to a batch of CSV rows
-    """
-
-    # shuffle & shuffle_buffer_size added to rearrange input data
-    # passed into model training
-    # num_rows_for_inference is for auto detection of datatypes
-    # while creating the dataset.
-    # If a float column has a high proportion of integer values (0/1 etc),
-    # the method wrongly detects it as a tf.int32 which fails during training time,
-    # hence the high hardcoded value (default is 100)
-
-    # Apply data sharding: Sharded elements are produced by the dataset
-    # Each worker will process the whole dataset and discard the portion that is
-    # not for itself. Note that for this mode to correctly partitions the dataset
-    # elements, the dataset needs to produce elements in a deterministic order.
-    data_options = tf.data.Options()
-    data_options.experimental_distribute.auto_shard_policy = (
-        tf.data.experimental.AutoShardPolicy.DATA
-    )
-
-    logging.info(f"Creating dataset from CSV file(s) at {input_data}...")
-    created_dataset = tf.data.experimental.make_csv_dataset(
-        file_pattern=str(input_data),
-        batch_size=model_params["batch_size"],
-        label_name=label_name,
-        num_epochs=model_params["epochs"],
-        shuffle=True,
-        shuffle_buffer_size=1000,
-        num_rows_for_inference=20000,
-    )
-    return created_dataset.with_options(data_options)
-
-
-def get_distribution_strategy(distribute_strategy: str) -> tf.distribute.Strategy:
-    """Set distribute strategy based on input string.
-    Args:
-        distribute_strategy (str): single, mirror or multi
-    Returns:
-        strategy (tf.distribute.Strategy): distribution strategy
-    """
-    logging.info(f"Distribution strategy: {distribute_strategy}")
-
-    # Single machine, single compute device
-    if distribute_strategy == "single":
-        if len(tf.config.list_physical_devices("GPU")):
-            strategy = tf.distribute.OneDeviceStrategy(device="/gpu:0")
-        else:
-            strategy = tf.distribute.OneDeviceStrategy(device="/cpu:0")
-    # Single machine, multiple compute device
-    elif distribute_strategy == "mirror":
-        strategy = tf.distribute.MirroredStrategy()
-    # Multiple machine, multiple compute device
-    elif distribute_strategy == "multi":
-        strategy = tf.distribute.MultiWorkerMirroredStrategy()
-    else:
-        raise RuntimeError(f"Distribute strategy: {distribute_strategy} not supported")
-    return strategy
-
-
-def normalization(name: str, dataset: Dataset) -> Normalization:
-    """Create a Normalization layer for a feature.
-    Args:
-        name (str): name of feature to be normalized
-        dataset (Dataset): dataset to adapt layer
-    Returns:
-        normalization layer (Normalization): adapted normalization layer
-            of shape (?,1)
-    """
-    logging.info(f"Normalizing numerical input '{name}'...")
-    x = Normalization(axis=None, name=f"normalize_{name}")
-    x.adapt(dataset.map(lambda y, _: y[name]))
-    return x
-
-
-def str_lookup(name: str, dataset: Dataset, output_mode: str) -> StringLookup:
-    """Create a StringLookup layer for a feature.
-    Args:
-        name (str): name of feature to be encoded
-        dataset (Dataset): dataset to adapt layer
-        output_mode (str): argument for StringLookup layer (e.g. 'one_hot', 'int')
-    Returns:
-        StringLookup layer (StringLookup): adapted StringLookup layer of shape (?,X)
-    """
-    logging.info(f"Encoding categorical input '{name}' ({output_mode})...")
-    x = StringLookup(output_mode=output_mode, name=f"str_lookup_{output_mode}_{name}")
-    x.adapt(dataset.map(lambda y, _: y[name]))
-    logging.info(f"Vocabulary: {x.get_vocabulary()}")
-    return x
-
-
-def build_and_compile_model(dataset: Dataset, model_params: dict) -> Model:
-    """Build and compile model.
-    Args:
-        dataset (Dataset): training dataset
-        model_params (dict): model parameters
-    Returns:
-        model (Model): built and compiled model
-    """
-
-    # create inputs (scalars with shape `()`)
-    num_ins = {name: Input(shape=(), name=name, dtype=tf.float32) for name in NUM_COLS}
-    ord_ins = {name: Input(shape=(), name=name, dtype=tf.string) for name in ORD_COLS}
-    cat_ins = {name: Input(shape=(), name=name, dtype=tf.string) for name in OHE_COLS}
-
-    # join all inputs and expand by 1 dimension. NOTE: this is useful when passing
-    # in scalar inputs to a model in Vertex AI batch predictions or endpoints e.g.
-    # `{"instances": {"input1": 1.0, "input2": "str"}}` instead of
-    # `{"instances": {"input1": [1.0], "input2": ["str"]}`
-    all_ins = {**num_ins, **ord_ins, **cat_ins}
-    exp_ins = {n: tf.expand_dims(i, axis=-1) for n, i in all_ins.items()}
-
-    # preprocess expanded inputs
-    num_encoded = [normalization(n, dataset)(exp_ins[n]) for n in NUM_COLS]
-    ord_encoded = [str_lookup(n, dataset, "int")(exp_ins[n]) for n in ORD_COLS]
-    ohe_encoded = [str_lookup(n, dataset, "one_hot")(exp_ins[n]) for n in OHE_COLS]
-
-    # ensure ordinal encoded layers is of type float32 (like the other layers)
-    ord_encoded = [tf.cast(x, tf.float32) for x in ord_encoded]
-
-    # concat encoded inputs and add dense layers including output layer
-    x = num_encoded + ord_encoded + ohe_encoded
-    x = Concatenate()(x)
-    for units, activation in model_params["hidden_units"]:
-        x = Dense(units, activation=activation)(x)
-    x = Dense(1, name="output", activation="linear")(x)
-
-    model = Model(inputs=all_ins, outputs=x, name="nn_model")
-    model.summary()
-
-    logging.info(f"Use optimizer {model_params['optimizer']}")
-    optimizer = optimizers.get(model_params["optimizer"])
-    optimizer.learning_rate = model_params["learning_rate"]
-
-    model.compile(
-        loss=model_params["loss_fn"],
-        optimizer=optimizer,
-        metrics=model_params["metrics"],
-    )
-
-    return model
-
-
-def _is_chief(strategy: tf.distribute.Strategy) -> bool:
-    """Determine whether current worker is the chief (master). See more info:
-    - https://www.tensorflow.org/tutorials/distribute/multi_worker_with_keras
-    - https://www.tensorflow.org/api_docs/python/tf/distribute/cluster_resolver/ClusterResolver # noqa: E501
-    Args:
-        strategy (tf.distribute.Strategy): strategy
-    Returns:
-        is_chief (bool): True if worker is chief, otherwise False
-    """
-    cr = strategy.cluster_resolver
-    return (cr is None) or (cr.task_type == "chief" and cr.task_id == 0)
-
-
-def _get_temp_dir(dirpath, task_id):
-    base_dirpath = "workertemp_" + str(task_id)
-    temp_dir = os.path.join(dirpath, base_dirpath)
-    tf.io.gfile.makedirs(temp_dir)
-    return temp_dir
-
-
-parser = argparse.ArgumentParser()
-parser.add_argument("--train_data", type=str, required=True)
-parser.add_argument("--valid_data", type=str, required=True)
-parser.add_argument("--test_data", type=str, required=True)
-parser.add_argument("--model", default=os.getenv("AIP_MODEL_DIR"), type=str, help="")
-parser.add_argument("--metrics", type=str, required=True)
-parser.add_argument("--hparams", default={}, type=json.loads)
-args = parser.parse_args()
-
-if args.model.startswith("gs://"):
-    args.model = Path("/gcs/" + args.model[5:])
-
-# merge dictionaries by overwriting default_model_params if provided in model_params
-hparams = {**DEFAULT_HPARAMS, **args.hparams}
-logging.info(f"Using model hyper-parameters: {hparams}")
-label = hparams["label"]
-
-# Set distribute strategy before any TF operations
-strategy = get_distribution_strategy(hparams["distribute_strategy"])
-
-train_ds = create_dataset(Path(args.train_data), label, hparams)
-valid_ds = create_dataset(Path(args.valid_data), label, hparams)
-test_ds = create_dataset(Path(args.test_data), label, hparams)
-
-train_features = list(train_ds.element_spec[0].keys())
-valid_features = list(valid_ds.element_spec[0].keys())
-logging.info(f"Training feature names: {train_features}")
-logging.info(f"Validation feature names: {valid_features}")
-
-if len(train_features) != len(valid_features):
-    raise RuntimeError(f"No. of training features != # validation features")
-
-with strategy.scope():
-    tf_model = build_and_compile_model(train_ds, hparams)
-
-logging.info("Use early stopping")
-callback = tf.keras.callbacks.EarlyStopping(
-    monitor="loss", mode="min", patience=hparams["early_stopping_epochs"]
-)
-
-logging.info("Fit model...")
-history = tf_model.fit(
-    train_ds,
-    batch_size=hparams["batch_size"],
-    epochs=hparams["epochs"],
-    validation_data=valid_ds,
-    callbacks=[callback],
-)
-
-# only persist output files if current worker is chief
-if not _is_chief(strategy):
-    logging.info("not chief node, exiting now")
-    sys.exit()
-
-logging.info(f"Save model to: {args.model}")
-args.model.mkdir(parents=True)
-tf_model.save(str(args.model), save_format="tf")
-
-logging.info(f"Save metrics to: {args.metrics}")
-eval_metrics = dict(zip(tf_model.metrics_names, tf_model.evaluate(test_ds)))
-
-metrics = {
-    "problemType": "regression",
-    "rootMeanSquaredError": eval_metrics["root_mean_squared_error"],
-    "meanAbsoluteError": eval_metrics["mean_absolute_error"],
-    "meanAbsolutePercentageError": eval_metrics["mean_absolute_percentage_error"],
-    "rSquared": None,
-    "rootMeanSquaredLogError": eval_metrics["mean_squared_logarithmic_error"],
-}
-
-with open(args.metrics, "w") as fp:
-    json.dump(metrics, fp)
-
-# Persist URIs of training file(s) for model monitoring in batch predictions
-# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
-# for the expected schema.
-path = args.model / TRAINING_DATASET_INFO
-training_dataset_for_monitoring = {
-    "gcsSource": {"uris": [args.train_data]},
-    "dataFormat": "csv",
-    "targetField": label,
-}
-logging.info(f"Save training dataset info for model monitoring: {path}")
-logging.info(f"Training dataset: {training_dataset_for_monitoring}")
-
-with open(path, "w") as fp:
-    json.dump(training_dataset_for_monitoring, fp)
diff --git a/pipelines/assets/train_xgb_model.py b/pipelines/assets/train_xgb_model.py
deleted file mode 100644
index 71cc65b5..00000000
--- a/pipelines/assets/train_xgb_model.py
+++ /dev/null
@@ -1,142 +0,0 @@
-import argparse
-from pathlib import Path
-
-import joblib
-import json
-import os
-import logging
-
-import numpy as np
-import pandas as pd
-from sklearn import metrics
-from sklearn.compose import ColumnTransformer
-from sklearn.pipeline import Pipeline
-from sklearn.preprocessing import StandardScaler, OrdinalEncoder, OneHotEncoder
-from xgboost import XGBRegressor
-
-logging.basicConfig(level=logging.DEBUG)
-
-# used for monitoring during prediction time
-TRAINING_DATASET_INFO = "training_dataset.json"
-# numeric/categorical features in Chicago trips dataset to be preprocessed
-NUM_COLS = ["dayofweek", "hourofday", "trip_distance", "trip_miles", "trip_seconds"]
-ORD_COLS = ["company"]
-OHE_COLS = ["payment_type"]
-
-
-def split_xy(df: pd.DataFrame, label: str) -> (pd.DataFrame, pd.Series):
-    """Split dataframe into X and y."""
-    return df.drop(columns=[label]), df[label]
-
-
-def indices_in_list(elements: list, base_list: list) -> list:
-    """Get indices of specific elements in a base list"""
-    return [idx for idx, elem in enumerate(base_list) if elem in elements]
-
-
-parser = argparse.ArgumentParser()
-parser.add_argument("--train_data", type=str, required=True)
-parser.add_argument("--valid_data", type=str, required=True)
-parser.add_argument("--test_data", type=str, required=True)
-parser.add_argument("--model", default=os.getenv("AIP_MODEL_DIR"), type=str, help="")
-parser.add_argument("--metrics", type=str, required=True)
-parser.add_argument("--hparams", default={}, type=json.loads)
-args = parser.parse_args()
-
-if args.model.startswith("gs://"):
-    args.model = Path("/gcs/" + args.model[5:])
-
-logging.info("Read csv files into dataframes")
-df_train = pd.read_csv(args.train_data)
-df_valid = pd.read_csv(args.valid_data)
-df_test = pd.read_csv(args.test_data)
-
-logging.info("Split dataframes")
-label = args.hparams["label"]
-X_train, y_train = split_xy(df_train, label)
-X_valid, y_valid = split_xy(df_valid, label)
-X_test, y_test = split_xy(df_test, label)
-
-logging.info("Get the number of unique categories for ordinal encoded columns")
-ordinal_columns = X_train[ORD_COLS]
-n_unique_cat = ordinal_columns.nunique()
-
-logging.info("Get indices of columns in base data")
-col_list = X_train.columns.tolist()
-num_indices = indices_in_list(NUM_COLS, col_list)
-cat_indices_onehot = indices_in_list(OHE_COLS, col_list)
-cat_indices_ordinal = indices_in_list(ORD_COLS, col_list)
-
-ordinal_transformers = [
-    (
-        f"ordinal encoding for {ord_col}",
-        OrdinalEncoder(
-            handle_unknown="use_encoded_value", unknown_value=n_unique_cat[ord_col]
-        ),
-        [ord_index],
-    )
-    for ord_col in ORD_COLS
-    for ord_index in cat_indices_ordinal
-]
-all_transformers = [
-    ("numeric_scaling", StandardScaler(), num_indices),
-    (
-        "one_hot_encoding",
-        OneHotEncoder(handle_unknown="ignore"),
-        cat_indices_onehot,
-    ),
-] + ordinal_transformers
-
-logging.info("Build sklearn preprocessing steps")
-preprocesser = ColumnTransformer(transformers=all_transformers)
-logging.info("Build sklearn pipeline with XGBoost model")
-xgb_model = XGBRegressor(**args.hparams)
-
-pipeline = Pipeline(
-    steps=[("feature_engineering", preprocesser), ("train_model", xgb_model)]
-)
-
-logging.info("Transform validation data")
-valid_preprocesser = preprocesser.fit(X_train)
-X_valid_transformed = valid_preprocesser.transform(X_valid)
-
-logging.info("Fit model")
-pipeline.fit(X_train, y_train, train_model__eval_set=[(X_valid_transformed, y_valid)])
-
-logging.info("Predict test data")
-y_pred = pipeline.predict(X_test)
-y_pred = y_pred.clip(0)
-
-metrics = {
-    "problemType": "regression",
-    "rootMeanSquaredError": np.sqrt(metrics.mean_squared_error(y_test, y_pred)),
-    "meanAbsoluteError": metrics.mean_absolute_error(y_test, y_pred),
-    "meanAbsolutePercentageError": metrics.mean_absolute_percentage_error(
-        y_test, y_pred
-    ),
-    "rSquared": metrics.r2_score(y_test, y_pred),
-    "rootMeanSquaredLogError": np.sqrt(metrics.mean_squared_log_error(y_test, y_pred)),
-}
-
-logging.info(f"Save model to: {args.model}")
-args.model.mkdir(parents=True)
-joblib.dump(pipeline, str(args.model / "model.joblib"))
-
-logging.info(f"Metrics: {metrics}")
-with open(args.metrics, "w") as fp:
-    json.dump(metrics, fp)
-
-# Persist URIs of training file(s) for model monitoring in batch predictions
-# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
-# for the expected schema.
-path = args.model / TRAINING_DATASET_INFO
-training_dataset_for_monitoring = {
-    "gcsSource": {"uris": [args.train_data]},
-    "dataFormat": "csv",
-    "targetField": label,
-}
-logging.info(f"Training dataset info: {training_dataset_for_monitoring}")
-
-with open(path, "w") as fp:
-    logging.info(f"Save training dataset info for model monitoring: {path}")
-    json.dump(training_dataset_for_monitoring, fp)
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
index 20deca08..03f5e18f 100644
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
@@ -16,14 +16,14 @@
 import pathlib
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp import compiler, dsl
+from kfp import dsl
 
 from pipelines import generate_query
 from vertex_components import lookup_model, model_batch_predict
 
 
 @dsl.pipeline(name="tensorflow-prediction-pipeline")
-def tensorflow_pipeline(
+def pipeline(
     project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
     project_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
@@ -149,11 +149,3 @@ def tensorflow_pipeline(
         .after(preprocessing)
         .set_display_name("Batch prediction job")
     )
-
-
-if __name__ == "__main__":
-    compiler.Compiler().compile(
-        pipeline_func=tensorflow_pipeline,
-        package_path="prediction.json",
-        type_check=False,
-    )
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
index 13ccb817..67f267b1 100644
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ b/pipelines/src/pipelines/tensorflow/training/pipeline.py
@@ -16,7 +16,7 @@
 import pathlib
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp import compiler, dsl
+from kfp import dsl
 from pipelines import generate_query
 from bigquery_components import extract_bq_to_dataset
 from vertex_components import (
@@ -28,7 +28,7 @@
 
 
 @dsl.pipeline(name="tensorflow-train-pipeline")
-def tensorflow_pipeline(
+def pipeline(
     project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
     project_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
@@ -38,7 +38,6 @@ def tensorflow_pipeline(
     ingestion_dataset_id: str = "chicago_taxi_trips",
     timestamp: str = "2022-12-01 00:00:00",
     staging_bucket: str = os.environ.get("VERTEX_PIPELINE_ROOT"),
-    pipeline_files_gcs_path: str = os.environ.get("PIPELINE_FILES_GCS_PATH"),
     resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
     test_dataset_uri: str = "",
 ):
@@ -64,7 +63,6 @@ def tensorflow_pipeline(
             (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
             If any time part is missing, it will be regarded as zero.
         staging_bucket (str): Staging bucket for pipeline artifacts.
-        pipeline_files_gcs_path (str): GCS path where the pipeline files are located
         resource_suffix (str): Optional. Additional suffix to append GCS resources
             that get overwritten.
         test_dataset_uri (str): Optional. GCS URI of statis held-out test dataset.
@@ -82,6 +80,7 @@ def tensorflow_pipeline(
     valid_table = "valid_data" + table_suffix
     test_table = "test_data" + table_suffix
     primary_metric = "rootMeanSquaredError"
+    pipeline_files_gcs_path = "TODO - remove"
     train_script_uri = f"{pipeline_files_gcs_path}/assets/train_tf_model.py"
     hparams = dict(
         batch_size=100,
@@ -203,11 +202,3 @@ def tensorflow_pipeline(
             project_id=project_id,
             project_location=project_location,
         ).set_display_name("Update best model")
-
-
-if __name__ == "__main__":
-    compiler.Compiler().compile(
-        pipeline_func=tensorflow_pipeline,
-        package_path="training.json",
-        type_check=False,
-    )
diff --git a/pipelines/src/pipelines/utils/upload_pipeline.py b/pipelines/src/pipelines/utils/upload_pipeline.py
new file mode 100644
index 00000000..d5137f41
--- /dev/null
+++ b/pipelines/src/pipelines/utils/upload_pipeline.py
@@ -0,0 +1,19 @@
+import argparse
+from kfp.registry import RegistryClient
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--dest", type=str, required=True)
+    parser.add_argument("--yaml", type=str, required=True)
+    parser.add_argument("--tag", type=str, action="append")
+    args = parser.parse_args()
+
+    client = RegistryClient(
+        host=args.dest,
+    )
+
+    templateName, versionName = client.upload_pipeline(
+        file_name=args.yaml,
+        tags=args.tag,
+    )
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
index c7225e10..6d618511 100644
--- a/pipelines/src/pipelines/xgboost/prediction/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/prediction/pipeline.py
@@ -16,14 +16,14 @@
 import pathlib
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp import compiler, dsl
+from kfp import dsl
 
 from pipelines import generate_query
 from vertex_components import lookup_model, model_batch_predict
 
 
 @dsl.pipeline(name="xgboost-prediction-pipeline")
-def xgboost_pipeline(
+def pipeline(
     project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
     project_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
@@ -141,11 +141,3 @@ def xgboost_pipeline(
         .after(preprocessing)
         .set_display_name("Batch prediction job")
     )
-
-
-if __name__ == "__main__":
-    compiler.Compiler().compile(
-        pipeline_func=xgboost_pipeline,
-        package_path="prediction.json",
-        type_check=False,
-    )
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/xgboost/training/pipeline.py
index 228d7afa..93c83228 100644
--- a/pipelines/src/pipelines/xgboost/training/pipeline.py
+++ b/pipelines/src/pipelines/xgboost/training/pipeline.py
@@ -16,7 +16,7 @@
 import pathlib
 
 from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp import compiler, dsl
+from kfp import dsl
 from kfp.dsl import Dataset, Input, Metrics, Model, Output, OutputPath
 from pipelines import generate_query
 from bigquery_components import extract_bq_to_dataset
@@ -32,7 +32,7 @@ def train(
     test_data: Input[Dataset],
     model: Output[Model],
     model_output_uri: OutputPath(str),
-    metrics: Output[Metrics],  # TODO could be a more specific type of metrics object
+    metrics: Output[Metrics],
     hparams: dict,
 ):
     return dsl.ContainerSpec(
@@ -59,7 +59,7 @@ def train(
 
 
 @dsl.pipeline(name="xgboost-train-pipeline")
-def xgboost_pipeline(
+def pipeline(
     project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
     project_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
@@ -68,8 +68,6 @@ def xgboost_pipeline(
     dataset_location: str = os.environ.get("VERTEX_LOCATION"),
     ingestion_dataset_id: str = "chicago_taxi_trips",
     timestamp: str = "2022-12-01 00:00:00",
-    staging_bucket: str = os.environ.get("VERTEX_PIPELINE_ROOT"),
-    pipeline_files_gcs_path: str = os.environ.get("PIPELINE_FILES_GCS_PATH"),
     resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
     test_dataset_uri: str = "",
 ):
@@ -93,8 +91,6 @@ def xgboost_pipeline(
         timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
             (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
             If any time part is missing, it will be regarded as zero.
-        staging_bucket (str): Staging bucket for pipeline artifacts.
-        pipeline_files_gcs_path (str): GCS path where the pipeline files are located.
         resource_suffix (str): Optional. Additional suffix to append GCS resources
             that get overwritten.
         test_dataset_uri (str): Optional. GCS URI of statis held-out test dataset.
@@ -208,11 +204,3 @@ def xgboost_pipeline(
         pipeline_job_id="{{$.pipeline_job_name}}",
         test_dataset=test_dataset,
     ).set_display_name("Upload model")
-
-
-if __name__ == "__main__":
-    compiler.Compiler().compile(
-        pipeline_func=xgboost_pipeline,
-        package_path="training.json",
-        type_check=False,
-    )
diff --git a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
index a92fd2df..beb66051 100644
--- a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
+++ b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
@@ -21,17 +21,14 @@ cloud_schedulers_config = {
     description  = "Trigger my XGBoost training pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
-    template_path = "gs://my-assets-bucket/<Git tag>/training/training.json"
+    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/<Git tag>"
     enable_caching = null
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west2"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
       model_label = "label_name"
-      tfdv_schema_filename = "tfdv_schema_training.pbtxt"
-      tfdv_train_stats_path = "gs://my-pipeline-root-bucket/train_stats/train.stats"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
@@ -44,17 +41,14 @@ cloud_schedulers_config = {
     description  = "Trigger my XGBoost prediction pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
-    template_path = "gs://my-assets-bucket/<Git tag>/prediction/prediction.json"
+    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/<Git tag>"
     enable_caching = null
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
       model_label = "label_name"
-      tfdv_schema_filename = "tfdv_schema_training.pbtxt"
-      tfdv_train_stats_path = "gs://my-pipeline-root-bucket/train_stats/train.stats"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
@@ -70,17 +64,14 @@ cloud_schedulers_config = {
     description  = "Trigger my TensorFlow training pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
-    template_path = "gs://my-assets-bucket/<Git tag>/training/training.json"
+    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/tensorflow-train-pipeline/<Git tag>"
     enable_caching = null
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
       ingestion_project_id = "my-project-id"
       model_name = "tensorflow_with_preprocessing"
       model_label = "label_name"
-      tfdv_schema_filename = "tfdv_schema_training.pbtxt"
-      tfdv_train_stats_path = "gs://my-pipeline-root-bucket/train_stats/train.stats"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
@@ -93,17 +84,14 @@ cloud_schedulers_config = {
     description  = "Trigger my TensorFlow prediction pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
-    template_path = "gs://my-assets-bucket/<Git tag>/prediction/prediction.json"
+    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/tensorflow-prediction-pipeline/<Git tag>"
     enable_caching = null
     pipeline_parameters = {
       project_id = "my-project-id"
       project_location = "europe-west4"
-      pipeline_files_gcs_path = "gs://my-assets-bucket/<Git tag>"
       ingestion_project_id = "my-project-id"
       model_name = "tensorflow_with_preprocessing"
       model_label = "label_name"
-      tfdv_schema_filename = "tfdv_schema_training.pbtxt"
-      tfdv_train_stats_path = "gs://my-pipeline-root-bucket/train_stats/train.stats"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
diff --git a/terraform/modules/vertex_deployment/iam.tf b/terraform/modules/vertex_deployment/iam.tf
index 8cacdcbe..2d58475a 100644
--- a/terraform/modules/vertex_deployment/iam.tf
+++ b/terraform/modules/vertex_deployment/iam.tf
@@ -26,28 +26,6 @@ resource "google_storage_bucket_iam_member" "pipelines_sa_pipeline_root_bucket_i
   role   = each.key
 }
 
-# Give pipelines SA read-only access to objects in "assets" bucket
-resource "google_storage_bucket_iam_member" "pipelines_sa_pipeline_assets_bucket_iam" {
-  for_each = toset([
-    "roles/storage.objectViewer",
-    "roles/storage.legacyBucketReader",
-  ])
-  bucket = google_storage_bucket.pipeline_assets_bucket.name
-  member = google_service_account.pipelines_sa.member
-  role   = each.key
-}
-
-# Give cloud functions SA access to read compiled pipelines from bucket
-resource "google_storage_bucket_iam_member" "cloudfunction_sa_pipeline_assets_bucket_iam" {
-  for_each = toset([
-    "roles/storage.objectViewer",
-    "roles/storage.legacyBucketReader",
-  ])
-  bucket = google_storage_bucket.pipeline_assets_bucket.name
-  member = google_service_account.vertex_cloudfunction_sa.member
-  role   = each.key
-}
-
 # Give cloud functions SA access to use the pipelines SA for triggering pipelines
 resource "google_service_account_iam_member" "cloudfunction_sa_can_use_pipelines_sa" {
   service_account_id = google_service_account.pipelines_sa.name
diff --git a/terraform/modules/vertex_deployment/main.tf b/terraform/modules/vertex_deployment/main.tf
index 335ca64f..73c6a4fa 100644
--- a/terraform/modules/vertex_deployment/main.tf
+++ b/terraform/modules/vertex_deployment/main.tf
@@ -50,15 +50,6 @@ resource "google_storage_bucket" "pipeline_root_bucket" {
   depends_on                  = [google_project_service.gcp_services]
 }
 
-resource "google_storage_bucket" "pipeline_assets_bucket" {
-  name                        = "${var.project_id}-pl-assets"
-  location                    = var.region
-  project                     = var.project_id
-  uniform_bucket_level_access = true
-  public_access_prevention    = "enforced"
-  depends_on                  = [google_project_service.gcp_services]
-}
-
 ## Cloud Function - used to trigger pipelines ##
 
 locals {
@@ -123,7 +114,7 @@ resource "google_vertex_ai_metadata_store" "default_metadata_store" {
   depends_on  = [google_project_service.gcp_services]
 }
 
-## Artifact Registry ##
+## Artifact Registry - container images ##
 resource "google_artifact_registry_repository" "vertex-images" {
   repository_id = "vertex-images"
   description   = "Container image repository for training container images"
@@ -132,3 +123,13 @@ resource "google_artifact_registry_repository" "vertex-images" {
   format        = "DOCKER"
   depends_on    = [google_project_service.gcp_services]
 }
+
+## Artifact Registry - KFP pipelines ##
+resource "google_artifact_registry_repository" "vertex-pipelines" {
+  repository_id = "vertex-pipelines"
+  description   = "KFP repository for Vertex Pipelines"
+  project       = var.project_id
+  location      = var.region
+  format        = "KFP"
+  depends_on    = [google_project_service.gcp_services]
+}
diff --git a/terraform/modules/vertex_deployment/outputs.tf b/terraform/modules/vertex_deployment/outputs.tf
index 608e9bcc..e77014e6 100644
--- a/terraform/modules/vertex_deployment/outputs.tf
+++ b/terraform/modules/vertex_deployment/outputs.tf
@@ -26,10 +26,6 @@ output "pipeline_root_bucket_name" {
   value = google_storage_bucket.pipeline_root_bucket.name
 }
 
-output "pipeline_assets_bucket_name" {
-  value = google_storage_bucket.pipeline_assets_bucket.name
-}
-
 output "vertex_pipelines_sa_email" {
   value = google_service_account.pipelines_sa.email
 }

From 496cf159f48637d8fea91e61a314b8b04f3f7f43 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Wed, 26 Jul 2023 13:11:31 +0100
Subject: [PATCH 128/238] remove tensorflow pipelines

---
 Makefile                                      |   6 +-
 cloudbuild/e2e-test.yaml                      |   1 -
 cloudbuild/pr-checks.yaml                     |   1 -
 cloudbuild/release.yaml                       |   7 +-
 .../tests/test_import_model_evaluation.py     |  57 -----
 .../tests/test_lookup_model.py                |  96 ---------
 .../tests/test_update_best_model.py           |  51 -----
 env.sh.example                                |   3 -
 .../{xgboost => }/prediction/pipeline.py      |   0
 .../prediction/queries/preprocessing.sql      |   0
 pipelines/src/pipelines/tensorflow/README.md  |  89 --------
 .../tensorflow/prediction/pipeline.py         | 151 -------------
 .../prediction/queries/preprocessing.sql      |  69 ------
 .../pipelines/tensorflow/training/pipeline.py | 204 ------------------
 .../training/queries/preprocessing.sql        |  88 --------
 .../{xgboost => }/training/pipeline.py        |   0
 .../training/queries/preprocessing.sql        |   0
 pipelines/src/pipelines/xgboost/README.md     |  49 -----
 .../{xgboost => }/prediction/test_e2e.py      |   4 +-
 .../tests/tensorflow/prediction/test_e2e.py   |  37 ----
 .../tests/tensorflow/training/test_e2e.py     |  37 ----
 .../tests/{xgboost => }/training/test_e2e.py  |   4 +-
 .../scheduled_jobs.auto.tfvars.example        |  53 +----
 23 files changed, 14 insertions(+), 993 deletions(-)
 delete mode 100644 components/vertex-components/tests/test_import_model_evaluation.py
 delete mode 100644 components/vertex-components/tests/test_lookup_model.py
 delete mode 100644 components/vertex-components/tests/test_update_best_model.py
 rename pipelines/src/pipelines/{xgboost => }/prediction/pipeline.py (100%)
 rename pipelines/src/pipelines/{xgboost => }/prediction/queries/preprocessing.sql (100%)
 delete mode 100644 pipelines/src/pipelines/tensorflow/README.md
 delete mode 100644 pipelines/src/pipelines/tensorflow/prediction/pipeline.py
 delete mode 100644 pipelines/src/pipelines/tensorflow/prediction/queries/preprocessing.sql
 delete mode 100644 pipelines/src/pipelines/tensorflow/training/pipeline.py
 delete mode 100644 pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
 rename pipelines/src/pipelines/{xgboost => }/training/pipeline.py (100%)
 rename pipelines/src/pipelines/{xgboost => }/training/queries/preprocessing.sql (100%)
 delete mode 100644 pipelines/src/pipelines/xgboost/README.md
 rename pipelines/tests/{xgboost => }/prediction/test_e2e.py (92%)
 delete mode 100644 pipelines/tests/tensorflow/prediction/test_e2e.py
 delete mode 100644 pipelines/tests/tensorflow/training/test_e2e.py
 rename pipelines/tests/{xgboost => }/training/test_e2e.py (92%)

diff --git a/Makefile b/Makefile
index 179d929c..f7ec8a3f 100644
--- a/Makefile
+++ b/Makefile
@@ -35,7 +35,7 @@ test-trigger: ## Runs unit tests for the pipeline trigger code
 
 compile-pipeline: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
 	@cd pipelines/src && \
-	poetry run kfp dsl compile --py pipelines/${PIPELINE_TEMPLATE}/${pipeline}/pipeline.py --output pipelines/${PIPELINE_TEMPLATE}/${pipeline}/pipeline.yaml --function pipeline
+	poetry run kfp dsl compile --py pipelines/${pipeline}/pipeline.py --output pipelines/${pipeline}/pipeline.yaml --function pipeline
 
 setup-components: ## Run unit tests for a component group
 	@cd "components/${GROUP}" && \
@@ -74,11 +74,11 @@ test-all-components-coverage: ## Run tests with coverage
 run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
 	@ $(MAKE) compile-pipeline && \
 	cd pipelines/src && \
-	poetry run python -m pipelines.trigger --template_path=pipelines/${PIPELINE_TEMPLATE}/${pipeline}/pipeline.yaml --enable_caching=$(enable_pipeline_caching)
+	poetry run python -m pipelines.trigger --template_path=pipelines/${pipeline}/pipeline.yaml --enable_caching=$(enable_pipeline_caching)
 
 e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour).
 	@ cd pipelines && \
-	poetry run pytest --log-cli-level=INFO tests/${PIPELINE_TEMPLATE}/$(pipeline) --enable_caching=$(enable_pipeline_caching)
+	poetry run pytest --log-cli-level=INFO tests/$(pipeline) --enable_caching=$(enable_pipeline_caching)
 
 env ?= dev
 deploy-infra: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 2a9af102..7c6494ee 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -30,7 +30,6 @@ steps:
       - VERTEX_SA_EMAIL=${_TEST_VERTEX_SA_EMAIL}
       - VERTEX_CMEK_IDENTIFIER=${_TEST_VERTEX_CMEK_IDENTIFIER}
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
-      - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
       - RESOURCE_SUFFIX=${COMMIT_SHA}
 
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 969e7bbf..93934970 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -32,7 +32,6 @@ steps:
         make test-all-components
     env:
       - SKIP=terraform-fmt,git-dirty
-      - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index f2ac361c..5852e0bd 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -27,19 +27,16 @@ steps:
         for dest in ${_PIPELINE_PUBLISH_AR_PATHS} ; do \
           poetry run python -m pipelines.utils.upload_pipeline \
           --dest=$$dest \
-          --yaml=src/pipelines/${_PIPELINE_TEMPLATE}/training/pipeline.yaml \
+          --yaml=src/pipelines/training/pipeline.yaml \
           --tag=latest \
           --tag=${TAG_NAME} && \
           poetry run python -m pipelines.utils.upload_pipeline \
           --dest=$$dest \
-          --yaml=src/pipelines/${_PIPELINE_TEMPLATE}/prediction/pipeline.yaml \
+          --yaml=src/pipelines/prediction/pipeline.yaml \
           --tag=latest \
           --tag=${TAG_NAME}; \
         done
 
-    env:
-      - PIPELINE_TEMPLATE=${_PIPELINE_TEMPLATE}
-
 options:
   logging: CLOUD_LOGGING_ONLY
 
diff --git a/components/vertex-components/tests/test_import_model_evaluation.py b/components/vertex-components/tests/test_import_model_evaluation.py
deleted file mode 100644
index cfe8c5ab..00000000
--- a/components/vertex-components/tests/test_import_model_evaluation.py
+++ /dev/null
@@ -1,57 +0,0 @@
-from unittest import mock
-from kfp.dsl import Model, Metrics, Dataset
-
-import vertex_components
-from google.cloud.aiplatform_v1 import ModelEvaluation
-
-
-import_model_evaluation = vertex_components.import_model_evaluation.python_func
-
-
-@mock.patch("google.cloud.aiplatform_v1.ModelServiceClient")
-@mock.patch(
-    "builtins.open",
-    new_callable=mock.mock_open,
-    read_data='{"accuracy": 0.85, "problemType": "classification"}',
-)
-@mock.patch("google.protobuf.json_format.ParseDict")
-def test_import_model_evaluation(
-    mock_parse_dict, mock_open, mock_service_client, tmpdir
-):
-    """
-    Checks that when the model evaluation is running and it is writing the metrics
-    """
-    mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
-    mock_metrics = Metrics(uri=tmpdir)
-    mock_dataset = Dataset(uri=tmpdir)
-
-    # Create an instance of the mocked ModelServiceClient.
-    service_client_instance = mock.MagicMock()
-    mock_service_client.return_value = service_client_instance
-    # When import_model_evaluation is called during the test,
-    # it will return a new ModelEvaluation with the specified name.
-    service_client_instance.import_model_evaluation.return_value = ModelEvaluation(
-        name="model_evaluation_name"
-    )
-
-    # Set the return value for ParseDict to be a mock ModelEvaluation
-    mock_parse_dict.return_value = mock.MagicMock(spec=ModelEvaluation)
-
-    model_evaluation_name = import_model_evaluation(
-        model=mock_model,
-        metrics=mock_metrics,
-        test_dataset=mock_dataset,
-        pipeline_job_id="1234",
-        project_location="my-location",
-        evaluation_name="Imported evaluation",
-    )
-
-    service_client_instance.import_model_evaluation.assert_called_once_with(
-        parent=mock_model.metadata["resourceName"],
-        model_evaluation=mock_parse_dict.return_value,
-    )
-
-    # Check that open was called with the correct path
-    mock_open.assert_called_once_with(mock_metrics.uri)
-
-    assert model_evaluation_name[0] == "model_evaluation_name"
diff --git a/components/vertex-components/tests/test_lookup_model.py b/components/vertex-components/tests/test_lookup_model.py
deleted file mode 100644
index a869f7cd..00000000
--- a/components/vertex-components/tests/test_lookup_model.py
+++ /dev/null
@@ -1,96 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import google.cloud.aiplatform  # noqa
-from kfp.dsl import Model
-from unittest import mock
-import pytest
-
-import vertex_components
-
-lookup_model = vertex_components.lookup_model.python_func
-
-
-@mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model(mock_model, tmpdir):
-    """
-    Assert lookup_model produces expected resource name, and that list method is
-    called with the correct arguemnts
-    """
-
-    # Mock attribute and method
-    mock_path = tmpdir
-    mock_model.resource_name = "my-model-resource-name"
-    mock_model.uri = mock_path
-    mock_model.list.return_value = [mock_model]
-
-    # Invoke the model look up
-    found_model_resource_name, _ = lookup_model(
-        model_name="my-model",
-        project_location="europe-west4",
-        project_id="my-project-id",
-        order_models_by="create_time desc",
-        fail_on_model_not_found=False,
-        model=Model(uri=mock_path),
-    )
-
-    assert found_model_resource_name == "my-model-resource-name"
-
-    # Check the list method was called once with the correct arguments
-    mock_model.list.assert_called_once_with(
-        filter='display_name="my-model"',
-        order_by="create_time desc",
-        location="europe-west4",
-        project="my-project-id",
-    )
-
-
-@mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model_when_no_models(mock_model, tmpdir):
-    """
-    Checks that when there are no models and fail_on_model_found = False,
-    lookup_model returns an empty string.
-    """
-    mock_model.list.return_value = []
-    exported_model_resource_name, _ = lookup_model(
-        model_name="my-model",
-        project_location="europe-west4",
-        project_id="my-project-id",
-        order_models_by="create_time desc",
-        fail_on_model_not_found=False,
-        model=Model(uri=str(tmpdir)),
-    )
-
-    print(exported_model_resource_name)
-    assert exported_model_resource_name == ""
-
-
-@mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model_when_no_models_fail(mock_model, tmpdir):
-    """
-    Checks that when there are no models and fail_on_model_found = True,
-    lookup_model raises a RuntimeError.
-    """
-    mock_model.list.return_value = []
-
-    # Verify that a ValueError is raised
-    with pytest.raises(RuntimeError):
-        lookup_model(
-            model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
-            fail_on_model_not_found=True,
-            model=Model(uri=str(tmpdir)),
-        )
diff --git a/components/vertex-components/tests/test_update_best_model.py b/components/vertex-components/tests/test_update_best_model.py
deleted file mode 100644
index 481cd605..00000000
--- a/components/vertex-components/tests/test_update_best_model.py
+++ /dev/null
@@ -1,51 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-from unittest import mock
-
-from kfp.dsl import Model
-
-
-import vertex_components
-
-update_best_model = vertex_components.update_best_model.python_func
-
-
-@mock.patch("google.cloud.aiplatform.Model")
-@mock.patch("google.cloud.aiplatform.model_evaluation.ModelEvaluation")
-@mock.patch("google.cloud.aiplatform.models.ModelRegistry")
-@mock.patch("google.protobuf.json_format.MessageToDict")
-def test_model_batch_predict(
-    mock_message_to_dict,
-    mock_model_registry,
-    mock_model_evaluation,
-    mock_model_class,
-    tmpdir,
-):
-    """
-    Asserts model_batch_predict successfully creates requests given different arguments.
-    """
-    mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
-    mock_message = {"metrics": {"rmse": 0.01}}
-    mock_message_to_dict.return_value = mock_message
-
-    (challenger_wins,) = update_best_model(
-        challenger=mock_model,
-        challenger_evaluation="",
-        parent_model="",
-        project_id="",
-        project_location="",
-        eval_metric="rmse",
-        eval_lower_is_better=True,
-    )
-    assert not challenger_wins
diff --git a/env.sh.example b/env.sh.example
index 3a84eb80..528c3ae7 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -13,9 +13,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-# pipeline template - update to any pipelines under the pipelines folder
-# tensorflow or xgboost
-export PIPELINE_TEMPLATE=tensorflow
 export VERTEX_CMEK_IDENTIFIER= # optional
 export VERTEX_LOCATION=europe-west2
 export VERTEX_NETWORK= # optional
diff --git a/pipelines/src/pipelines/xgboost/prediction/pipeline.py b/pipelines/src/pipelines/prediction/pipeline.py
similarity index 100%
rename from pipelines/src/pipelines/xgboost/prediction/pipeline.py
rename to pipelines/src/pipelines/prediction/pipeline.py
diff --git a/pipelines/src/pipelines/xgboost/prediction/queries/preprocessing.sql b/pipelines/src/pipelines/prediction/queries/preprocessing.sql
similarity index 100%
rename from pipelines/src/pipelines/xgboost/prediction/queries/preprocessing.sql
rename to pipelines/src/pipelines/prediction/queries/preprocessing.sql
diff --git a/pipelines/src/pipelines/tensorflow/README.md b/pipelines/src/pipelines/tensorflow/README.md
deleted file mode 100644
index a5a6bfec..00000000
--- a/pipelines/src/pipelines/tensorflow/README.md
+++ /dev/null
@@ -1,89 +0,0 @@
-<!-- 
-Copyright 2022 Google LLC
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    https://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
- -->
-# TensorFlow Pipelines
-
-## Training pipeline
-The TensorFlow training pipeline can be found in [`training/pipeline.py`](training/pipeline.py). The training component [`train_tensorflow_model`](../../../pipeline_components/_tensorflow/_tensorflow/train/component.py) is the main training component which contains the implementation of a TensorFlow Keras model.
-This component can then be wrapped in a custom kfp ContainerOp from [`google-cloud-pipeline-components`](https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/experimental/custom_job/utils.py) which submits a Vertex Training job with added flexibility for `machine_type`, `replica_count`, `accelerator_type` among other machine configurations. 
-
-### Data
-The input data is split into three parts in BigQuery and stored in Google Cloud Storage: 
-- 80% of the input data is used for model training
-- 10% of the input data is used for model validation
-- 10% of the input data is used for model testing/evaluation
-
-### Model Architecture
-The architecture of the example TensorFlow Keras model is shown below:
-
-![TensorFlow Model Architecture](../../docs/images/tf_model_architecture.png)
-
-- **Input layer**: there is one input node for each of the 7 features used in the example:
-    - `dayofweek`
-    - `hourofday`
-    - `trip_distance`
-    - `trip_miles`
-    - `trip_seconds`
-    - `payment_type`
-    - `company`
-- **Pre-processing layers**
-    - Categorical encoding for categorical features is done using Tensorflow's `StringLookup` layer. New/unknown values are handled using this layer's default parameters. (https://www.tensorflow.org/api_docs/python/tf/keras/layers/StringLookup). 
-        - The feature `payment_type` is one-hot encoded. New/unknown categories are assigned to a one-hot encoded array with zeroes everywhere. 
-        - The feature `company` is ordinal encoded. New/unknown categories are assigned to zero.  
-    - Normalization for the numerical features (`dayofweek`, `hourofday`, `trip_distance`, `trip_miles`, `trip_seconds`)
-- **Dense layers**
-    - One `Dense` layer with 64 units whose activation function is ReLU. 
-    - One `Dense` layer with 32 units whose activation function is ReLU.
-- **Output layer**
-    - One `Dense` layer with 1 unit where no activation is applied (this is because the example is a regression problem)
-
-
-### Model hyperparameters
-You can specify different hyperparameters through the `model_params` argument of `train_tensorflow_model`, including:
-- Batch size
-- No. of epochs to check for early stopping
-- Learning rate
-- Number of hidden units and type of activation function in each layer
-- Loss function
-- Optimization method
-- Evaluation metrics
-- Whether you want early stopping
-
-For a comprehensive list of options for the above hyperparameters, see the docstring in [`train.py`](../../../pipeline_components/_tensorflow/_tensorflow/train/component.py). 
-
-### Model artifacts
-A number of different model artifacts/objects are created by the training of the TensorFlow model. With these files, you can load the model into a new script (without any of the original training code) and run it or resume training from exactly where you left off. For more information, see [this](https://www.tensorflow.org/api_docs/python/tf/keras/models/save_model). 
-
-
-![tensorflow_component_model&metrics_artifact](../../docs/images/tensorflow_component_model&metrics_artifact.png)
-### Model test/evaluation
-Once the model is trained, it will be used to get challenger predictions for evaluation purposes. In general, the component [`predict_tensorflow_model`](../kfp_components/tensorflow/predict.py)
-which expects a single CSV file to create predictions for test data is implemented in the pipeline, However, if you are working working with larger test data, it is more efficient to 
-replace it with a prebuilt component provided by Google, [`ModelBatchPredictOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-0.2.1/google_cloud_pipeline_components.aiplatform.html), 
-to avoid crash caused by insufficent memory usage.
-
-### Distribution strategy
-In deep learning, it is common to use GPUs, which utilise a large number of simple cores allowing parallel computing though thousands of threads at a time, to train complicated neural networks fed by massive datasets.
-For optimisation tasks, it is often better to use CPUs.
-
- There is a variable, `distribute_strategy`, in tensorflow training pipeline that allows you to set up distribution strategy. You have three options:
-|Value| description |
-|---|---|
-|`single` | This strategy use GPU is a GPU device of the requested kind is available, otherwise, it uses CPU |
-|`mirror` | This strategy is typically used for training on one machine with multiple GPUs. |
-|`multi`|This strategy implements synchronous distributed training across multiple machines, each with potentially multiple GPUs|
-
-## Prediction pipeline
-The TensorFlow prediction pipeline can be found in [prediction/pipeline.py](prediction/pipeline.py). 
diff --git a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py b/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
deleted file mode 100644
index 03f5e18f..00000000
--- a/pipelines/src/pipelines/tensorflow/prediction/pipeline.py
+++ /dev/null
@@ -1,151 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import pathlib
-
-from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp import dsl
-
-from pipelines import generate_query
-from vertex_components import lookup_model, model_batch_predict
-
-
-@dsl.pipeline(name="tensorflow-prediction-pipeline")
-def pipeline(
-    project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
-    project_location: str = os.environ.get("VERTEX_LOCATION"),
-    ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
-    model_name: str = "simple_tensorflow",
-    preprocessing_dataset_id: str = "preprocessing",
-    dataset_location: str = os.environ.get("VERTEX_LOCATION"),
-    ingestion_dataset_id: str = "chicago_taxi_trips",
-    prediction_dataset_id: str = "prediction",
-    timestamp: str = "2022-12-01 00:00:00",
-    batch_prediction_machine_type: str = "n1-standard-4",
-    batch_prediction_min_replicas: int = 3,
-    batch_prediction_max_replicas: int = 10,
-    resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
-):
-    """
-    Tensorflow prediction pipeline which:
-     1. Extracts a dataset from BQ
-     2. Looks up the default model version (champion) and
-        dataset which was used to the train model.
-     3. Runs a BatchPredictionJob with optional training-serving skew detection.
-     4. Post-processes predictions
-     5. Loads predictions into BQ
-
-    Args:
-        project_id (str): project id of the Google Cloud project
-        project_location (str): location of the Google Cloud project
-        ingestion_project_id (str): project id containing the source bigquery data
-            for ingestion. This can be the same as `project_id` if the source data is
-            in the same project where the ML pipeline is executed.
-        model_name (str): name of model
-         preprocessing_dataset_id (str): id of BQ dataset used to
-            store all staging data .
-        prediction_dataset_id (str): id of BQ dataset used to
-            store all predictions.
-        dataset_location (str): location of dataset
-        ingestion_dataset_id (str): dataset id of ingestion data
-        timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
-            (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
-            If any time part is missing, it will be regarded as zero.
-        batch_prediction_machine_type (str): Machine type to be used for Vertex Batch
-            Prediction. Example machine_types - n1-standard-4, n1-standard-16 etc
-        batch_prediction_min_replicas (int): Minimum no of machines to distribute the
-            Vertex Batch Prediction job for horizontal scalability
-        batch_prediction_max_replicas (int): Maximum no of machines to distribute the
-            Vertex Batch Prediction job for horizontal scalability.
-        resource_suffix (str): Optional. Additional suffix to append GCS resources
-            that get overwritten.
-
-    Returns:
-        None
-
-    """
-
-    # Create variables to ensure the same arguments are passed
-    # into different components of the pipeline
-    file_pattern = ""  # e.g. "files-*.csv", used as file pattern on storage
-    time_column = "trip_start_timestamp"
-    ingestion_table = "taxi_trips"
-    table_suffix = "_tf_prediction" + str(resource_suffix)  # suffix to table names
-    ingested_table = "ingested_data" + table_suffix
-    monitoring_alert_email_addresses = []
-    monitoring_skew_config = {"defaultSkewThreshold": {"value": 0.001}}
-
-    # generate sql queries which are used in ingestion and preprocessing
-    # operations
-    queries_folder = pathlib.Path(__file__).parent / "queries"
-
-    preprocessing_query = generate_query(
-        queries_folder / "preprocessing.sql",
-        source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
-        source_table=ingestion_table,
-        prediction_dataset=f"{ingestion_project_id}.{prediction_dataset_id}",
-        preprocessing_dataset=f"{ingestion_project_id}.{preprocessing_dataset_id}",
-        ingested_table=ingested_table,
-        dataset_region=project_location,
-        filter_column=time_column,
-        filter_start_value=timestamp,
-    )
-
-    # data ingestion and preprocessing operations
-    preprocessing = BigqueryQueryJobOp(
-        project=project_id, location=dataset_location, query=preprocessing_query
-    ).set_display_name("Ingest data")
-
-    # lookup champion model
-    champion_model = (
-        lookup_model(
-            model_name=model_name,
-            project_location=project_location,
-            project_id=project_id,
-            fail_on_model_not_found=True,
-        )
-        .set_display_name("Look up champion model")
-        .set_caching_options(False)
-    )
-
-    # batch predict from BigQuery to BigQuery
-    bigquery_source_input_uri = (
-        f"bq://{project_id}.{preprocessing_dataset_id}.{ingested_table}"
-    )
-    bigquery_destination_output_uri = f"bq://{project_id}.{prediction_dataset_id}"
-    instance_config = {"instanceType": "object"}
-
-    # predict data
-    batch_prediction = (
-        model_batch_predict(
-            model=champion_model.outputs["model"],
-            job_display_name="my-tensorflow-batch-prediction-job",
-            project_location=project_location,
-            project_id=project_id,
-            source_uri=bigquery_source_input_uri,
-            destination_uri=bigquery_destination_output_uri,
-            source_format="bigquery",
-            destination_format="bigquery",
-            machine_type=batch_prediction_machine_type,
-            starting_replica_count=batch_prediction_min_replicas,
-            max_replica_count=batch_prediction_max_replicas,
-            monitoring_training_dataset=champion_model.outputs["training_dataset"],
-            monitoring_alert_email_addresses=monitoring_alert_email_addresses,
-            monitoring_skew_config=monitoring_skew_config,
-            instance_config=instance_config,
-        )
-        .after(preprocessing)
-        .set_display_name("Batch prediction job")
-    )
diff --git a/pipelines/src/pipelines/tensorflow/prediction/queries/preprocessing.sql b/pipelines/src/pipelines/tensorflow/prediction/queries/preprocessing.sql
deleted file mode 100644
index 3e25a603..00000000
--- a/pipelines/src/pipelines/tensorflow/prediction/queries/preprocessing.sql
+++ /dev/null
@@ -1,69 +0,0 @@
--- Copyright 2022 Google LLC
-
--- Licensed under the Apache License, Version 2.0 (the 'License');
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an 'AS IS' BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
--- Treat 'filter_start_value' as the current time, unless it is empty then use CURRENT_DATETIME() instead
--- This allows us to set the filter_start_value to a specific time for testing or for backfill
-
--- If prediction dataset don't exist, create it
-CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
-  OPTIONS (
-    description = 'Prediction Dataset',
-    location = '{{ dataset_region }}');
-
--- We recreate the ingestion table every time the pipeline run,
--- so we need to drop the generated in the  previous run
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
-with filter_start_values as (
-    SELECT
-    IF('{{ filter_start_value }}' = '', CURRENT_DATETIME(), CAST('{{ filter_start_value }}' AS DATETIME)) as filter_start_value
-)
--- Ingest data between 2 and 3 months ago
-,filtered_data as (
-    SELECT
-    *
-    FROM `{{ source_dataset }}.{{ source_table }}`, filter_start_values
-    WHERE
-         DATE({{ filter_column }}) BETWEEN
-         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value as DATETIME)), INTERVAL 3 MONTH) AND
-         DATE_SUB(DATE(filter_start_value), INTERVAL 2 MONTH)
-)
--- Use the average trip_seconds as a replacement for NULL or 0 values
-,mean_time as (
-    SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
-    FROM filtered_data
-)
-
-SELECT
-    CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
-    CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
-    ST_DISTANCE(
-        ST_GEOGPOINT(pickup_longitude, pickup_latitude),
-        ST_GEOGPOINT(dropoff_longitude, dropoff_latitude)) AS trip_distance,
-    trip_miles,
-    CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
-               WHEN trip_seconds <= 0 then m.avg_trip_seconds
-               ELSE trip_seconds
-               END AS FLOAT64) AS trip_seconds,
-    payment_type,
-    company,
-FROM filtered_data as t, mean_time as m
-WHERE
-    trip_miles > 0 AND fare > 0 AND fare < 1500
-    {% for field in ['fare', 'trip_start_timestamp', 'pickup_longitude',
-                'pickup_latitude', 'dropoff_longitude', 'dropoff_latitude','payment_type','company'] %}
-        AND `{{ field }}` IS NOT NULL
-    {% endfor %}
-    );
diff --git a/pipelines/src/pipelines/tensorflow/training/pipeline.py b/pipelines/src/pipelines/tensorflow/training/pipeline.py
deleted file mode 100644
index 67f267b1..00000000
--- a/pipelines/src/pipelines/tensorflow/training/pipeline.py
+++ /dev/null
@@ -1,204 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import pathlib
-
-from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp import dsl
-from pipelines import generate_query
-from bigquery_components import extract_bq_to_dataset
-from vertex_components import (
-    lookup_model,
-    custom_train_job,
-    import_model_evaluation,
-    update_best_model,
-)
-
-
-@dsl.pipeline(name="tensorflow-train-pipeline")
-def pipeline(
-    project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
-    project_location: str = os.environ.get("VERTEX_LOCATION"),
-    ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
-    model_name: str = "simple_tensorflow",
-    dataset_id: str = "preprocessing",
-    dataset_location: str = os.environ.get("VERTEX_LOCATION"),
-    ingestion_dataset_id: str = "chicago_taxi_trips",
-    timestamp: str = "2022-12-01 00:00:00",
-    staging_bucket: str = os.environ.get("VERTEX_PIPELINE_ROOT"),
-    resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
-    test_dataset_uri: str = "",
-):
-    """
-    Tensorflow Keras training pipeline which:
-     1. Splits and extracts a dataset from BQ to GCS
-     2. Trains a model via Vertex AI CustomTrainingJob
-     3. Evaluates the model against the current champion model
-     4. If better the model becomes the new default model
-
-    Args:
-        project_id (str): project id of the Google Cloud project
-        project_location (str): location of the Google Cloud project
-        ingestion_project_id (str): project id containing the source bigquery data
-            for ingestion. This can be the same as `project_id` if the source data is
-            in the same project where the ML pipeline is executed.
-        model_name (str): name of model
-        model_label (str): label of model
-        dataset_id (str): id of BQ dataset used to store all staging data & predictions
-        dataset_location (str): location of dataset
-        ingestion_dataset_id (str): dataset id of ingestion data
-        timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
-            (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
-            If any time part is missing, it will be regarded as zero.
-        staging_bucket (str): Staging bucket for pipeline artifacts.
-        resource_suffix (str): Optional. Additional suffix to append GCS resources
-            that get overwritten.
-        test_dataset_uri (str): Optional. GCS URI of statis held-out test dataset.
-    """
-
-    # Create variables to ensure the same arguments are passed
-    # into different components of the pipeline
-    label_column_name = "total_fare"
-    time_column = "trip_start_timestamp"
-    ingestion_table = "taxi_trips"
-    table_suffix = f"_tf_training_{resource_suffix}"  # suffix to table names
-    ingested_table = "ingested_data" + table_suffix
-    preprocessed_table = "preprocessed_data" + table_suffix
-    train_table = "train_data" + table_suffix
-    valid_table = "valid_data" + table_suffix
-    test_table = "test_data" + table_suffix
-    primary_metric = "rootMeanSquaredError"
-    pipeline_files_gcs_path = "TODO - remove"
-    train_script_uri = f"{pipeline_files_gcs_path}/assets/train_tf_model.py"
-    hparams = dict(
-        batch_size=100,
-        epochs=5,
-        loss_fn="MeanSquaredError",
-        optimizer="Adam",
-        learning_rate=0.01,
-        hidden_units=[(64, "relu"), (32, "relu")],
-        distribute_strategy="single",
-        early_stopping_epochs=5,
-    )
-
-    # generate sql queries which are used in ingestion and preprocessing
-    # operations
-
-    queries_folder = pathlib.Path(__file__).parent / "queries"
-
-    preprocessing_query = generate_query(
-        queries_folder / "preprocessing.sql",
-        source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
-        source_table=ingestion_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        ingested_table=ingested_table,
-        dataset_region=project_location,
-        filter_column=time_column,
-        target_column=label_column_name,
-        filter_start_value=timestamp,
-        train_table=train_table,
-        validation_table=valid_table,
-        test_table=test_table,
-    )
-
-    preprocessing = BigqueryQueryJobOp(
-        project=project_id, location=dataset_location, query=preprocessing_query
-    ).set_display_name("Ingest & preprocess data")
-
-    # data extraction to gcs
-
-    train_dataset = (
-        extract_bq_to_dataset(
-            bq_client_project_id=project_id,
-            source_project_id=project_id,
-            dataset_id=dataset_id,
-            table_name=train_table,
-            dataset_location=dataset_location,
-        )
-        .after(preprocessing)
-        .set_display_name("Extract train")
-        .set_caching_options(False)
-    ).outputs["dataset"]
-    valid_dataset = (
-        extract_bq_to_dataset(
-            bq_client_project_id=project_id,
-            source_project_id=project_id,
-            dataset_id=dataset_id,
-            table_name=valid_table,
-            dataset_location=dataset_location,
-        )
-        .after(preprocessing)
-        .set_display_name("Extract validation data")
-        .set_caching_options(False)
-    ).outputs["dataset"]
-    test_dataset = (
-        extract_bq_to_dataset(
-            bq_client_project_id=project_id,
-            source_project_id=project_id,
-            dataset_id=dataset_id,
-            table_name=test_table,
-            dataset_location=dataset_location,
-            destination_gcs_uri=test_dataset_uri,
-        )
-        .after(preprocessing)
-        .set_display_name("Extract test data")
-        .set_caching_options(False)
-    ).outputs["dataset"]
-
-    existing_model = (
-        lookup_model(
-            model_name=model_name,
-            project_location=project_location,
-            project_id=project_id,
-            fail_on_model_not_found=False,
-        )
-        .set_display_name("Lookup past model")
-        .set_caching_options(False)
-        .outputs["model_resource_name"]
-    )
-
-    train_model = custom_train_job(
-        train_script_uri=train_script_uri,
-        train_data=train_dataset,
-        valid_data=valid_dataset,
-        test_data=test_dataset,
-        project_id=project_id,
-        project_location=project_location,
-        model_display_name=model_name,
-        train_container_uri="europe-docker.pkg.dev/vertex-ai/training/tf-cpu.2-6:latest",  # noqa: E501
-        serving_container_uri="europe-docker.pkg.dev/vertex-ai/prediction/tf2-cpu.2-6:latest",  # noqa: E501
-        hparams=hparams,
-        staging_bucket=staging_bucket,
-        parent_model=existing_model,
-    ).set_display_name("Train model")
-
-    evaluation = import_model_evaluation(
-        model=train_model.outputs["model"],
-        metrics=train_model.outputs["metrics"],
-        test_dataset=test_dataset,
-        pipeline_job_id="{{$.pipeline_job_name}}",
-        project_location=project_location,
-    ).set_display_name("Import evaluation")
-
-    with dsl.Condition(existing_model != "", "champion-exists"):
-        update_best_model(
-            challenger=train_model.outputs["model"],
-            challenger_evaluation=evaluation.outputs["model_evaluation"],
-            parent_model=existing_model,
-            eval_metric=primary_metric,
-            eval_lower_is_better=True,
-            project_id=project_id,
-            project_location=project_location,
-        ).set_display_name("Update best model")
diff --git a/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql b/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
deleted file mode 100644
index 0182aac2..00000000
--- a/pipelines/src/pipelines/tensorflow/training/queries/preprocessing.sql
+++ /dev/null
@@ -1,88 +0,0 @@
--- If preprocessing dataset don't exist, create it
-CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
-  OPTIONS (
-    description = 'Preprocessing Dataset',
-    location = '{{ dataset_region }}');
-
--- We recreate the ingestion table every time the pipeline run,
--- so we need to drop the generated in the  previous run
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
-WITH filter_start_values AS (
-SELECT
-	IF('{{ filter_start_value }}' = '',
-	CURRENT_DATETIME(),
-	CAST('{{ filter_start_value }}' AS DATETIME)) AS filter_start_value
-)
--- Ingest data between 2 and 3 months ago
-,filtered_data AS (
-    SELECT
-    *
-    FROM `{{ source_dataset }}.{{ source_table }}`, filter_start_values
-    WHERE
-         DATE({{ filter_column }}) BETWEEN
-         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value AS DATETIME)), INTERVAL 3 MONTH) AND
-         DATE_SUB(DATE(filter_start_value), INTERVAL 2 MONTH)
-)
--- Use the average trip_seconds as a replacement for NULL or 0 values
-,mean_time AS (
-    SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
-    FROM filtered_data
-)
-SELECT
-    CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
-    CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
-    ST_DISTANCE(
-        ST_GEOGPOINT(pickup_longitude, pickup_latitude),
-        ST_GEOGPOINT(dropoff_longitude, dropoff_latitude)) AS trip_distance,
-    trip_miles,
-    CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
-               WHEN trip_seconds <= 0 then m.avg_trip_seconds
-               ELSE trip_seconds
-               END AS FLOAT64) AS trip_seconds,
-    payment_type,
-    company,
-    (fare + tips + tolls + extras) AS `{{ target_column }}`,
-FROM filtered_data AS t, mean_time AS m
-WHERE
-    trip_miles > 0 AND fare > 0 AND fare < 1500
-    {% for field in ['fare', 'trip_start_timestamp', 'pickup_longitude',
-                'pickup_latitude', 'dropoff_longitude', 'dropoff_latitude','payment_type','company'] %}
-        AND `{{ field }}` IS NOT NULL
-    {% endfor %}
-);
-
--- Drop and creation of train, testing and validations tables
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ train_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ train_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	10) IN (0, 1, 2, 3, 4, 5, 6, 7));
-
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ validation_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ validation_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	10) IN (8));
-
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ test_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ test_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	10) IN (9));
diff --git a/pipelines/src/pipelines/xgboost/training/pipeline.py b/pipelines/src/pipelines/training/pipeline.py
similarity index 100%
rename from pipelines/src/pipelines/xgboost/training/pipeline.py
rename to pipelines/src/pipelines/training/pipeline.py
diff --git a/pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql b/pipelines/src/pipelines/training/queries/preprocessing.sql
similarity index 100%
rename from pipelines/src/pipelines/xgboost/training/queries/preprocessing.sql
rename to pipelines/src/pipelines/training/queries/preprocessing.sql
diff --git a/pipelines/src/pipelines/xgboost/README.md b/pipelines/src/pipelines/xgboost/README.md
deleted file mode 100644
index b40ec332..00000000
--- a/pipelines/src/pipelines/xgboost/README.md
+++ /dev/null
@@ -1,49 +0,0 @@
-# XGBoost Pipelines
-
-## Training pipeline 
-
-The XGBoost training pipeline can be found in [`training/pipeline.py`](training/pipeline.py) . Within the kubeflow pipeline, [`train_xgboost_model`](../kfp_components/xgboost/train.py) is the main training component which contains the implementation of an XGB model with `scikit-learn` preprocessing.This component can then be wrapped in a custom kfp ContainerOp from [`google-cloud-pipeline-components`](https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/experimental/custom_job/utils.py) which submits a Vertex Training job with added flexibility for `machine_type`, `replica_count`, `accelerator_type` among other machine configurations.
-
-The training phase is preceded by a preprocessing phase where different transformations are applied to the training and evaluation data using scikit-learn preprocessing functions. The **preprocessing** step and the **training** step define the two components of the Scikit-Learn pipeline as shown in the diagram below.
-
-![Training process](../../docs/images/xgboost_architecture.png)
-
-## Preprocessing with Scikit-learn
-The 3 data transformation steps considered in the `train.py` script are:
-
-|Encoder|Description|Features|
-|:----|:----|:----|
-|[StandardScaler()](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html)|Centering and scaling numerical values|   `dayofweek`, `hourofday`, `trip_distance`, `trip_miles`, `trip_seconds`|
-|[OneHotEncoder()](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html)|Encoding a chosen subset of categorical features as a one-hot numeric array|`payment_type`, new/unknown values in categorial features are represented as zeroes everywhere in the one-hot numeric array|
-|[OrdinalEncoder()](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html)|Encoding a chosen subset of categorical features as an integer array|`company`, new/unknown values in categorical features are assigned to an integer equal to the number of categories for that feature in the training set|
-
-More processing steps can be included to the pipeline. For more details, see the [official documentation](https://scikit-learn.org/stable/modules/preprocessing.html). Ensure that these additional pre-processing steps can handle new/unknown values in test data.
-
-## The XGBoost Model
-
-In our example implementation, we have a regression problem of predicting the total fare of a taxi trip in Chicago. Thus, we use XGBRegressor whose hyperparameteres are defined in the variable `model_params` in the file [training/pipeline.py](training/pipeline.py).
-
-### Model Hyperparameters
-
-You can specify different hyperparameters through the `model_params` argument of `train_xgboost_model`, including:
-  - `Booster`: the type of booster (`gbtree` is a tree based booster used by default).
-  - `max_depth`: the depth of each tree.
-  - `Objective`: equivalent to the loss function (squared loss, `reg:squarederror`, is the default).
-  - `min_split_loss`: the minimum loss reduction required to make a further partition on a leaf node of the tree.
-
-More hyperparameters can be used to customize your training. For more details consult the [XGBoost documentation](https://xgboost.readthedocs.io/en/stable/parameter.html)
-
-### Model artifacts
-Two model artifacts are generated when we run the training job: 
-  - `Model.joblib` : The model is exported to GCS file as a [joblib](https://joblib.readthedocs.io/en/latest/why.html#benefits-of-pipelines) object.
-  - `Eval_result` : The evaluation metrics are exported to GCS as JSON file.
-
-![xgboost_component_model&metrics_artifact](../../docs/images/xgboost_component_model&metrics_artifact.png)
-### Model test/evaluation
-Once the model is trained, it will be used to get challenger predictions for evaluation purposes. In general, the component [`predict_tensorflow_model`](../kfp_components/tensorflow/predict.py)
-which expects a single CSV file to create predictions for test data is implemented in the pipeline. However, if you are working with larger test data, it is more efficient to 
-replace it with a Google prebuilt component, [`ModelBatchPredictOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-0.2.1/google_cloud_pipeline_components.aiplatform.html), 
-to avoid crash caused by memory overload.
-
-## Prediction pipeline
-The XGBoost prediction pipeline can be found in [prediction/pipeline.py](prediction/pipeline.py). 
diff --git a/pipelines/tests/xgboost/prediction/test_e2e.py b/pipelines/tests/prediction/test_e2e.py
similarity index 92%
rename from pipelines/tests/xgboost/prediction/test_e2e.py
rename to pipelines/tests/prediction/test_e2e.py
index 635fdd36..4dd903cd 100644
--- a/pipelines/tests/xgboost/prediction/test_e2e.py
+++ b/pipelines/tests/prediction/test_e2e.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from pipelines.xgboost.prediction.pipeline import xgboost_pipeline
+from pipelines.prediction.pipeline import pipeline
 from tests.e2e.test_e2e import pipeline_e2e_test
 
 
@@ -35,7 +35,7 @@ def test_pipeline_run(enable_caching) -> None:
 
     # tasks (components) and outputs for tasks which occur unconditionally
     pipeline_e2e_test(
-        xgboost_pipeline,
+        pipeline,
         enable_caching=enable_caching,
         common_tasks={},
     )
diff --git a/pipelines/tests/tensorflow/prediction/test_e2e.py b/pipelines/tests/tensorflow/prediction/test_e2e.py
deleted file mode 100644
index c0e56e8e..00000000
--- a/pipelines/tests/tensorflow/prediction/test_e2e.py
+++ /dev/null
@@ -1,37 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from pipelines.tensorflow.prediction.pipeline import tensorflow_pipeline
-from tests.e2e.test_e2e import pipeline_e2e_test
-
-
-def test_pipeline_run(enable_caching) -> None:
-    """
-    Tests if pipeline is run successfully
-    Triggers pipeline synchronously.
-    Tests will fail if:
-    - Any errors are thrown during execution
-    - Any of the expected component outputs are empty (size == 0kb)
-
-    Arguments:
-        None
-
-    Returns:
-        None
-    """
-    pipeline_e2e_test(
-        tensorflow_pipeline,
-        enable_caching=enable_caching,
-        common_tasks={},
-    )
diff --git a/pipelines/tests/tensorflow/training/test_e2e.py b/pipelines/tests/tensorflow/training/test_e2e.py
deleted file mode 100644
index fa306ec7..00000000
--- a/pipelines/tests/tensorflow/training/test_e2e.py
+++ /dev/null
@@ -1,37 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from pipelines.tensorflow.training.pipeline import tensorflow_pipeline
-from tests.e2e.test_e2e import pipeline_e2e_test
-
-
-def test_pipeline_run(enable_caching) -> None:
-    """
-    Tests if pipeline is run successfully
-    Triggers pipeline synchronously.
-    Tests will fail if:
-    - Any errors are thrown during execution
-    - Any of the expected component outputs are empty (size == 0kb)
-
-    Arguments:
-        None
-
-    Returns:
-        None
-    """
-    pipeline_e2e_test(
-        tensorflow_pipeline,
-        common_tasks={},
-        enable_caching=enable_caching,
-    )
diff --git a/pipelines/tests/xgboost/training/test_e2e.py b/pipelines/tests/training/test_e2e.py
similarity index 92%
rename from pipelines/tests/xgboost/training/test_e2e.py
rename to pipelines/tests/training/test_e2e.py
index b494fe9e..9886c6db 100644
--- a/pipelines/tests/xgboost/training/test_e2e.py
+++ b/pipelines/tests/training/test_e2e.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from pipelines.xgboost.training.pipeline import xgboost_pipeline
+from pipelines.training.pipeline import pipeline
 from tests.e2e.test_e2e import pipeline_e2e_test
 
 
@@ -31,7 +31,7 @@ def test_pipeline_run(enable_caching) -> None:
         None
     """
     pipeline_e2e_test(
-        xgboost_pipeline,
+        pipeline,
         enable_caching=enable_caching,
         common_tasks={},
     )
diff --git a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
index beb66051..0fefcd87 100644
--- a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
+++ b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
@@ -18,7 +18,7 @@ cloud_schedulers_config = {
 
   xgboost_training = {
     name         = "xgboost-training-pipeline-trigger"
-    description  = "Trigger my XGBoost training pipeline in Vertex"
+    description  = "Trigger my training pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
     template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/<Git tag>"
@@ -33,12 +33,12 @@ cloud_schedulers_config = {
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
       timestamp = "2022-12-01 00:00:00"
-    },
+    }
   },
 
   xgboost_prediction = {
     name         = "xgboost-prediction-pipeline-trigger"
-    description  = "Trigger my XGBoost prediction pipeline in Vertex"
+    description  = "Trigger my prediction pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
     template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/<Git tag>"
@@ -56,49 +56,6 @@ cloud_schedulers_config = {
       batch_prediction_machine_type = "n1-standard-4"
       batch_prediction_min_replicas = 3
       batch_prediction_max_replicas = 5
-    },
-  },
-
-  tensorflow_training = {
-    name         = "tensorflow-training-pipeline-trigger"
-    description  = "Trigger my TensorFlow training pipeline in Vertex"
-    schedule     = "0 0 * * 0"
-    time_zone    = "UTC"
-    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/tensorflow-train-pipeline/<Git tag>"
-    enable_caching = null
-    pipeline_parameters = {
-      project_id = "my-project-id"
-      project_location = "europe-west4"
-      ingestion_project_id = "my-project-id"
-      model_name = "tensorflow_with_preprocessing"
-      model_label = "label_name"
-      dataset_id = "preprocessing"
-      dataset_location = "europe-west2"
-      ingestion_dataset_id = "chicago_taxi_trips"
-      timestamp = "2022-12-01 00:00:00"
-    },
-  },
-
-  tensorflow_prediction = {
-    name         = "tensorflow-prediction-pipeline-trigger"
-    description  = "Trigger my TensorFlow prediction pipeline in Vertex"
-    schedule     = "0 0 * * 0"
-    time_zone    = "UTC"
-    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/tensorflow-prediction-pipeline/<Git tag>"
-    enable_caching = null
-    pipeline_parameters = {
-      project_id = "my-project-id"
-      project_location = "europe-west4"
-      ingestion_project_id = "my-project-id"
-      model_name = "tensorflow_with_preprocessing"
-      model_label = "label_name"
-      dataset_id = "preprocessing"
-      dataset_location = "europe-west2"
-      ingestion_dataset_id = "chicago_taxi_trips"
-      timestamp = "2022-12-01 00:00:00"
-      batch_prediction_machine_type = "n1-standard-4"
-      batch_prediction_min_replicas = 3
-      batch_prediction_max_replicas = 5
-    },
-  },
+    }
+  }
 }

From 5abfa36b14645275fb782dd54d88851ebf6d73c6 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Wed, 26 Jul 2023 13:17:34 +0100
Subject: [PATCH 129/238] fix: restore lookup_model component for prediction
 pipeline

---
 .../src/vertex_components/__init__.py         |   2 +
 .../src/vertex_components/lookup_model.py     |  99 +++++++++++++++
 .../tests/test_lookup_model.py                | 114 ++++++++++++++++++
 3 files changed, 215 insertions(+)
 create mode 100644 components/vertex-components/src/vertex_components/lookup_model.py
 create mode 100644 components/vertex-components/tests/test_lookup_model.py

diff --git a/components/vertex-components/src/vertex_components/__init__.py b/components/vertex-components/src/vertex_components/__init__.py
index 040039b3..3e112c57 100644
--- a/components/vertex-components/src/vertex_components/__init__.py
+++ b/components/vertex-components/src/vertex_components/__init__.py
@@ -1,9 +1,11 @@
+from .lookup_model import lookup_model
 from .model_batch_predict import model_batch_predict
 from .upload_model import upload_model
 
 
 __version__ = "0.0.1"
 __all__ = [
+    "lookup_model",
     "model_batch_predict",
     "upload_model",
 ]
diff --git a/components/vertex-components/src/vertex_components/lookup_model.py b/components/vertex-components/src/vertex_components/lookup_model.py
new file mode 100644
index 00000000..76b24ac1
--- /dev/null
+++ b/components/vertex-components/src/vertex_components/lookup_model.py
@@ -0,0 +1,99 @@
+# Copyright 2022 Google LLC
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+#     https://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from kfp.v2.dsl import component, Output, Model
+from typing import NamedTuple
+
+
+@component(
+    base_image="python:3.9",
+    packages_to_install=["google-cloud-aiplatform==1.24.1"],
+)
+def lookup_model(
+    model_name: str,
+    project_location: str,
+    project_id: str,
+    model: Output[Model],
+    order_models_by: str = "create_time desc",
+    fail_on_model_not_found: bool = False,
+) -> NamedTuple("Outputs", [("model_resource_name", str), ("training_dataset", dict)]):
+    """
+    Fetch a model given a model name (display name) and export to GCS.
+
+    Args:
+        model_name (str): display name of the model
+        project_location (str): location of the Google Cloud project
+        project_id (str): project id of the Google Cloud project
+        model (Output[Model]): a Vertex AI model
+        order_models_by (str): if multiple models are found based on the display name,
+            use a filter clause:
+            A comma-separated list of fields to order by, sorted in
+            ascending order. Use "desc" after a field name for descending.
+            Supported fields: `display_name`, `create_time`, `update_time`
+            Defaults to "create_time desc".
+        fail_on_model_not_found (bool): if set to True, raise runtime error if
+            model is not found
+
+    Returns:
+        str: Resource name of the found model. Empty string if model not found.
+    """
+
+    import json
+    import logging
+    import os
+    from pathlib import Path
+    from google.cloud.aiplatform import Model
+
+    TRAINING_DATASET_INFO = "training_dataset.json"
+
+    logging.info(f"listing models with display name {model_name}")
+    models = Model.list(
+        filter=f'display_name="{model_name}"',
+        order_by=order_models_by,
+        location=project_location,
+        project=project_id,
+    )
+    logging.info(f"found {len(models)} models")
+
+    training_dataset = {}
+    model_resource_name = ""
+    if len(models) == 0:
+        logging.error(
+            f"No model found with name {model_name}"
+            + f"(project: {project_id} location: {project_location})"
+        )
+        if fail_on_model_not_found:
+            raise RuntimeError(f"Failed as model was not found")
+    elif len(models) == 1:
+        target_model = models[0]
+        model_resource_name = target_model.resource_name
+        logging.info(f"choosing model by order ({order_models_by})")
+        logging.info(f"model display name: {target_model.display_name}")
+        logging.info(f"model resource name: {target_model.resource_name}")
+        logging.info(f"model uri: {target_model.uri}")
+        model.uri = target_model.uri
+        model.metadata["resourceName"] = target_model.resource_name
+
+        path = Path(model.path) / TRAINING_DATASET_INFO
+        logging.info(f"Reading training dataset metadata: {path}")
+
+        if os.path.exists(path):
+            with open(path, "r") as fp:
+                training_dataset = json.load(fp)
+        else:
+            logging.warning("Training dataset metadata doesn't exist!")
+    else:
+        raise RuntimeError(f"Multiple models with name {model_name} were found.")
+
+    return model_resource_name, training_dataset
diff --git a/components/vertex-components/tests/test_lookup_model.py b/components/vertex-components/tests/test_lookup_model.py
new file mode 100644
index 00000000..1ba31f81
--- /dev/null
+++ b/components/vertex-components/tests/test_lookup_model.py
@@ -0,0 +1,114 @@
+# Copyright 2022 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import google.cloud.aiplatform  # noqa
+from kfp.v2.dsl import Model
+from unittest import mock
+import pytest
+
+import vertex_components
+
+lookup_model = vertex_components.lookup_model.python_func
+
+
+def test_lookup_model(tmpdir):
+    """
+    Assert lookup_model produces expected resource name, and that list method is
+    called with the correct arguemnts
+
+    Args:
+        tmpdir: built-in pytest tmpdir fixture
+
+    Returns:
+        None
+    """
+    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
+
+        # Mock attribute and method
+
+        mock_path = tmpdir
+        mock_model.resource_name = "my-model-resource-name"
+        mock_model.uri = mock_path
+        mock_model.list.return_value = [mock_model]
+
+        # Invoke the model look up
+        found_model_resource_name, _ = lookup_model(
+            model_name="my-model",
+            project_location="europe-west4",
+            project_id="my-project-id",
+            order_models_by="create_time desc",
+            fail_on_model_not_found=False,
+            model=Model(uri=mock_path),
+        )
+
+        assert found_model_resource_name == "my-model-resource-name"
+
+        # Check the list method was called once with the correct arguments
+        mock_model.list.assert_called_once_with(
+            filter='display_name="my-model"',
+            order_by="create_time desc",
+            location="europe-west4",
+            project="my-project-id",
+        )
+
+
+def test_lookup_model_when_no_models(tmpdir):
+    """
+    Checks that when there are no models and fail_on_model_found = False,
+    lookup_model returns an empty string.
+
+    Args:
+        tmpdir: built-in pytest tmpdir fixture
+
+    Returns:
+        None
+    """
+    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
+        mock_model.list.return_value = []
+        exported_model_resource_name, _ = lookup_model(
+            model_name="my-model",
+            project_location="europe-west4",
+            project_id="my-project-id",
+            order_models_by="create_time desc",
+            fail_on_model_not_found=False,
+            model=Model(uri=str(tmpdir)),
+        )
+    print(exported_model_resource_name)
+    assert exported_model_resource_name == ""
+
+
+def test_lookup_model_when_no_models_fail(tmpdir):
+    """
+    Checks that when there are no models and fail_on_model_found = True,
+    lookup_model raises a RuntimeError.
+
+    Args:
+        tmpdir: built-in pytest tmpdir fixture
+
+    Returns:
+        None
+    """
+    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
+        mock_model.list.return_value = []
+
+        # Verify that a ValueError is raised
+        with pytest.raises(RuntimeError):
+            lookup_model(
+                model_name="my-model",
+                project_location="europe-west4",
+                project_id="my-project-id",
+                order_models_by="create_time desc",
+                fail_on_model_not_found=True,
+                model=Model(uri=str(tmpdir)),
+            )

From 15b4c98f8e9d9da280c2b691861902dc77b90f43 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Thu, 27 Jul 2023 09:08:19 +0100
Subject: [PATCH 130/238] feat: add custom serving container

---
 Makefile                                      |  15 +-
 .../src/vertex_components/upload_model.py     |   2 +
 env.sh.example                                |   1 +
 {training => model}/.gitignore                |   0
 model/poetry.lock                             | 991 ++++++++++++++++++
 {training => model}/pyproject.toml            |   7 +-
 {training => model/serving}/.gcloudignore     |   0
 model/serving/Dockerfile                      |  10 +
 model/serving/main.py                         |  29 +
 model/training/.gcloudignore                  |   2 +
 {training => model/training}/Dockerfile       |   2 +-
 training/main.py => model/training/train.py   |   0
 .../src/pipelines/prediction/pipeline.py      |   7 +-
 pipelines/src/pipelines/training/pipeline.py  |  11 +-
 training/poetry.lock                          | 283 -----
 15 files changed, 1065 insertions(+), 295 deletions(-)
 rename {training => model}/.gitignore (100%)
 create mode 100644 model/poetry.lock
 rename {training => model}/pyproject.toml (64%)
 rename {training => model/serving}/.gcloudignore (100%)
 create mode 100644 model/serving/Dockerfile
 create mode 100644 model/serving/main.py
 create mode 100644 model/training/.gcloudignore
 rename {training => model/training}/Dockerfile (89%)
 rename training/main.py => model/training/train.py (100%)
 delete mode 100644 training/poetry.lock

diff --git a/Makefile b/Makefile
index f7ec8a3f..ef889513 100644
--- a/Makefile
+++ b/Makefile
@@ -92,10 +92,21 @@ destroy-infra: ## DESTROY the Terraform infrastructure in your project. Requires
 	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
 
 build-training-container: ## Build and push training container image using Docker
-	@ cd training && \
-	poetry export -f requirements.txt -o requirements.txt && \
+	@ cd model && \
+	poetry export -f requirements.txt -o training/requirements.txt && \
+	cd training && \
 	gcloud builds submit . \
 	--tag=${TRAINING_CONTAINER_IMAGE} \
 	--region=${VERTEX_LOCATION} \
 	--project=${VERTEX_PROJECT_ID} \
 	--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source
+
+build-serving-container: ## Build and push serving container image using Docker
+	@ cd model && \
+	poetry export --with serving -f requirements.txt -o serving/requirements.txt && \
+	cd serving && \
+	gcloud builds submit . \
+	--tag=${SERVING_CONTAINER_IMAGE} \
+	--region=${VERTEX_LOCATION} \
+	--project=${VERTEX_PROJECT_ID} \
+	--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source
diff --git a/components/vertex-components/src/vertex_components/upload_model.py b/components/vertex-components/src/vertex_components/upload_model.py
index 59838d37..4f3b5729 100644
--- a/components/vertex-components/src/vertex_components/upload_model.py
+++ b/components/vertex-components/src/vertex_components/upload_model.py
@@ -193,6 +193,8 @@ def import_evaluation(
         display_name=model_name,
         artifact_uri=model.uri,
         serving_container_image_uri=serving_container_image,
+        serving_container_predict_route="/predict",
+        serving_container_health_route="/healthz",
         parent_model=(
             champion_model.resource_name if champion_model is not None else None
         ),
diff --git a/env.sh.example b/env.sh.example
index 528c3ae7..eedd1308 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -25,3 +25,4 @@ export RESOURCE_SUFFIX=default
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
 export TRAINING_CONTAINER_IMAGE=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images/training:${RESOURCE_SUFFIX}
+export SERVING_CONTAINER_IMAGE=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images/serving:${RESOURCE_SUFFIX}
diff --git a/training/.gitignore b/model/.gitignore
similarity index 100%
rename from training/.gitignore
rename to model/.gitignore
diff --git a/model/poetry.lock b/model/poetry.lock
new file mode 100644
index 00000000..93cadc26
--- /dev/null
+++ b/model/poetry.lock
@@ -0,0 +1,991 @@
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+
+[[package]]
+name = "annotated-types"
+version = "0.5.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "annotated_types-0.5.0-py3-none-any.whl", hash = "sha256:58da39888f92c276ad970249761ebea80ba544b77acddaa1a4d6cf78287d45fd"},
+    {file = "annotated_types-0.5.0.tar.gz", hash = "sha256:47cdc3490d9ac1506ce92c7aaa76c579dc3509ff11e098fc867e5130ab7be802"},
+]
+
+[[package]]
+name = "anyio"
+version = "3.7.1"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
+    {file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+
+[package.extras]
+doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
+test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (<0.22)"]
+
+[[package]]
+name = "cachetools"
+version = "5.3.1"
+description = "Extensible memoizing collections and decorators"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
+    {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
+]
+
+[[package]]
+name = "certifi"
+version = "2023.7.22"
+description = "Python package for providing Mozilla's CA Bundle."
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
+    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
+]
+
+[[package]]
+name = "charset-normalizer"
+version = "3.2.0"
+description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "charset-normalizer-3.2.0.tar.gz", hash = "sha256:3bb3d25a8e6c0aedd251753a79ae98a093c7e7b471faa3aa9a93a81431987ace"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b87549028f680ca955556e3bd57013ab47474c3124dc069faa0b6545b6c9710"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7c70087bfee18a42b4040bb9ec1ca15a08242cf5867c58726530bdf3945672ed"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a103b3a7069b62f5d4890ae1b8f0597618f628b286b03d4bc9195230b154bfa9"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:94aea8eff76ee6d1cdacb07dd2123a68283cb5569e0250feab1240058f53b623"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:db901e2ac34c931d73054d9797383d0f8009991e723dab15109740a63e7f902a"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b0dac0ff919ba34d4df1b6131f59ce95b08b9065233446be7e459f95554c0dc8"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:193cbc708ea3aca45e7221ae58f0fd63f933753a9bfb498a3b474878f12caaad"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09393e1b2a9461950b1c9a45d5fd251dc7c6f228acab64da1c9c0165d9c7765c"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:baacc6aee0b2ef6f3d308e197b5d7a81c0e70b06beae1f1fcacffdbd124fe0e3"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:bf420121d4c8dce6b889f0e8e4ec0ca34b7f40186203f06a946fa0276ba54029"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:c04a46716adde8d927adb9457bbe39cf473e1e2c2f5d0a16ceb837e5d841ad4f"},
+    {file = "charset_normalizer-3.2.0-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:aaf63899c94de41fe3cf934601b0f7ccb6b428c6e4eeb80da72c58eab077b19a"},
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+    {file = "uvicorn-0.23.1-py3-none-any.whl", hash = "sha256:1d55d46b83ee4ce82b4e82f621f2050adb3eb7b5481c13f9af1744951cae2f1f"},
+    {file = "uvicorn-0.23.1.tar.gz", hash = "sha256:da9b0c8443b2d7ee9db00a345f1eee6db7317432c9d4400f5049cc8d358383be"},
+]
+
+[package.dependencies]
+click = ">=7.0"
+h11 = ">=0.8"
+typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1)", "watchfiles (>=0.13)", "websockets (>=10.4)"]
+
+[[package]]
+name = "xgboost"
+version = "1.7.6"
+description = "XGBoost Python Package"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "xgboost-1.7.6-py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.macosx_12_0_x86_64.whl", hash = "sha256:4c34675b4d2678c624ddde5d45361e7e16046923e362e4e609b88353e6b87124"},
+    {file = "xgboost-1.7.6-py3-none-macosx_12_0_arm64.whl", hash = "sha256:59b4b366d2cafc7f645e87d897983a5b59be02876194b1d213bd8d8b811d8ce8"},
+    {file = "xgboost-1.7.6-py3-none-manylinux2014_aarch64.whl", hash = "sha256:281c3c6f4fbed2d36bf95cd02a641afa95e72e9abde70064056da5e76233e8df"},
+    {file = "xgboost-1.7.6-py3-none-manylinux2014_x86_64.whl", hash = "sha256:b1d5db49b199152d62bd9217c98760207d3de86d2b9d243260c573ffe638f80a"},
+    {file = "xgboost-1.7.6-py3-none-win_amd64.whl", hash = "sha256:127cf1f5e2ec25cd41429394c6719b87af1456ce583e89f0bffd35d02ad18bcb"},
+    {file = "xgboost-1.7.6.tar.gz", hash = "sha256:1c527554a400445e0c38186039ba1a00425dcdb4e40b37eed0e74cb39a159c47"},
+]
+
+[package.dependencies]
+numpy = "*"
+scipy = "*"
+
+[package.extras]
+dask = ["dask", "distributed", "pandas"]
+datatable = ["datatable"]
+pandas = ["pandas"]
+plotting = ["graphviz", "matplotlib"]
+pyspark = ["cloudpickle", "pyspark", "scikit-learn"]
+scikit-learn = ["scikit-learn"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = "^3.9"
+content-hash = "2bbdc91e77ecba39a913eb039abe6c1be55f6dcd0b756ff97b8f11b7e376c970"
diff --git a/training/pyproject.toml b/model/pyproject.toml
similarity index 64%
rename from training/pyproject.toml
rename to model/pyproject.toml
index ad6df515..e879a489 100644
--- a/training/pyproject.toml
+++ b/model/pyproject.toml
@@ -1,5 +1,5 @@
 [tool.poetry]
-name = "training"
+name = "model"
 version = "0.1.0"
 description = ""
 authors = ["Your Name <you@example.com>"]
@@ -12,6 +12,11 @@ xgboost = "^1.7.6"
 pandas = "^2.0.3"
 
 
+[tool.poetry.group.serving.dependencies]
+fastapi = {extras = ["uvicorn"], version = "^0.100.0"}
+uvicorn = "^0.23.1"
+google-cloud-storage = "^2.10.0"
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
diff --git a/training/.gcloudignore b/model/serving/.gcloudignore
similarity index 100%
rename from training/.gcloudignore
rename to model/serving/.gcloudignore
diff --git a/model/serving/Dockerfile b/model/serving/Dockerfile
new file mode 100644
index 00000000..71207403
--- /dev/null
+++ b/model/serving/Dockerfile
@@ -0,0 +1,10 @@
+FROM python:3.9.16-slim
+ENV PIP_NO_CACHE_DIR=off \
+    PIP_DISABLE_PIP_VERSION_CHECK=on \
+    PIP_DEFAULT_TIMEOUT=100
+
+COPY requirements.txt requirements.txt
+RUN pip install -r requirements.txt
+COPY main.py main.py
+
+CMD exec uvicorn main:app --host "0.0.0.0" --port "$AIP_HTTP_PORT"
diff --git a/model/serving/main.py b/model/serving/main.py
new file mode 100644
index 00000000..3b264b02
--- /dev/null
+++ b/model/serving/main.py
@@ -0,0 +1,29 @@
+import joblib
+import os
+
+import pandas as pd
+from fastapi import FastAPI, Request
+from google.cloud import storage
+
+app = FastAPI()
+client = storage.Client()
+
+with open("model.joblib", "wb") as f:
+    client.download_blob_to_file(f"{os.environ['AIP_STORAGE_URI']}/model.joblib", f)
+_model = joblib.load("model.joblib")
+
+
+@app.get(os.environ.get("AIP_HEALTH_ROUTE", "/healthz"))
+def health():
+    return {}
+
+
+@app.post(os.environ.get("AIP_PREDICT_ROUTE", "/predict"))
+async def predict(request: Request):
+    body = await request.json()
+
+    instances = body["instances"]
+    inputs_df = pd.DataFrame(instances)
+    outputs = _model.predict(inputs_df).tolist()
+
+    return {"predictions": outputs}
diff --git a/model/training/.gcloudignore b/model/training/.gcloudignore
new file mode 100644
index 00000000..510bf9ce
--- /dev/null
+++ b/model/training/.gcloudignore
@@ -0,0 +1,2 @@
+.venv
+.DS_Store
diff --git a/training/Dockerfile b/model/training/Dockerfile
similarity index 89%
rename from training/Dockerfile
rename to model/training/Dockerfile
index bf4587f2..4b4effce 100644
--- a/training/Dockerfile
+++ b/model/training/Dockerfile
@@ -5,4 +5,4 @@ ENV PIP_NO_CACHE_DIR=off \
 
 COPY requirements.txt requirements.txt
 RUN pip install -r requirements.txt
-COPY main.py main.py
+COPY train.py train.py
diff --git a/training/main.py b/model/training/train.py
similarity index 100%
rename from training/main.py
rename to model/training/train.py
diff --git a/pipelines/src/pipelines/prediction/pipeline.py b/pipelines/src/pipelines/prediction/pipeline.py
index 6d618511..cf038d70 100644
--- a/pipelines/src/pipelines/prediction/pipeline.py
+++ b/pipelines/src/pipelines/prediction/pipeline.py
@@ -78,8 +78,8 @@ def pipeline(
     # into different components of the pipeline
     time_column = "trip_start_timestamp"
     ingestion_table = "taxi_trips"
-    table_suffix = "_xgb_prediction" + str(resource_suffix)  # suffix to table names
-    ingested_table = "ingested_data" + table_suffix
+    table_suffix = "_xgb_prediction_" + str(resource_suffix)  # suffix to table names
+    ingested_table = "ingested_data_" + table_suffix
     monitoring_alert_email_addresses = []
     monitoring_skew_config = {"defaultSkewThreshold": {"value": 0.001}}
 
@@ -131,6 +131,9 @@ def pipeline(
             destination_uri=bigquery_destination_output_uri,
             source_format="bigquery",
             destination_format="bigquery",
+            instance_config={
+                "instanceType": "object",
+            },
             machine_type=batch_prediction_machine_type,
             starting_replica_count=batch_prediction_min_replicas,
             max_replica_count=batch_prediction_max_replicas,
diff --git a/pipelines/src/pipelines/training/pipeline.py b/pipelines/src/pipelines/training/pipeline.py
index 93c83228..3e2c3ed4 100644
--- a/pipelines/src/pipelines/training/pipeline.py
+++ b/pipelines/src/pipelines/training/pipeline.py
@@ -22,7 +22,8 @@
 from bigquery_components import extract_bq_to_dataset
 from vertex_components import upload_model
 
-IMAGE = os.environ.get("TRAINING_CONTAINER_IMAGE")
+TRAINING_IMAGE = os.environ["TRAINING_CONTAINER_IMAGE"]
+SERVING_IMAGE = os.environ["SERVING_CONTAINER_IMAGE"]
 
 
 @dsl.container_component
@@ -36,10 +37,10 @@ def train(
     hparams: dict,
 ):
     return dsl.ContainerSpec(
-        image=IMAGE,
+        image=TRAINING_IMAGE,
         command=["python"],
         args=[
-            "main.py",
+            "train.py",
             "--train-data",
             train_data.path,
             "--valid-data",
@@ -197,9 +198,7 @@ def pipeline(
         eval_metric=primary_metric,
         eval_lower_is_better=True,
         model=train_model.outputs["model"],
-        serving_container_image=(
-            "europe-docker.pkg.dev/vertex-ai/prediction/sklearn-cpu.0-24:latest"
-        ),
+        serving_container_image=SERVING_IMAGE,
         model_name=model_name,
         pipeline_job_id="{{$.pipeline_job_name}}",
         test_dataset=test_dataset,
diff --git a/training/poetry.lock b/training/poetry.lock
deleted file mode 100644
index 611c8c73..00000000
--- a/training/poetry.lock
+++ /dev/null
@@ -1,283 +0,0 @@
-# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
-
-[[package]]
-name = "joblib"
-version = "1.3.1"
-description = "Lightweight pipelining with Python functions"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "joblib-1.3.1-py3-none-any.whl", hash = "sha256:89cf0529520e01b3de7ac7b74a8102c90d16d54c64b5dd98cafcd14307fdf915"},
-    {file = "joblib-1.3.1.tar.gz", hash = "sha256:1f937906df65329ba98013dc9692fe22a4c5e4a648112de500508b18a21b41e3"},
-]
-
-[[package]]
-name = "numpy"
-version = "1.25.1"
-description = "Fundamental package for array computing in Python"
-optional = false
-python-versions = ">=3.9"
-files = [
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-
-[[package]]
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-version = "2.0.3"
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-optional = false
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-numpy = [
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-    {version = ">=1.21.0", markers = "python_version >= \"3.10\""},
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From e0939cf1074f6dca7b429037bec4c5ba5f18c4bd Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Thu, 27 Jul 2023 10:01:58 +0100
Subject: [PATCH 131/238] consolidate training and serving image builds

---
 Makefile                                     | 19 ++++------------
 env.sh.example                               |  3 +--
 model/{serving => }/.gcloudignore            |  0
 model/.gitignore                             |  1 -
 model/Dockerfile                             | 24 ++++++++++++++++++++
 model/cloudbuild.yaml                        |  7 ++++++
 model/serving/Dockerfile                     | 10 --------
 model/training/.gcloudignore                 |  2 --
 model/training/Dockerfile                    |  8 -------
 pipelines/src/pipelines/training/pipeline.py |  8 ++++---
 10 files changed, 41 insertions(+), 41 deletions(-)
 rename model/{serving => }/.gcloudignore (100%)
 delete mode 100644 model/.gitignore
 create mode 100644 model/Dockerfile
 create mode 100644 model/cloudbuild.yaml
 delete mode 100644 model/serving/Dockerfile
 delete mode 100644 model/training/.gcloudignore
 delete mode 100644 model/training/Dockerfile

diff --git a/Makefile b/Makefile
index ef889513..72adc2a1 100644
--- a/Makefile
+++ b/Makefile
@@ -91,22 +91,11 @@ destroy-infra: ## DESTROY the Terraform infrastructure in your project. Requires
 	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
 	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
 
-build-training-container: ## Build and push training container image using Docker
+target ?= training
+build-container: ## Build and push training/serving container image using Docker. Specify target=<training|serving>
 	@ cd model && \
-	poetry export -f requirements.txt -o training/requirements.txt && \
-	cd training && \
 	gcloud builds submit . \
-	--tag=${TRAINING_CONTAINER_IMAGE} \
 	--region=${VERTEX_LOCATION} \
 	--project=${VERTEX_PROJECT_ID} \
-	--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source
-
-build-serving-container: ## Build and push serving container image using Docker
-	@ cd model && \
-	poetry export --with serving -f requirements.txt -o serving/requirements.txt && \
-	cd serving && \
-	gcloud builds submit . \
-	--tag=${SERVING_CONTAINER_IMAGE} \
-	--region=${VERTEX_LOCATION} \
-	--project=${VERTEX_PROJECT_ID} \
-	--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source
+	--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source \
+	--substitutions=_DOCKER_TARGET=${target},_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/${target}:${RESOURCE_SUFFIX}
diff --git a/env.sh.example b/env.sh.example
index eedd1308..63152c5c 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -24,5 +24,4 @@ export RESOURCE_SUFFIX=default
 # Leave as-is
 export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
 export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
-export TRAINING_CONTAINER_IMAGE=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images/training:${RESOURCE_SUFFIX}
-export SERVING_CONTAINER_IMAGE=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images/serving:${RESOURCE_SUFFIX}
+export CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images
diff --git a/model/serving/.gcloudignore b/model/.gcloudignore
similarity index 100%
rename from model/serving/.gcloudignore
rename to model/.gcloudignore
diff --git a/model/.gitignore b/model/.gitignore
deleted file mode 100644
index 4414fc1e..00000000
--- a/model/.gitignore
+++ /dev/null
@@ -1 +0,0 @@
-requirements.txt
diff --git a/model/Dockerfile b/model/Dockerfile
new file mode 100644
index 00000000..24e387bd
--- /dev/null
+++ b/model/Dockerfile
@@ -0,0 +1,24 @@
+FROM python:3.9.16-slim AS builder
+
+ENV PIP_NO_CACHE_DIR=off \
+    PIP_DISABLE_PIP_VERSION_CHECK=on \
+    PIP_DEFAULT_TIMEOUT=100
+
+ARG POETRY_VERSION=1.5.1
+
+COPY pyproject.toml pyproject.toml
+COPY poetry.lock poetry.lock
+
+RUN pip install poetry==${POETRY_VERSION}
+RUN poetry config virtualenvs.create false && poetry install
+
+FROM builder AS training
+
+COPY training/train.py training/train.py
+
+FROM builder AS serving
+
+RUN poetry install --with serving
+COPY serving/main.py serving/main.py
+
+CMD exec uvicorn serving.main:app --host "0.0.0.0" --port "$AIP_HTTP_PORT"
diff --git a/model/cloudbuild.yaml b/model/cloudbuild.yaml
new file mode 100644
index 00000000..167ceb0f
--- /dev/null
+++ b/model/cloudbuild.yaml
@@ -0,0 +1,7 @@
+---
+steps:
+  - name: 'gcr.io/kaniko-project/executor:latest'
+    args:
+      - --destination=${_DESTINATION_IMAGE_URI}
+      - --target=${_DOCKER_TARGET}
+      - --cache=true
diff --git a/model/serving/Dockerfile b/model/serving/Dockerfile
deleted file mode 100644
index 71207403..00000000
--- a/model/serving/Dockerfile
+++ /dev/null
@@ -1,10 +0,0 @@
-FROM python:3.9.16-slim
-ENV PIP_NO_CACHE_DIR=off \
-    PIP_DISABLE_PIP_VERSION_CHECK=on \
-    PIP_DEFAULT_TIMEOUT=100
-
-COPY requirements.txt requirements.txt
-RUN pip install -r requirements.txt
-COPY main.py main.py
-
-CMD exec uvicorn main:app --host "0.0.0.0" --port "$AIP_HTTP_PORT"
diff --git a/model/training/.gcloudignore b/model/training/.gcloudignore
deleted file mode 100644
index 510bf9ce..00000000
--- a/model/training/.gcloudignore
+++ /dev/null
@@ -1,2 +0,0 @@
-.venv
-.DS_Store
diff --git a/model/training/Dockerfile b/model/training/Dockerfile
deleted file mode 100644
index 4b4effce..00000000
--- a/model/training/Dockerfile
+++ /dev/null
@@ -1,8 +0,0 @@
-FROM python:3.9.16-slim
-ENV PIP_NO_CACHE_DIR=off \
-    PIP_DISABLE_PIP_VERSION_CHECK=on \
-    PIP_DEFAULT_TIMEOUT=100
-
-COPY requirements.txt requirements.txt
-RUN pip install -r requirements.txt
-COPY train.py train.py
diff --git a/pipelines/src/pipelines/training/pipeline.py b/pipelines/src/pipelines/training/pipeline.py
index 3e2c3ed4..a2906e44 100644
--- a/pipelines/src/pipelines/training/pipeline.py
+++ b/pipelines/src/pipelines/training/pipeline.py
@@ -22,8 +22,10 @@
 from bigquery_components import extract_bq_to_dataset
 from vertex_components import upload_model
 
-TRAINING_IMAGE = os.environ["TRAINING_CONTAINER_IMAGE"]
-SERVING_IMAGE = os.environ["SERVING_CONTAINER_IMAGE"]
+CONTAINER_IMAGE_REGISTRY = os.environ["CONTAINER_IMAGE_REGISTRY"]
+RESOURCE_SUFFIX = os.environ.get("RESOURCE_SUFFIX", "default")
+TRAINING_IMAGE = f"{CONTAINER_IMAGE_REGISTRY}/training:{RESOURCE_SUFFIX}"
+SERVING_IMAGE = f"{CONTAINER_IMAGE_REGISTRY}/serving:{RESOURCE_SUFFIX}"
 
 
 @dsl.container_component
@@ -40,7 +42,7 @@ def train(
         image=TRAINING_IMAGE,
         command=["python"],
         args=[
-            "train.py",
+            "training/train.py",
             "--train-data",
             train_data.path,
             "--valid-data",

From c7449564cf0b95263d71fe2a1d01dc9c17565a73 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Thu, 27 Jul 2023 19:02:10 +0100
Subject: [PATCH 132/238] add container builds to ci/cd

---
 cloudbuild/e2e-test.yaml  | 27 ++++++++++++++++++++++++++-
 cloudbuild/pr-checks.yaml |  2 ++
 cloudbuild/release.yaml   | 30 ++++++++++++++++++++++++++++++
 3 files changed, 58 insertions(+), 1 deletion(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 7c6494ee..150a4c57 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -14,9 +14,30 @@
 ---
 steps:
 
+  - id: build-training-image
+    name: gcr.io/kaniko-project/executor:latest
+    args:
+      - --context=dir:///workspace/model
+      - --destination=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images/training:${COMMIT_SHA}
+      - --target=training
+      - --cache=true
+      - --compressed-caching=false
+    waitFor: ['-']
+
+  - id: build-serving-image
+    name: gcr.io/kaniko-project/executor:latest
+    args:
+      - --context=dir:///workspace/model
+      - --destination=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images/serving:${COMMIT_SHA}
+      - --target=serving
+      - --cache=true
+      - --compressed-caching=false
+    waitFor: ['-']
+
   # Install Python deps
   # Run end-to-end (E2E) pipeline tests on both pipelines
-  - name: python:3.9
+  - id: e2e-tests
+    name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
@@ -32,6 +53,10 @@ steps:
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
       - VERTEX_PIPELINE_ROOT=${_TEST_VERTEX_PIPELINE_ROOT}
       - RESOURCE_SUFFIX=${COMMIT_SHA}
+      - CONTAINER_IMAGE_REGISTRY=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images
+    waitFor:
+      - build-training-image
+      - build-serving-image
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 93934970..61e1c923 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -32,6 +32,8 @@ steps:
         make test-all-components
     env:
       - SKIP=terraform-fmt,git-dirty
+      - CONTAINER_IMAGE_REGISTRY=dummy_value
+      - RESOURCE_SUFFIX=default
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 5852e0bd..ea6d44d8 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -14,6 +14,30 @@
 ---
 steps:
 
+  - id: build-training-image
+    name: gcr.io/kaniko-project/executor:latest
+    args:
+      - --context=dir:///workspace/model
+      - --destination=${_DEV_VERTEX_LOCATION}-docker.pkg.dev/${_DEV_VERTEX_PROJECT_ID}/vertex-images/training:${TAG_NAME}
+      - --destination=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images/training:${TAG_NAME}
+      - --destination=${_PROD_VERTEX_LOCATION}-docker.pkg.dev/${_PROD_VERTEX_PROJECT_ID}/vertex-images/training:${TAG_NAME}
+      - --target=training
+      - --cache=true
+      - --compressed-caching=false
+    waitFor: ['-']
+
+  - id: build-serving-image
+    name: gcr.io/kaniko-project/executor:latest
+    args:
+      - --context=dir:///workspace/model
+      - --destination=${_DEV_VERTEX_LOCATION}-docker.pkg.dev/${_DEV_VERTEX_PROJECT_ID}/vertex-images/serving:${TAG_NAME}
+      - --destination=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images/serving:${TAG_NAME}
+      - --destination=${_PROD_VERTEX_LOCATION}-docker.pkg.dev/${_PROD_VERTEX_PROJECT_ID}/vertex-images/serving:${TAG_NAME}
+      - --target=serving
+      - --cache=true
+      - --compressed-caching=false
+    waitFor: ['-']
+
   # Install poetry, install deps, compile pipelines
   - name: python:3.9
     entrypoint: /bin/sh
@@ -36,6 +60,12 @@ steps:
           --tag=latest \
           --tag=${TAG_NAME}; \
         done
+    env:
+      - RESOURCE_SUFFIX=default
+      - CONTAINER_IMAGE_REGISTRY=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images
+    waitFor:
+      - build-training-image
+      - build-serving-image
 
 options:
   logging: CLOUD_LOGGING_ONLY

From 6ba229896ff633e4744fb963ce10e1d518d64091 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Fri, 28 Jul 2023 11:26:23 +0100
Subject: [PATCH 133/238] fix: update E2E tests for kfp v2

---
 pipelines/tests/e2e/test_e2e.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/pipelines/tests/e2e/test_e2e.py b/pipelines/tests/e2e/test_e2e.py
index c7b8081c..0ff9a25b 100644
--- a/pipelines/tests/e2e/test_e2e.py
+++ b/pipelines/tests/e2e/test_e2e.py
@@ -13,12 +13,12 @@
 # limitations under the License.
 
 import logging
-from typing import Callable
 
 import pytest
 import os
 from google.cloud import storage
 from kfp import compiler
+from kfp.components import BaseComponent
 
 from pipelines.trigger.main import trigger_pipeline_from_payload
 
@@ -151,7 +151,7 @@ def test_batch_prediction_job_uri(
 
 
 def pipeline_e2e_test(
-    pipeline_func: Callable,
+    pipeline_func: BaseComponent,
     common_tasks: dict,
     enable_caching: bool = None,
     **kwargs: dict,
@@ -168,11 +168,11 @@ def pipeline_e2e_test(
         **kwargs (dict): conditional tasks groups in dictionary
     """
 
-    pipeline_json = f"{pipeline_func.__name__}.json"
+    pipeline_yaml = f"{pipeline_func.name}.yaml"
 
     compiler.Compiler().compile(
         pipeline_func=pipeline_func,
-        package_path=pipeline_json,
+        package_path=pipeline_yaml,
         type_check=False,
     )
 
@@ -181,7 +181,7 @@ def pipeline_e2e_test(
         enable_caching = None
 
     payload = {
-        "attributes": {"template_path": pipeline_json, "enable_caching": enable_caching}
+        "attributes": {"template_path": pipeline_yaml, "enable_caching": enable_caching}
     }
 
     try:

From 12c5dc2d7fd9d11ddf00fa5f22b5433a885809a1 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Fri, 28 Jul 2023 15:07:03 +0100
Subject: [PATCH 134/238] ci: fix release.yaml pipeline

---
 cloudbuild/release.yaml | 56 +++++++++++++++++------------------------
 1 file changed, 23 insertions(+), 33 deletions(-)

diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index ea6d44d8..d9c93ce7 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -14,58 +14,48 @@
 ---
 steps:
 
-  - id: build-training-image
-    name: gcr.io/kaniko-project/executor:latest
+  - id: build-container-images
+    name: gcr.io/cloud-builders/docker
+    dir: /workspace/model
+    entrypoint: sh
     args:
-      - --context=dir:///workspace/model
-      - --destination=${_DEV_VERTEX_LOCATION}-docker.pkg.dev/${_DEV_VERTEX_PROJECT_ID}/vertex-images/training:${TAG_NAME}
-      - --destination=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images/training:${TAG_NAME}
-      - --destination=${_PROD_VERTEX_LOCATION}-docker.pkg.dev/${_PROD_VERTEX_PROJECT_ID}/vertex-images/training:${TAG_NAME}
-      - --target=training
-      - --cache=true
-      - --compressed-caching=false
-    waitFor: ['-']
-
-  - id: build-serving-image
-    name: gcr.io/kaniko-project/executor:latest
-    args:
-      - --context=dir:///workspace/model
-      - --destination=${_DEV_VERTEX_LOCATION}-docker.pkg.dev/${_DEV_VERTEX_PROJECT_ID}/vertex-images/serving:${TAG_NAME}
-      - --destination=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images/serving:${TAG_NAME}
-      - --destination=${_PROD_VERTEX_LOCATION}-docker.pkg.dev/${_PROD_VERTEX_PROJECT_ID}/vertex-images/serving:${TAG_NAME}
-      - --target=serving
-      - --cache=true
-      - --compressed-caching=false
-    waitFor: ['-']
+      - -c
+      - |
+        docker build --target=training -t training:latest . && \
+        docker build --target=serving -t serving:latest . && \
+        for proj in ${_DESTINATION_PROJECTS} ; do \
+          docker tag training:latest ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/training:${TAG_NAME} && \
+          docker tag serving:latest ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/serving:${TAG_NAME} && \
+          docker push ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/training:${TAG_NAME} && \
+          docker push ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/serving:${TAG_NAME}; \
+        done
 
   # Install poetry, install deps, compile pipelines
-  - name: python:3.9
+  - id: compile-and-publish-pipelines
+    name: python:3.9
     entrypoint: /bin/sh
     args:
       - -c
       - |
         make setup && \
-        make compile-pipeline pipeline=training && \
-        make compile-pipeline pipeline=prediction && \
-        cd pipelines && \
-        for dest in ${_PIPELINE_PUBLISH_AR_PATHS} ; do \
+        for proj in ${_DESTINATION_PROJECTS} ; do \
+          CONTAINER_IMAGE_REGISTRY=${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images \
+          make compile-pipeline pipeline=training && \
+          make compile-pipeline pipeline=prediction && \
+          cd pipelines && \
           poetry run python -m pipelines.utils.upload_pipeline \
-          --dest=$$dest \
+          --dest=https://${_VERTEX_LOCATION}-kfp.pkg.dev/$$proj/vertex-pipelines \
           --yaml=src/pipelines/training/pipeline.yaml \
           --tag=latest \
           --tag=${TAG_NAME} && \
           poetry run python -m pipelines.utils.upload_pipeline \
-          --dest=$$dest \
+          --dest=https://${_VERTEX_LOCATION}-kfp.pkg.dev/$$proj/vertex-pipelines \
           --yaml=src/pipelines/prediction/pipeline.yaml \
           --tag=latest \
           --tag=${TAG_NAME}; \
         done
     env:
       - RESOURCE_SUFFIX=default
-      - CONTAINER_IMAGE_REGISTRY=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images
-    waitFor:
-      - build-training-image
-      - build-serving-image
 
 options:
   logging: CLOUD_LOGGING_ONLY

From 130addc7786324c25ff221f1f465b97d60a66932 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Sat, 29 Jul 2023 10:24:35 +0100
Subject: [PATCH 135/238] test: add unit tests for new component

---
 .../src/vertex_components/lookup_model.py     |   2 +-
 .../vertex-components/tests/conftest.py       |   4 +-
 .../tests/test_upload_model.py                | 340 ++++++++++++++++++
 3 files changed, 343 insertions(+), 3 deletions(-)
 create mode 100644 components/vertex-components/tests/test_upload_model.py

diff --git a/components/vertex-components/src/vertex_components/lookup_model.py b/components/vertex-components/src/vertex_components/lookup_model.py
index 76b24ac1..ac73eeef 100644
--- a/components/vertex-components/src/vertex_components/lookup_model.py
+++ b/components/vertex-components/src/vertex_components/lookup_model.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from kfp.v2.dsl import component, Output, Model
+from kfp.dsl import component, Output, Model
 from typing import NamedTuple
 
 
diff --git a/components/vertex-components/tests/conftest.py b/components/vertex-components/tests/conftest.py
index 898c2590..f689a9b9 100644
--- a/components/vertex-components/tests/conftest.py
+++ b/components/vertex-components/tests/conftest.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import pytest
-import kfp.v2.dsl
+import kfp.dsl
 
 
 @pytest.fixture(autouse=True)
@@ -47,4 +47,4 @@ def _get_path(self):
         return self.uri
 
     # mock the _get_path method of Artifact which is used by the property path
-    monkeypatch.setattr(kfp.v2.dsl.Artifact, "_get_path", _get_path)
+    monkeypatch.setattr(kfp.dsl.Artifact, "_get_path", _get_path)
diff --git a/components/vertex-components/tests/test_upload_model.py b/components/vertex-components/tests/test_upload_model.py
new file mode 100644
index 00000000..42fba113
--- /dev/null
+++ b/components/vertex-components/tests/test_upload_model.py
@@ -0,0 +1,340 @@
+# Copyright 2022 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import json
+import logging
+from unittest import mock
+from kfp.dsl import Dataset, Metrics, Model
+from google.protobuf.json_format import ParseDict
+from google.cloud.aiplatform_v1 import ModelEvaluation
+from google_cloud_pipeline_components.types.artifact_types import VertexModel
+
+
+import vertex_components
+
+upload_model = vertex_components.upload_model.python_func
+
+
+@mock.patch("google.cloud.aiplatform_v1.ModelServiceClient")
+@mock.patch("google.cloud.aiplatform.Model")
+def test_model_upload_no_champion(
+    mock_model_class, mock_model_service_client, caplog, tmp_path
+):
+
+    caplog.set_level(logging.INFO)
+
+    metrics_json = json.dumps(
+        {
+            "problemType": "regression",
+            "auc": 0.4,
+            "accuracy": 0.80,
+        }
+    )
+    metrics_file_path = tmp_path / "metrics.json"
+    metrics_file_path.write_text(metrics_json)
+
+    mock_model_class.list.return_value = []
+
+    model = Model(uri="dummy-model-uri")
+    serving_container_image = "dummy_image:latest"
+    model_name = "dummy-model-name"
+    vertex_model = VertexModel.create(
+        name=model_name, uri="chall_uri", model_resource_name="chall_resource_name"
+    )
+    project = "dummy-project"
+    location = "dummy-location"
+    model_evaluation = Metrics(uri="")
+    model_evaluation.path = str(metrics_file_path)
+    eval_metric = "auc"
+    eval_lower_is_better = False
+
+    pipeline_job_id = "dummy-pipeline-job-id"
+    test_dataset = Dataset(uri="test-dataset-uri")
+    evaluation_name = "dummy evaluation name"
+    order_models_by = "dummy_order_models_by"
+
+    upload_model(
+        model=model,
+        serving_container_image=serving_container_image,
+        vertex_model=vertex_model,
+        project=project,
+        location=location,
+        model_evaluation=model_evaluation,
+        eval_metric=eval_metric,
+        eval_lower_is_better=eval_lower_is_better,
+        model_name=model_name,
+        pipeline_job_id=pipeline_job_id,
+        test_dataset=test_dataset,
+        evaluation_name=evaluation_name,
+        order_models_by=order_models_by,
+    )
+
+    # Check that model lookup is performed, and no existing model is found
+    mock_model_class.list.assert_called_once_with(
+        filter=f'display_name="{model_name}"',
+        order_by=order_models_by,
+        location=location,
+        project=project,
+    )
+    assert "found 0 models" in caplog.text
+
+    # Check no model comparison occurs
+    assert "wins" not in caplog.text
+
+    # Check model upload call
+    mock_model_class.upload.assert_called_once_with(
+        display_name=model_name,
+        artifact_uri="dummy-model-uri",
+        serving_container_image_uri=serving_container_image,
+        serving_container_predict_route="/predict",
+        serving_container_health_route="/healthz",
+        parent_model=None,
+        is_default_version=True,
+    )
+
+    # check model output URI
+    assert vertex_model.uri == f"https://{location}-aiplatform.googleapis.com/v1/" + (
+        str(mock_model_class.upload.return_value.versioned_resource_name)
+    )
+
+    # check evaluation import
+    mock_model_service_client.return_value.import_model_evaluation.assert_called_once_with(  # noqa
+        parent=mock_model_class.upload.return_value.versioned_resource_name,
+        model_evaluation=mock.ANY,
+    )
+
+
+@mock.patch("google.cloud.aiplatform_v1.ModelServiceClient")
+@mock.patch("google.cloud.aiplatform.Model")
+def test_model_upload_challenger_wins(
+    mock_model_class, mock_model_service_client, caplog, tmp_path
+):
+
+    caplog.set_level(logging.INFO)
+
+    metrics_json = json.dumps(
+        {
+            "problemType": "regression",
+            "auc": 0.4,
+            "accuracy": 0.80,
+        }
+    )
+    metrics_file_path = tmp_path / "metrics.json"
+    metrics_file_path.write_text(metrics_json)
+
+    # create mock champion model
+    mock_champion_model = mock.Mock()
+    mock_champion_model.version_id = "123"
+    dummy_champion_eval = ModelEvaluation()
+    dummy_champion_metrics = {
+        "auc": 0.2,
+        "f1": 0.7,
+    }
+    message_dict = {
+        "displayName": "Previously imported evaluation",
+        "metricsSchemaUri": "gs://google-cloud-aiplatform/schema/modelevaluation/regression_metrics_1.0.0.yaml",  # noqa
+        "metrics": dummy_champion_metrics,
+        "metadata": {
+            "pipeline_job_id": "dummy-pipeline-id",
+            "evaluation_dataset_type": "gcs",
+            "evaluation_dataset_path": ["dummy-gcs-uri"],
+        },
+    }
+    ParseDict(message_dict, dummy_champion_eval._pb)
+    mock_champion_model.get_model_evaluation.return_value._gca_resource = (
+        dummy_champion_eval
+    )
+    mock_champion_model.resource_name = "dummy-champion-resource-name"
+    mock_model_class.list.return_value = [mock_champion_model]
+
+    # create mock challenger model
+    model = Model(uri="dummy-model-uri")
+    serving_container_image = "dummy_image:latest"
+    model_name = "dummy-model-name"
+    vertex_model = VertexModel.create(
+        name=model_name, uri="chall_uri", model_resource_name="chall_resource_name"
+    )
+    project = "dummy-project"
+    location = "dummy-location"
+    model_evaluation = Metrics(uri="")
+    model_evaluation.path = str(metrics_file_path)
+    eval_metric = "auc"
+    eval_lower_is_better = False
+
+    pipeline_job_id = "dummy-pipeline-job-id"
+    test_dataset = Dataset(uri="test-dataset-uri")
+    evaluation_name = "dummy evaluation name"
+    order_models_by = "dummy_order_models_by"
+
+    upload_model(
+        model=model,
+        serving_container_image=serving_container_image,
+        vertex_model=vertex_model,
+        project=project,
+        location=location,
+        model_evaluation=model_evaluation,
+        eval_metric=eval_metric,
+        eval_lower_is_better=eval_lower_is_better,
+        model_name=model_name,
+        pipeline_job_id=pipeline_job_id,
+        test_dataset=test_dataset,
+        evaluation_name=evaluation_name,
+        order_models_by=order_models_by,
+    )
+
+    # Check that model lookup is performed, and no existing model is found
+    mock_model_class.list.assert_called_once_with(
+        filter=f'display_name="{model_name}"',
+        order_by=order_models_by,
+        location=location,
+        project=project,
+    )
+    assert "is being challenged by new model" in caplog.text
+
+    # Check challenger wins in model comparison
+    assert "Challenger wins!" in caplog.text
+
+    # Check model upload call
+    mock_model_class.upload.assert_called_once_with(
+        display_name=model_name,
+        artifact_uri="dummy-model-uri",
+        serving_container_image_uri=serving_container_image,
+        serving_container_predict_route="/predict",
+        serving_container_health_route="/healthz",
+        parent_model=mock_champion_model.resource_name,
+        is_default_version=True,
+    )
+
+    # check model output URI
+    assert vertex_model.uri == f"https://{location}-aiplatform.googleapis.com/v1/" + (
+        str(mock_model_class.upload.return_value.versioned_resource_name)
+    )
+
+    # check evaluation import
+    mock_model_service_client.return_value.import_model_evaluation.assert_called_once_with(  # noqa
+        parent=mock_model_class.upload.return_value.versioned_resource_name,
+        model_evaluation=mock.ANY,
+    )
+
+
+@mock.patch("google.cloud.aiplatform_v1.ModelServiceClient")
+@mock.patch("google.cloud.aiplatform.Model")
+def test_model_upload_champion_wins(
+    mock_model_class, mock_model_service_client, caplog, tmp_path
+):
+
+    caplog.set_level(logging.INFO)
+
+    metrics_json = json.dumps(
+        {
+            "problemType": "regression",
+            "auc": 0.4,
+            "accuracy": 0.80,
+        }
+    )
+    metrics_file_path = tmp_path / "metrics.json"
+    metrics_file_path.write_text(metrics_json)
+
+    # Create mock champion model
+    mock_champion_model = mock.Mock()
+    mock_champion_model.version_id = "123"
+    dummy_champion_eval = ModelEvaluation()
+    dummy_champion_metrics = {
+        "auc": 0.8,
+        "f1": 0.7,
+    }
+    message_dict = {
+        "displayName": "Previously imported evaluation",
+        "metricsSchemaUri": "gs://google-cloud-aiplatform/schema/modelevaluation/regression_metrics_1.0.0.yaml",  # noqa
+        "metrics": dummy_champion_metrics,
+        "metadata": {
+            "pipeline_job_id": "dummy-pipeline-id",
+            "evaluation_dataset_type": "gcs",
+            "evaluation_dataset_path": ["dummy-gcs-uri"],
+        },
+    }
+    ParseDict(message_dict, dummy_champion_eval._pb)
+    mock_champion_model.get_model_evaluation.return_value._gca_resource = (
+        dummy_champion_eval
+    )
+    mock_champion_model.resource_name = "dummy-champion-resource-name"
+    mock_model_class.list.return_value = [mock_champion_model]
+
+    # create mock challenger model
+    model = Model(uri="dummy-model-uri")
+    serving_container_image = "dummy_image:latest"
+    model_name = "dummy-model-name"
+    vertex_model = VertexModel.create(
+        name=model_name, uri="chall_uri", model_resource_name="chall_resource_name"
+    )
+    project = "dummy-project"
+    location = "dummy-location"
+    model_evaluation = Metrics(uri="")
+    model_evaluation.path = str(metrics_file_path)
+    eval_metric = "auc"
+    eval_lower_is_better = False
+
+    pipeline_job_id = "dummy-pipeline-job-id"
+    test_dataset = Dataset(uri="test-dataset-uri")
+    evaluation_name = "dummy evaluation name"
+    order_models_by = "dummy_order_models_by"
+
+    upload_model(
+        model=model,
+        serving_container_image=serving_container_image,
+        vertex_model=vertex_model,
+        project=project,
+        location=location,
+        model_evaluation=model_evaluation,
+        eval_metric=eval_metric,
+        eval_lower_is_better=eval_lower_is_better,
+        model_name=model_name,
+        pipeline_job_id=pipeline_job_id,
+        test_dataset=test_dataset,
+        evaluation_name=evaluation_name,
+        order_models_by=order_models_by,
+    )
+
+    # Check that model lookup is performed, and no existing model is found
+    mock_model_class.list.assert_called_once_with(
+        filter=f'display_name="{model_name}"',
+        order_by=order_models_by,
+        location=location,
+        project=project,
+    )
+    assert "is being challenged by new model" in caplog.text
+
+    # Check champion wins in model comparison
+    assert "Champion wins!" in caplog.text
+
+    # Check model upload call
+    mock_model_class.upload.assert_called_once_with(
+        display_name=model_name,
+        artifact_uri="dummy-model-uri",
+        serving_container_image_uri=serving_container_image,
+        serving_container_predict_route="/predict",
+        serving_container_health_route="/healthz",
+        parent_model=mock_champion_model.resource_name,
+        is_default_version=False,
+    )
+
+    # check model output URI
+    assert vertex_model.uri == f"https://{location}-aiplatform.googleapis.com/v1/" + (
+        str(mock_model_class.upload.return_value.versioned_resource_name)
+    )
+
+    # check evaluation import
+    mock_model_service_client.return_value.import_model_evaluation.assert_called_once_with(  # noqa
+        parent=mock_model_class.upload.return_value.versioned_resource_name,
+        model_evaluation=mock.ANY,
+    )

From d28e2b2de15a6ef03d121990732f89e6b14d6bc9 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Sat, 29 Jul 2023 10:38:13 +0100
Subject: [PATCH 136/238] docs: update copyright headers

---
 .../src/vertex_components/upload_model.py           | 10 +++++-----
 .../vertex-components/tests/test_upload_model.py    |  2 +-
 model/Dockerfile                                    | 13 +++++++++++++
 model/cloudbuild.yaml                               | 13 +++++++++++++
 model/serving/main.py                               | 13 +++++++++++++
 model/training/train.py                             | 13 +++++++++++++
 pipelines/src/pipelines/utils/upload_pipeline.py    | 13 +++++++++++++
 7 files changed, 71 insertions(+), 6 deletions(-)

diff --git a/components/vertex-components/src/vertex_components/upload_model.py b/components/vertex-components/src/vertex_components/upload_model.py
index 4f3b5729..fad15e3e 100644
--- a/components/vertex-components/src/vertex_components/upload_model.py
+++ b/components/vertex-components/src/vertex_components/upload_model.py
@@ -1,11 +1,11 @@
-# Copyright 2022 Google LLC
-
+# Copyright 2023 Google LLC
+#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
 # Unless required by applicable law or agreed to in writing, software
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
diff --git a/components/vertex-components/tests/test_upload_model.py b/components/vertex-components/tests/test_upload_model.py
index 42fba113..d62e0bc9 100644
--- a/components/vertex-components/tests/test_upload_model.py
+++ b/components/vertex-components/tests/test_upload_model.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/model/Dockerfile b/model/Dockerfile
index 24e387bd..db0b33cd 100644
--- a/model/Dockerfile
+++ b/model/Dockerfile
@@ -1,3 +1,16 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 FROM python:3.9.16-slim AS builder
 
 ENV PIP_NO_CACHE_DIR=off \
diff --git a/model/cloudbuild.yaml b/model/cloudbuild.yaml
index 167ceb0f..43998648 100644
--- a/model/cloudbuild.yaml
+++ b/model/cloudbuild.yaml
@@ -1,3 +1,16 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 ---
 steps:
   - name: 'gcr.io/kaniko-project/executor:latest'
diff --git a/model/serving/main.py b/model/serving/main.py
index 3b264b02..32f76450 100644
--- a/model/serving/main.py
+++ b/model/serving/main.py
@@ -1,3 +1,16 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 import joblib
 import os
 
diff --git a/model/training/train.py b/model/training/train.py
index 18486e2d..a5cf8544 100644
--- a/model/training/train.py
+++ b/model/training/train.py
@@ -1,3 +1,16 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 import argparse
 from pathlib import Path
 
diff --git a/pipelines/src/pipelines/utils/upload_pipeline.py b/pipelines/src/pipelines/utils/upload_pipeline.py
index d5137f41..b9524c51 100644
--- a/pipelines/src/pipelines/utils/upload_pipeline.py
+++ b/pipelines/src/pipelines/utils/upload_pipeline.py
@@ -1,3 +1,16 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 import argparse
 from kfp.registry import RegistryClient
 

From 0d778b4ca5a57b822b57f8b6b8d97a3a0949755a Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Sat, 29 Jul 2023 10:41:47 +0100
Subject: [PATCH 137/238] test: revert accidental changes to test_lookup_model

---
 .../tests/test_lookup_model.py                | 129 ++++++++----------
 1 file changed, 55 insertions(+), 74 deletions(-)

diff --git a/components/vertex-components/tests/test_lookup_model.py b/components/vertex-components/tests/test_lookup_model.py
index 1ba31f81..5e0b2e4c 100644
--- a/components/vertex-components/tests/test_lookup_model.py
+++ b/components/vertex-components/tests/test_lookup_model.py
@@ -12,8 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import google.cloud.aiplatform  # noqa
-from kfp.v2.dsl import Model
+from kfp.dsl import Model
 from unittest import mock
 import pytest
 
@@ -22,93 +21,75 @@
 lookup_model = vertex_components.lookup_model.python_func
 
 
-def test_lookup_model(tmpdir):
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model(mock_model, tmpdir):
     """
     Assert lookup_model produces expected resource name, and that list method is
     called with the correct arguemnts
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-
-        # Mock attribute and method
-
-        mock_path = tmpdir
-        mock_model.resource_name = "my-model-resource-name"
-        mock_model.uri = mock_path
-        mock_model.list.return_value = [mock_model]
-
-        # Invoke the model look up
-        found_model_resource_name, _ = lookup_model(
-            model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
-            fail_on_model_not_found=False,
-            model=Model(uri=mock_path),
-        )
-
-        assert found_model_resource_name == "my-model-resource-name"
-
-        # Check the list method was called once with the correct arguments
-        mock_model.list.assert_called_once_with(
-            filter='display_name="my-model"',
-            order_by="create_time desc",
-            location="europe-west4",
-            project="my-project-id",
-        )
-
 
-def test_lookup_model_when_no_models(tmpdir):
+    # Mock attribute and method
+    mock_path = tmpdir
+    mock_model.resource_name = "my-model-resource-name"
+    mock_model.uri = mock_path
+    mock_model.list.return_value = [mock_model]
+
+    # Invoke the model look up
+    found_model_resource_name, _ = lookup_model(
+        model_name="my-model",
+        project_location="europe-west4",
+        project_id="my-project-id",
+        order_models_by="create_time desc",
+        fail_on_model_not_found=False,
+        model=Model(uri=mock_path),
+    )
+
+    assert found_model_resource_name == "my-model-resource-name"
+
+    # Check the list method was called once with the correct arguments
+    mock_model.list.assert_called_once_with(
+        filter='display_name="my-model"',
+        order_by="create_time desc",
+        location="europe-west4",
+        project="my-project-id",
+    )
+
+
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model_when_no_models(mock_model, tmpdir):
     """
     Checks that when there are no models and fail_on_model_found = False,
     lookup_model returns an empty string.
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-        mock_model.list.return_value = []
-        exported_model_resource_name, _ = lookup_model(
-            model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
-            fail_on_model_not_found=False,
-            model=Model(uri=str(tmpdir)),
-        )
+    mock_model.list.return_value = []
+    exported_model_resource_name, _ = lookup_model(
+        model_name="my-model",
+        project_location="europe-west4",
+        project_id="my-project-id",
+        order_models_by="create_time desc",
+        fail_on_model_not_found=False,
+        model=Model(uri=str(tmpdir)),
+    )
+
     print(exported_model_resource_name)
     assert exported_model_resource_name == ""
 
 
-def test_lookup_model_when_no_models_fail(tmpdir):
+@mock.patch("google.cloud.aiplatform.Model")
+def test_lookup_model_when_no_models_fail(mock_model, tmpdir):
     """
     Checks that when there are no models and fail_on_model_found = True,
     lookup_model raises a RuntimeError.
-
-    Args:
-        tmpdir: built-in pytest tmpdir fixture
-
-    Returns:
-        None
     """
-    with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-        mock_model.list.return_value = []
+    mock_model.list.return_value = []
 
-        # Verify that a ValueError is raised
-        with pytest.raises(RuntimeError):
-            lookup_model(
-                model_name="my-model",
-                project_location="europe-west4",
-                project_id="my-project-id",
-                order_models_by="create_time desc",
-                fail_on_model_not_found=True,
-                model=Model(uri=str(tmpdir)),
-            )
+    # Verify that a ValueError is raised
+    with pytest.raises(RuntimeError):
+        lookup_model(
+            model_name="my-model",
+            project_location="europe-west4",
+            project_id="my-project-id",
+            order_models_by="create_time desc",
+            fail_on_model_not_found=True,
+            model=Model(uri=str(tmpdir)),
+        )

From 8e138cddd070eecb60a812b8a8837968450bb310 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 1 Aug 2023 14:00:30 +0100
Subject: [PATCH 138/238] docs: update documentation and Makefile

---
 CONTRIBUTING.md                       | 273 --------------------------
 Makefile                              |   4 +-
 README.md                             | 209 ++++++++++----------
 USAGE.md                              |  72 -------
 cloudbuild/README.md                  |  33 ++--
 docs/PRODUCTION.md                    |  40 ++--
 docs/TESTING_SETUP.md                 |  36 +++-
 docs/TROUBLESHOOTING.md               |  46 -----
 docs/images/architecture.png          | Bin 0 -> 247418 bytes
 docs/images/cf_view.png               | Bin 80012 -> 0 bytes
 docs/images/prediction_pipeline.png   | Bin 0 -> 96747 bytes
 docs/images/tf_model_architecture.png | Bin 248682 -> 0 bytes
 docs/images/training_pipeline.png     | Bin 0 -> 162349 bytes
 docs/images/use_template.png          | Bin 3127 -> 0 bytes
 pipelines/README.md                   | 142 ++++++--------
 15 files changed, 230 insertions(+), 625 deletions(-)
 delete mode 100644 CONTRIBUTING.md
 delete mode 100644 USAGE.md
 delete mode 100644 docs/TROUBLESHOOTING.md
 create mode 100644 docs/images/architecture.png
 delete mode 100644 docs/images/cf_view.png
 create mode 100644 docs/images/prediction_pipeline.png
 delete mode 100644 docs/images/tf_model_architecture.png
 create mode 100644 docs/images/training_pipeline.png
 delete mode 100644 docs/images/use_template.png

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
deleted file mode 100644
index 905de864..00000000
--- a/CONTRIBUTING.md
+++ /dev/null
@@ -1,273 +0,0 @@
-<!-- 
-Copyright 2022 Google LLC
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    https://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
- -->
- # Contributing
-
-Welcome to the Vertex Templates Project, and thank you for your interest in contributing! 
-
-This guide is chiefly for users wishing to contribute to the opensource version. Those who want to edit the templates to suit their own purposes should look at [USAGE](USAGE.md), but may find some sections useful.
-
-## Links to Important Resources
-- [pytest](https://docs.pytest.org)
-- [unittest.mock](https://docs.python.org/3/library/unittest.mock.html)
-- [poetry](https://python-poetry.org/docs/#installation)
-- [Kubeflow Pipelines](https://www.kubeflow.org/docs/components/pipelines/overview)
-- [Vertex AI](https://cloud.google.com/vertex-ai/docs)
-- [AI Platform SDK](https://googleapis.dev/python/aiplatform/latest/index.html)
-
-## Python code guidelines
-
-### Code linting and formatting
-We use linting to highlight problems in our Python code which could later produce errors or affect efficiency. For example, linting detects things such as uninitialised or undefined variables, unused imported modules, and missing parentheses. To detect and enact fixes to these problems, we make use of the Python linter: [Flake8](https://flake8.pycqa.org/en/latest/) and the formatter [Black](https://black.readthedocs.io/en/stable/). These are run as part of our [pre-commit checks](#Pre-commit-checks). We have some configurations for Flake8 that you can find [here](.flake8).
-### Docstring format
-Please include docstrings that are compliant with the [Google Style](https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html).
-
-In brief, the docstring is a triple quoted string placed immediately after the function definition and should contain:
-- A brief description of the function
-- A section `Args:` where you list the function arguments
-  - For each argument, include the argument type in brackets
-- A section `Returns:` where you list what the function returns
-  - For each returned item, include the type
-## Testing
-Testing is an important way for us to check that our code works as expected and forms a key part of our CI/CD strategy. For example, pull requests will not pass our checks if any unit tests fail. You should therefore ensure that your pull request passes all tests before merging.
-
-### Unit Tests
-
-We use unit tests to test small sections of logically isolated code in our pipeline components.
-
-#### Mocking & patching
-When we test a function that makes an external API call (for example to a service on GCP), we mock the associated module or class and its functions and attributes. The rationale behind this is that we want to test our own logic and not the API call(s) themselves. Indeed, API calls can be broken, computationally expensive, slow, or limited, and we do not want our unit tests to fail because of any of these. 
-
-We do mocking/patching in two different ways:
-1. [`monkeypatch`](https://docs.pytest.org/en/6.2.x/monkeypatch.html): this built-in `pytest` fixture allows you to modify an attribute (such as an instance method in a class). We use `monkeypatch` only in the relevant `conftest.py` file for the fixtures that are applied before every unit test. We have used `monkeypatch` in the following fixtures:
-    - `mock_kfp_artifact`: used to mock the `Artifact` object (and thus any derived classes such as `Dataset`, `Model`, etc.) in `kfp.v2.dsl` to return the URI as
-    the path. This lets us create mock Artifact objects locally for our unit tests.
-2. `unittest.mock.patch`: this object in the `unittest` library enables us to mock classes (and its associated attributes and methods) within a context manager. We use `mock.patch` inside the individual test scripts to mock object(s) that are used in the function being tested. This allows us to replace the target class/object with a Mock object, ultimately allowing us to make assertions on how this Mock object has been used. For example, the `assert_called_once_with` method allows us to check that a specific method of a Mock object was called once with specific arguments. Alternatively, we can set the attributes of our Mock objects to specific values, and assert that the component logic being tested handles these cases correctly (e.g. by raising a `ValueError`). An example of using the `mock.patch` context manager is in [`test_lookup_model.py`](tests/kfp_components/aiplatform/test_lookup_model.py) for [`lookup_model.py`](./pipeline_components/aiplatform/aiplatform/lookup_model/component.py), where there is an API call to list models (in Vertex AI) based on a filter, namely `google.cloud.aiplatform.Model.list`. When we test this KFP component, we are not interested in actually making this API call, so instead we mock it. We do this by mocking the `google.cloud.aiplatform.Model` class:
-```
-with mock.patch("google.cloud.aiplatform.Model") as mock_model:
-
-    # Mock attribute and method
-    mock_model.resource_name = "my-model-resource-name"
-    mock_model.list.return_value = [mock_model]
-
-    # Invoke the model look up
-    found_model_resource_name = lookup_model(
-        model_name="my-model",
-        project_location="europe-west4",
-        project_id="my-project_id",
-        order_models_by="create_time desc",
-        fail_on_model_not_found=False,
-    )
-
-    assert found_model_resource_name == "my-model-resource-name"
-```
-
-#### `pytest` fixtures & `conftest.py`
-- `tmpdir`: a built-in `pytest` fixture that we use to create temporary paths for our unit tests.
-- `monkeypatch`: see above.
-- The file `conftest.py` contains our custom `pytest` fixtures which we apply for each testing session. 
-
-#### How to write unit tests
-Some things to consider testing for in your code:
-- **Do you have any logical conditions?** Consider writing tests that assert the desired outcome occurs for each possible outcome. In particular, you can assert that a certain error is raised in your function under certain conditions. For example, in [`lookup_model.py`](./pipeline_components/aiplatform/aiplatform/lookup_model/component.py), the function `lookup_model` raises a `RuntimeError` if no models are found:
-```
-if fail_on_model_not_found:
-    raise RuntimeError(f"Failed as model not found")
-```
-Now in [`test_lookup_model.py`](./pipeline_components/aiplatform/tests/test_lookup_model.py), in the unit test `test_lookup_model_when_no_models_fail` you can use `pytest.raises` to check that `lookup_model` actually raises a `RuntimeError`:
-```
-with pytest.raises(RuntimeError):
-    lookup_model(
-        model_name="my-model",
-        project_location="europe-west4",
-        project_id="my-project-id",
-        order_models_by="create_time desc",
-        fail_on_model_not_found=True,
-    )
-```
-
-#### How to run unit tests
-Unit tests for pipeline components are run automatically on each pull request. You can also run them on your local machine:
-```
-make test-all-components
-```
-
-Or to just run the unit tests for a given component group (e.g. `aiplatform`):
-```
-make test-components GROUP=vertex-components
-```
-
-### End-to-end (E2E) pipeline tests
-We use End-to-end (E2E) pipeline tests to ensure that our pipelines are running as expected. Our E2E tests ensure:
-- That the pipeline is successfully triggered locally, and that the pipeline run is completed
-- That common tasks(components), which are stored in a dictionary object (`common_tasks`), occurred in the pipeline
-- That if any task in a conditional tasks dictionary object occurred in the pipeline, the remaining tasks based on that condition should have all occurred as well
-- That these pipeline tasks output the correct artifacts, by checking whether they have been saved to a GCS URI or have been generated successfully in Vertex AI.
-
-Note:
-These dictionary objects (`common_tasks`, `conditional_tasks`) are defined in `test_e2e.py` in each pipeline folder e.g (`./pipelines/tests/xgboost/training/test_e2e.py`). 
-The E2E test only allows one common tasks group but the number of conditional tasks group is not limited. To define the correct task group, 
-please go to pipeline job on Vertex AI for more information. 
-For example, in the XGBoost training pipeline, we have two conditional tasks groups that are bounded in the dashed frame. 
-Thus, in `./pipelines/tests/xgboost/training/test_e2e.py`, there are two dictionaries of two conditional tasks group.
-
-- Optionally check for executed tasks and created output artifacts.
-
-#### How to run end-to-end (E2E) pipeline tests
-E2E tests are run on each PR that is merged to the main branch. You can also run them on your local machine: 
-```
-make e2e-tests pipeline=<training|prediction>
-```
-
-### How to adapt the end-to-end (E2E) pipeline tests for your own pipeline
-As described above, we provide our E2E tests with a dictionary of expected outputs for the pipeline components, and confirm that these outputs are stored in a GCS uri or generated successfully in Vertex AI.
- For information on how tasks and outputs are stored in your pipeline, we recommend looking at these [AI Platform documents](https://googleapis.dev/python/aiplatform/latest/aiplatform_v1beta1/types.html#google.cloud.aiplatform_v1beta1.types.PipelineJob). The following briefly describes how we created this dictionary, and you can use this to create your own dictionary of expected tasks:
-1. Trigger a pipeline (using the default pipeline input parameters), and collect the pipeline tasks and their details. For example:
-```
-from trigger.main import trigger_pipeline_from_payload
-
-...
-
-    payload = {
-        "attributes": {
-            "template_path": template_path,
-            "enable_caching": False
-        }
-    }
-    pl = trigger_pipeline_from_payload(payload)
-    pl.wait()
-    details = pl.to_dict()
-    tasks = details["jobDetail"]["taskDetails"]
-
-```
-2. Check missing tasks by comparing the actual task produced in pipeline and the expected tasks defined in each pipeline test file ( e.g `./pipelines/tests/xgboost/training/test_e2e.py`))
-```
-    missing_tasks = [
-        task_name
-        for task_name in expected_tasks.keys()
-        if task_name not in actual_tasks.keys()
-    ]
-```
-3. Check all tasks outputs are as expected and accessible
-```
-    storage_client = storage.Client()
-    # 2. Missing outputs check
-    for task_name, expected_output in expected_tasks.items():
-        actual_outputs = actual_tasks[task_name]
-        # 2-2. if the output artifact are as expected
-        diff = set(expected_output).symmetric_difference(actual_outputs.keys())
-        assert (
-            len(diff) == 0
-        ), f"task: {task_name}, expected_output {expected_output}, actual_outputs: {actual_outputs.keys()}"
-        for output_artifact in expected_output:
-            output_uri = actual_outputs[output_artifact]
-
-            # 2-2. if output is generated successfully
-            # for all gcs uri check its file size
-            if output_uri.startswith("gs://"):
-                file_size = test_gcs_uri(output_uri, storage_client)
-                assert (
-                    file_size > 0
-                ),  f"{output_artifact} in task {task_name} is not accessible"
-            # for Vertex resource check if the resource exists
-            else: 
-                # all Vertex AI resource uri following this pattern: 
-                # ‘projects/<my-project>/locations/<location>/<resource_type>/<resource_name>’
-                artifact_type = output_uri.split('/')[-2] 
-                object_existence = test_functions[artifact_type](output_uri.split('/')[-1])
-                assert (
-                    object_existence
-                ), f"{output_artifact} in task {task_name} is not accessible"
-
-```
-Notes:
-This template only provides three Vertex AI resource check functions: `test_vertex_model_uri`,`test_vertex_endpoint_uri`,`test_batch_prediction_job_uri`. 
-For other Vertex artifacts, you can create a new one following this code:
-```
-def test_vertex_endpoint_uri(output_uri: str):
-    from google.cloud.aiplatform import Model
-    try: 
-        Model(
-            endpoint_name=output_uri,
-            project=project_id,
-            location=project_location,
-        )
-        return True
-    except:
-        return False
-
-```
-
-## Adding or changing python dependencies
-We use [poetry](https://python-poetry.org/docs/#installation) to handle our packages and their dependencies. Each group of pipeline components (e.g. [vertex](./components/vertex-components/)) includes its own poetry environment, and there is a [separate poetry environment](./pipelines/) for the ML pipelines themselves and the pipeline trigger code.
-
-### Adding python dependencies
-You may need to add new packages for your own use cases. To do this, run the following from the relevant directory ([pipelines](./pipelines) for the main ML pipeline dependencies or the directory of the relevant component group e.g. [aiplatform](./pipeline_components/aiplatform/)):
-```
-poetry install <package name>
-```
-
-## Committing Changes
-
-### Add changed files to staging area
-```
-git add <path(s) of changed file(s)>
-```
-### Commit messages
-To allow others (and yourself!) to understand your changes easily, we encourage writing detailed commit messages. We use [Commitizen](https://commitizen-tools.github.io/commitizen/) as a guide. In brief, all commit messages should start with one of the following prefixes:
-- **feat**: A new feature
-- **fix**: A bug fix
-- **docs**: Documentation only changes
-- **style**: Changes that do not affect the meaning of the code (white-space, formatting, missing semi-colons etc)
-- **refactor**: A change that neither fixes a bug or adds a feature
-- **perf**: A change that improves performance
-- **test**: Add new tests or correct existing tests
-- **build**: Changes that affect the build system or external dependencies (e.g. pip, docker, npm)
-- **ci**: Changes to CI configuration files and scripts
-
-After the prefix, you can specify the scope (e.g. the class or file name) of the change in brackets. Finally, you include the details of the change. For example
-```
-git commit -s -m"prefix(scope): message here"
-```
-
-### Things to avoid in your commit messages:
-- Too brief or non-specific messages (e.g. `bug fix`, `small changes`)
-- Commit message does not explain why changes were made
-
-
-### Pre-commit checks
-We use pre-commit hooks to automatically identify and correct issues in code. You can find the details of the hooks we use [here](.pre-commit-config.yaml). If any of these fail, the commit will be unsuccessful and you will be able to see which hook failed and some additional details in your terminal.
-
-To run the pre-commit hooks over the entire repo, run:
-```
-make pre-commit
-```
-
-#### What to do if pre-commit checks fail:
-- **Checks fail and the pre-commit hook edits a file to fix the error**. Sometimes the pre-commit hook will identify an error (e.g. the absence of a blank line at the end of a file), and will correct this automatically by changing your file. You will then need to re-add these files to the staging area before trying to commit again.
-- **Checks fail and displays an error message**. Some errors cannot be automatically fixed by pre-commit hooks, and instead they will display the error number and the file and line which failed. For more details beyond the error message, you can look up the error number online. The most common errors are caused by lines which exceed the character limit. Once you identify the cause of the error, you will need to fix this in your code, add the edited file to the staging area, and then commit again.
-
-### Commit changes to Python packages and dependencies
-If you have changes to `pyproject.toml` and `poetry.lock`, please make sure you commit these files!
-
-## Makefile
-This project contains a [Makefile](Makefile) which contains "rules" describing the commands to be executed by the system. These allow you to quickly and easily run commands for specific purposes, for example running all of the unit-tests, or compiling a pipeline. You can find the full set of available `make` rules by running:
-```
-make help
-```
-
-Some of these rules use the environment variables specified in [`env.sh`](env.sh).
-
-**It is not expected that you will need to change the Makefile or create a new one.**
diff --git a/Makefile b/Makefile
index 72adc2a1..13020ced 100644
--- a/Makefile
+++ b/Makefile
@@ -24,9 +24,7 @@ pre-commit: ## Runs the pre-commit checks over entire repo
 	poetry run pre-commit run --all-files
 
 setup: ## Set up local environment for Python development on pipelines
-	@pip install pip --upgrade && \
-	pip install poetry --upgrade && \
-	cd pipelines && \
+	@cd pipelines && \
 	poetry install --with dev
 
 test-trigger: ## Runs unit tests for the pipeline trigger code
diff --git a/README.md b/README.md
index efc9196c..09022920 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,5 @@
 <!-- 
-Copyright 2022 Google LLC
+Copyright 2023 Google LLC
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -13,62 +13,38 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
  -->
- # Vertex Pipelines End-to-end Samples
 
-## Introduction
-
-This repository provides a reference implementation of [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/) for creating a production-ready MLOps solution on Google Cloud.
-
-### Why does this matter?
-
-It is hard to productionalize data science use cases, especially because the journey from experimentation is lacking standardisation. 
-Thus, this project aims at boosting, scalability, productivity and standardisation of data science use cases amongst data science teams.
-As a result, this will free up time for data scientists so that they can focus on data science with minimal engineering overhead.
-
-This project bundles reusable code and provides the creation of a MLOps platform via an template-driven approach allowing to:
+# Vertex Pipelines End-to-end Samples
 
-- **Create a new use case from a template.** Create a new ML training pipeline and batch prediction pipeline based on a template. 
-- **Execute a one-off pipeline run in a sandbox environment.** Try out a pipeline during the development cycle in a sandbox (development) environment.
-- **Deploy a pipeline to a production environment.** Deploy a new or updated pipeline to a production environment allowing for orchestration, schedules and triggers.
-- **Publish a new template.** Customize or extend the existing templates to create a new pipeline template that can be used by the data scientists on the team to support new use cases.
+_AKA "Vertex AI Turbo Templates"_
 
-As such, this project includes the infrastructure on Google Cloud, a CI/CD integration and existing templates to support training and prediction pipelines for common ML frameworks such as TensorFlow and XGBoost.
-To showcase the pipelines in action, the [Public Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset) is used to predict the total fare of a taxi trip in Chicago.
-
-### Cloud Architecture
-
-Vertex AI Pipelines is a serverless orchestrator for running ML pipelines, using either the KFP SDK or TFX. However, unlike Kubeflow Pipelines, it does not have a built-in mechanism for saving Pipelines so that they can be run later, either on a schedule or via an external trigger. Instead, every time you want to run an ML pipeline in Vertex AI, you must make the API call to Vertex AI Pipelines, including the full pipeline definition, and Vertex Pipelines will run the pipeline there and then.
-
-In a production MLOps solution, your ML pipelines need to be repeatable. So, we have created a Cloud Function to trigger the execution of ML pipelines on Vertex AI. This can be done either using a schedule (via Cloud Scheduler), or from an external system using Pub/Sub. We use Cloud Build to compile the pipelines using the KFP SDK, and publish them to a GCS bucket. The Cloud Function retrieves the pipeline definition from the bucket, and triggers an execution of the pipeline in Vertex AI.
-
-![Using a Cloud Function to trigger Vertex Pipelines](docs/images/cf_view.png)
+## Introduction
 
-## Getting started
+This repository provides a reference implementation of [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/) for creating a production-ready MLOps solution on Google Cloud.
+You can take this repository as a starting point you own ML use cases. The implementation includes:
 
-### Prerequisites
+* Infrastructure-as-Code using Terraform for a typical dev/test/prod setup of Vertex AI and other relevant services
+* ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case (using the [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset))
+* Reusable KFP components that can be used in ML pipelines
+* CI/CD using Google Cloud Build for linting, testing, and deploying ML pipelines
+* Developer scripts (Makefile, Python scripts etc)
 
-- [pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions
-- [Cloud SDK](https://cloud.google.com/sdk/docs/quickstart)
-- Make
+## Cloud Architecture
 
-### Local setup
+The diagram below shows the cloud architecture for this repository.
 
-1. Clone the repository locally
-1. Install Python: `pyenv install`
-1. Install poetry and poetry dependencies: `make setup`
-1. Install pre-commit hooks: `cd pipelines && poetry run pre-commit install`
-1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh`
-1. Load the environment variables in `env.sh` by running `source env.sh`
+![Cloud Architecture diagram](/docs/images/architecture.png)
 
-Note: `poetry install` or `poetry add`, installs packages within the project's virtual environment. 
-If you use `pip` directly, you might accidentally install packages globally or in the wrong environment, leading to conflicts or difficulties in managing dependencies.
+There are four different Google Cloud projects in use
 
-### Configuring poetry to detect python version using pyenv
+* `dev` - a shared sandbox environment for use during development
+* `test` - environment for testing new changes before they are promoted to production. This environment should be treated as much as possible like a production environment.
+* `prod` - production environment
+* `admin` - separate Google Cloud project for setting up CI/CD in Cloud Build (since the CI/CD pipelines operate across the different environments)
 
-1. Run `poetry config virtualenvs.prefer-active-python true`
-1. Install project dependencies using `poetry install`
+Vertex Pipelines are scheduled using Google Cloud Scheduler. Cloud Scheduler emits a Pub/Sub message that triggers a Cloud Function, which in turn triggers the Vertex Pipeline to run. _In future, this will be replaced with the Vertex Pipelines Scheduler (once there is a Terraform resource for it)._
 
-### Deploying Cloud Infrastructure
+## Infrastructure
 
 The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):
 
@@ -78,22 +54,31 @@ The cloud infrastructure is managed using Terraform and is defined in the [`terr
 
 There is a Terraform configuration for each environment (dev/test/prod) under [`terraform/envs`](terraform/envs/).
 
-#### Deploying only the dev environment
+How to deploy this infrastructure is covered in a [later section](#deploying-infrastructure).
 
-We recommend that you set up CI/CD to deploy your environments. However, if you would prefer to deploy the dev environment manually (for example to try out the repo), you can do so as follows:
+## Developer setup
 
-(Assuming you have an empty Google Cloud project where you are an Owner)
+### Prerequisites
 
-1. Install Terraform on your local machine. We recommend using [`tfswitch`](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version for you (run `tfswitch` from the [`terraform/envs/dev`](terraform/envs/dev/) directory).
-2. Using the `gsutil` command line tool, create a Cloud Storage bucket for the Terraform state:
+- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions
+- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)
+- Make
 
-```
-gsutil mb -l ${VERTEX_LOCATION} -p ${VERTEX_PROJECT_ID} --pap=enforced gs://${VERTEX_PROJECT_ID}-tfstate && gsutil ubla set on gs://${VERTEX_PROJECT_ID}-tfstate
-```
+### Local setup
 
-3. Deploy the cloud infrastructure by running the `make deploy-infra` command from the root of the repository.
+1. Clone the repository locally (or create a new repo from this template)
+1. Install the correct Python version: `pyenv install`
+1. Install poetry - follow the instructions in the [poetry documentation](https://python-poetry.org/docs/#installation)
+1. Configure poetry to use the Python version from pyenv: `poetry config virtualenvs.prefer-active-python true`
+1. Install poetry dependencies for ML pipelines: `make setup`
+1. Install pre-commit hooks: `cd pipelines && poetry run pre-commit install`
+1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh` for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)
+1. (Optional) If you want to make changes to the KFP components under [/components](/components/), set up the Python virtual environments for these by running `make setup-all-components`
+1. Authenticate to Google Cloud
+    1. `gcloud auth login`
+    1. `gcloud auth application-default login`
 
-#### Full deployment of dev/test/prod using CI/CD
+### Deploying infrastructure
 
 You will need four Google Cloud projects:
 
@@ -121,19 +106,33 @@ gcloud services enable cloudresourcemanager.googleapis.com --project=<ADMIN PROJ
 gcloud services enable serviceusage.googleapis.com --project=<ADMIN PROJECT ID>
 ```
 
-Now that you have created a Terraform state bucket for each environment, you can set up the CI/CD pipelines. You can find instructions for this [here](cloudbuild/README.md).
+Install Terraform on your local machine. We recommend using [`tfswitch`](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version for you (run `tfswitch` from the [`terraform/envs/dev`](terraform/envs/dev/) directory).
+
+Now you can deploy the infrastructure using Terraform:
+
+```bash
+make deploy-infra env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
+make deploy-infra env=test VERTEX_PROJECT_ID=<TEST PROJECT ID>
+make deploy-infra env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
+```
+
+#### Optional - Tearing down infrastructure
 
-#### Tearing down infrastructure
+To tear down the infrastructure you have created with Terraform, run these commands:
 
-To tear down the infrastructure you have created with Terraform, run `make destroy-infra`.
+```bash
+make destroy-infra env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
+make destroy-infra env=test VERTEX_PROJECT_ID=<TEST PROJECT ID>
+make destroy-infra env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
+```
 
 ### Example ML pipelines
 
-This repository contains example ML training and prediction pipelines for two popular frameworks (XGBoost/sklearn and Tensorflow) using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips). The details of these can be found in the [separate README](pipelines/README.md).
+This repository contains example ML training and prediction pipelines for scikit-learn/XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips). The details of these can be found in the [separate README](pipelines/README.md).
 
 #### Pre-requisites
 
-Before you can run these example pipelines successfully there are a few additional things you will need to deploy (they have not been included in the Terraform code as they are specific to these pipelines)
+Before you can run these example pipelines successfully there are a few additional things you will need to deploy into each environment (they have not been included in the Terraform code as they are specific to these Chicago Taxi pipelines)
 
 1. Create a new BigQuery dataset for the Chicago Taxi data:
 
@@ -158,26 +157,28 @@ bq mk --transfer_config \
   --params='{"source_dataset_id":"'"chicago_taxi_trips"'","source_project_id":"'"bigquery-public-data"'"}'
 ```
 
-#### Building the training container image
+### Building the container images
+
+The [model/](/model/) directory contains the code for custom training and serving container images, including the model training script at [model/training/train.py](model/training/train.py). You can modify this to suit your own use case.
 
-Build the container image and push it to Artifact Registry with:
+Build the training container image and push it to Artifact Registry with:
 
 ```bash
-make build-training-container
+make build-container target=training
 ```
 
-#### Running Pipelines
-
-You can run the XGBoost training pipeline (for example) with:
+Do the same for the serving container image:
 
 ```bash
-make run PIPELINE_TEMPLATE=xgboost pipeline=training
+make build-container target=serving
 ```
 
-Alternatively, add the environment variable `PIPELINE_TEMPLATE=xgboost` and/or `pipeline=training` to `env.sh`, then:
+### Running Pipelines
+
+You can run the training pipeline (for example) with:
 
 ```bash
-make run pipeline=<training|prediction>
+make run pipeline=training
 ```
 
 This will execute the pipeline using the chosen template on Vertex AI, namely it will:
@@ -185,25 +186,23 @@ This will execute the pipeline using the chosen template on Vertex AI, namely it
 1. Compile the pipeline using the Kubeflow Pipelines SDK
 1. Trigger the pipeline with the help of `pipelines/trigger/main.py`
 
-To avoid resource conflicts when running pipelines concurrently in the same Google Cloud project with multiple developers, populate the `RESOURCE_SUFFIX` environment variable in your `env.sh` file. This will append your defined suffix to Google resources and ensure each developer's resources remain unique and separate, preventing unintentional overwriting.
-
 #### Pipeline input parameters
 
-The ML pipelines have input parameters. As you can see in the pipeline definition files (`pipelines/pipelines/<xgboost|tensorflow>/<training|prediction>/pipeline.py`), they have default values, and some of these default values are derived from environment variables (which in turn are defined in `env.sh`).
+The ML pipelines have input parameters. As you can see in the pipeline definition files (`pipelines/src/pipelines/<training|prediction>/pipeline.py`), they have default values, and some of these default values are derived from environment variables (which in turn are defined in `env.sh`).
 
-When triggering ad hoc runs in your dev/sandbox environment, or when running the E2E tests in CI, these default values are used. For the test and production deployments, the pipeline parameters are defined in the Terraform code for the Cloud Scheduler jobs (`terraform/envs/<test|prod>/variables.auto.tfvars`).
+When triggering ad hoc runs in your dev/sandbox environment, or when running the E2E tests in CI, these default values are used. For the test and production deployments, the pipeline parameters are defined in the Terraform code for the Cloud Scheduler jobs (`terraform/envs/<dev|test|prod>/scheduled_jobs.auto.tfvars`) - see the section on [Scheduling pipelines](#scheduling-pipelines).
 
 ## Testing
 
 Unit tests and end-to-end (E2E) pipeline tests are performed using [pytest](https://docs.pytest.org). 
-The unit tests for custom KFP components are run on each pull request, and the E2E tests are run on merge to the main branch. To run them on your local machine:
+The unit tests for custom KFP components are run on each pull request, as well as the E2E tests. To run them on your local machine:
 
 ```
 make setup-all-components
 make test-all-components
 ```
 
-Alternatively, only setup and install one of the components groups by running:
+Alternatively, only setup and install one of the component groups by running:
 ```
 make setup-components GROUP=vertex-components
 make test-components GROUP=vertex-components
@@ -215,8 +214,7 @@ To run end-to-end tests of a single pipeline, you can use:
 make e2e-tests pipeline=<training|prediction> [ enable_caching=<true|false> ]
 ```
 
-There are also unit tests for the pipeline triggering code. 
-This is not run as part of a CI/CD pipeline, as we don't expect this to be changed for each use case. To run them on your local machine:
+There are also unit tests for the pipeline triggering code/Cloud Function. To run them on your local machine:
 
 ```
 make test-trigger
@@ -224,43 +222,50 @@ make test-trigger
 
 ## Customize pipelines
 
-### Update existing pipelines
+### Adding a new pipeline
 
-See existing [XGBoost](pipelines/src/pipelines/xgboost) and [Tensorflow](pipelines/src/pipelines/tensorflow) pipelines as part of this template.
-Update `PIPELINE_TEMPLATE` to `xgboost` or `tensorflow` in [env.sh](env.sh.example) to specify whether to run the XGBoost pipelines or TensorFlow pipelines. 
-Make changes to the ML pipelines and their associated tests.
-Refer to the [contribution instructions](CONTRIBUTING.md) for more information on committing changes. 
+This repository contains a training and a (batch) prediction pipeline. To add another ML pipeline (e.g. for continuous evaluation), create a new directory under the `pipelines/src/pipelines` directory. Within your new pipeline folder, create a `pipeline.py` file - this is where you should provide your pipeline definition using the KFP DSL (in a function named `pipeline`).
 
-### Add new pipelines
+Alternatively, you can just copy and paste the `training` or `prediction` directory.
 
-See [USAGE](USAGE.md) for guidelines on how to add new pipelines (e.g. other than XGBoost and TensorFlow).
+See below for an example folder structure:
 
-### Scheduling pipelines
+```
+vertex-pipelines-end-to-end-samples
+|
+├── pipelines
+│   ├── src
+│   │   ├── pipelines
+│   │   │   ├── new_pipeline
+│   │   │   │   ├── pipeline.py
+│   │   │   │   └── queries
+│   │   │   │       └── my_query.sql
+```
 
-Terraform is used to deploy Cloud Scheduler jobs that trigger the Vertex Pipeline runs. This is done by the CI/CD pipelines (see section below on CI/CD).
+Make sure that you give the ML pipeline a unique name in the `@pipeline` decorator.
 
-To schedule pipelines into an environment, you will need to provide the `cloud_schedulers_config` variable to the Terraform configuration for the relevant environment. You can find an example of this configuration in [`terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example`](terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example). Copy this example file into the relevant directory for your environment (e.g. `terraform/envs/dev` for the dev environment) and remove the `.example` suffix. Adjust the configuration file as appropriate.
+To run your pipeline, use `make run` as before:
 
-### CI/CD
+```bash
+make run pipeline=your_new_pipeline
+```
 
-There are five CI/CD pipelines located under the [cloudbuild](cloudbuild) directory:
+You will also need to add an E2E test - copy and paste the `training` or `prediction` example in [pipelines/tests/](/pipelines/tests/).
 
-1. `pr-checks.yaml` - runs pre-commit checks and unit tests on the custom KFP components, and checks that the ML pipelines (training and prediction) can compile.
-2. `e2e-test.yaml` - runs end-to-end tests of the training and prediction pipeline.
-3. `release.yaml` - Compiles the training and prediction pipelines, and copies the compiled pipelines to Google Cloud Storage in the build / CI/CD environment. The Google Cloud Storage destination is namespaced using the git tag (see below). Following this, the E2E tests are run on the new compiled pipelines.
+Some of the scripts e.g. CI/CD pipelines assume only a training and prediction pipeline. You will need to adapt these to add in the compile, run and upload steps for your new pipeline in [cloudbuild/pr-checks.yaml](/cloudbuild/pr-checks.yaml), [cloudbuild/e2e-test.yaml](/cloudbuild/e2e-test.yaml) and [cloudbuild/release.yaml](/cloudbuild/release.yaml).
 
-Below is a diagram of how the files are published in each environment in the `e2e-test.yaml` and `release.yaml` pipelines:
+### Scheduling pipelines
 
-```
-. <-- GCS directory set by _PIPELINE_PUBLISH_GCS_PATH
-└── TAG_NAME or GIT COMMIT HASH <-- Git tag used for the release (release.yaml) OR git commit hash (e2e-test.yaml)
-    ├── training.json
-    ├── prediction.json
-```
+Terraform is used to deploy Cloud Scheduler jobs that trigger the Vertex Pipeline runs. This is done by the CI/CD pipelines (see section below on CI/CD).
+
+To schedule pipelines into an environment, you will need to provide the `cloud_schedulers_config` variable to the Terraform configuration for the relevant environment. You can find an example of this configuration in [`terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example`](terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example). Copy this example file into the relevant directory for your environment (e.g. `terraform/envs/dev` for the dev environment) and remove the `.example` suffix. Adjust the configuration file as appropriate.
+
+## CI/CD
+
+For details on setting up CI/CD, see the [CI/CD README](/cloudbuild/README.md).
 
-4. `terraform-plan.yaml` - Checks the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`), and produces a summary of any proposed changes that will be applied on merge to the main branch.
-5. `terraform-apply.yaml` - Applies the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`).
+For details on setting up CI/CD for the template codebase itself (instead of for your own ML use case), follow the guide [here](/docs/TESTING_SETUP.md).
 
-For more details on setting up CI/CD, see the [separate README](cloudbuild/README.md).
+## Putting it all together
 
 For a full walkthrough of the journey from changing the ML pipeline code to having it scheduled and running in production, please see the guide [here](docs/PRODUCTION.md).
diff --git a/USAGE.md b/USAGE.md
deleted file mode 100644
index 12688e02..00000000
--- a/USAGE.md
+++ /dev/null
@@ -1,72 +0,0 @@
-<!-- 
-Copyright 2022 Google LLC
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    https://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
- -->
- # USAGE.md 
-
-## Introduction
-This document is for users who are editing these templates for their own purposes and would like to add their own pipelines. If you are looking to contribute to the open source templates themselves, please refer to [`CONTRIBUTING`](CONTRIBUTING.md).
-
-## How to add a new pipeline
-
-### Folder structure
-Add your new pipeline as a folder under the `pipelines` directory. Within your new pipeline folder you should have two separate folders: `training` and `prediction`. For both `training` and `prediction`, you should include the appropriate `pipeline.py` which describes the structure of the pipeline built from the components under `pipelines/kfp_components/`. Your pipeline may make use of supporting SQL scripts, and you can store these under a separate folder named `queries`.
-
-See below for an example folder structure:
-
-```
-kfp-template-0
-│
-├── pipelines
-│   │
-│   ├── new-pipeline
-│   │   │
-│   │   ├── training
-│   │   │   ├── queries
-│   │   │   └── pipeline.py
-│   │   │
-│   │   └── prediction
-│   │       ├── queries
-│   │       └── pipeline.py
-
-```
-
-## Testing
-Please refer to [`CONTRIBUTING.md`](CONTRIBUTING.md#Testing) for information on how to write both unit and end-to-end (E2E) pipeline tests for your pipeline. It is advisable to check that your pipelines pass all tests before being shared with others. 
-
-## Compiling and running your pipeline using the Makefile
-To use the same rules listed in the Makefile, you will only need to update the environment variables. In [`.env.sh`](.env.sh), change the value of `PIPELINE_TEMPLATE` to the name of your new pipeline (this should be the same name as the new folder you have created for the pipeline).
-
-If you have organised your pipeline as described [above](#Folder-structure), you should then be able to use the Makefile as usual.
-
-Before compiling your pipeline, make sure to re-compile your pipeline components if you have made any changes:
-
-```
-make compile-components GROUP=<component group e.g. aiplatform>
-```
-
-Or to re-compile all pipeline components to YAML:
-```
-make compile-all-components
-```
-
-You can compile your pipeline to `training.json` or `prediction.json` with the following command:
-```
-make compile pipeline=<training|prediction>
-```
-
-Or you can compile your pipeline, and then immediately run it with the following command:
-```
-make run pipeline=<training|prediction>
-```
diff --git a/cloudbuild/README.md b/cloudbuild/README.md
index 7adc610f..a1c90943 100644
--- a/cloudbuild/README.md
+++ b/cloudbuild/README.md
@@ -1,5 +1,5 @@
 <!-- 
-Copyright 2022 Google LLC
+Copyright 2023 Google LLC
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -18,9 +18,10 @@ limitations under the License.
 
 ## Overview
 
-There are five CI/CD pipelines
+There are six CI/CD pipelines
 
 1. `pr-checks.yaml` - runs pre-commit checks and unit tests on the custom KFP components, and checks that the ML pipelines (training and prediction) can compile.
+1. `trigger-tests.yaml` - runs unit tests for the pipeline trigger script / Cloud Function located in [pipelines/src/pipelines/trigger](/pipelines/src/pipelines/trigger/). If you don't need to change this code, you can ignore this CI/CD pipeline.
 1. `e2e-test.yaml` - runs end-to-end tests of the training and prediction pipeline.
 1. `release.yaml` - compiles training and prediction pipelines, then copies the compiled pipelines to the chosen GCS destination (versioned by git tag).
 1. `terraform-plan.yaml` - Checks the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`), and produces a summary of any proposed changes that will be applied on merge to the main branch.
@@ -30,48 +31,39 @@ There are five CI/CD pipelines
 
 ### Which project should I use for Cloud Build?
 
-It is recommended to use a separate `admin` project, so that your dev/test/prod projects are treated identically.
+We recommend to use a separate `admin` project, since the CI/CD pipelines operate across all the different environments (dev/test/prod).
 
 ### Connecting your repository to Google Cloud Build
 
 See the [Google Cloud Documentation](https://cloud.google.com/build/docs/automating-builds/create-manage-triggers) for details on how to link your repository to Cloud Build, and set up triggers.
 
-### Cloud Build service accounts
+### Cloud Build service account
 
-Your Cloud Build pipelines will need a service account to use. We recommend the following service accounts to be created in the _admin_ project:
+Your Cloud Build pipelines will need a service account to use. Create a new service account in the _admin_ project named `cloud-build`. Then, give it these permissions in the different Google Cloud projects:
 
-| Service account name | Pipeline(s) | Permissions |
-|---|---|---|
-| `cloudbuild-prchecks` | `pr-checks.yaml` | `roles/logging.logWriter` (`admin` project) |
-| `cloudbuild-e2e-test` | `e2e-test.yaml` | `roles/logging.logWriter` (`admin` project)<br>`roles/storage.admin` (`dev` project)<br>`roles/aiplatform.user` (`dev` project)<br>`roles/iam.serviceAccountUser` (`dev` project) |
-| `cloudbuild-release` | `release.yaml` | `roles/logging.logWriter` (`admin` project)<br>`roles/storage.admin` (`dev` project)<br>`roles/storage.admin` (`test` project)<br>`roles/storage.admin` (`prod` project) |
-| `terraform-dev` | `terraform-plan.yaml` (dev)<br>`terraform-apply.yaml` (dev) | `roles/logging.logWriter` (`admin` project)<br>`roles/owner` (`dev` project)<br>`roles/storage.admin` (`dev` project) |
-| `terraform-test` | `terraform-plan.yaml` (test)<br>`terraform-apply.yaml` (test) | `roles/logging.logWriter` (`admin` project)<br>`roles/owner` (`test` project)<br>`roles/storage.admin` (`test` project) |
-| `terraform-prod` | `terraform-plan.yaml` (prod)<br>`terraform-apply.yaml` (prod) | `roles/logging.logWriter` (`admin` project)<br>`roles/owner` (`prod` project)<br>`roles/storage.admin` (`prod` project) |
+* dev/test/prod projects - `roles/owner`
+* admin project - `roles/logging.logWriter`
 
 ## Recommended triggers
 
-Use the service accounts specified above for these triggers respectively.
-
 ### On Pull Request to `main` / `master` branch
 
-Set up a trigger for the `pr-checks.yaml` pipeline, and provide a substitution value for the variable `_PIPELINE_TEMPLATE` (either `xgboost` or `tensorflow`, depending which pipelines you are using).
+Set up a trigger for the `pr-checks.yaml` pipeline.
 
 Set up a trigger for the `e2e-test.yaml` pipeline, and provide substitution values for the following variables:
 
 | Variable | Description | Suggested value |
 |---|---|---|
-| `_PIPELINE_TEMPLATE` | The set of pipelines in the repo that you would like to use - i.e. the subfolder under `pipelines` where your pipelines live. | Currently, can be either `xgboost` or `tensorflow`. |
 | `_TEST_VERTEX_CMEK_IDENTIFIER` | Optional. ID of the CMEK (Customer Managed Encryption Key) that you want to use for the ML pipeline runs in the E2E tests as part of the CI/CD pipeline with the format `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key` | Leave blank |
 | `_TEST_VERTEX_LOCATION` | The Google Cloud region where you want to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | Your chosen Google Cloud region |
 | `_TEST_VERTEX_NETWORK` | Optional. The full name of the Compute Engine network to which the ML pipelines should be peered during the E2E tests as part of the CI/CD pipeline with the format `projects/<project number>/global/networks/my-vpc` |
 | `_TEST_VERTEX_PIPELINE_ROOT` | The GCS folder (i.e. path prefix) that you want to use for the pipeline artifacts and for passing data between stages in the pipeline. Used during the pipeline runs in the E2E tests as part of the CI/CD pipeline. | `gs://<Project ID for dev environment>-pl-root` |
-| `_TEST_VERTEX_PROJECT_ID` | Google Cloud project ID in which you want to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | Project ID for the dev environment |
+| `_TEST_VERTEX_PROJECT_ID` | Google Cloud project ID in which you want to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | Project ID for the DEV environment |
 | `_TEST_VERTEX_SA_EMAIL` | Email address of the service account you want to use to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | `vertex-pipelines@<Project ID for dev environment>.iam.gserviceaccount.com` |
 | `_TEST_ENABLE_PIPELINE_CACHING` | Override the default caching behaviour of the ML pipelines. Leave blank to use the default caching behaviour. | `False` |
 
 We recommend to enable comment control for this trigger (select `Required` under `Comment Control`). This will mean that the end-to-end tests will only run once a repository collaborator or owner comments `/gcbrun` on the pull request.
-This will help to avoid unnecessary runs of the ML pipelines while a Pull Request is still being worked on, as they can take a long time (and can be expensive to run on every pull request!)
+This will help to avoid unnecessary runs of the ML pipelines while a Pull Request is still being worked on, as they can take a long time (and can be expensive to run on every Pull Request!)
 
 Set up three triggers for `terraform-plan.yaml` - one for each of the dev/test/prod environments. Set the Cloud Build substitution variables as follows:
 
@@ -87,8 +79,7 @@ Set up a trigger for the `release.yaml` pipeline, and provide substitution value
 
 | Variable | Description | Suggested value |
 |---|---|---|
-| `_PIPELINE_PUBLISH_AR_PATHS` | The (space separated) Artifact Registry repositories (plural!) where the compiled pipelines will be copied to. | `gs://europe-west2-kfp.pkg.dev/<Project ID for dev environment>/vertex-pipelines gs://europe-west2-kfp.pkg.dev/<Project ID for test environment>/vertex-pipelines gs://europe-west2-kfp.pkg.dev/<Project ID for prod environment>/vertex-pipelines` |
-| `_PIPELINE_TEMPLATE` | The set of pipelines in the repo that you would like to use - i.e. the subfolder under `pipelines` where your pipelines live. | Currently, can be either `xgboost` or `tensorflow`. |
+| `_PIPELINE_PUBLISH_AR_PATHS` | The (space separated) Artifact Registry repositories (plural!) where the compiled pipelines will be copied to - one for each environment (dev/test/prod). | `https://europe-west2-kfp.pkg.dev/<Project ID for dev environment>/vertex-pipelines https://europe-west2-kfp.pkg.dev/<Project ID for test environment>/vertex-pipelines https://europe-west2-kfp.pkg.dev/<Project ID for prod environment>/vertex-pipelines` |
 
 ### On merge to `main` / `master` branch
 
diff --git a/docs/PRODUCTION.md b/docs/PRODUCTION.md
index 47fb4a7e..398a6907 100644
--- a/docs/PRODUCTION.md
+++ b/docs/PRODUCTION.md
@@ -20,16 +20,16 @@ This document describes the full process from making a change to your pipeline c
 
 ## Pre-requisites
 
-- Suitable GCP environments set up - see the README section on [Deploying Cloud Infrastructure](../README.md#deploying-cloud-infrastructure)
+- Suitable GCP environments set up - see the README section on [Deploying Cloud Infrastructure](/README.md#deploying-cloud-infrastructure)
 - This repo forked / used as a template for a new GitHub repo
 - CI/CD set up - see the instructions [here](cloudbuild/README.md)
 - Access set up for the BigQuery datasets used in the example pipelines
-- Git repo cloned locally (or in a notebook environment) and local setup complete - see [here](../README.md#local-setup)
+- Git repo cloned locally (or in a notebook environment) and local setup complete - see [here](/README.md#local-setup)
 
 ## Making your changes to the pipelines
 
 1. Create a feature branch off the main/master branch: `git checkout -b my-feature-branch`
-1. Make changes to your pipeline code locally (see main README and [USAGE.md](../USAGE.md) for more details)
+1. Make changes to your pipeline code locally (e.g. [pipelines/src/pipelines/training/pipeline.py](/pipelines/src/pipelines/training/pipeline.py))
 1. Commit these changes to your feature branch
 1. Push your feature branch to GitHub
 1. Open a Pull Request (PR) from your feature branch to the main/master branch
@@ -40,33 +40,33 @@ When you open the Pull Request, the CI pipeline (`pr-checks.yaml`) should be tri
 |:-------------------|
 | Make sure to update any unit tests and end-to-end tests in line with your changes to the pipelines |
 
+| :exclamation: IMPORTANT    |
+|:---------------------------|
+| Before your E2E tests can run correctly, you need to make sure that the parameters have been set up correctly for the cloud environment in the relevant pipeline definition files (`pipeline.py`). These can inherit from environment variables set in `env.sh` (for triggering ad hoc) or in your Cloud Build trigger setup (for triggering through CI/CD) |
+
 ## Creating a release
 
 To compile and publish your ML pipelines into your test and prod environments, you will need to [create a release](https://docs.github.com/en/repositories/releasing-projects-on-github/managing-releases-in-a-repository#creating-a-release).
 
-When the new tag is created, the `release.yaml` pipeline should be triggered. It will compile both the training and prediction pipelines, then copy the ML pipelines and their [assets](../README.md#assets) to the Cloud Storage locations specified in your [CI/CD setup](../cloudbuild/README.md) under a folder with the name of your git tag.
+When the new tag is created, the `release.yaml` pipeline should be triggered. It will build and push the training and serving container images, compile the training and prediction pipelines, then upload the compiled ML pipelines to Artifact Registry in each environment (dev/test/prod).
 
 #### Example
 
-- You are using the `xgboost` template
-- You create a release from the main/master branch and use the git tag `v1.2`
+
 - You have set up the following Cloud Build variables / substitutions for the `release.yaml` CI/CD pipeline
-  - `_PIPELINE_PUBLISH_GCS_PATHS` = `gs://<Project ID of dev project>-pl-assets gs://<Project ID of test project>-pl-assets gs://<Project ID of prod project>-pl-assets`
+  - `_PIPELINE_PUBLISH_AR_PATHS` = `https://<GCP region>-kfp.pkg.dev/<Project ID of dev project>/vertex-pipelines https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines https://<GCP region>-kfp.pkg.dev/<Project ID of prod project>/vertex-pipelines`
+- You create a release from the main/master branch and use the git tag `v1.2`
 
-Assuming your end-to-end tests pass, your compiled training pipeline will be published to:
+Your compiled training pipeline will be published to:
 - `https://<GCP region>-kfp.pkg.dev/<Project ID of dev project>/vertex-pipelines/xgboost-train-pipeline/v1.2`
 - `https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/v1.2`
 - `https://<GCP region>-kfp.pkg.dev/<Project ID of prod project>/vertex-pipelines/xgboost-train-pipeline/v1.2`
 
-Similarly, your compiled prediction pipeline will be published in this location:
+Similarly, your compiled prediction pipeline will be published in these locations:
 - `https://<GCP region>-kfp.pkg.dev/<Project ID of dev project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2`
 - `https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2`
 - `https://<GCP region>-kfp.pkg.dev/<Project ID of prod project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2`
 
-| :exclamation: IMPORTANT    |
-|:---------------------------|
-| Before your E2E tests can run correctly, you need to make sure that the parameters have been set up correctly for the cloud environment in the relevant pipeline definition files (`pipeline.py`). These can inherit from environment variables set in `env.sh` (for triggering ad hoc) or in your Cloud Build trigger setup (for triggering through CI/CD) |
-
 ## Deploying a release to the test environment
 
 Now that you have created a release, and the compiled pipelines have been copied to the test and prod environments, you can now schedule your pipelines to run in those environments.
@@ -84,16 +84,16 @@ cloud_schedulers_config = {
 
   xgboost_training = {
     name         = "xgboost-training-pipeline-trigger"
-    description  = "Trigger my XGBoost training pipeline in Vertex"
+    description  = "Trigger my training pipeline in Vertex"
     schedule     = "0 0 1 * *"
     time_zone    = "UTC"
-    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/<Git tag>"
+    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/v1.2"
     enable_caching = null
     pipeline_parameters = {
       project_id = <Project ID of test project>
       project_location = "europe-west2"
       ingestion_project_id = <Project ID of test project>
-      model_name = "xgboost-with-preprocessing"
+      model_name = "simple_xgboost"
       model_label = "label_name"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
@@ -104,16 +104,16 @@ cloud_schedulers_config = {
 
     xgboost_prediction = {
     name         = "xgboost-prediction-pipeline-trigger"
-    description  = "Trigger my XGBoost prediction pipeline in Vertex"
+    description  = "Trigger my prediction pipeline in Vertex"
     schedule     = "0 0 * * *"
     time_zone    = "UTC"
-    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/<Git tag>"
+    template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2"
     enable_caching = null
     pipeline_parameters = {
       project_id = <Project ID of test project>
       project_location = "europe-west2"
       ingestion_project_id = <Project ID of test project>
-      model_name = "xgboost-with-preprocessing"
+      model_name = "simple_xgboost"
       model_label = "label_name"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
@@ -134,4 +134,4 @@ cloud_schedulers_config = {
 
 ## Deploying a release to the production environment
 
-Once you are happy with how `v1.2` is working in the test environment, you can follow the same process for the prod environment (using `terraform/envs/prod`, swapping the necessary values out for the different environment e.g. bucket names).
+Once you are happy with how `v1.2` is working in the test environment, you can follow the same process for the prod environment (using `terraform/envs/prod`, swapping the necessary values out for the different environment e.g. Artifact Registry names).
diff --git a/docs/TESTING_SETUP.md b/docs/TESTING_SETUP.md
index ef358f09..b1f07e49 100644
--- a/docs/TESTING_SETUP.md
+++ b/docs/TESTING_SETUP.md
@@ -47,6 +47,24 @@ storage.googleapis.com \
 --project $GCP_PROJECT_ID
 ```
 
+### Google Cloud Storage
+
+Create a bucket to use for the Vertex Pipelines pipeline root.
+
+```
+gsutil mb -l ${GCP_REGION} -p ${GCP_PROJECT_ID} --pap=enforced gs://${GCP_PROJECT_ID}-pl-root && gsutil ubla set on gs://${GCP_PROJECT_ID}-pl-root
+```
+
+### Artifact Registry
+
+Create a new container image registry in Artifact Registry. This is where training and serving container images will be stored before they can be used in the E2E tests.
+
+```
+gcloud artifacts repositories create vertex-images \
+    --repository-format=docker \
+    --location=${GCP_REGION}
+```
+
 ### BigQuery 
 
 Create a new BigQuery dataset for the Chicago Taxi data:
@@ -100,11 +118,13 @@ The service account we have created for Cloud Build requires the following proje
 - roles/logging.logWriter
 - roles/storage.admin
 - roles/aiplatform.user
+- roles/artifactregistry.writer
 
 ```
 gcloud projects add-iam-policy-binding $GCP_PROJECT_ID --member="serviceAccount:cloud-build@${GCP_PROJECT_ID}.iam.gserviceaccount.com" --role="roles/logging.logWriter" --condition=None
 gcloud projects add-iam-policy-binding $GCP_PROJECT_ID --member="serviceAccount:cloud-build@${GCP_PROJECT_ID}.iam.gserviceaccount.com" --role="roles/storage.admin" --condition=None
 gcloud projects add-iam-policy-binding $GCP_PROJECT_ID --member="serviceAccount:cloud-build@${GCP_PROJECT_ID}.iam.gserviceaccount.com" --role="roles/aiplatform.user" --condition=None
+gcloud projects add-iam-policy-binding $GCP_PROJECT_ID --member="serviceAccount:cloud-build@${GCP_PROJECT_ID}.iam.gserviceaccount.com" --role="roles/artifactregistry.writer" --condition=None
 ```
 
 It also requires the "Service Account User" role for the Vertex Pipelines service account ([docs here](https://cloud.google.com/iam/docs/impersonating-service-accounts#impersonate-sa-level)):
@@ -144,13 +164,11 @@ Follow the [Google Cloud documentation](https://cloud.google.com/build/docs/auto
 
 ### Set up Cloud Build Triggers
 
-There are five Cloud Build triggers to set up.
+There are three Cloud Build triggers to set up.
 
-1. `pr-checks.yaml` (tensorflow)
-2. `pr-checks.yaml` (xgboost)
-3. `trigger-tests.yaml` 
-4. `e2e-test.yaml` (tensorflow)
-5. `e2e-test.yaml` (xgboost)
+1. `pr-checks.yaml`
+2. `trigger-tests.yaml` 
+3. `e2e-test.yaml`
 
 For each of the above, create a Cloud Build trigger with the following settings:
 
@@ -164,8 +182,6 @@ For each of the above, create a Cloud Build trigger with the following settings:
 
 |  Cloud Build Trigger          |  Substitution variables             |
 |-------------------------------|-------------------------------------|
-| `pr-checks.yaml` (tensorflow) |  _PIPELINE_TEMPLATE = `tensorflow`  |
-| `pr-checks.yaml` (xgboost)    |  _PIPELINE_TEMPLATE = `xgboost`     |
+| `pr-checks.yaml`              |                                     |
 | `trigger-tests.yaml`          |                                     |
-| `e2e-test.yaml` (tensorflow)  |  _PIPELINE_TEMPLATE = `tensorflow`<br>_PIPELINE_PUBLISH_GCS_PATH = `gs://<GCP PROJECT ID>-assets/e2e-test-tensorflow`<br>_TEST_ENABLE_PIPELINE_CACHING = `False`<br>_TEST_TRAIN_STATS_GCS_PATH = `gs://<GCP PROJECT ID>-pl-root/e2e-test-tensorflow/train-stats/train.stats`<br>_TEST_VERTEX_LOCATION = `<GCP REGION (same as buckets etc above)>`<br>_TEST_VERTEX_PIPELINE_ROOT = `gs://<GCP PROJECT ID>-pl-root`<br>_TEST_VERTEX_PROJECT_ID = `<GCP PROJECT ID>`<br>_TEST_VERTEX_SA_EMAIL = `vertex-pipelines@<GCP PROJECT ID>.iam.gserviceaccount.com`  |
-| `e2e-test.yaml` (xgboost)  |  _PIPELINE_TEMPLATE = `xgboost`<br>_TEST_ENABLE_PIPELINE_CACHING = `False`<br>_TEST_VERTEX_LOCATION = `<GCP REGION (same as buckets etc above)>`<br>_TEST_VERTEX_PIPELINE_ROOT = `gs://<GCP PROJECT ID>-pl-root`<br>_TEST_VERTEX_PROJECT_ID = `<GCP PROJECT ID>`<br>_TEST_VERTEX_SA_EMAIL = `vertex-pipelines@<GCP PROJECT ID>.iam.gserviceaccount.com`  |
+| `e2e-test.yaml`               |  _TEST_ENABLE_PIPELINE_CACHING = `False`<br>_TEST_VERTEX_LOCATION = `<GCP REGION (same as buckets etc above)>`<br>_TEST_VERTEX_PIPELINE_ROOT = `gs://<GCP PROJECT ID>-pl-root`<br>_TEST_VERTEX_PROJECT_ID = `<GCP PROJECT ID>`<br>_TEST_VERTEX_SA_EMAIL = `vertex-pipelines@<GCP PROJECT ID>.iam.gserviceaccount.com` |
diff --git a/docs/TROUBLESHOOTING.md b/docs/TROUBLESHOOTING.md
deleted file mode 100644
index c970836e..00000000
--- a/docs/TROUBLESHOOTING.md
+++ /dev/null
@@ -1,46 +0,0 @@
-<!-- 
-Copyright 2022 Google LLC
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    https://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
- -->
-
-# Troubleshooting
-
-List of common issues during project setup:
-
-```bash
-$ make run pipeline=<training|prediction>`
-
-google.auth.exceptions.DefaultCredentialsError: Could not automatically determine credentials. 
-Please set GOOGLE_APPLICATION_CREDENTIALS or explicitly create credentials and re-run the application.
-```
-
-**Solution:** `gcloud auth application-default login`
-
-```bash
-$ make run pipeline=<training|prediction>
-
-google.api_core.exceptions.InvalidArgument: 400 You do not have permission to act as service_account: 
-<...>@<...>.iam.gserviceaccount.com. (or it may not exist).
-```
-
-**Solution:** Ensure the service account mentioned in `.env.sh` (`VERTEX_SA_EMAIL`) 
-exists and you have permission to act as the service account.
-
-```bash
-$ make test-components GROUP=_xgboost
-
-FAILED tests/test_train.py::test_xgboost_train - xgboost.core.XGBoostError: XGBoost Library (libxgboost.dylib) could not be loaded.
-```
-
-**Solution:** if you are using macOS, try to also install XGBoost using Homebrew: `brew install xgboost`
diff --git a/docs/images/architecture.png b/docs/images/architecture.png
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diff --git a/pipelines/README.md b/pipelines/README.md
index 1453995d..ec328036 100644
--- a/pipelines/README.md
+++ b/pipelines/README.md
@@ -13,106 +13,103 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
  -->
- # Pipelines
+# ML Pipelines
 
-## Introduction
+There are two ML pipelines defined in this repository: a training pipeline (located in [pipelines/src/pipelines/training/pipeline.py](/pipelines/src/pipelines/training/pipeline.py)) and a batch prediction pipeline (located in [pipelines/src/pipelines/prediction/pipeline.py](/pipelines/src/pipelines/prediction/pipeline.py)).
 
-This repository provides templates and reference implementations of [Vertex AI Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/) for production-grade training and batch prediction pipelines on GCP for:
-- [TensorFlow](https://www.tensorflow.org/api_docs)
-- [XGBoost](https://xgboost.readthedocs.io/en/stable/) (using the [Scikit-Learn wrapper interface for XGBoost](https://xgboost.readthedocs.io/en/latest/python/python_api.html#module-xgboost.sklearn))
+## Training pipeline
 
-Further useful documentation:
-- [KubeFlow Pipelines SDK](https://www.kubeflow.org/docs/components/pipelines/sdk/sdk-overview/)
-- [Google Cloud Pipeline Components - Vertex Training Wrapper](https://github.com/kubeflow/pipelines/blob/master/components/google-cloud/google_cloud_pipeline_components/experimental/custom_job/utils.py)
-- [Vertex AI](https://cloud.google.com/vertex-ai)
+A screenshot of the completed ML pipeline is shown below.
 
-The sections below provide a general description of the ML pipelines (training and prediction) for both the TensorFlow template and XGBoost template. These two templates are similar in most ways and a complete overview of their key differences are given in their own README files:
-- [TensorFlow pipelines README](src/pipelines/tensorflow/README.md)
-- [XGBoost pipelines README](src/pipelines/xgboost/README.md)
+![Screenshot of the training pipeline in Vertex Pipelines](/docs/images/training_pipeline.png)
 
-## Training Pipeline
-### Prerequisites for training pipeline
+In the next sections we will walk through the different pipeline steps.
 
-Optional: an existing champion model
+### Ingestion / preprocessing step
 
-### Components in training pipeline
+The first pipeline step runs a SQL script in BigQuery to extract data from the source table and load it into tables according to a train/test/validation split.
 
-The training pipeline can be broken down into the following sequence of components at a high level:
+The SQL query for this can be found in [pipelines/src/pipelines/training/queries/preprocessing.sql](/pipelines/src/pipelines/training/queries/preprocessing.sql).
 
-| Step No |           Step Name            | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | Input(s)                                                                                                                                                                                                                          | Output(s)                                                                              |
-|:-------:| :----------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------- |
-|    1    |        Generate Queries        | Generate base preprocessing & train-test-validation split queries for Google BigQuery. This component only needs a `.sql` file and all parametrized values in that `.sql` file (`source_dataset`, `source_table`, `filter_column`, and so on)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |                                                                                                                                                                                                                                   |                                                                                        |
-|    2    |       BQ Query to Table        | This component takes the generated query from the previous component & runs it on Google BigQuery to create the required table (preprocessed data/ train-test-validation data).                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              | Output from **Generate Queries**                                                                                                                                                                                                  | New Google BigQuery table created                                                      |
-|    3    |     Extract BQ to Dataset      | Creates CSV file/s in Google Cloud Storage from the Google BigQuery tables created in the previous component                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | BigQuery table created from **BQ Query to Table**                                                                                                                                                                                 | BigQuery table converted to Google Cloud Storage objects as CSV/JSONL files and corresponding file directory and path |
-|    4    |        Vertex Training         | Run a Vertex Training job with train-validation data using a training component wrapped in a ContainerOp from `google-cloud-pipeline-components`                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             | <ul><li>*Train/Validation data* - Google Cloud Storage CSV files for `train_data` + `valid_data` from **Extract BQ to Dataset**</li><li>*Model Parameters* - Specific model parameters for model training</li></ul>               | Trained challenger model object/s or binaries stored in Google Cloud Storage           |
-|    5    |  Challenger Model Predictions  | Use the trained model to get challenger predictions for evaluation purposes                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | <ul><li>*Test data* - Google Cloud Storage CSV files for `test_data` from **Extract BQ to Dataset**</li><li>*Trained Model* - Trained challenger model binaries stored in Google Cloud Storage from **Vertex Training**</li></ul> | Challenger predictions on test data stored as CSV files in Google Cloud Storage        |
-|    6    |  Calculate Evaluation Metrics  | Use predictions from previous component to compute user-defined evaluation metrics. This component uses TFMA.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                | <ul><li>Test data predictions stored as CSV files in Google Cloud Storage from **Challenger Model Predictions**</li><li>Data slices if required</li><ul>                                                                                                                           | Evaluation metrics stored in Google Cloud Storage. Plots for all evaluation metrics and slices stored as HTML files in Google CLoud Storage                                       |
-|    7    |          Lookup Model          | Fetch the required model and its resource name if a previous champion model exists in Vertex AI                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      | Base model name to check if it exists in Vertex AI                                                                                                                                                                                | Model resource name as a string if a champion model exists else an empty string        |
-|    8    | Champion-Challenger Comparison | All model training activities until this point were for a new challenger model. Basic idea is to compare this newly trained challenger model with an existing champion model & decide deployment of this challenger model based on performance comparison. <ul><li>*If champion model does not exist* - Upload Challenger model as the new Champion model to Vertex AI</li><li>*If champion model exists* -<ul><li>**Calculate evaluation metrics** - Compute user-defined evaluation metrics on the same `test_data`</li><li>**Compare Models** - Compare computed evaluation metrics for the champion model<ul><li>*If challenger model performance is better* - Upload Challenger model as the new Champion model to Vertex AI</li><li>*If champion model performance is better* - End pipeline (Champion model remains as is in Vertex AI)</li></ul></li></ul></li></ul> |                                                                                                                                                                                                                                   |                                                                                        |
+As you can see in this SQL query, there are some placeholder values (marked by the curly brace syntax `{{ }}`). When the pipeline runs, these are replaced with values provided from the ML pipeline.
 
-Each of these components can be connected using `.after({component_name})` or if the output of a preceding component is used as input for that component
-Every component can be set with a display name using `.set_display_name({display_name})`. Note that this applies to both the training pipeline and the prediction pipeline. 
+In the pipeline definition, the `generate_query` function is run at pipeline compile time to generate a SQL query (as a string) from the template file (`preprocessing.sql`). The placeholders (`{{ }}` values) are replaced with KFP placeholders that represent pipeline parameters, or values passed from other pipeline components at runtime. In turn, these placeholders are automatically replaced with the actual values at runtime by Vertex Pipelines.
 
+The `preprocessing` step in the pipeline uses this string (`preprocessing_query`) in the `BigqueryQueryJobOp` component (provided by [Google Cloud Pipeline Components](https://cloud.google.com/vertex-ai/docs/pipelines/components-introduction))
 
-## Prediction Pipeline
-### Prerequisites for prediction pipeline
+### Extraction steps
 
-- A champion model
-- A successful run of the training pipeline
+Once the data has been split into three tables (for train/test/validation split), each table is downloaded to Google Cloud Storage as a CSV file. This is done so that there is a copy of the train/test/validation data for each pipeline run that you have a record of.
 
-### Components in prediction pipeline
+(Alternatively, you could choose to omit this step, leave the data in BigQuery and consume the data directly from BigQuery for your training step).
 
-The prediction pipeline can be broken down into the following sequence of components at a high level:
+This step is performed using a custom KFP component located in [components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py](/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py).
 
-| Step No |                        Name                        | Description                                                                                                                                                                                                                                                                                                  | Input(s)                                                                                                                                                                                                                          | Output(s)                                                                     |
-|:-------:| :------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :---------------------------------------------------------------------------- |
-|    1    |                  Generate Queries                  | Generate base preprocessing & prediction data creation queries for Google BigQuery. This component only needs a `.sql` file & all parametrized values in that `.sql` file (source_dataset, source_table, filter_column etc)                                                                                     |                                                                                                                                                                                                                                   |                                                                               |
-|    2    |                 BQ Query to Table                  | This component takes the generated query from the previous component & runs it on Google BigQuery to create the required table (preprocessed data/ prediction data).                                                                                                                                            | Output from **Generate Queries**                                                                                                                                                                                                  | New Google BigQuery table created                                             |
-|    3    |               Extract BQ to Dataset                | Creates CSV/JSONL file/s in Google Cloud Storage from the Google BigQuery tables created in the previous component                                                                                                                                                                                           | BigQuery table created from *BQ Query to Table*. Full table name required i.e `{project_id}.{dataset_id}.{table_id}`                                                                                                              | BigQuery table converted to Google Cloud Storage objects as CSV/JSONL files, and corresponding file directory and path  |
-|    4    |                    Lookup Model                    | Fetch the required model resource name for a champion model in Vertex AI. Since the prediction pipeline will always run after the training pipeline, a champion model will always exist                                                                                                                         | Base champion model name as a string                                                                                                                                                                                              | Champion model resource name as a string                                      |
-|    5    | Vertex Batch Predictions from Google Cloud Storage | Run a Vertex Batch Prediction job with prediction data as input in Tensorflow prediction Pipeline                                                                                                                                                                                                                                                 | <ul><li>*Prediction data* - The uris of Google Cloud Storage CSV/JSONL files for `prediction_data` from **Extract BQ to Dataset**</li><li>*Model* - Champion model as per Vertex AI</li></ul>                             | A batch prediction job artifact with metadata: resourceName(batch prediction job ID) and gcsOutputDirectory(output JSONL files in Google Cloud Storage) |
-|    6    |       Vertex Batch Predictions from BigQuery       | Run a Vertex Batch Prediction job with prediction data as input in XGBoost prediction Pipeline                                                                                                                                                                                                                                                 | <ul><li>*Prediction data* - Google BigQuery table of `prediction_data` from **Extract BQ to Dataset**</li><li>*Model Resource name* - Champion model as per Vertex AI</li></ul>                                             | A batch prediction job artifact with metadata: resourceName(batch prediction job ID) and bigqueryOutputTable(output BigQuery tables) |
-|    7    |                 Load Dataset to BQ                 | Upload the batch predictions stored in Google Cloud Storage to a BigQuery table in Tensorflow prediction Pipeline                                                                                                                                                                                                                              | Batch predictions stored as JSONL files in Google Cloud Storage from **Vertex Batch Predictions**  The specific URL could be read from metadata from batch prediction job                                                                                                                               | Google BigQuery table with the batch predictions & input instances/features   |
+### Training step
 
-Each of these components can be connected using `.after({component_name})` or if the output of a preceding component is used as input for that component
-Every component can be set with a display name using `.set_display_name({display_name})`. Note that this applies to both the training pipeline and the prediction pipeline. 
+The training step is defined as a [KFP container component](https://www.kubeflow.org/docs/components/pipelines/v2/components/container-components/) in the [pipeline.py](/pipelines/src/pipelines/training/pipeline.py) file.
 
-The final loading stage has an optional argument `dataset_location` which is the location to run the loading job and must match the location of the destination table. It is defaulted to "EU" in the [component definition](pipeline_components/bigquery/bigquery/upload_prediction/component.py). 
+The container image used for this component is built using CI/CD (or the `make build-container target=training` command if you want to build it during development).
 
-## Trigger
+The source code for this container image (and the serving container image) can be found in the [model](/model/) directory. Dependencies are managed using Poetry. The model training script can be found at [model/training/train.py](/model/training/train.py) and can be modified to suit your use case.
 
-- Trigger script can be found [here](src/pipelines/trigger)
+The training script trains a simple XGBoost model wrapped in a scikit-learn pipeline, and saves it as `model.joblib`.
 
-## Pipeline configuration
+![Architecture of the XGBoost model](/docs/images/xgboost_architecture.png)
 
-In order to orchestrate machine learning (ML) pipelines on Vertex AI, you need to configure a few things.
+The model is evaluated and metrics are saved as a JSON file. In the Vertex pipeline, the model appears as a KFP Model artifact, and the JSON file appears as a KFP Metrics artifact.
 
-### env.sh
+### Upload model step
 
-The first thing to do is to copy `env.sh.example` to `env.sh`, and fill in the values of `env.sh` with the values relevant to your development/sandbox environment. These environment variables will be used when you trigger pipeline runs in Vertex AI.
+The upload model step uploads the model to the Vertex model registry. This step uses a custom KFP component that can be 
+found in [components/vertex-components/src/vertex_components/upload_model.py](/components/vertex-components/src/vertex_components/upload_model.py). It does the following:
 
-### Pipeline input parameters
+1. Checks if there is an existing "champion" model with the same name in the Vertex Model Registry
+1. If there is, fetch its latest model evaluation and compare it with the model evaluation of the newly trained "challenger" model
+1. If the new model performs better, or if there is no existing champion model, upload the newly trained "challenger" model and tag it with the `default` alias to designate it as the new champion model
+1. If the new model performs worse than the existing "champion" model, upload the new model to the registry, but don't tag it with the `default` alias
+1. Import the model evaluation of the newly-trained model and attach it to the newly-uploaded model in the Vertex Registry
 
-The ML pipelines have input parameters. As you can see in the pipeline definition files (`pipelines/<xgboost|tensorflow>/<training|prediction>/pipeline.py`), they have default values, and some of these default values are derived from environment variables (which in turn are defined in `env.sh` as described above).
+| :bulb: Quick note on Champion-Challenger comparisons    |
+|:-------------------|
+| In practice, you should be aware of that and give the model a specific name related to the ML project you are working on once the new model is not comparable with the previous models. 
+For example, when you want to train a new model using different features, the best practice is to change your model name in the pipeline input parameters. |
 
-When triggering ad hoc runs in your dev/sandbox environment, or when running the E2E tests in CI, these default values are used. For the test and production deployments, the pipeline parameters are defined in the Terraform code for the Cloud Scheduler jobs (`envs/<test|prod>/variables.auto.tfvars`).
+## Batch prediction pipeline
 
-### Python packages and Docker images
+A screenshot of the completed ML pipeline is shown below.
 
-You can specify the Python base image and packages required for KFP components in the `@component` decorator using the `base_image` and `packages_to_install` arguments respectively.
+![Screenshot of the prediction pipeline in Vertex Pipelines](/docs/images/prediction_pipeline.png)
+In the next sections we will walk through the different pipeline steps.
 
-### Compute resources configuration in pipeline
-In general there are two methods to configure compute resources in each pipeline. 
-Firstly, by setting the `machine_type` variable in [XGBoost training pipeline](src/pipelines/xgboost/training/pipeline.py), [XGBoost prediction pipeline](src/pipelines/xgboost/prediction/pipeline.py), [TensorFlow training pipeline](src/pipelines/tensorflow/training/pipeline.py), [TensorFlow prediction pipeline](src/pipelines/tensorflow/prediction/pipeline.py). The default value is `n1-standard-4` with 4 core CPUs and 15GB memory.
-Secondly, in order to manage the requirements of each step in your pipeline, you can set up machine type on the pipeline steps. 
-This is because some steps might need more computational resources than others. 
-You can increase CPU and memory limits by applying `.set_cpu_limit({CPU_LIMIT})` and `.set_memory_limit('MEMORY_LIMIT')` for any component. 
-- CPU_LIMIT: The maximum CPU limit for this operator. This string value can be a number (integer value for number of CPUs), or a number followed by "m", which means 1/1000. You can specify at most 96 CPUs.
-- MEMORY_LIMIT: The maximum memory limit for this operator. This string value can be a number, or a number followed by "K" (kilobyte), "M" (megabyte), or "G" (gigabyte). At most 624GB is supported.
+### Ingestion / preprocessing step
 
-For more information, please refer to the guide on [specifying machine types for a pipeline step](https://cloud.google.com/vertex-ai/docs/pipelines/machine-types). 
+The first pipeline step runs a SQL script in BigQuery to extract data from the source table and load it into a different BigQuery table, ready for predictions to generated.
+
+The SQL query for this can be found in [pipelines/src/pipelines/prediction/queries/preprocessing.sql](/pipelines/src/pipelines/prediction/queries/preprocessing.sql).
+
+As you can see in this SQL query, there are some placeholder values (marked by the curly brace syntax `{{ }}`). When the pipeline runs, these are replaced with values provided from the ML pipeline.
+
+In the pipeline definition, the `generate_query` function is run at pipeline compile time to generate a SQL query (as a string) from the template file (`preprocessing.sql`). The placeholders (`{{ }}` values) are replaced with KFP placeholders that represent pipeline parameters, or values passed from other pipeline components at runtime. In turn, these placeholders are automatically replaced with the actual values at runtime by Vertex Pipelines.
+
+The `preprocessing` step in the pipeline uses this string (`preprocessing_query`) in the `BigqueryQueryJobOp` component (provided by [Google Cloud Pipeline Components](https://cloud.google.com/vertex-ai/docs/pipelines/components-introduction))
+
+### Lookup model
+
+This step looks up the "champion" model from the Vertex Model Registry. It uses a custom KFP component that can be found in [components/vertex-components/src/vertex_components/lookup_model.py](/components/vertex-components/src/vertex_components/lookup_model.py). It uses the Vertex AI Python SDK to list models with a given model name and retrieve the model version that uses the `default` alias, indicating that it is the "champion" model.
+
+### Batch Prediction
+
+This step submits a Vertex Batch Prediction job that generates predictions from the BigQuery table from the ingestion/preprocessing step. It uses a custom KFP component that can be found in [components/vertex-components/src/vertex_components/model_batch_predict.py](/components/vertex-components/src/vertex_components/model_batch_predict.py). It uses Vertex Model Monitoring for batch prediction to monitor the data for drift.
+
+## Pipeline input parameters
+
+The ML pipelines have input parameters. As you can see in the pipeline definition files (`src/pipelines/<training|prediction>/pipeline.py`), they have default values, and some of these default values are derived from environment variables (which in turn are defined in `env.sh` as described above).
+
+When triggering ad hoc runs in your dev/sandbox environment, or when running the E2E tests in CI, these default values are used. For the test and production deployments, the pipeline parameters are defined in the Terraform code for the Cloud Scheduler jobs (`envs/<test|prod>/scheduled_jobs.auto.tfvars`).
 
 ### Cache Usage in pipeline
+
 When Vertex AI Pipelines runs a pipeline, it checks to see whether or not an execution exists in Vertex ML Metadata with the interface (cache key) of each pipeline step (component).
 If the component is exactly the same and the arguments are exactly the same as in some previous execution, then the task can be skipped and the outputs of the old step can be used. 
 Since most of the ML projects take a long time and expensive computation resources, it is cost-effective to use cache when you are sure that the output of components is correct. 
@@ -120,14 +117,3 @@ In terms of [how to control cache reuse behavior](https://cloud.google.com/verte
 If you want to control caching behavior for individual components, add `.set_caching_options(<True|False>)` after each component when building a pipeline.
 To change the caching behaviour of ALL components within a pipeline, you can specify this when you trigger the pipeline like so: `make run pipeline=<training|prediction> enable_caching=<true|false>`
 It is suggested to start by disabling caching of components during development, until you have a good idea of how the caching behaviour works, as it can lead to unexpected results.
-
-Note:
-Disable caching if you want to use new data:
-When caching is enabled for the pipeline, changing `timestamp` or source of data (such as `ingestion_dataset_id`) will only change the output of 
-corresponding step, for example `Ingest data`. While for the other components, which take the same arguments, they will use caches instead of using the new data. 
-
-### Champion / Challenger evaluation
-
-In the training pipelines, a Champion-Challenger evaluation is conducted via the models with same name pattern in the same project. Explore [`lookup_model.py`](../pipeline_components/aiplatform/aiplatform/lookup_model/component.py) for more detailed information.
-In practice, you should be aware of that and give the model a specific name related to the ML project you are working on once the new model is not comparable with the previous models. 
-For example, when you want to train a new model using different features, the best practice is to change you model name in the pipeline input parameters.

From 1d577c0d0a42854480f920734570643da1b50e5f Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 1 Aug 2023 15:10:52 +0100
Subject: [PATCH 139/238] docs: add container reg to arch diagram

---
 docs/images/architecture.png | Bin 247418 -> 287568 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/docs/images/architecture.png b/docs/images/architecture.png
index 73a2388a438e3675cb6f6974e7c1acd2acc92cf9..a6b587459e22fb448efd57002188e8639da97a96 100644
GIT binary patch
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VyHjVKK4AxyxG5u+A)@{G{{f6|a>oDw


From 78755b36b0406794a307736fd4a3f197a303ae76 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 1 Aug 2023 17:17:05 +0100
Subject: [PATCH 140/238] ci: fix poetry install in ci

---
 cloudbuild/e2e-test.yaml      | 2 ++
 cloudbuild/pr-checks.yaml     | 2 ++
 cloudbuild/release.yaml       | 2 ++
 cloudbuild/trigger-tests.yaml | 2 ++
 4 files changed, 8 insertions(+)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 150a4c57..b6724cec 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -42,6 +42,8 @@ steps:
     args:
       - -c
       - |
+        curl -sSL https://install.python-poetry.org | python3 - && \
+        export PATH="/builder/home/.local/bin:$$PATH" && \
         make setup && \
         make e2e-tests pipeline=training enable_pipeline_caching=False && \
         make e2e-tests pipeline=prediction enable_pipeline_caching=False
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 61e1c923..a7819caa 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -22,6 +22,8 @@ steps:
     args:
       - -c
       - |
+        curl -sSL https://install.python-poetry.org | python3 - && \
+        export PATH="/builder/home/.local/bin:$$PATH" && \
         make setup && \
         git init && \
         git add . && \
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index d9c93ce7..c7e514b3 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -37,6 +37,8 @@ steps:
     args:
       - -c
       - |
+        curl -sSL https://install.python-poetry.org | python3 - && \
+        export PATH="/builder/home/.local/bin:$$PATH" && \
         make setup && \
         for proj in ${_DESTINATION_PROJECTS} ; do \
           CONTAINER_IMAGE_REGISTRY=${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images \
diff --git a/cloudbuild/trigger-tests.yaml b/cloudbuild/trigger-tests.yaml
index 295e2c50..4778396c 100644
--- a/cloudbuild/trigger-tests.yaml
+++ b/cloudbuild/trigger-tests.yaml
@@ -17,6 +17,8 @@ steps:
     args:
       - '-c'
       - |
+        curl -sSL https://install.python-poetry.org | python3 - && \
+        export PATH="/builder/home/.local/bin:$$PATH" && \
         make setup && \
         make test-trigger
     entrypoint: /bin/sh

From ee15c995f052cea7bf495a7033f42ac81df077c1 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Fri, 4 Aug 2023 16:42:12 +0100
Subject: [PATCH 141/238] Update docstrings and code structure in
 upload_model.py

---
 .../src/vertex_components/upload_model.py     | 182 +++++++++---------
 .../tests/test_upload_model.py                |  34 ++--
 2 files changed, 101 insertions(+), 115 deletions(-)

diff --git a/components/vertex-components/src/vertex_components/upload_model.py b/components/vertex-components/src/vertex_components/upload_model.py
index fad15e3e..ce392496 100644
--- a/components/vertex-components/src/vertex_components/upload_model.py
+++ b/components/vertex-components/src/vertex_components/upload_model.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 
 from kfp.dsl import Dataset, Input, Metrics, Model, Output, component
-from google_cloud_pipeline_components.types import artifact_types
+from google_cloud_pipeline_components.types.artifact_types import VertexModel
 
 
 @component(
@@ -25,59 +25,61 @@
 )
 def upload_model(
     model: Input[Model],
-    serving_container_image: str,
-    vertex_model: Output[artifact_types.VertexModel],
-    project: str,
-    location: str,
+    test_dataset: Input[Dataset],
     model_evaluation: Input[Metrics],
+    vertex_model: Output[VertexModel],
+    project_id: str,
+    project_location: str,
+    model_name: str,
     eval_metric: str,
     eval_lower_is_better: bool,
-    model_name: str,
     pipeline_job_id: str,
-    test_dataset: Input[Dataset],
+    serving_container_image: str,
     evaluation_name: str = "Imported evaluation",
-    order_models_by: str = "create_time desc",
 ) -> None:
     """
     Args:
-        challenger (Model): Challenger model.
-        challenger_evaluation (str): Resource URI of challenger model evaluation e.g.
-            `projects/.../locations/.../models/.../evaluations/...`
-        parent_model (str): Resource URI of parent model.
-        eval_metric (str): Metric to compare champion and challenger on.
-        eval_lower_is_better (bool): Usually True for losses and
-            False for classification metrics.
+        model (Model): Input challenger model.
+        test_dataset (Dataset): Test dataset used for evaluating challenger model.
+        vertex_model (VertexModel): Output model uploaded to Vertex AI Model Registry.
+        model_evaluation (Metrics): Evaluation metrics of challenger model.
         project_id (str): project id of the Google Cloud project.
         project_location (str): location of the Google Cloud project.
-        model_alias (str): alias of the parent model.
+        pipeline_job_id (str):
+        model_name (str): Name of champion and challenger model in
+            Vertex AI Model Registry.
+        eval_metric (str): Metric name to compare champion and challenger on.
+        eval_lower_is_better (bool): Usually True for losses and
+            False for classification metrics.
+        serving_container_image (str): Container URI for serving the challenger
+            model.
+        evaluation_name (str): Name of evaluation results which are displayed in the
+            Vertex AI UI of the challenger model.
     """
 
     import json
     import logging
     import google.cloud.aiplatform as aip
     from google.protobuf.json_format import MessageToDict
+    from google.cloud.aiplatform_v1 import ModelEvaluation, ModelServiceClient
+    from google.protobuf.json_format import ParseDict
 
     def lookup_model(
-        order_models_by: str,
-        location: str,
-        project: str,
-        model_name: str,
+        project_id: str, project_location: str, model_name: str
     ) -> aip.Model:
-
+        """Look up model in model registry."""
         logging.info(f"listing models with display name {model_name}")
-        logging.info(f"choosing model by order ({order_models_by})")
         models = aip.Model.list(
             filter=f'display_name="{model_name}"',
-            order_by=order_models_by,
-            location=location,
-            project=project,
+            location=project_location,
+            project=project_id,
         )
         logging.info(f"found {len(models)} models")
 
         if len(models) == 0:
             logging.info(
                 f"No model found with name {model_name}"
-                + f"(project: {project} location: {location})"
+                + f"(project: {project_id} location: {project_location})"
             )
             return None
         elif len(models) == 1:
@@ -88,10 +90,9 @@ def lookup_model(
     def compare_models(
         champion_metrics: dict,
         challenger_metrics: dict,
-        eval_metric: str,
-        eval_lower_is_better,
+        eval_lower_is_better: bool,
     ) -> bool:
-
+        """Compare models by evaluating a primary metric."""
         logging.info(f"Comparing {eval_metric} of models")
         logging.debug(f"Champion metrics: {champion_metrics}")
         logging.debug(f"Challenger metrics: {challenger_metrics}")
@@ -103,29 +104,48 @@ def compare_models(
         challenger_wins = (
             (m_chall < m_champ) if eval_lower_is_better else (m_chall > m_champ)
         )
-
-        if challenger_wins:
-            logging.info("Challenger wins!")
-        else:
-            logging.info("Champion wins!")
+        logging.info(f"{'Challenger' if challenger_wins else 'Champion'} wins!")
 
         return challenger_wins
 
+    def upload_model_to_registry(
+        is_default_version: bool, parent_model_uri: str = None
+    ) -> Model:
+        """Upload model to registry."""
+        logging.info(f"Uploading model {model_name} (default: {is_default_version}")
+        uploaded_model = aip.Model.upload(
+            display_name=model_name,
+            artifact_uri=model.uri,
+            serving_container_image_uri=serving_container_image,
+            serving_container_predict_route="/predict",
+            serving_container_health_route="/health",
+            parent_model=parent_model_uri,
+            is_default_version=is_default_version,
+        )
+        logging.info(f"Uploaded model {uploaded_model}")
+
+        # Output google.VertexModel artifact
+        vertex_model.uri = (
+            f"https://{project_location}-aiplatform.googleapis.com/v1/"
+            f"{uploaded_model.versioned_resource_name}"
+        )
+        vertex_model.metadata["resourceName"] = uploaded_model.versioned_resource_name
+
+        return uploaded_model
+
     def import_evaluation(
         parsed_metrics: dict,
         challenger_model: aip.Model,
-        location: str,
-        evaluation_name: str = "Imported evaluation",
-    ):
-        from google.cloud.aiplatform_v1 import ModelEvaluation, ModelServiceClient
-        from google.protobuf.json_format import ParseDict
-
-        logging.info(f"Parsed metrics: {parsed_metrics}")
-
-        schema_template = (
-            "gs://google-cloud-aiplatform/schema/modelevaluation/%s_metrics_1.0.0.yaml"
+        project_location: str,
+        evaluation_name: str,
+    ) -> str:
+        """Import model evaluation."""
+        logging.info(f"Evaluation metrics: {parsed_metrics}")
+        problem_type = parsed_metrics.pop("problemType")
+        schema = (
+            f"gs://google-cloud-aiplatform/schema/modelevaluation/"
+            f"{problem_type}_metrics_1.0.0.yaml"
         )
-        schema = schema_template % parsed_metrics.pop("problemType")
         evaluation = {
             "displayName": evaluation_name,
             "metricsSchemaUri": schema,
@@ -138,80 +158,54 @@ def import_evaluation(
         }
 
         request = ParseDict(evaluation, ModelEvaluation()._pb)
-        logging.info(f"Request: {request}")
-
-        model_name = challenger_model.versioned_resource_name
-        logging.info(model_name)
-
+        logging.debug(f"Request: {request}")
+        challenger_name = challenger_model.versioned_resource_name
         client = ModelServiceClient(
-            client_options={"api_endpoint": location + "-aiplatform.googleapis.com"}
+            client_options={
+                "api_endpoint": project_location + "-aiplatform.googleapis.com"
+            }
         )
+        logging.info(f"Uploading model evaluation for {challenger_name}")
         response = client.import_model_evaluation(
-            parent=model_name,
+            parent=challenger_name,
             model_evaluation=request,
         )
-        logging.info(f"Response: {response}")
-        return (response.name,)
+        logging.debug(f"Response: {response}")
+        return response.name
 
     # Parse metrics to dict
     with open(model_evaluation.path, "r") as f:
-        metrics = json.load(f)
+        challenger_metrics = json.load(f)
 
     champion_model = lookup_model(
-        order_models_by=order_models_by,
-        location=location,
-        project=project,
-        model_name=model_name,
+        project_id=project_id, project_location=project_location, model_name=model_name
     )
 
-    if champion_model is not None:
+    challenger_wins = True
+    parent_model_uri = None
+    if champion_model is None:
+        logging.info("No champion model found, uploading new model.")
+    else:
         # Compare models
         logging.info(
             f"Model default version {champion_model.version_id} "
             "is being challenged by new model."
         )
         # Look up Vertex model evaluation for champion model
-        eval_champion = champion_model.get_model_evaluation()
-        champion_metrics = MessageToDict(eval_champion._gca_resource._pb)["metrics"]
-
-        # Take challenger metrics as input to this component
-        challenger_metrics = metrics
+        champion_eval = champion_model.get_model_evaluation()
+        champion_metrics = MessageToDict(champion_eval._gca_resource._pb)["metrics"]
 
         challenger_wins = compare_models(
             champion_metrics=champion_metrics,
             challenger_metrics=challenger_metrics,
-            eval_metric=eval_metric,
             eval_lower_is_better=eval_lower_is_better,
         )
+        parent_model_uri = champion_model.uri
 
-    else:
-        logging.info("No champion model found, uploading new model.")
-        challenger_wins = True
-
-    # Upload model to registry
-    uploaded_model = aip.Model.upload(
-        display_name=model_name,
-        artifact_uri=model.uri,
-        serving_container_image_uri=serving_container_image,
-        serving_container_predict_route="/predict",
-        serving_container_health_route="/healthz",
-        parent_model=(
-            champion_model.resource_name if champion_model is not None else None
-        ),
-        is_default_version=challenger_wins,
-    )
-
-    # Output google.VertexModel artifact
-    vertex_model.uri = (
-        f"https://{location}-aiplatform.googleapis.com/v1/"
-        f"{uploaded_model.versioned_resource_name}"
-    )
-    vertex_model.metadata["resourceName"] = uploaded_model.versioned_resource_name
-
-    # Import evaluation to model registry
+    model = upload_model_to_registry(challenger_wins, parent_model_uri)
     import_evaluation(
-        location=location,
-        parsed_metrics=metrics,
-        challenger_model=uploaded_model,
+        parsed_metrics=challenger_metrics,
+        challenger_model=model,
+        project_location=project_location,
         evaluation_name=evaluation_name,
     )
diff --git a/components/vertex-components/tests/test_upload_model.py b/components/vertex-components/tests/test_upload_model.py
index d62e0bc9..d1f60444 100644
--- a/components/vertex-components/tests/test_upload_model.py
+++ b/components/vertex-components/tests/test_upload_model.py
@@ -19,7 +19,6 @@
 from google.cloud.aiplatform_v1 import ModelEvaluation
 from google_cloud_pipeline_components.types.artifact_types import VertexModel
 
-
 import vertex_components
 
 upload_model = vertex_components.upload_model.python_func
@@ -61,14 +60,13 @@ def test_model_upload_no_champion(
     pipeline_job_id = "dummy-pipeline-job-id"
     test_dataset = Dataset(uri="test-dataset-uri")
     evaluation_name = "dummy evaluation name"
-    order_models_by = "dummy_order_models_by"
 
     upload_model(
         model=model,
         serving_container_image=serving_container_image,
         vertex_model=vertex_model,
-        project=project,
-        location=location,
+        project_id=project,
+        project_location=location,
         model_evaluation=model_evaluation,
         eval_metric=eval_metric,
         eval_lower_is_better=eval_lower_is_better,
@@ -76,13 +74,11 @@ def test_model_upload_no_champion(
         pipeline_job_id=pipeline_job_id,
         test_dataset=test_dataset,
         evaluation_name=evaluation_name,
-        order_models_by=order_models_by,
     )
 
     # Check that model lookup is performed, and no existing model is found
     mock_model_class.list.assert_called_once_with(
         filter=f'display_name="{model_name}"',
-        order_by=order_models_by,
         location=location,
         project=project,
     )
@@ -97,7 +93,7 @@ def test_model_upload_no_champion(
         artifact_uri="dummy-model-uri",
         serving_container_image_uri=serving_container_image,
         serving_container_predict_route="/predict",
-        serving_container_health_route="/healthz",
+        serving_container_health_route="/health",
         parent_model=None,
         is_default_version=True,
     )
@@ -135,6 +131,7 @@ def test_model_upload_challenger_wins(
     # create mock champion model
     mock_champion_model = mock.Mock()
     mock_champion_model.version_id = "123"
+    mock_champion_model.uri = "dummy-champion-model-uri"
     dummy_champion_eval = ModelEvaluation()
     dummy_champion_metrics = {
         "auc": 0.2,
@@ -174,14 +171,13 @@ def test_model_upload_challenger_wins(
     pipeline_job_id = "dummy-pipeline-job-id"
     test_dataset = Dataset(uri="test-dataset-uri")
     evaluation_name = "dummy evaluation name"
-    order_models_by = "dummy_order_models_by"
 
     upload_model(
         model=model,
         serving_container_image=serving_container_image,
         vertex_model=vertex_model,
-        project=project,
-        location=location,
+        project_id=project,
+        project_location=location,
         model_evaluation=model_evaluation,
         eval_metric=eval_metric,
         eval_lower_is_better=eval_lower_is_better,
@@ -189,13 +185,11 @@ def test_model_upload_challenger_wins(
         pipeline_job_id=pipeline_job_id,
         test_dataset=test_dataset,
         evaluation_name=evaluation_name,
-        order_models_by=order_models_by,
     )
 
     # Check that model lookup is performed, and no existing model is found
     mock_model_class.list.assert_called_once_with(
         filter=f'display_name="{model_name}"',
-        order_by=order_models_by,
         location=location,
         project=project,
     )
@@ -210,8 +204,8 @@ def test_model_upload_challenger_wins(
         artifact_uri="dummy-model-uri",
         serving_container_image_uri=serving_container_image,
         serving_container_predict_route="/predict",
-        serving_container_health_route="/healthz",
-        parent_model=mock_champion_model.resource_name,
+        serving_container_health_route="/health",
+        parent_model=mock_champion_model.uri,
         is_default_version=True,
     )
 
@@ -248,6 +242,7 @@ def test_model_upload_champion_wins(
     # Create mock champion model
     mock_champion_model = mock.Mock()
     mock_champion_model.version_id = "123"
+    mock_champion_model.uri = "dummy-champion-model-uri"
     dummy_champion_eval = ModelEvaluation()
     dummy_champion_metrics = {
         "auc": 0.8,
@@ -287,14 +282,13 @@ def test_model_upload_champion_wins(
     pipeline_job_id = "dummy-pipeline-job-id"
     test_dataset = Dataset(uri="test-dataset-uri")
     evaluation_name = "dummy evaluation name"
-    order_models_by = "dummy_order_models_by"
 
     upload_model(
         model=model,
         serving_container_image=serving_container_image,
         vertex_model=vertex_model,
-        project=project,
-        location=location,
+        project_id=project,
+        project_location=location,
         model_evaluation=model_evaluation,
         eval_metric=eval_metric,
         eval_lower_is_better=eval_lower_is_better,
@@ -302,13 +296,11 @@ def test_model_upload_champion_wins(
         pipeline_job_id=pipeline_job_id,
         test_dataset=test_dataset,
         evaluation_name=evaluation_name,
-        order_models_by=order_models_by,
     )
 
     # Check that model lookup is performed, and no existing model is found
     mock_model_class.list.assert_called_once_with(
         filter=f'display_name="{model_name}"',
-        order_by=order_models_by,
         location=location,
         project=project,
     )
@@ -323,8 +315,8 @@ def test_model_upload_champion_wins(
         artifact_uri="dummy-model-uri",
         serving_container_image_uri=serving_container_image,
         serving_container_predict_route="/predict",
-        serving_container_health_route="/healthz",
-        parent_model=mock_champion_model.resource_name,
+        serving_container_health_route="/health",
+        parent_model=mock_champion_model.uri,
         is_default_version=False,
     )
 

From 0ee7152da0b89e356d5673f1c1ba29220469f09f Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Fri, 4 Aug 2023 16:49:04 +0100
Subject: [PATCH 142/238] Update training/pipeline.py with renamed parameters

---
 pipelines/src/pipelines/training/pipeline.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/pipelines/src/pipelines/training/pipeline.py b/pipelines/src/pipelines/training/pipeline.py
index a2906e44..1da22b4b 100644
--- a/pipelines/src/pipelines/training/pipeline.py
+++ b/pipelines/src/pipelines/training/pipeline.py
@@ -194,14 +194,14 @@ def pipeline(
     ).set_display_name("Train model")
 
     upload_model_op = upload_model(
-        project=project_id,
-        location=project_location,
+        project_id=project_id,
+        project_location=project_location,
+        model=train_model.outputs["model"],
         model_evaluation=train_model.outputs["metrics"],
+        test_dataset=test_dataset,
         eval_metric=primary_metric,
         eval_lower_is_better=True,
-        model=train_model.outputs["model"],
         serving_container_image=SERVING_IMAGE,
         model_name=model_name,
         pipeline_job_id="{{$.pipeline_job_name}}",
-        test_dataset=test_dataset,
     ).set_display_name("Upload model")

From c868bd47ecf5e7b0a17478a6822eda88c4224ec7 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Fri, 4 Aug 2023 17:10:43 +0100
Subject: [PATCH 143/238] Fix upload_model.py

---
 .../vertex-components/src/vertex_components/upload_model.py | 2 +-
 components/vertex-components/tests/test_upload_model.py     | 6 ++----
 2 files changed, 3 insertions(+), 5 deletions(-)

diff --git a/components/vertex-components/src/vertex_components/upload_model.py b/components/vertex-components/src/vertex_components/upload_model.py
index ce392496..be94a9ff 100644
--- a/components/vertex-components/src/vertex_components/upload_model.py
+++ b/components/vertex-components/src/vertex_components/upload_model.py
@@ -200,7 +200,7 @@ def import_evaluation(
             challenger_metrics=challenger_metrics,
             eval_lower_is_better=eval_lower_is_better,
         )
-        parent_model_uri = champion_model.uri
+        parent_model_uri = champion_model.resource_name
 
     model = upload_model_to_registry(challenger_wins, parent_model_uri)
     import_evaluation(
diff --git a/components/vertex-components/tests/test_upload_model.py b/components/vertex-components/tests/test_upload_model.py
index d1f60444..a9ef4258 100644
--- a/components/vertex-components/tests/test_upload_model.py
+++ b/components/vertex-components/tests/test_upload_model.py
@@ -131,7 +131,6 @@ def test_model_upload_challenger_wins(
     # create mock champion model
     mock_champion_model = mock.Mock()
     mock_champion_model.version_id = "123"
-    mock_champion_model.uri = "dummy-champion-model-uri"
     dummy_champion_eval = ModelEvaluation()
     dummy_champion_metrics = {
         "auc": 0.2,
@@ -205,7 +204,7 @@ def test_model_upload_challenger_wins(
         serving_container_image_uri=serving_container_image,
         serving_container_predict_route="/predict",
         serving_container_health_route="/health",
-        parent_model=mock_champion_model.uri,
+        parent_model=mock_champion_model.resource_name,
         is_default_version=True,
     )
 
@@ -242,7 +241,6 @@ def test_model_upload_champion_wins(
     # Create mock champion model
     mock_champion_model = mock.Mock()
     mock_champion_model.version_id = "123"
-    mock_champion_model.uri = "dummy-champion-model-uri"
     dummy_champion_eval = ModelEvaluation()
     dummy_champion_metrics = {
         "auc": 0.8,
@@ -316,7 +314,7 @@ def test_model_upload_champion_wins(
         serving_container_image_uri=serving_container_image,
         serving_container_predict_route="/predict",
         serving_container_health_route="/health",
-        parent_model=mock_champion_model.uri,
+        parent_model=mock_champion_model.resource_name,
         is_default_version=False,
     )
 

From 92467895f9685b0a3a44f1644a0b5c0b9371f506 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 7 Aug 2023 10:18:27 +0100
Subject: [PATCH 144/238] fix: disable incorrect caching

---
 pipelines/src/pipelines/prediction/pipeline.py | 13 ++++++++++---
 pipelines/src/pipelines/training/pipeline.py   | 12 +++++++++---
 2 files changed, 19 insertions(+), 6 deletions(-)

diff --git a/pipelines/src/pipelines/prediction/pipeline.py b/pipelines/src/pipelines/prediction/pipeline.py
index cf038d70..a97713a2 100644
--- a/pipelines/src/pipelines/prediction/pipeline.py
+++ b/pipelines/src/pipelines/prediction/pipeline.py
@@ -99,9 +99,15 @@ def pipeline(
         filter_start_value=timestamp,
     )
 
-    preprocessing = BigqueryQueryJobOp(
-        project=project_id, location=dataset_location, query=preprocessing_query
-    ).set_display_name("Ingest data")
+    preprocessing = (
+        BigqueryQueryJobOp(
+            project=project_id,
+            location=dataset_location,
+            query=preprocessing_query,
+        )
+        .set_caching_options(False)
+        .set_display_name("Ingest data")
+    )
 
     # lookup champion model
     champion_model = (
@@ -141,6 +147,7 @@ def pipeline(
             monitoring_alert_email_addresses=monitoring_alert_email_addresses,
             monitoring_skew_config=monitoring_skew_config,
         )
+        .set_caching_options(False)
         .after(preprocessing)
         .set_display_name("Batch prediction job")
     )
diff --git a/pipelines/src/pipelines/training/pipeline.py b/pipelines/src/pipelines/training/pipeline.py
index 1da22b4b..be5861f3 100644
--- a/pipelines/src/pipelines/training/pipeline.py
+++ b/pipelines/src/pipelines/training/pipeline.py
@@ -142,9 +142,15 @@ def pipeline(
         test_table=test_table,
     )
 
-    preprocessing = BigqueryQueryJobOp(
-        project=project_id, location=dataset_location, query=preprocessing_query
-    ).set_display_name("Ingest & preprocess data")
+    preprocessing = (
+        BigqueryQueryJobOp(
+            project=project_id,
+            location=dataset_location,
+            query=preprocessing_query,
+        )
+        .set_caching_options(False)
+        .set_display_name("Ingest & preprocess data")
+    )
 
     # data extraction to gcs
 

From 627143ff96869a3aa2a25e89d63afc098c976917 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 7 Aug 2023 23:06:22 +0100
Subject: [PATCH 145/238] docs: update PR template

---
 .github/pull_request_template.md | 9 +++------
 1 file changed, 3 insertions(+), 6 deletions(-)

diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md
index b365839c..033da80c 100644
--- a/.github/pull_request_template.md
+++ b/.github/pull_request_template.md
@@ -1,5 +1,5 @@
 <!-- 
-Copyright 2022 Google LLC
+Copyright 2023 Google LLC
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -24,10 +24,7 @@ Please explain how you have tested the new changes.
 # Checklist
 
 - [ ] I have commented my code, particularly in hard-to-understand areas
-- [ ] I have successfully run the E2E tests, and have included the links to the pipeline runs below
 - [ ] I have added tests that prove my fix is effective or that my feature works
-- [ ] New and existing unit tests pass locally with my changes
+- [ ] New and existing unit tests pass locally with my changes (`make test-trigger` and `make test-all-components`)
+- [ ] I have successfully run the E2E tests
 - [ ] I have updated any relevant documentation to reflect my changes
-- [ ] I have assigned a reviewer and messaged them
-
-# Pipeline run links:

From 0b226cd87d257730c96408cb8e3d4ca4d7cb7f58 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 7 Aug 2023 18:06:26 +0100
Subject: [PATCH 146/238] refactor: pipeline trigger code + cloud function

---
 Makefile                                      |  10 +-
 README.md                                     |   4 +-
 cloudbuild/README.md                          |   2 +-
 cloudbuild/pr-checks.yaml                     |   1 +
 cloudbuild/trigger-tests.yaml                 |  14 +-
 docs/PRODUCTION.md                            |   5 +-
 pipelines/src/pipelines/trigger/README.md     |  64 -----
 pipelines/src/pipelines/trigger/__main__.py   |   5 -
 pipelines/src/pipelines/trigger/main.py       | 219 ----------------
 .../src/pipelines/utils/trigger_pipeline.py   |  87 +++++++
 .../src/pipelines/utils/upload_pipeline.py    |  41 ++-
 pipelines/tests/e2e/test_e2e.py               |  20 +-
 pipelines/tests/prediction/test_e2e.py        |   5 +-
 pipelines/tests/training/test_e2e.py          |   3 +-
 pipelines/tests/trigger/test_main.py          | 244 ------------------
 .../tests/utils/test_trigger_pipeline.py      |  81 ++++++
 pipelines/tests/utils/test_upload_pipeline.py |  76 ++++++
 terraform/envs/dev/main.tf                    |   2 +-
 terraform/envs/prod/main.tf                   |   2 +-
 terraform/envs/test/main.tf                   |   2 +-
 .../modules/cloudfunction/.python-version     |   1 +
 terraform/modules/cloudfunction/README.md     |  28 ++
 terraform/modules/cloudfunction/function.tf   |  12 +-
 terraform/modules/cloudfunction/src/main.py   |  78 ++++++
 .../cloudfunction/src/requirements-dev.txt    |  15 ++
 .../cloudfunction/src}/requirements.txt       |   0
 .../modules/cloudfunction/test/test_main.py   |  93 +++++++
 terraform/modules/cloudfunction/variables.tf  |   5 -
 terraform/modules/scheduled_pipelines/main.tf |  11 +-
 .../scheduled_jobs.auto.tfvars.example        |   2 -
 terraform/modules/vertex_deployment/main.tf   |   1 -
 31 files changed, 535 insertions(+), 598 deletions(-)
 delete mode 100644 pipelines/src/pipelines/trigger/README.md
 delete mode 100644 pipelines/src/pipelines/trigger/__main__.py
 delete mode 100644 pipelines/src/pipelines/trigger/main.py
 create mode 100644 pipelines/src/pipelines/utils/trigger_pipeline.py
 delete mode 100644 pipelines/tests/trigger/test_main.py
 create mode 100644 pipelines/tests/utils/test_trigger_pipeline.py
 create mode 100644 pipelines/tests/utils/test_upload_pipeline.py
 create mode 100644 terraform/modules/cloudfunction/.python-version
 create mode 100644 terraform/modules/cloudfunction/README.md
 create mode 100644 terraform/modules/cloudfunction/src/main.py
 create mode 100644 terraform/modules/cloudfunction/src/requirements-dev.txt
 rename {pipelines/src/pipelines/trigger => terraform/modules/cloudfunction/src}/requirements.txt (100%)
 create mode 100644 terraform/modules/cloudfunction/test/test_main.py

diff --git a/Makefile b/Makefile
index 13020ced..0db5ca45 100644
--- a/Makefile
+++ b/Makefile
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -27,9 +27,9 @@ setup: ## Set up local environment for Python development on pipelines
 	@cd pipelines && \
 	poetry install --with dev
 
-test-trigger: ## Runs unit tests for the pipeline trigger code
+test-utils: ## Runs unit tests for the util scripts
 	@cd pipelines && \
-	poetry run python -m pytest tests/trigger
+	poetry run python -m pytest tests/utils
 
 compile-pipeline: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
 	@cd pipelines/src && \
@@ -72,11 +72,11 @@ test-all-components-coverage: ## Run tests with coverage
 run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
 	@ $(MAKE) compile-pipeline && \
 	cd pipelines/src && \
-	poetry run python -m pipelines.trigger --template_path=pipelines/${pipeline}/pipeline.yaml --enable_caching=$(enable_pipeline_caching)
+	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline}
 
 e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour).
 	@ cd pipelines && \
-	poetry run pytest --log-cli-level=INFO tests/$(pipeline) --enable_caching=$(enable_pipeline_caching)
+	poetry run pytest --log-cli-level=INFO tests/$(pipeline)
 
 env ?= dev
 deploy-infra: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
diff --git a/README.md b/README.md
index 09022920..59169d5a 100644
--- a/README.md
+++ b/README.md
@@ -214,10 +214,10 @@ To run end-to-end tests of a single pipeline, you can use:
 make e2e-tests pipeline=<training|prediction> [ enable_caching=<true|false> ]
 ```
 
-There are also unit tests for the pipeline triggering code/Cloud Function. To run them on your local machine:
+There are also unit tests for the utility scripts in [pipelines/src/pipelines/utils](/pipelines/src/pipelines/utils/). To run them on your local machine:
 
 ```
-make test-trigger
+make test-utils
 ```
 
 ## Customize pipelines
diff --git a/cloudbuild/README.md b/cloudbuild/README.md
index a1c90943..e3a5bedd 100644
--- a/cloudbuild/README.md
+++ b/cloudbuild/README.md
@@ -21,7 +21,7 @@ limitations under the License.
 There are six CI/CD pipelines
 
 1. `pr-checks.yaml` - runs pre-commit checks and unit tests on the custom KFP components, and checks that the ML pipelines (training and prediction) can compile.
-1. `trigger-tests.yaml` - runs unit tests for the pipeline trigger script / Cloud Function located in [pipelines/src/pipelines/trigger](/pipelines/src/pipelines/trigger/). If you don't need to change this code, you can ignore this CI/CD pipeline.
+1. `trigger-tests.yaml` - runs unit tests for the Cloud Function located in [terraform/modules/cloudfunction](/terraform/modules/cloudfunction/). If you don't need to change this code, you can ignore this CI/CD pipeline.
 1. `e2e-test.yaml` - runs end-to-end tests of the training and prediction pipeline.
 1. `release.yaml` - compiles training and prediction pipelines, then copies the compiled pipelines to the chosen GCS destination (versioned by git tag).
 1. `terraform-plan.yaml` - Checks the Terraform configuration under `terraform/envs/<env>` (e.g. `terraform/envs/test`), and produces a summary of any proposed changes that will be applied on merge to the main branch.
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index a7819caa..4b1b73e7 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -28,6 +28,7 @@ steps:
         git init && \
         git add . && \
         make pre-commit && \
+        make test-utils && \
         make compile-pipeline pipeline=training && \
         make compile-pipeline pipeline=prediction && \
         make setup-all-components && \
diff --git a/cloudbuild/trigger-tests.yaml b/cloudbuild/trigger-tests.yaml
index 4778396c..07073738 100644
--- a/cloudbuild/trigger-tests.yaml
+++ b/cloudbuild/trigger-tests.yaml
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -14,14 +14,16 @@
 ---
 steps:
   - name: 'python:3.9'
+    dir: /workspace/terraform/modules/cloudfunction
+    entrypoint: /bin/sh
     args:
       - '-c'
       - |
-        curl -sSL https://install.python-poetry.org | python3 - && \
-        export PATH="/builder/home/.local/bin:$$PATH" && \
-        make setup && \
-        make test-trigger
-    entrypoint: /bin/sh
+        pip install -r src/requirements.txt && \
+        pip install -r src/requirements-dev.txt && \
+        pytest
+    env:
+      - PYTHONPATH=.
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/docs/PRODUCTION.md b/docs/PRODUCTION.md
index 398a6907..a14db1fd 100644
--- a/docs/PRODUCTION.md
+++ b/docs/PRODUCTION.md
@@ -80,10 +80,8 @@ Create a new branch off the main/master branch e.g. `git checkout -b test-env-sc
 
 ```
 cloud_schedulers_config = {
-  # Uncomment and amend as required
 
   xgboost_training = {
-    name         = "xgboost-training-pipeline-trigger"
     description  = "Trigger my training pipeline in Vertex"
     schedule     = "0 0 1 * *"
     time_zone    = "UTC"
@@ -102,8 +100,7 @@ cloud_schedulers_config = {
     },
   },
 
-    xgboost_prediction = {
-    name         = "xgboost-prediction-pipeline-trigger"
+  xgboost_prediction = {
     description  = "Trigger my prediction pipeline in Vertex"
     schedule     = "0 0 * * *"
     time_zone    = "UTC"
diff --git a/pipelines/src/pipelines/trigger/README.md b/pipelines/src/pipelines/trigger/README.md
deleted file mode 100644
index 215b0caf..00000000
--- a/pipelines/src/pipelines/trigger/README.md
+++ /dev/null
@@ -1,64 +0,0 @@
-<!-- 
-Copyright 2022 Google LLC
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    https://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
- -->
-# Trigger pipeline runs in the sandbox environment
-
-The simplest way to trigger a pipeline run in the sandbox environment is to use the following make command:
-```
-make run pipeline=<training|prediction> [ enable_caching=<true|false> ]
-```
-This command compiles the pipeline, copies assets to GCS, and then triggers the pipeline. It relies on several environment variables which you must specify beforehand in `env.sh`. These variables are:
-
-- `VERTEX_PROJECT_ID`: your project id
-- `VERTEX_LOCATION`: your project location
-- `VERTEX_PIPELINE_ROOT`: URI for root directory
-- `VERTEX_SA_EMAIL`: service account
-- `VERTEX_CMEK_IDENTIFIER`: customer-managed encryption key (can be `""` or `None`)
-- `VERTEX_NETWORK`: private network (can be `""` or `None`)
-
-Before you run the pipeline, if you have made any changes to pipeline components, make sure to re-compile the pipeline components to their YAML format with:
-
-```bash
-make compile-components GROUP=<component group e.g. vertex-components>
-```
-
-Or to re-compile all pipeline components to YAML:
-```bash
-make compile-all-components
-```
-
-### Deploy as a Cloud Function
-
-This directory can also be deployed as a Cloud Function to trigger pipeline runs from a Pub/Sub message. The format of the Pub/Sub message is as follows:
-
-#### Pub/Sub attributes
-
-- `template_path` - the GCS path to the compiled KFP pipeline definition (JSON)
-- `enable_caching` (optional) - True or False. This can be used to override the default Vertex Pipelines caching behaviour.
-
-#### Pub/Sub data
-
-The data field contains the pipeline input parameters as a JSON string, encoded using base64 encoding.
-
-**NB**: Please note that the Cloud Function service account will need permission to:
-- read from the bucket where the compiled pipeline is stored
-- have "service account user" permission on the service account being used to run the Vertex pipelines
-- subscribe to the pub/sub topic)
-
-## Testing the trigger
-To run the unit tests developed for the trigger code, use the following make command:
-```
-make test-trigger
-```
diff --git a/pipelines/src/pipelines/trigger/__main__.py b/pipelines/src/pipelines/trigger/__main__.py
deleted file mode 100644
index 93b22bb0..00000000
--- a/pipelines/src/pipelines/trigger/__main__.py
+++ /dev/null
@@ -1,5 +0,0 @@
-from .main import sandbox_run
-
-
-if __name__ == "__main__":
-    sandbox_run()
diff --git a/pipelines/src/pipelines/trigger/main.py b/pipelines/src/pipelines/trigger/main.py
deleted file mode 100644
index fc8263fc..00000000
--- a/pipelines/src/pipelines/trigger/main.py
+++ /dev/null
@@ -1,219 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import argparse
-import base64
-import json
-import os
-import distutils.util
-from typing import Optional, List
-
-from google.cloud import aiplatform
-
-
-def cf_handler(event, context) -> aiplatform.PipelineJob:
-    """Handle the Pub/Sub message and make the call to trigger_pipeline_from_payload()
-    to trigger the ML pipeline on Vertex. Returns the PipelineJob object.
-
-    Args:
-         event (dict):  The dictionary with data specific to this type of
-                        event. The `@type` field maps to
-                         `type.googleapis.com/google.pubsub.v1.PubsubMessage`.
-                        The `data` field maps to the PubsubMessage data
-                        in a base64-encoded string. The `attributes` field maps
-                        to the PubsubMessage attributes if any is present.
-         context (google.cloud.functions.Context): Metadata of triggering event
-                        including `event_id` which maps to the PubsubMessage
-                        messageId, `timestamp` which maps to the PubsubMessage
-                        publishTime, `event_type` which maps to
-                        `google.pubsub.topic.publish`, and `resource` which is
-                        a dictionary that describes the service API endpoint
-                        pubsub.googleapis.com, the triggering topic's name, and
-                        the triggering event type
-                        `type.googleapis.com/google.pubsub.v1.PubsubMessage`.
-    Returns:
-        aiplatform.PipelineJob
-    """
-
-    # take event["data"], base64-decode it and JSON decode to dict
-    event["data"] = base64.b64decode(event["data"]).decode("utf-8")
-    event["data"] = json.loads(event["data"])
-
-    return trigger_pipeline_from_payload(event)
-
-
-def trigger_pipeline_from_payload(payload: dict) -> aiplatform.PipelineJob:
-    """Triggers a pipeline run from a payload dict, JSON pipeline definition,
-    and env variables.
-    Args:
-        payload (dict): payload containing attributes and data.
-        template_path (str): File path (local or GCS) of compiled pipeline definition.
-    """
-
-    payload = convert_payload(payload)
-    env = get_env()
-
-    return trigger_pipeline(
-        project_id=env["project_id"],
-        location=env["location"],
-        template_path=payload["attributes"]["template_path"],
-        parameter_values=payload["data"],
-        pipeline_root=env["pipeline_root"],
-        service_account=env["service_account"],
-        encryption_spec_key_name=env["encryption_spec_key_name"],
-        network=env["network"],
-        enable_caching=payload["attributes"]["enable_caching"],
-    )
-
-
-def trigger_pipeline(
-    project_id: str,
-    location: str,
-    template_path: str,
-    pipeline_root: str,
-    service_account: str,
-    parameter_values: dict = {},
-    encryption_spec_key_name: Optional[str] = None,
-    network: Optional[str] = None,
-    enable_caching: Optional[bool] = None,
-) -> aiplatform.PipelineJob:
-    """Trigger the Vertex Pipeline run.
-    Args:
-        project_id (str): GCP Project ID in which to run the Vertex Pipeline
-        location (str): GCP region in which to run the Vertex Pipeline
-        template_path (str): local or GCS path containing the (JSON) KFP
-        pipeline definition
-        pipeline_root (str): GCS path to use as the pipeline root (for passing
-         metadata/artifacts within the pipeline)
-        parameter_values (dict): dictionary containing the input parameters
-        for the KFP pipeline
-        service_account (str): email address of the service account that
-        should be used to execute the ML pipeline in Vertex
-        encryption_spec_key_name (Optional[str]): Cloud KMS resource ID
-        of the customer managed encryption key (CMEK) that will protect the job
-        network (Optional[str]): name of Compute Engine network to
-        which the job should be visible
-        enable_caching (Optional[bool]): Whether to enable caching of pipeline
-        component results if component+inputs are the same. Defaults to None
-        (enable caching, except where disabled at a component level)
-    """
-
-    # Initialise API client
-    aiplatform.init(project=project_id, location=location)
-
-    # Instantiate PipelineJob object
-    pl = aiplatform.pipeline_jobs.PipelineJob(
-        # Display name is required but seemingly not used
-        # see
-        # https://github.com/googleapis/python-aiplatform/blob/9dcf6fb0bc8144d819938a97edf4339fe6f2e1e6/google/cloud/aiplatform/pipeline_jobs.py#L260 # noqa
-        display_name=template_path,
-        enable_caching=enable_caching,
-        template_path=template_path,
-        parameter_values=parameter_values,
-        pipeline_root=pipeline_root,
-        encryption_spec_key_name=encryption_spec_key_name,
-    )
-
-    # Execute pipeline in Vertex
-    pl.submit(
-        service_account=service_account,
-        network=network,
-    )
-
-    return pl
-
-
-def convert_payload(payload: dict) -> dict:
-    """
-    Processes the payload dictionary.
-    Converts enable_caching and adds their defaults if they are missing.
-
-    Args:
-        payload (dict): Cloud Function event payload,
-        or the contents of a payload JSON file
-    """
-
-    # make a copy of the payload so we are not modifying the original
-    payload = payload.copy()
-
-    # if payload["data"] is missing, add it as empty dict
-    payload["data"] = payload.get("data", {})
-
-    # if enable_caching value is present and not None, convert from str to bool
-    # otherwise, it needs to be None
-    if payload["attributes"].get("enable_caching") is not None:
-        payload["attributes"]["enable_caching"] = bool(
-            distutils.util.strtobool(payload["attributes"]["enable_caching"])
-        )
-    else:
-        payload["attributes"]["enable_caching"] = None
-
-    return payload
-
-
-def get_env() -> dict:
-    """Get the necessary environment variables for pipeline runs,
-    and return them as a dictionary.
-    """
-
-    project_id = os.environ["VERTEX_PROJECT_ID"]
-    location = os.environ["VERTEX_LOCATION"]
-    pipeline_root = os.environ["VERTEX_PIPELINE_ROOT"]
-    service_account = os.environ["VERTEX_SA_EMAIL"]
-    # For CMEK and network, we want an empty string to become None, so we add "or None"
-    encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER") or None
-    network = os.environ.get("VERTEX_NETWORK") or None
-
-    return {
-        "project_id": project_id,
-        "location": location,
-        "pipeline_root": pipeline_root,
-        "service_account": service_account,
-        "encryption_spec_key_name": encryption_spec_key_name,
-        "network": network,
-    }
-
-
-def sandbox_run(args: List[str] = None) -> aiplatform.PipelineJob:
-    """Trigger a Vertex Pipeline run from a (local) compiled pipeline definition.
-    Returns the PipelineJob object of the triggered pipeline run.
-    Usage: python main.py --template_path=pipeline.json --enable_caching=true
-    """
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        "--template_path", help="Path to the compiled pipeline (JSON)", type=str
-    )
-    parser.add_argument("--enable_caching", type=str, default=None)
-
-    # Get commandline args
-    args = parser.parse_args(args)
-
-    # If empty value for enable_caching provided on commandline default to None
-    if args.enable_caching == "":
-        args.enable_caching = None
-
-    payload = {
-        "attributes": {
-            "template_path": args.template_path,
-            "enable_caching": args.enable_caching,
-        }
-        # "data" omitted as pipeline params are taken from the default args
-        # in compiled JSON pipeline
-    }
-
-    return trigger_pipeline_from_payload(payload)
-
-
-if __name__ == "__main__":
-    sandbox_run()
diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
new file mode 100644
index 00000000..3984e40b
--- /dev/null
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -0,0 +1,87 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import argparse
+import os
+from distutils.util import strtobool
+from google.cloud import aiplatform
+
+
+def trigger_pipeline(
+    template_path: str,
+    display_name: str,
+) -> aiplatform.PipelineJob:
+    """Trigger a Vertex Pipeline run from a (local) compiled pipeline definition.
+
+    Args:
+        template_path (str): file path to the compiled YAML pipeline
+        display_name (str): Display name to use for the PipelineJob
+
+    Returns:
+        aiplatform.PipelineJob: the Vertex PipelineJob object
+    """
+    project_id = os.environ["VERTEX_PROJECT_ID"]
+    location = os.environ["VERTEX_LOCATION"]
+    pipeline_root = os.environ["VERTEX_PIPELINE_ROOT"]
+    service_account = os.environ["VERTEX_SA_EMAIL"]
+
+    enable_caching = os.environ.get("enable_pipeline_caching", None)
+    if enable_caching:
+        enable_caching = bool(strtobool(enable_caching))
+
+    # For below options, we want an empty string to become None, so we add "or None"
+    encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER") or None
+    network = os.environ.get("VERTEX_NETWORK") or None
+
+    # Instantiate PipelineJob object
+    pl = aiplatform.PipelineJob(
+        project=project_id,
+        location=location,
+        display_name=display_name,
+        enable_caching=enable_caching,
+        template_path=template_path,
+        pipeline_root=pipeline_root,
+        encryption_spec_key_name=encryption_spec_key_name,
+    )
+
+    # Execute pipeline in Vertex
+    pl.submit(
+        service_account=service_account,
+        network=network,
+    )
+
+    return pl
+
+
+if __name__ == "__main__":
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--template_path",
+        help="Path to the compiled pipeline (YAML)",
+        type=str,
+    )
+    parser.add_argument(
+        "--display_name",
+        help="Display name for the PipelineJob",
+        type=str,
+    )
+
+    # Get commandline args
+    args = parser.parse_args()
+
+    trigger_pipeline(
+        template_path=args.template_path,
+        display_name=args.display_name,
+    )
diff --git a/pipelines/src/pipelines/utils/upload_pipeline.py b/pipelines/src/pipelines/utils/upload_pipeline.py
index b9524c51..358d66de 100644
--- a/pipelines/src/pipelines/utils/upload_pipeline.py
+++ b/pipelines/src/pipelines/utils/upload_pipeline.py
@@ -12,21 +12,46 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import argparse
+from typing import List
 from kfp.registry import RegistryClient
 
-if __name__ == "__main__":
 
+def upload_pipeline(host: str, file_name: str, tags: List[str]) -> tuple[str, str]:
+    """Upload a compiled YAML pipeline to Artifact Registry
+
+    Args:
+        host (str): URL of the Artifact Registry repository
+        file_name (str): File path to the compiled YAML pipeline
+        tags (List[str]): List of tags to use for the uploaded pipeline
+
+    Returns:
+        A tuple of the package name and the version.
+    """
+
+    client = RegistryClient(
+        host=host,
+    )
+
+    return client.upload_pipeline(
+        file_name=file_name,
+        tags=tags,
+    )
+
+
+def main(args: List[str] = None):
+    """CLI entrypoint for the upload_pipeline.py script"""
     parser = argparse.ArgumentParser()
     parser.add_argument("--dest", type=str, required=True)
     parser.add_argument("--yaml", type=str, required=True)
     parser.add_argument("--tag", type=str, action="append")
-    args = parser.parse_args()
+    parsed_args = parser.parse_args(args)
 
-    client = RegistryClient(
-        host=args.dest,
+    upload_pipeline(
+        host=parsed_args.dest,
+        file_name=parsed_args.yaml,
+        tags=parsed_args.tag,
     )
 
-    templateName, versionName = client.upload_pipeline(
-        file_name=args.yaml,
-        tags=args.tag,
-    )
+
+if __name__ == "__main__":
+    main()
diff --git a/pipelines/tests/e2e/test_e2e.py b/pipelines/tests/e2e/test_e2e.py
index 0ff9a25b..e9b84525 100644
--- a/pipelines/tests/e2e/test_e2e.py
+++ b/pipelines/tests/e2e/test_e2e.py
@@ -20,7 +20,7 @@
 from kfp import compiler
 from kfp.components import BaseComponent
 
-from pipelines.trigger.main import trigger_pipeline_from_payload
+from pipelines.utils.trigger_pipeline import trigger_pipeline
 
 project_id = os.environ["VERTEX_PROJECT_ID"]
 project_location = os.environ["VERTEX_LOCATION"]
@@ -153,7 +153,6 @@ def test_batch_prediction_job_uri(
 def pipeline_e2e_test(
     pipeline_func: BaseComponent,
     common_tasks: dict,
-    enable_caching: bool = None,
     **kwargs: dict,
 ):
     """
@@ -168,24 +167,19 @@ def pipeline_e2e_test(
         **kwargs (dict): conditional tasks groups in dictionary
     """
 
-    pipeline_yaml = f"{pipeline_func.name}.yaml"
+    template_path = f"{pipeline_func.name}.yaml"
 
     compiler.Compiler().compile(
         pipeline_func=pipeline_func,
-        package_path=pipeline_yaml,
+        package_path=template_path,
         type_check=False,
     )
 
-    # If empty value for enable_caching provided on commandline default to None
-    if enable_caching == "":
-        enable_caching = None
-
-    payload = {
-        "attributes": {"template_path": pipeline_yaml, "enable_caching": enable_caching}
-    }
-
     try:
-        pl = trigger_pipeline_from_payload(payload)
+        pl = trigger_pipeline(
+            template_path=template_path,
+            display_name=f"{pipeline_func.name}-E2E-test",
+        )
 
         pl.wait()
 
diff --git a/pipelines/tests/prediction/test_e2e.py b/pipelines/tests/prediction/test_e2e.py
index 4dd903cd..e1fa5f1f 100644
--- a/pipelines/tests/prediction/test_e2e.py
+++ b/pipelines/tests/prediction/test_e2e.py
@@ -16,7 +16,7 @@
 from tests.e2e.test_e2e import pipeline_e2e_test
 
 
-def test_pipeline_run(enable_caching) -> None:
+def test_pipeline_run() -> None:
     """
     Tests if pipeline is run successfully
     Triggers pipeline synchronously.
@@ -31,11 +31,8 @@ def test_pipeline_run(enable_caching) -> None:
         None
     """
 
-    pipeline_json = "prediction.json"
-
     # tasks (components) and outputs for tasks which occur unconditionally
     pipeline_e2e_test(
         pipeline,
-        enable_caching=enable_caching,
         common_tasks={},
     )
diff --git a/pipelines/tests/training/test_e2e.py b/pipelines/tests/training/test_e2e.py
index 9886c6db..72efa4fa 100644
--- a/pipelines/tests/training/test_e2e.py
+++ b/pipelines/tests/training/test_e2e.py
@@ -16,7 +16,7 @@
 from tests.e2e.test_e2e import pipeline_e2e_test
 
 
-def test_pipeline_run(enable_caching) -> None:
+def test_pipeline_run() -> None:
     """
     Tests if pipeline is run successfully
     Triggers pipeline synchronously.
@@ -32,6 +32,5 @@ def test_pipeline_run(enable_caching) -> None:
     """
     pipeline_e2e_test(
         pipeline,
-        enable_caching=enable_caching,
         common_tasks={},
     )
diff --git a/pipelines/tests/trigger/test_main.py b/pipelines/tests/trigger/test_main.py
deleted file mode 100644
index 90e7dbe7..00000000
--- a/pipelines/tests/trigger/test_main.py
+++ /dev/null
@@ -1,244 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from unittest import mock
-import pytest
-import base64
-import json
-import os
-
-from pipelines.trigger.main import cf_handler, convert_payload, get_env
-
-
-def test_cf_handler():
-
-    test_parameter_values = {"key1": "val1", "key2": "val2"}
-
-    encoded_param_values = str(
-        base64.b64encode(json.dumps(test_parameter_values).encode("utf-8")), "utf-8"
-    )
-
-    payload = {
-        "attributes": {"template_path": "gs://my-bucket/my-template-path.json"},
-        "data": encoded_param_values,
-    }
-
-    with mock.patch(
-        "pipelines.trigger.main.trigger_pipeline_from_payload"
-    ) as mock_trigger_pipeline_from_payload:
-
-        cf_handler(payload, {})
-
-        mock_trigger_pipeline_from_payload.assert_called_with(
-            payload,
-        )
-
-
-def test_trigger_pipeline():
-
-    project_id = "my-test-project"
-    location = "europe-west4"
-    template_path = "gs://my-bucket/pipeline.json"
-    parameter_values = {"key1": "val1", "key2": "val2"}
-    pipeline_root = "gs://my-bucket/pipeline_root"
-    service_account = "my_service_account@my-test-project.iam.gserviceaccount.com"
-    encryption_spec_key_name = "my-cmek"
-    network = "my-network"
-    enable_caching = True
-
-    with mock.patch("pipelines.trigger.main.aiplatform") as mock_aiplatform:
-
-        from pipelines.trigger.main import trigger_pipeline
-
-        pl = trigger_pipeline(
-            project_id=project_id,
-            location=location,
-            template_path=template_path,
-            parameter_values=parameter_values,
-            pipeline_root=pipeline_root,
-            service_account=service_account,
-            encryption_spec_key_name=encryption_spec_key_name,
-            network=network,
-            enable_caching=enable_caching,
-        )
-
-        mock_aiplatform.init.assert_called_with(project=project_id, location=location)
-
-        mock_aiplatform.pipeline_jobs.PipelineJob.assert_called_with(
-            display_name=template_path,
-            enable_caching=enable_caching,
-            template_path=template_path,
-            parameter_values=parameter_values,
-            pipeline_root=pipeline_root,
-            encryption_spec_key_name=encryption_spec_key_name,
-        )
-
-        pl.submit.assert_called_with(
-            service_account=service_account,
-            network=network,
-        )
-
-
-@pytest.mark.parametrize(
-    "env_vars,test_input,expected",
-    [
-        # enable_caching
-        (
-            {},
-            {"attributes": {"template_path": "pipeline.json"}},
-            {
-                "attributes": {
-                    "template_path": "pipeline.json",
-                    "enable_caching": None,
-                },
-                "data": {},
-            },
-        ),
-        # enable_caching true
-        (
-            {},
-            {
-                "attributes": {
-                    "template_path": "pipeline.json",
-                    "enable_caching": "true",
-                }
-            },
-            {
-                "attributes": {
-                    "template_path": "pipeline.json",
-                    "enable_caching": True,
-                },
-                "data": {},
-            },
-        ),
-    ],
-)
-def test_convert_payload(env_vars, test_input, expected):
-
-    with mock.patch.dict(os.environ, env_vars, clear=True):
-        assert convert_payload(test_input) == expected
-
-
-@pytest.mark.parametrize(
-    "env_vars,expected",
-    [
-        # encryption_spec_key_name and network present
-        (
-            {
-                "VERTEX_PROJECT_ID": "my-project-id",
-                "VERTEX_LOCATION": "europe-west4",
-                "VERTEX_PIPELINE_ROOT": "gs://my-pipeline-root/folder",
-                "VERTEX_SA_EMAIL": "my-sa@my-project-id.iam.gserviceaccount.com",
-                "VERTEX_CMEK_IDENTIFIER": "my-cmek",
-                "VERTEX_NETWORK": "my-network",
-            },
-            {
-                "project_id": "my-project-id",
-                "location": "europe-west4",
-                "pipeline_root": "gs://my-pipeline-root/folder",
-                "service_account": "my-sa@my-project-id.iam.gserviceaccount.com",
-                "encryption_spec_key_name": "my-cmek",
-                "network": "my-network",
-            },
-        ),
-        # encryption_spec_key_name and network are empty string
-        (
-            {
-                "VERTEX_PROJECT_ID": "my-project-id",
-                "VERTEX_LOCATION": "europe-west4",
-                "VERTEX_PIPELINE_ROOT": "gs://my-pipeline-root/folder",
-                "VERTEX_SA_EMAIL": "my-sa@my-project-id.iam.gserviceaccount.com",
-                "VERTEX_CMEK_IDENTIFIER": "",
-                "VERTEX_NETWORK": "",
-            },
-            {
-                "project_id": "my-project-id",
-                "location": "europe-west4",
-                "pipeline_root": "gs://my-pipeline-root/folder",
-                "service_account": "my-sa@my-project-id.iam.gserviceaccount.com",
-                "encryption_spec_key_name": None,
-                "network": None,
-            },
-        ),
-        # encryption_spec_key_name and network absent
-        (
-            {
-                "VERTEX_PROJECT_ID": "my-project-id",
-                "VERTEX_LOCATION": "europe-west4",
-                "VERTEX_PIPELINE_ROOT": "gs://my-pipeline-root/folder",
-                "VERTEX_SA_EMAIL": "my-sa@my-project-id.iam.gserviceaccount.com",
-            },
-            {
-                "project_id": "my-project-id",
-                "location": "europe-west4",
-                "pipeline_root": "gs://my-pipeline-root/folder",
-                "service_account": "my-sa@my-project-id.iam.gserviceaccount.com",
-                "encryption_spec_key_name": None,
-                "network": None,
-            },
-        ),
-    ],
-)
-def test_get_env(env_vars, expected, monkeypatch):
-
-    for k, v in env_vars.items():
-        monkeypatch.setenv(k, v)
-
-    env = get_env()
-
-    assert env == expected
-
-
-@pytest.mark.parametrize(
-    "cmdline_args,expected_payload",
-    [
-        (
-            [
-                "--template_path=pipeline.json",
-                "--enable_caching=True",
-            ],
-            {
-                "attributes": {
-                    "template_path": "pipeline.json",
-                    "enable_caching": "True",
-                },
-            },
-        ),
-        # enable_caching omitted on commandline
-        (
-            [
-                "--template_path=pipeline.json",
-                "--enable_caching=",
-            ],
-            {
-                "attributes": {
-                    "template_path": "pipeline.json",
-                    "enable_caching": None,
-                },
-            },
-        ),
-    ],
-)
-def test_sandbox_run(cmdline_args, expected_payload):
-
-    # mock get_args(), and trigger_pipeline_from_payload()
-    with mock.patch(
-        "pipelines.trigger.main.trigger_pipeline_from_payload"
-    ) as mock_trigger_pipeline_from_payload:
-
-        from pipelines.trigger.main import sandbox_run
-
-        sandbox_run(cmdline_args)
-
-        mock_trigger_pipeline_from_payload.assert_called_once_with(expected_payload)
diff --git a/pipelines/tests/utils/test_trigger_pipeline.py b/pipelines/tests/utils/test_trigger_pipeline.py
new file mode 100644
index 00000000..7ba37f1e
--- /dev/null
+++ b/pipelines/tests/utils/test_trigger_pipeline.py
@@ -0,0 +1,81 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest import mock
+import pytest
+import os
+
+from pipelines.utils.trigger_pipeline import trigger_pipeline
+
+
+@pytest.mark.parametrize(
+    "test_enable_caching_input,enable_caching_expected",
+    # test for different values of "enable_pipeline_caching" env var (left)
+    # vs actual value passed to PipelineJob enable_caching (right)
+    [
+        ("True", True),
+        ("true", True),
+        ("False", False),
+        ("false", False),
+        (None, None),  # enable_pipeline_caching env var not set
+    ],
+)
+@mock.patch("google.cloud.aiplatform.PipelineJob")
+def test_trigger_pipeline(
+    mock_pipelinejob, test_enable_caching_input, enable_caching_expected
+):
+
+    template_path = "path/to/template.yaml"
+    enable_caching = test_enable_caching_input
+    pipeline_root = "gs://my-pipeline-root/abc123"
+    encryption_spec_key_name = "dummy_encryption_spec_key_name"
+    project_id = "dummy_project_id"
+    region = "dummy_region"
+    service_account = "dummy_sa@dummy_project_id.iam.gserviceaccount.com"
+    network = "dummy_network"
+    display_name = "my first pipeline"
+
+    env_vars = {
+        "VERTEX_PROJECT_ID": project_id,
+        "VERTEX_LOCATION": region,
+        "VERTEX_SA_EMAIL": service_account,
+        "VERTEX_NETWORK": network,
+        "VERTEX_CMEK_IDENTIFIER": encryption_spec_key_name,
+        "VERTEX_PIPELINE_ROOT": pipeline_root,
+    }
+
+    if enable_caching is not None:
+        env_vars["enable_pipeline_caching"] = enable_caching
+
+    with mock.patch.dict(os.environ, env_vars):
+
+        trigger_pipeline(
+            template_path=template_path,
+            display_name=display_name,
+        )
+
+        mock_pipelinejob.assert_called_with(
+            project=project_id,
+            location=region,
+            display_name=display_name,
+            enable_caching=enable_caching_expected,
+            template_path=template_path,
+            pipeline_root=pipeline_root,
+            encryption_spec_key_name=encryption_spec_key_name,
+        )
+
+        mock_pipelinejob.return_value.submit.assert_called_with(
+            service_account=service_account,
+            network=network,
+        )
diff --git a/pipelines/tests/utils/test_upload_pipeline.py b/pipelines/tests/utils/test_upload_pipeline.py
new file mode 100644
index 00000000..e7d93a8b
--- /dev/null
+++ b/pipelines/tests/utils/test_upload_pipeline.py
@@ -0,0 +1,76 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest import mock
+import pytest
+
+
+@pytest.mark.parametrize(
+    "input_tags",
+    # test for different combinations of AR tags to use
+    # when uploading the compiled pipeline to Artifact Registry
+    [
+        None,  # no tag
+        ["dummy_tag1"],  # single tag
+        ["dummy_tag1", "dummy_tag2"],  # multiple tags
+    ],
+)
+@mock.patch("pipelines.utils.upload_pipeline.upload_pipeline")
+def test_main(mock_upload_pipeline, input_tags):
+    yaml = "path/to/template.yaml"
+    dest = "https://europe-west1-kfp.pkg.dev/dummy-project/dummy-repo"
+
+    args = [
+        f"--dest={dest}",
+        f"--yaml={yaml}",
+    ]
+
+    if input_tags:
+        args.extend([f"--tag={tag}" for tag in input_tags])
+
+    from pipelines.utils.upload_pipeline import main
+
+    main(args)
+
+    mock_upload_pipeline.assert_called_with(
+        host=dest,
+        file_name=yaml,
+        tags=input_tags,
+    )
+
+
+@mock.patch("pipelines.utils.upload_pipeline.RegistryClient")
+def test_upload_pipeline(mock_registry_client):
+
+    yaml = "path/to/template.yaml"
+    dest = "https://europe-west1-kfp.pkg.dev/dummy-project/dummy-repo"
+
+    input_tags = ["dummy_tag1", "dummy_tag2"]
+
+    from pipelines.utils.upload_pipeline import upload_pipeline
+
+    upload_pipeline(
+        host=dest,
+        file_name=yaml,
+        tags=input_tags,
+    )
+
+    mock_registry_client.assert_called_with(
+        host=dest,
+    )
+
+    mock_registry_client.return_value.upload_pipeline.assert_called_with(
+        file_name=yaml,
+        tags=input_tags,
+    )
diff --git a/terraform/envs/dev/main.tf b/terraform/envs/dev/main.tf
index c7c46208..a5b9e07c 100644
--- a/terraform/envs/dev/main.tf
+++ b/terraform/envs/dev/main.tf
@@ -48,7 +48,7 @@ module "scheduler" {
   source              = "../../modules/scheduled_pipelines"
   project_id          = var.project_id
   region              = var.region
-  name                = each.value.name
+  name                = each.key
   description         = lookup(each.value, "description", null)
   schedule            = each.value.schedule
   time_zone           = lookup(each.value, "time_zone", "UTC")
diff --git a/terraform/envs/prod/main.tf b/terraform/envs/prod/main.tf
index c7c46208..a5b9e07c 100644
--- a/terraform/envs/prod/main.tf
+++ b/terraform/envs/prod/main.tf
@@ -48,7 +48,7 @@ module "scheduler" {
   source              = "../../modules/scheduled_pipelines"
   project_id          = var.project_id
   region              = var.region
-  name                = each.value.name
+  name                = each.key
   description         = lookup(each.value, "description", null)
   schedule            = each.value.schedule
   time_zone           = lookup(each.value, "time_zone", "UTC")
diff --git a/terraform/envs/test/main.tf b/terraform/envs/test/main.tf
index c7c46208..a5b9e07c 100644
--- a/terraform/envs/test/main.tf
+++ b/terraform/envs/test/main.tf
@@ -48,7 +48,7 @@ module "scheduler" {
   source              = "../../modules/scheduled_pipelines"
   project_id          = var.project_id
   region              = var.region
-  name                = each.value.name
+  name                = each.key
   description         = lookup(each.value, "description", null)
   schedule            = each.value.schedule
   time_zone           = lookup(each.value, "time_zone", "UTC")
diff --git a/terraform/modules/cloudfunction/.python-version b/terraform/modules/cloudfunction/.python-version
new file mode 100644
index 00000000..9f3d4c17
--- /dev/null
+++ b/terraform/modules/cloudfunction/.python-version
@@ -0,0 +1 @@
+3.9.16
diff --git a/terraform/modules/cloudfunction/README.md b/terraform/modules/cloudfunction/README.md
new file mode 100644
index 00000000..6d152d84
--- /dev/null
+++ b/terraform/modules/cloudfunction/README.md
@@ -0,0 +1,28 @@
+# Cloud Function for triggering Vertex Pipelines
+
+This Terraform module deploys a Google Cloud Function that is used to trigger the Vertex Pipeline run. The Cloud Function is triggered by a Pub/Sub message, which is published by Cloud Scheduler.
+
+## Pub/Sub message format
+
+The Pub/Sub message data is a base64-encoded JSON string containing these fields:
+
+```python
+{
+    "template_path": <Artifact Registry URI pointing to the compiled ML pipeline to run>,
+    "enable_caching": <whether to enable/disable pipeline caching. "True" or "False" (omit this field to use default values from pipeline definitions)>,
+    "pipeline_parameters": { # Pipeline input parameters
+        "foo": "bar",
+    }
+}
+```
+
+To use this module, you just need to provide the Terraform variables - see [scheduling pipelines](/README.md#scheduling-pipelines) in the main README file for more details.
+
+## Development
+
+1. Change the working directory to this directory e.g. `cd terraform/modules/cloudfunction`.
+1. Make sure that you are using the correct version of Python that matches `.python-version`. You can use [pyenv](https://github.com/pyenv/pyenv) to manage the different Python versions on your system.
+1. Create a new virtual environment `python3 -m venv .venv`.
+1. Activate the new virtual environment `source .venv/bin/activate`.
+1. Install Python dependencies and dev dependencies `pip install -r src/requirements.txt && pip install -r src/requirements-dev.txt`.
+1. To run unit tests, run `PYTHONPATH=. pytest`.
diff --git a/terraform/modules/cloudfunction/function.tf b/terraform/modules/cloudfunction/function.tf
index 4d8ae574..ab9c7ce0 100644
--- a/terraform/modules/cloudfunction/function.tf
+++ b/terraform/modules/cloudfunction/function.tf
@@ -16,11 +16,13 @@
 
 locals {
 
+  cloudfunction_dir = "${path.module}/src"
+
   # List of all the files in the Cloud Function source dir
-  cloudfunction_files = fileset(var.source_dir, "*")
+  cloudfunction_files = fileset(local.cloudfunction_dir, "*")
 
   # Get the MD5 of each file in the directory
-  file_hashes = [for f in local.cloudfunction_files : filemd5("${var.source_dir}/${f}")]
+  file_hashes = [for f in local.cloudfunction_files : filemd5("${local.cloudfunction_dir}/${f}")]
 
   # Concatenate hashes and then hash them for an overall hash
   # This method ensures that the hash only changes (and therefore the Cloud Function only re-deploys)
@@ -31,12 +33,12 @@ locals {
 
 data "archive_file" "function_archive" {
   type        = "zip"
-  source_dir  = var.source_dir
-  output_path = "${var.function_name}.zip"
+  source_dir  = local.cloudfunction_dir
+  output_path = "${var.function_name}_${local.cloudfunction_hash}.zip"
 }
 
 resource "google_storage_bucket_object" "archive" {
-  name   = "${data.archive_file.function_archive.output_path}_${local.cloudfunction_hash}.zip"
+  name   = data.archive_file.function_archive.output_path
   bucket = var.source_code_bucket_name
   source = data.archive_file.function_archive.output_path
 
diff --git a/terraform/modules/cloudfunction/src/main.py b/terraform/modules/cloudfunction/src/main.py
new file mode 100644
index 00000000..9a283787
--- /dev/null
+++ b/terraform/modules/cloudfunction/src/main.py
@@ -0,0 +1,78 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import base64
+import json
+import os
+from distutils.util import strtobool
+from google.cloud import aiplatform
+
+
+def cf_handler(event, context):
+    """Background Cloud Function to be triggered by Pub/Sub.
+    Args:
+         event (dict):  The dictionary with data specific to this type of
+                        event. The `@type` field maps to
+                         `type.googleapis.com/google.pubsub.v1.PubsubMessage`.
+                        The `data` field maps to the PubsubMessage data
+                        in a base64-encoded string. The `attributes` field maps
+                        to the PubsubMessage attributes if any is present.
+         context (google.cloud.functions.Context): Metadata of triggering event
+                        including `event_id` which maps to the PubsubMessage
+                        messageId, `timestamp` which maps to the PubsubMessage
+                        publishTime, `event_type` which maps to
+                        `google.pubsub.topic.publish`, and `resource` which is
+                        a dictionary that describes the service API endpoint
+                        pubsub.googleapis.com, the triggering topic's name, and
+                        the triggering event type
+                        `type.googleapis.com/google.pubsub.v1.PubsubMessage`.
+    Returns:
+        None. The output is written to Cloud Logging.
+    """
+
+    payload = json.loads(base64.b64decode(event["data"]).decode("utf-8"))
+
+    project_id = os.environ["VERTEX_PROJECT_ID"]
+    location = os.environ["VERTEX_LOCATION"]
+    pipeline_root = os.environ["VERTEX_PIPELINE_ROOT"]
+    service_account = os.environ["VERTEX_SA_EMAIL"]
+
+    template_path = payload["template_path"]
+    display_name = payload["display_name"]
+    pipeline_parameters = payload.get("pipeline_parameters")
+    enable_caching = payload.get("enable_pipeline_caching")
+    if enable_caching:
+        enable_caching = bool(strtobool(enable_caching))
+
+    # For below options, we want an empty string to become None, so we add "or None"
+    encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER") or None
+    network = os.environ.get("VERTEX_NETWORK") or None
+
+    # Instantiate PipelineJob object
+    pl = aiplatform.pipeline_jobs.PipelineJob(
+        project=project_id,
+        location=location,
+        display_name=display_name,
+        enable_caching=enable_caching,
+        template_path=template_path,
+        parameter_values=pipeline_parameters,
+        pipeline_root=pipeline_root,
+        encryption_spec_key_name=encryption_spec_key_name,
+    )
+
+    # Execute pipeline in Vertex
+    pl.submit(
+        service_account=service_account,
+        network=network,
+    )
diff --git a/terraform/modules/cloudfunction/src/requirements-dev.txt b/terraform/modules/cloudfunction/src/requirements-dev.txt
new file mode 100644
index 00000000..7a04e1cf
--- /dev/null
+++ b/terraform/modules/cloudfunction/src/requirements-dev.txt
@@ -0,0 +1,15 @@
+# Copyright 2022 Google LLC
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+#     https://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+pytest
diff --git a/pipelines/src/pipelines/trigger/requirements.txt b/terraform/modules/cloudfunction/src/requirements.txt
similarity index 100%
rename from pipelines/src/pipelines/trigger/requirements.txt
rename to terraform/modules/cloudfunction/src/requirements.txt
diff --git a/terraform/modules/cloudfunction/test/test_main.py b/terraform/modules/cloudfunction/test/test_main.py
new file mode 100644
index 00000000..c4cc06fa
--- /dev/null
+++ b/terraform/modules/cloudfunction/test/test_main.py
@@ -0,0 +1,93 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest import mock
+import pytest
+import os
+import base64
+import json
+
+from src.main import cf_handler
+
+
+@pytest.mark.parametrize(
+    "test_enable_caching_input,enable_caching_expected",
+    # test for different values of "enable_pipeline_caching" env var (left)
+    # vs actual value passed to PipelineJob enable_caching (right)
+    [
+        ("True", True),
+        ("true", True),
+        ("False", False),
+        ("false", False),
+        (None, None),  # enable_pipeline_caching env var not set
+    ],
+)
+@mock.patch("google.cloud.aiplatform.pipeline_jobs.PipelineJob")
+def test_trigger_pipeline(
+    mock_pipelinejob, test_enable_caching_input, enable_caching_expected
+):
+
+    template_path = "path/to/template.yaml"
+    enable_caching = test_enable_caching_input
+    pipeline_root = "gs://my-pipeline-root/abc123"
+    encryption_spec_key_name = "dummy_encryption_spec_key_name"
+    project_id = "dummy_project_id"
+    region = "dummy_region"
+    service_account = "dummy_sa@dummy_project_id.iam.gserviceaccount.com"
+    network = "dummy_network"
+    display_name = "my first pipeline"
+
+    payload = {
+        "template_path": template_path,
+        "display_name": display_name,
+        "pipeline_parameters": {
+            "foo": "bar",
+            "abc": 123,
+        },
+    }
+
+    if enable_caching is not None:
+        payload["enable_pipeline_caching"] = enable_caching
+
+    # encode as base64 to feed into Cloud Function
+    event = {"data": base64.b64encode(json.dumps(payload).encode("utf-8"))}
+
+    env_vars = {
+        "VERTEX_PROJECT_ID": project_id,
+        "VERTEX_LOCATION": region,
+        "VERTEX_SA_EMAIL": service_account,
+        "VERTEX_NETWORK": network,
+        "VERTEX_CMEK_IDENTIFIER": encryption_spec_key_name,
+        "VERTEX_PIPELINE_ROOT": pipeline_root,
+    }
+
+    with mock.patch.dict(os.environ, env_vars):
+
+        cf_handler(event, None)
+
+        mock_pipelinejob.assert_called_with(
+            project=project_id,
+            location=region,
+            display_name=display_name,
+            enable_caching=enable_caching_expected,
+            template_path=template_path,
+            pipeline_root=pipeline_root,
+            encryption_spec_key_name=encryption_spec_key_name,
+            parameter_values=payload["pipeline_parameters"],
+        )
+
+        mock_pipelinejob.return_value.submit.assert_called_with(
+            service_account=service_account,
+            network=network,
+        )
diff --git a/terraform/modules/cloudfunction/variables.tf b/terraform/modules/cloudfunction/variables.tf
index baafb9a2..4a8d6667 100644
--- a/terraform/modules/cloudfunction/variables.tf
+++ b/terraform/modules/cloudfunction/variables.tf
@@ -114,11 +114,6 @@ variable "source_code_bucket_name" {
   type        = string
 }
 
-variable "source_dir" {
-  description = "The pathname of the directory which contains the function source code."
-  type        = string
-}
-
 variable "max_instances" {
   description = "The maximum number of parallel executions of the function."
   type        = number
diff --git a/terraform/modules/scheduled_pipelines/main.tf b/terraform/modules/scheduled_pipelines/main.tf
index 5163060c..20f2c813 100644
--- a/terraform/modules/scheduled_pipelines/main.tf
+++ b/terraform/modules/scheduled_pipelines/main.tf
@@ -25,10 +25,11 @@ resource "google_cloud_scheduler_job" "scheduled_pipeline" {
 
   pubsub_target {
     topic_name = var.topic_name
-    attributes = {
-      template_path  = var.template_path,
-      enable_caching = var.enable_caching
-    }
-    data = base64encode(jsonencode(var.pipeline_parameters))
+    data = base64encode(jsonencode({
+      template_path       = var.template_path,
+      display_name        = var.name,
+      enable_caching      = var.enable_caching,
+      pipeline_parameters = var.pipeline_parameters,
+    }))
   }
 }
diff --git a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
index 0fefcd87..54c25bb4 100644
--- a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
+++ b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
@@ -17,7 +17,6 @@
 cloud_schedulers_config = {
 
   xgboost_training = {
-    name         = "xgboost-training-pipeline-trigger"
     description  = "Trigger my training pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
@@ -37,7 +36,6 @@ cloud_schedulers_config = {
   },
 
   xgboost_prediction = {
-    name         = "xgboost-prediction-pipeline-trigger"
     description  = "Trigger my prediction pipeline in Vertex"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
diff --git a/terraform/modules/vertex_deployment/main.tf b/terraform/modules/vertex_deployment/main.tf
index 73c6a4fa..66a3b4b9 100644
--- a/terraform/modules/vertex_deployment/main.tf
+++ b/terraform/modules/vertex_deployment/main.tf
@@ -83,7 +83,6 @@ module "cloudfunction" {
   region                        = local.cloudfunction_region
   function_name                 = var.cloudfunction_name
   description                   = var.cloudfunction_description
-  source_dir                    = "../../../pipelines/src/pipelines/trigger"
   source_code_bucket_name       = google_storage_bucket.staging_bucket.name
   runtime                       = "python39"
   entry_point                   = "cf_handler"

From cce5a1504cccc606ab87ab635a57acd60ec79cb8 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 14 Aug 2023 10:54:32 +0100
Subject: [PATCH 147/238] fix: terraform variables declaration

---
 terraform/envs/dev/variables.tf | 1 -
 1 file changed, 1 deletion(-)

diff --git a/terraform/envs/dev/variables.tf b/terraform/envs/dev/variables.tf
index 543dac1d..0bc03ded 100644
--- a/terraform/envs/dev/variables.tf
+++ b/terraform/envs/dev/variables.tf
@@ -27,7 +27,6 @@ variable "region" {
 variable "cloud_schedulers_config" {
   description = "Map of configurations for cloud scheduler jobs (each a different pipeline schedule)."
   type = map(object({
-    name                = string
     description         = string
     schedule            = string
     time_zone           = string

From 5a8a167b441915f93bf5987eec48dfd7e2830500 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 14 Aug 2023 11:04:05 +0100
Subject: [PATCH 148/238] fix: fix cloud function YAML and bump
 google-cloud-aiplatform version

---
 components/vertex-components/poetry.lock      | 581 ++++++++--------
 components/vertex-components/pyproject.toml   |   2 +-
 .../src/vertex_components/lookup_model.py     |   2 +-
 .../vertex_components/model_batch_predict.py  |   2 +-
 .../src/vertex_components/upload_model.py     |   2 +-
 pipelines/poetry.lock                         | 631 +++++++++---------
 pipelines/pyproject.toml                      |   2 +-
 .../cloudfunction/src/requirements.txt        |   2 +-
 8 files changed, 597 insertions(+), 627 deletions(-)

diff --git a/components/vertex-components/poetry.lock b/components/vertex-components/poetry.lock
index c5e25a3e..5368a62b 100644
--- a/components/vertex-components/poetry.lock
+++ b/components/vertex-components/poetry.lock
@@ -1,11 +1,11 @@
-# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
 
 [[package]]
 name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
     {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
@@ -13,113 +13,112 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.5.7"
+version = "2023.7.22"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2023.5.7-py3-none-any.whl", hash = "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"},
-    {file = "certifi-2023.5.7.tar.gz", hash = "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7"},
+    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
+    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
 ]
 
 [[package]]
 name = "charset-normalizer"
-version = "3.1.0"
+version = "3.2.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
-python-versions = ">=3.9.0"
+python-versions = ">=3.7.0"
 files = [
-    {file = "charset-normalizer-3.1.0.tar.gz", hash = "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e0ac8959c929593fee38da1c2b64ee9778733cdf03c482c9ff1d508b6b593b2b"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d7fc3fca01da18fbabe4625d64bb612b533533ed10045a2ac3dd194bfa656b60"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:04eefcee095f58eaabe6dc3cc2262f3bcd776d2c67005880894f447b3f2cb9c1"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:20064ead0717cf9a73a6d1e779b23d149b53daf971169289ed2ed43a71e8d3b0"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1435ae15108b1cb6fffbcea2af3d468683b7afed0169ad718451f8db5d1aff6f"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c84132a54c750fda57729d1e2599bb598f5fa0344085dbde5003ba429a4798c0"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75f2568b4189dda1c567339b48cba4ac7384accb9c2a7ed655cd86b04055c795"},
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 ]
 
 [[package]]
 name = "click"
-version = "8.1.3"
+version = "8.1.6"
 description = "Composable command line interface toolkit"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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-    {file = "click-8.1.3.tar.gz", hash = "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e"},
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 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
 [[package]]
 name = "colorama"
@@ -145,13 +144,13 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.1"
+version = "1.1.2"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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+    {file = "exceptiongroup-1.1.2-py3-none-any.whl", hash = "sha256:e346e69d186172ca7cf029c8c1d16235aa0e04035e5750b4b95039e65204328f"},
+    {file = "exceptiongroup-1.1.2.tar.gz", hash = "sha256:12c3e887d6485d16943a309616de20ae5582633e0a2eda17f4e10fd61c1e8af5"},
 ]
 
 [package.extras]
@@ -159,37 +158,37 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "google-api-core"
-version = "2.11.0"
+version = "2.11.1"
 description = "Google API client core library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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+    {file = "google-api-core-2.11.1.tar.gz", hash = "sha256:25d29e05a0058ed5f19c61c0a78b1b53adea4d9364b464d014fbda941f6d1c9a"},
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 ]
 
 [package.dependencies]
-google-auth = ">=2.14.1,<3.0dev"
-googleapis-common-protos = ">=1.56.2,<2.0dev"
+google-auth = ">=2.14.1,<3.0.dev0"
+googleapis-common-protos = ">=1.56.2,<2.0.dev0"
 grpcio = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-grpcio-status = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-requests = ">=2.18.0,<3.0.0dev"
+grpcio-status = {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "extra == \"grpc\""}
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0.dev0"
+requests = ">=2.18.0,<3.0.0.dev0"
 
 [package.extras]
-grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status (>=1.33.2,<2.0dev)", "grpcio-status (>=1.49.1,<2.0dev)"]
-grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
-grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
+grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status (>=1.33.2,<2.0.dev0)", "grpcio-status (>=1.49.1,<2.0.dev0)"]
+grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
+grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.19.0"
+version = "2.22.0"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "google-auth-2.19.0.tar.gz", hash = "sha256:f39d528077ac540793dd3c22a8706178f157642a67d874db25c640b7fead277e"},
-    {file = "google_auth-2.19.0-py2.py3-none-any.whl", hash = "sha256:be617bfaf77774008e9d177573f782e109188c8a64ae6e744285df5cea3e7df6"},
+    {file = "google-auth-2.22.0.tar.gz", hash = "sha256:164cba9af4e6e4e40c3a4f90a1a6c12ee56f14c0b4868d1ca91b32826ab334ce"},
+    {file = "google_auth-2.22.0-py2.py3-none-any.whl", hash = "sha256:d61d1b40897407b574da67da1a833bdc10d5a11642566e506565d1b1a46ba873"},
 ]
 
 [package.dependencies]
@@ -200,21 +199,21 @@ six = ">=1.9.0"
 urllib3 = "<2.0"
 
 [package.extras]
-aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "requests (>=2.20.0,<3.0.0dev)"]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0.dev0)", "requests (>=2.20.0,<3.0.0.dev0)"]
 enterprise-cert = ["cryptography (==36.0.2)", "pyopenssl (==22.0.0)"]
 pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
-requests = ["requests (>=2.20.0,<3.0.0dev)"]
+requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.24.1"
+version = "1.30.1"
 description = "Vertex AI API client library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-aiplatform-1.24.1.tar.gz", hash = "sha256:0ce9e97bf5c977397e52b3b7c4dc78610c135fbde11a60a6c0b77a4fdf776400"},
-    {file = "google_cloud_aiplatform-1.24.1-py2.py3-none-any.whl", hash = "sha256:942765a6bad97e46e262dd6599dc5f171663ce952130e0b0b2eb97e0b1b98bfd"},
+    {file = "google-cloud-aiplatform-1.30.1.tar.gz", hash = "sha256:7552a6b2e66d7a9ff3c4b2bb95b0e9c182e7475dfb35d6347e9299f78779135a"},
+    {file = "google_cloud_aiplatform-1.30.1-py2.py3-none-any.whl", hash = "sha256:ab1bbd4cf83cf583b7dea7e53421ad076f18b63e93cb22fb53c03176d5aa9258"},
 ]
 
 [package.dependencies]
@@ -232,26 +231,26 @@ autologging = ["mlflow (>=1.27.0,<=2.1.1)"]
 cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
 datasets = ["pyarrow (>=3.0.0,<8.0dev)"]
 endpoint = ["requests (>=2.28.1)"]
-full = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pyyaml (>=5.3,<6)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
+full = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pyyaml (>=5.3,<7)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
 lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"]
 metadata = ["numpy (>=1.15.0)", "pandas (>=1.0.0)"]
-pipelines = ["pyyaml (>=5.3,<6)"]
+pipelines = ["pyyaml (>=5.3,<7)"]
 prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<0.76.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"]
 private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"]
 tensorboard = ["tensorflow (>=2.3.0,<3.0.0dev)"]
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+testing = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "grpcio-testing", "ipython", "kfp", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3,<7)", "requests (>=2.28.1)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
 vizier = ["google-vizier (==0.0.4)"]
 xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "3.10.0"
+version = "3.11.4"
 description = "Google BigQuery API client library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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-    {file = "google_cloud_bigquery-3.10.0-py2.py3-none-any.whl", hash = "sha256:848a3cbce0ba7d4f1e9551400a7c99aa0eab72290d5a1bbbe69f18a24a10bd3a"},
+    {file = "google-cloud-bigquery-3.11.4.tar.gz", hash = "sha256:697df117241a2283bcbb93b21e10badc14e51c9a90800d2a7e1a3e1c7d842974"},
+    {file = "google_cloud_bigquery-3.11.4-py2.py3-none-any.whl", hash = "sha256:5fa7897743a0ed949ade25a0942fc9e7557d8fce307c6f8a76d1b604cf27f1b1"},
 ]
 
 [package.dependencies]
@@ -277,13 +276,13 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 
 [[package]]
 name = "google-cloud-core"
-version = "2.3.2"
+version = "2.3.3"
 description = "Google Cloud API client core library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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-    {file = "google_cloud_core-2.3.2-py2.py3-none-any.whl", hash = "sha256:8417acf6466be2fa85123441696c4badda48db314c607cf1e5d543fa8bdc22fe"},
+    {file = "google-cloud-core-2.3.3.tar.gz", hash = "sha256:37b80273c8d7eee1ae816b3a20ae43585ea50506cb0e60f3cf5be5f87f1373cb"},
+    {file = "google_cloud_core-2.3.3-py2.py3-none-any.whl", hash = "sha256:fbd11cad3e98a7e5b0343dc07cb1039a5ffd7a5bb96e1f1e27cee4bda4a90863"},
 ]
 
 [package.dependencies]
@@ -295,12 +294,12 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "2.0.0"
+version = "2.1.1"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
 optional = false
-python-versions = ">=3.9.0,<3.12.0"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
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+    {file = "google_cloud_pipeline_components-2.1.1-py3-none-any.whl", hash = "sha256:fdb1621a1db112833a299bfe6353edd2eb7b9195e0d39896491c75e0b6624dcc"},
 ]
 
 [package.dependencies]
@@ -314,13 +313,13 @@ tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
-version = "1.10.1"
+version = "1.10.3"
 description = "Google Cloud Resource Manager API client library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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+    {file = "google-cloud-resource-manager-1.10.3.tar.gz", hash = "sha256:f80efcea36f10c5a81889afe93910926e3978b4b1ceeb82f563a2fc863072d14"},
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 ]
 
 [package.dependencies]
@@ -331,13 +330,13 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.9.0"
+version = "2.10.0"
 description = "Google Cloud Storage API client library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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+    {file = "google-cloud-storage-2.10.0.tar.gz", hash = "sha256:934b31ead5f3994e5360f9ff5750982c5b6b11604dc072bc452c25965e076dc7"},
+    {file = "google_cloud_storage-2.10.0-py2.py3-none-any.whl", hash = "sha256:9433cf28801671de1c80434238fb1e7e4a1ba3087470e90f70c928ea77c2b9d7"},
 ]
 
 [package.dependencies]
@@ -355,7 +354,7 @@ name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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@@ -435,7 +434,7 @@ name = "google-resumable-media"
 version = "2.5.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
 optional = false
-python-versions = ">= 3.9"
+python-versions = ">= 3.7"
 files = [
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@@ -450,28 +449,28 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.59.0"
+version = "1.60.0"
 description = "Common protobufs used in Google APIs"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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+    {file = "googleapis-common-protos-1.60.0.tar.gz", hash = "sha256:e73ebb404098db405ba95d1e1ae0aa91c3e15a71da031a2eeb6b2e23e7bc3708"},
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 ]
 
 [package.dependencies]
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+grpcio = {version = ">=1.44.0,<2.0.0.dev0", optional = true, markers = "extra == \"grpc\""}
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0.dev0"
 
 [package.extras]
-grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
+grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 
 [[package]]
 name = "grpc-google-iam-v1"
 version = "0.12.6"
 description = "IAM API client library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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@@ -484,75 +483,75 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 
 [[package]]
 name = "grpcio"
-version = "1.54.2"
+version = "1.57.0"
 description = "HTTP/2-based RPC framework"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
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 ]
 
 [package.extras]
-protobuf = ["grpcio-tools (>=1.54.2)"]
+protobuf = ["grpcio-tools (>=1.57.0)"]
 
 [[package]]
 name = "grpcio-status"
-version = "1.47.0"
+version = "1.48.2"
 description = "Status proto mapping for gRPC"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "grpcio-status-1.47.0.tar.gz", hash = "sha256:c9ce3213e84c6fd8801c31aca3ea4a6b3453eaa40b93a6c0a23ea8999808fa00"},
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 ]
 
 [package.dependencies]
 googleapis-common-protos = ">=1.5.5"
-grpcio = ">=1.47.0"
+grpcio = ">=1.48.2"
 protobuf = ">=3.12.0"
 
 [[package]]
@@ -566,32 +565,12 @@ files = [
     {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
 ]
 
-[[package]]
-name = "importlib-metadata"
-version = "6.6.0"
-description = "Read metadata from Python packages"
-optional = false
-python-versions = ">=3.9"
-files = [
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-]
-
-[package.dependencies]
-typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
-zipp = ">=0.5"
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-perf = ["ipython"]
-testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
-
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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@@ -602,7 +581,7 @@ name = "kfp"
 version = "2.0.1"
 description = "Kubeflow Pipelines SDK"
 optional = false
-python-versions = ">=3.9.0,<3.12.0"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
     {file = "kfp-2.0.1.tar.gz", hash = "sha256:4a65811778c3a45892d8d11c0f95ba5e410476157ed63cacb1dd82316f60cd4d"},
 ]
@@ -620,7 +599,6 @@ protobuf = ">=3.13.0,<4"
 PyYAML = ">=5.3,<7"
 requests-toolbelt = ">=0.8.0,<1"
 tabulate = ">=0.8.6,<1"
-typing-extensions = {version = ">=3.9.4,<5", markers = "python_version < \"3.9\""}
 urllib3 = "<2.0.0"
 
 [package.extras]
@@ -632,7 +610,7 @@ name = "kfp-pipeline-spec"
 version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
 optional = false
-python-versions = ">=3.9.0"
+python-versions = ">=3.7.0"
 files = [
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 ]
@@ -658,13 +636,13 @@ urllib3 = ">=1.15"
 
 [[package]]
 name = "kubernetes"
-version = "25.3.0"
+version = "26.1.0"
 description = "Kubernetes python client"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "kubernetes-25.3.0-py2.py3-none-any.whl", hash = "sha256:eb42333dad0bb5caf4e66460c6a4a1a36f0f057a040f35018f6c05a699baed86"},
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+    {file = "kubernetes-26.1.0-py2.py3-none-any.whl", hash = "sha256:e3db6800abf7e36c38d2629b5cb6b74d10988ee0cba6fba45595a7cbe60c0042"},
+    {file = "kubernetes-26.1.0.tar.gz", hash = "sha256:5854b0c508e8d217ca205591384ab58389abdae608576f9c9afc35a3c76a366c"},
 ]
 
 [package.dependencies]
@@ -703,7 +681,7 @@ name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "packaging-23.1-py3-none-any.whl", hash = "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61"},
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
@@ -711,31 +689,28 @@ files = [
 
 [[package]]
 name = "pluggy"
-version = "1.0.0"
+version = "1.2.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
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-    {file = "pluggy-1.0.0.tar.gz", hash = "sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159"},
+    {file = "pluggy-1.2.0-py3-none-any.whl", hash = "sha256:c2fd55a7d7a3863cba1a013e4e2414658b1d07b6bc57b3919e0c63c9abb99849"},
+    {file = "pluggy-1.2.0.tar.gz", hash = "sha256:d12f0c4b579b15f5e054301bb226ee85eeeba08ffec228092f8defbaa3a4c4b3"},
 ]
 
-[package.dependencies]
-importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
-
 [package.extras]
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "proto-plus"
-version = "1.22.2"
+version = "1.22.3"
 description = "Beautiful, Pythonic protocol buffers."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "proto-plus-1.22.2.tar.gz", hash = "sha256:0e8cda3d5a634d9895b75c573c9352c16486cb75deb0e078b5fda34db4243165"},
-    {file = "proto_plus-1.22.2-py3-none-any.whl", hash = "sha256:de34e52d6c9c6fcd704192f09767cb561bb4ee64e70eede20b0834d841f0be4d"},
+    {file = "proto-plus-1.22.3.tar.gz", hash = "sha256:fdcd09713cbd42480740d2fe29c990f7fbd885a67efc328aa8be6ee3e9f76a6b"},
+    {file = "proto_plus-1.22.3-py3-none-any.whl", hash = "sha256:a49cd903bc0b6ab41f76bf65510439d56ca76f868adf0274e738bfdd096894df"},
 ]
 
 [package.dependencies]
@@ -749,7 +724,7 @@ name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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@@ -802,26 +777,25 @@ pyasn1 = ">=0.4.6,<0.6.0"
 
 [[package]]
 name = "pytest"
-version = "7.3.1"
+version = "7.4.0"
 description = "pytest: simple powerful testing with Python"
 optional = false
-python-versions = ">=3.9"
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 files = [
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 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
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 iniconfig = "*"
 packaging = "*"
 pluggy = ">=0.12,<2.0"
 tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
-testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"]
+testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "python-dateutil"
@@ -839,40 +813,51 @@ six = ">=1.5"
 
 [[package]]
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-version = "5.4.1"
+version = "6.0.1"
 description = "YAML parser and emitter for Python"
 optional = false
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 ]
 
 [[package]]
@@ -880,7 +865,7 @@ name = "requests"
 version = "2.31.0"
 description = "Python HTTP for Humans."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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@@ -944,18 +929,18 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "setuptools"
-version = "67.8.0"
+version = "68.0.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
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 ]
 
 [package.extras]
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 [[package]]
@@ -1030,7 +1015,7 @@ name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"},
     {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"},
@@ -1044,23 +1029,12 @@ name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
     {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
 ]
 
-[[package]]
-name = "typing-extensions"
-version = "4.6.2"
-description = "Backported and Experimental Type Hints for Python 3.9+"
-optional = false
-python-versions = ">=3.9"
-files = [
-    {file = "typing_extensions-4.6.2-py3-none-any.whl", hash = "sha256:3a8b36f13dd5fdc5d1b16fe317f5668545de77fa0b8e02006381fd49d731ab98"},
-    {file = "typing_extensions-4.6.2.tar.gz", hash = "sha256:06006244c70ac8ee83fa8282cb188f697b8db25bc8b4df07be1873c43897060c"},
-]
-
 [[package]]
 name = "urllib3"
 version = "1.26.16"
@@ -1079,13 +1053,13 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "websocket-client"
-version = "1.5.2"
+version = "1.6.1"
 description = "WebSocket client for Python with low level API options"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
-    {file = "websocket-client-1.5.2.tar.gz", hash = "sha256:c7d67c13b928645f259d9b847ab5b57fd2d127213ca41ebd880de1f553b7c23b"},
-    {file = "websocket_client-1.5.2-py3-none-any.whl", hash = "sha256:f8c64e28cd700e7ba1f04350d66422b6833b82a796b525a51e740b8cc8dab4b1"},
+    {file = "websocket-client-1.6.1.tar.gz", hash = "sha256:c951af98631d24f8df89ab1019fc365f2227c0892f12fd150e935607c79dd0dd"},
+    {file = "websocket_client-1.6.1-py3-none-any.whl", hash = "sha256:f1f9f2ad5291f0225a49efad77abf9e700b6fef553900623060dad6e26503b9d"},
 ]
 
 [package.extras]
@@ -1093,22 +1067,7 @@ docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
-[[package]]
-name = "zipp"
-version = "3.15.0"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.9"
-files = [
-    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
-    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
-]
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
-
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "60358af42655b9cff7889a1d3d0fbcf4ca40982c4dd4d29784544c511a63cb96"
+content-hash = "f1eb8e95cdba70c0a5f31de2527e75b4301ba6ab983e367a51a6bf5ef658ceac"
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index a12e1fdc..d64b4811 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -15,7 +15,7 @@ python = ">=3.9,<3.11"
 kfp = ">=2.0.1,<3.0.0"
 
 [tool.poetry.group.dev.dependencies]
-google-cloud-aiplatform = "1.24.1"
+google-cloud-aiplatform = "1.30.1"
 pytest = ">=7.3.1,<8.0.0"
 google-cloud-pipeline-components = "^2.0.0"
 
diff --git a/components/vertex-components/src/vertex_components/lookup_model.py b/components/vertex-components/src/vertex_components/lookup_model.py
index ac73eeef..e41c3ed8 100644
--- a/components/vertex-components/src/vertex_components/lookup_model.py
+++ b/components/vertex-components/src/vertex_components/lookup_model.py
@@ -18,7 +18,7 @@
 
 @component(
     base_image="python:3.9",
-    packages_to_install=["google-cloud-aiplatform==1.24.1"],
+    packages_to_install=["google-cloud-aiplatform==1.30.1"],
 )
 def lookup_model(
     model_name: str,
diff --git a/components/vertex-components/src/vertex_components/model_batch_predict.py b/components/vertex-components/src/vertex_components/model_batch_predict.py
index 80605a32..08370ac5 100644
--- a/components/vertex-components/src/vertex_components/model_batch_predict.py
+++ b/components/vertex-components/src/vertex_components/model_batch_predict.py
@@ -19,7 +19,7 @@
 @component(
     base_image="python:3.9",
     packages_to_install=[
-        "google-cloud-aiplatform==1.24.1",
+        "google-cloud-aiplatform==1.30.1",
         "google-cloud-pipeline-components==1.0.33",
     ],
 )
diff --git a/components/vertex-components/src/vertex_components/upload_model.py b/components/vertex-components/src/vertex_components/upload_model.py
index be94a9ff..2484ffec 100644
--- a/components/vertex-components/src/vertex_components/upload_model.py
+++ b/components/vertex-components/src/vertex_components/upload_model.py
@@ -19,7 +19,7 @@
 @component(
     base_image="python:3.9",
     packages_to_install=[
-        "google-cloud-aiplatform==1.28.1",
+        "google-cloud-aiplatform==1.30.1",
         "google-cloud-pipeline-components==2.1.0",
     ],
 )
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index 50d59be0..49e3e1f7 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -29,119 +29,119 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.5.7"
+version = "2023.7.22"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2023.5.7-py3-none-any.whl", hash = "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"},
-    {file = "certifi-2023.5.7.tar.gz", hash = "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7"},
+    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
+    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
 ]
 
 [[package]]
 name = "cfgv"
-version = "3.3.1"
+version = "3.4.0"
 description = "Validate configuration and produce human readable error messages."
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.8"
 files = [
-    {file = "cfgv-3.3.1-py2.py3-none-any.whl", hash = "sha256:c6a0883f3917a037485059700b9e75da2464e6c27051014ad85ba6aaa5884426"},
-    {file = "cfgv-3.3.1.tar.gz", hash = "sha256:f5a830efb9ce7a445376bb66ec94c638a9787422f96264c98edc6bdeed8ab736"},
+    {file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"},
+    {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
 ]
 
 [[package]]
 name = "charset-normalizer"
-version = "3.1.0"
+version = "3.2.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
 files = [
-    {file = "charset-normalizer-3.1.0.tar.gz", hash = "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e0ac8959c929593fee38da1c2b64ee9778733cdf03c482c9ff1d508b6b593b2b"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d7fc3fca01da18fbabe4625d64bb612b533533ed10045a2ac3dd194bfa656b60"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:04eefcee095f58eaabe6dc3cc2262f3bcd776d2c67005880894f447b3f2cb9c1"},
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+    {file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:c1c76a1743432b4b60ab3358c937a3fe1341c828ae6194108a94c69028247f22"},
+    {file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:f7560358a6811e52e9c4d142d497f1a6e10103d3a6881f18d04dbce3729c0e2c"},
+    {file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:c8063cf17b19661471ecbdb3df1c84f24ad2e389e326ccaf89e3fb2484d8dd7e"},
+    {file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:cd6dbe0238f7743d0efe563ab46294f54f9bc8f4b9bcf57c3c666cc5bc9d1299"},
+    {file = "charset_normalizer-3.2.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:1249cbbf3d3b04902ff081ffbb33ce3377fa6e4c7356f759f3cd076cc138d020"},
+    {file = "charset_normalizer-3.2.0-cp39-cp39-win32.whl", hash = "sha256:6c409c0deba34f147f77efaa67b8e4bb83d2f11c8806405f76397ae5b8c0d1c9"},
+    {file = "charset_normalizer-3.2.0-cp39-cp39-win_amd64.whl", hash = "sha256:7095f6fbfaa55defb6b733cfeb14efaae7a29f0b59d8cf213be4e7ca0b857b80"},
+    {file = "charset_normalizer-3.2.0-py3-none-any.whl", hash = "sha256:8e098148dd37b4ce3baca71fb394c81dc5d9c7728c95df695d2dca218edf40e6"},
 ]
 
 [[package]]
 name = "click"
-version = "8.1.3"
+version = "8.1.6"
 description = "Composable command line interface toolkit"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "click-8.1.3-py3-none-any.whl", hash = "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"},
-    {file = "click-8.1.3.tar.gz", hash = "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e"},
+    {file = "click-8.1.6-py3-none-any.whl", hash = "sha256:fa244bb30b3b5ee2cae3da8f55c9e5e0c0e86093306301fb418eb9dc40fbded5"},
+    {file = "click-8.1.6.tar.gz", hash = "sha256:48ee849951919527a045bfe3bf7baa8a959c423134e1a5b98c05c20ba75a1cbd"},
 ]
 
 [package.dependencies]
@@ -223,13 +223,13 @@ toml = ["tomli"]
 
 [[package]]
 name = "distlib"
-version = "0.3.6"
+version = "0.3.7"
 description = "Distribution utilities"
 optional = false
 python-versions = "*"
 files = [
-    {file = "distlib-0.3.6-py2.py3-none-any.whl", hash = "sha256:f35c4b692542ca110de7ef0bea44d73981caeb34ca0b9b6b2e6d7790dda8f80e"},
-    {file = "distlib-0.3.6.tar.gz", hash = "sha256:14bad2d9b04d3a36127ac97f30b12a19268f211063d8f8ee4f47108896e11b46"},
+    {file = "distlib-0.3.7-py2.py3-none-any.whl", hash = "sha256:2e24928bc811348f0feb63014e97aaae3037f2cf48712d51ae61df7fd6075057"},
+    {file = "distlib-0.3.7.tar.gz", hash = "sha256:9dafe54b34a028eafd95039d5e5d4851a13734540f1331060d31c9916e7147a8"},
 ]
 
 [[package]]
@@ -245,13 +245,13 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.1"
+version = "1.1.2"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.1.1-py3-none-any.whl", hash = "sha256:232c37c63e4f682982c8b6459f33a8981039e5fb8756b2074364e5055c498c9e"},
-    {file = "exceptiongroup-1.1.1.tar.gz", hash = "sha256:d484c3090ba2889ae2928419117447a14daf3c1231d5e30d0aae34f354f01785"},
+    {file = "exceptiongroup-1.1.2-py3-none-any.whl", hash = "sha256:e346e69d186172ca7cf029c8c1d16235aa0e04035e5750b4b95039e65204328f"},
+    {file = "exceptiongroup-1.1.2.tar.gz", hash = "sha256:12c3e887d6485d16943a309616de20ae5582633e0a2eda17f4e10fd61c1e8af5"},
 ]
 
 [package.extras]
@@ -259,52 +259,52 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "filelock"
-version = "3.12.0"
+version = "3.12.2"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "filelock-3.12.0-py3-none-any.whl", hash = "sha256:ad98852315c2ab702aeb628412cbf7e95b7ce8c3bf9565670b4eaecf1db370a9"},
-    {file = "filelock-3.12.0.tar.gz", hash = "sha256:fc03ae43288c013d2ea83c8597001b1129db351aad9c57fe2409327916b8e718"},
+    {file = "filelock-3.12.2-py3-none-any.whl", hash = "sha256:cbb791cdea2a72f23da6ac5b5269ab0a0d161e9ef0100e653b69049a7706d1ec"},
+    {file = "filelock-3.12.2.tar.gz", hash = "sha256:002740518d8aa59a26b0c76e10fb8c6e15eae825d34b6fdf670333fd7b938d81"},
 ]
 
 [package.extras]
-docs = ["furo (>=2023.3.27)", "sphinx (>=6.1.3)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
+docs = ["furo (>=2023.5.20)", "sphinx (>=7.0.1)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4.1)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
 
 [[package]]
 name = "google-api-core"
-version = "2.11.0"
+version = "2.11.1"
 description = "Google API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.11.0.tar.gz", hash = "sha256:4b9bb5d5a380a0befa0573b302651b8a9a89262c1730e37bf423cec511804c22"},
-    {file = "google_api_core-2.11.0-py3-none-any.whl", hash = "sha256:ce222e27b0de0d7bc63eb043b956996d6dccab14cc3b690aaea91c9cc99dc16e"},
+    {file = "google-api-core-2.11.1.tar.gz", hash = "sha256:25d29e05a0058ed5f19c61c0a78b1b53adea4d9364b464d014fbda941f6d1c9a"},
+    {file = "google_api_core-2.11.1-py3-none-any.whl", hash = "sha256:d92a5a92dc36dd4f4b9ee4e55528a90e432b059f93aee6ad857f9de8cc7ae94a"},
 ]
 
 [package.dependencies]
-google-auth = ">=2.14.1,<3.0dev"
-googleapis-common-protos = ">=1.56.2,<2.0dev"
+google-auth = ">=2.14.1,<3.0.dev0"
+googleapis-common-protos = ">=1.56.2,<2.0.dev0"
 grpcio = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-grpcio-status = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-requests = ">=2.18.0,<3.0.0dev"
+grpcio-status = {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "extra == \"grpc\""}
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0.dev0"
+requests = ">=2.18.0,<3.0.0.dev0"
 
 [package.extras]
-grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status (>=1.33.2,<2.0dev)", "grpcio-status (>=1.49.1,<2.0dev)"]
-grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
-grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
+grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status (>=1.33.2,<2.0.dev0)", "grpcio-status (>=1.49.1,<2.0.dev0)"]
+grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
+grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.19.1"
+version = "2.22.0"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "google-auth-2.19.1.tar.gz", hash = "sha256:a9cfa88b3e16196845e64a3658eb953992129d13ac7337b064c6546f77c17183"},
-    {file = "google_auth-2.19.1-py2.py3-none-any.whl", hash = "sha256:ea165e014c7cbd496558796b627c271aa8c18b4cba79dc1cc962b24c5efdfb85"},
+    {file = "google-auth-2.22.0.tar.gz", hash = "sha256:164cba9af4e6e4e40c3a4f90a1a6c12ee56f14c0b4868d1ca91b32826ab334ce"},
+    {file = "google_auth-2.22.0-py2.py3-none-any.whl", hash = "sha256:d61d1b40897407b574da67da1a833bdc10d5a11642566e506565d1b1a46ba873"},
 ]
 
 [package.dependencies]
@@ -315,21 +315,21 @@ six = ">=1.9.0"
 urllib3 = "<2.0"
 
 [package.extras]
-aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "requests (>=2.20.0,<3.0.0dev)"]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0.dev0)", "requests (>=2.20.0,<3.0.0.dev0)"]
 enterprise-cert = ["cryptography (==36.0.2)", "pyopenssl (==22.0.0)"]
 pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
-requests = ["requests (>=2.20.0,<3.0.0dev)"]
+requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.24.1"
+version = "1.30.1"
 description = "Vertex AI API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-aiplatform-1.24.1.tar.gz", hash = "sha256:0ce9e97bf5c977397e52b3b7c4dc78610c135fbde11a60a6c0b77a4fdf776400"},
-    {file = "google_cloud_aiplatform-1.24.1-py2.py3-none-any.whl", hash = "sha256:942765a6bad97e46e262dd6599dc5f171663ce952130e0b0b2eb97e0b1b98bfd"},
+    {file = "google-cloud-aiplatform-1.30.1.tar.gz", hash = "sha256:7552a6b2e66d7a9ff3c4b2bb95b0e9c182e7475dfb35d6347e9299f78779135a"},
+    {file = "google_cloud_aiplatform-1.30.1-py2.py3-none-any.whl", hash = "sha256:ab1bbd4cf83cf583b7dea7e53421ad076f18b63e93cb22fb53c03176d5aa9258"},
 ]
 
 [package.dependencies]
@@ -347,26 +347,26 @@ autologging = ["mlflow (>=1.27.0,<=2.1.1)"]
 cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
 datasets = ["pyarrow (>=3.0.0,<8.0dev)"]
 endpoint = ["requests (>=2.28.1)"]
-full = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pyyaml (>=5.3,<6)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
+full = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pyyaml (>=5.3,<7)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
 lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"]
 metadata = ["numpy (>=1.15.0)", "pandas (>=1.0.0)"]
-pipelines = ["pyyaml (>=5.3,<6)"]
+pipelines = ["pyyaml (>=5.3,<7)"]
 prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<0.76.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"]
 private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"]
 tensorboard = ["tensorflow (>=2.3.0,<3.0.0dev)"]
-testing = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "grpcio-testing", "ipython", "kfp", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3,<6)", "requests (>=2.28.1)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
+testing = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "grpcio-testing", "ipython", "kfp", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3,<7)", "requests (>=2.28.1)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
 vizier = ["google-vizier (==0.0.4)"]
 xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "3.11.0"
+version = "3.11.4"
 description = "Google BigQuery API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-bigquery-3.11.0.tar.gz", hash = "sha256:3a1c1b3566f9f27ea83a36aaf54eb879444ee73ef42456764018a0b3b556d0fb"},
-    {file = "google_cloud_bigquery-3.11.0-py2.py3-none-any.whl", hash = "sha256:f568c36dfc9b8a2cf7e8ac10dd0889e0a52e8edf3dd556f3dd1eb441eda14364"},
+    {file = "google-cloud-bigquery-3.11.4.tar.gz", hash = "sha256:697df117241a2283bcbb93b21e10badc14e51c9a90800d2a7e1a3e1c7d842974"},
+    {file = "google_cloud_bigquery-3.11.4-py2.py3-none-any.whl", hash = "sha256:5fa7897743a0ed949ade25a0942fc9e7557d8fce307c6f8a76d1b604cf27f1b1"},
 ]
 
 [package.dependencies]
@@ -392,13 +392,13 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 
 [[package]]
 name = "google-cloud-core"
-version = "2.3.2"
+version = "2.3.3"
 description = "Google Cloud API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-core-2.3.2.tar.gz", hash = "sha256:b9529ee7047fd8d4bf4a2182de619154240df17fbe60ead399078c1ae152af9a"},
-    {file = "google_cloud_core-2.3.2-py2.py3-none-any.whl", hash = "sha256:8417acf6466be2fa85123441696c4badda48db314c607cf1e5d543fa8bdc22fe"},
+    {file = "google-cloud-core-2.3.3.tar.gz", hash = "sha256:37b80273c8d7eee1ae816b3a20ae43585ea50506cb0e60f3cf5be5f87f1373cb"},
+    {file = "google_cloud_core-2.3.3-py2.py3-none-any.whl", hash = "sha256:fbd11cad3e98a7e5b0343dc07cb1039a5ffd7a5bb96e1f1e27cee4bda4a90863"},
 ]
 
 [package.dependencies]
@@ -410,12 +410,12 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "2.1.0"
+version = "2.1.1"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "google_cloud_pipeline_components-2.1.0-py3-none-any.whl", hash = "sha256:ddd6afd8e1ab302a3176d60934f289fb609faeacea09292f62d7eb3576e3e321"},
+    {file = "google_cloud_pipeline_components-2.1.1-py3-none-any.whl", hash = "sha256:fdb1621a1db112833a299bfe6353edd2eb7b9195e0d39896491c75e0b6624dcc"},
 ]
 
 [package.dependencies]
@@ -429,13 +429,13 @@ tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
-version = "1.10.1"
+version = "1.10.3"
 description = "Google Cloud Resource Manager API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-resource-manager-1.10.1.tar.gz", hash = "sha256:c974fb6f9810476cf7b63ea89394c1a8df47f7f2dc2303e728bb74b500bcde67"},
-    {file = "google_cloud_resource_manager-1.10.1-py2.py3-none-any.whl", hash = "sha256:41a2204532f084c707fde0bc1a9bc95c7e0b739d7072dd0b8a25106667a56184"},
+    {file = "google-cloud-resource-manager-1.10.3.tar.gz", hash = "sha256:f80efcea36f10c5a81889afe93910926e3978b4b1ceeb82f563a2fc863072d14"},
+    {file = "google_cloud_resource_manager-1.10.3-py2.py3-none-any.whl", hash = "sha256:1381a4b0f522248ebe0ebd1289d8822b99c54f4e1fe03924a6e723b2ed93dd7f"},
 ]
 
 [package.dependencies]
@@ -446,13 +446,13 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.9.0"
+version = "2.10.0"
 description = "Google Cloud Storage API client library"
 optional = false
 python-versions = ">=3.7"
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@@ -565,21 +565,21 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
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+version = "1.60.0"
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 [package.extras]
-grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
+grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 
 [[package]]
 name = "grpc-google-iam-v1"
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 ]
 
 [package.extras]
-protobuf = ["grpcio-tools (>=1.54.2)"]
+protobuf = ["grpcio-tools (>=1.57.0)"]
 
 [[package]]
 name = "grpcio-status"
-version = "1.47.0"
+version = "1.48.2"
 description = "Status proto mapping for gRPC"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
 googleapis-common-protos = ">=1.5.5"
-grpcio = ">=1.47.0"
+grpcio = ">=1.48.2"
 protobuf = ">=3.12.0"
 
 [[package]]
 name = "identify"
-version = "2.5.24"
+version = "2.5.26"
 description = "File identification library for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -783,13 +783,13 @@ urllib3 = ">=1.15"
 
 [[package]]
 name = "kubernetes"
-version = "25.3.0"
+version = "26.1.0"
 description = "Kubernetes python client"
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [package.dependencies]
@@ -809,61 +809,61 @@ adal = ["adal (>=1.0.2)"]
 
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 description = "Safely add untrusted strings to HTML/XML markup."
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 python-versions = ">=3.7"
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 [[package]]
@@ -909,28 +909,28 @@ files = [
 
 [[package]]
 name = "platformdirs"
-version = "3.5.1"
+version = "3.10.0"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
 optional = false
 python-versions = ">=3.7"
 files = [
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-test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.3.1)", "pytest-cov (>=4)", "pytest-mock (>=3.10)"]
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 [[package]]
 name = "pluggy"
-version = "1.0.0"
+version = "1.2.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
-python-versions = ">=3.6"
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 [package.extras]
@@ -957,13 +957,13 @@ virtualenv = ">=20.10.0"
 
 [[package]]
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-version = "1.22.2"
+version = "1.22.3"
 description = "Beautiful, Pythonic protocol buffers."
 optional = false
 python-versions = ">=3.6"
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 ]
 
 [package.dependencies]
@@ -1030,13 +1030,13 @@ pyasn1 = ">=0.4.6,<0.6.0"
 
 [[package]]
 name = "pytest"
-version = "7.3.1"
+version = "7.4.0"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.7"
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 [package.dependencies]
@@ -1048,7 +1048,7 @@ pluggy = ">=0.12,<2.0"
 tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
-testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"]
+testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "python-dateutil"
@@ -1066,40 +1066,51 @@ six = ">=1.5"
 
 [[package]]
 name = "pyyaml"
-version = "5.4.1"
+version = "6.0.1"
 description = "YAML parser and emitter for Python"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
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+    {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e07cbde391ba96ab58e532ff4803f79c4129397514e1413a7dc761ccd755735"},
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+    {file = "PyYAML-6.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:1e2722cc9fbb45d9b87631ac70924c11d3a401b2d7f410cc0e3bbf249f2dca62"},
+    {file = "PyYAML-6.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9eb6caa9a297fc2c2fb8862bc5370d0303ddba53ba97e71f08023b6cd73d16a8"},
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+    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"},
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+    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"},
+    {file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"},
+    {file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
+    {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
 ]
 
 [[package]]
@@ -1171,13 +1182,13 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "setuptools"
-version = "67.8.0"
+version = "68.0.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "setuptools-67.8.0-py3-none-any.whl", hash = "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f"},
-    {file = "setuptools-67.8.0.tar.gz", hash = "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"},
+    {file = "setuptools-68.0.0-py3-none-any.whl", hash = "sha256:11e52c67415a381d10d6b462ced9cfb97066179f0e871399e006c4ab101fc85f"},
+    {file = "setuptools-68.0.0.tar.gz", hash = "sha256:baf1fdb41c6da4cd2eae722e135500da913332ab3f2f5c7d33af9b492acb5235"},
 ]
 
 [package.extras]
@@ -1311,33 +1322,33 @@ url = "../components/vertex-components"
 
 [[package]]
 name = "virtualenv"
-version = "20.23.0"
+version = "20.24.3"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.23.0-py3-none-any.whl", hash = "sha256:6abec7670e5802a528357fdc75b26b9f57d5d92f29c5462ba0fbe45feacc685e"},
-    {file = "virtualenv-20.23.0.tar.gz", hash = "sha256:a85caa554ced0c0afbd0d638e7e2d7b5f92d23478d05d17a76daeac8f279f924"},
+    {file = "virtualenv-20.24.3-py3-none-any.whl", hash = "sha256:95a6e9398b4967fbcb5fef2acec5efaf9aa4972049d9ae41f95e0972a683fd02"},
+    {file = "virtualenv-20.24.3.tar.gz", hash = "sha256:e5c3b4ce817b0b328af041506a2a299418c98747c4b1e68cb7527e74ced23efc"},
 ]
 
 [package.dependencies]
-distlib = ">=0.3.6,<1"
-filelock = ">=3.11,<4"
-platformdirs = ">=3.2,<4"
+distlib = ">=0.3.7,<1"
+filelock = ">=3.12.2,<4"
+platformdirs = ">=3.9.1,<4"
 
 [package.extras]
-docs = ["furo (>=2023.3.27)", "proselint (>=0.13)", "sphinx (>=6.1.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=22.12)"]
-test = ["covdefaults (>=2.3)", "coverage (>=7.2.3)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.3.1)", "pytest-env (>=0.8.1)", "pytest-freezegun (>=0.4.2)", "pytest-mock (>=3.10)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=67.7.1)", "time-machine (>=2.9)"]
+docs = ["furo (>=2023.5.20)", "proselint (>=0.13)", "sphinx (>=7.0.1)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [[package]]
 name = "websocket-client"
-version = "1.5.2"
+version = "1.6.1"
 description = "WebSocket client for Python with low level API options"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "websocket-client-1.5.2.tar.gz", hash = "sha256:c7d67c13b928645f259d9b847ab5b57fd2d127213ca41ebd880de1f553b7c23b"},
-    {file = "websocket_client-1.5.2-py3-none-any.whl", hash = "sha256:f8c64e28cd700e7ba1f04350d66422b6833b82a796b525a51e740b8cc8dab4b1"},
+    {file = "websocket-client-1.6.1.tar.gz", hash = "sha256:c951af98631d24f8df89ab1019fc365f2227c0892f12fd150e935607c79dd0dd"},
+    {file = "websocket_client-1.6.1-py3-none-any.whl", hash = "sha256:f1f9f2ad5291f0225a49efad77abf9e700b6fef553900623060dad6e26503b9d"},
 ]
 
 [package.extras]
@@ -1348,4 +1359,4 @@ test = ["websockets"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "8430eb49df1dcdfd43c734f1850e97657a2f1b346cb7407778cf7f4cf1be46a0"
+content-hash = "6bb3645ba47001dbf63d97b06f3ab9086d3f444ac3876524dbb0a5f567eebe65"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 08c07fad..6e533bb2 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -16,7 +16,7 @@ packages = [
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
 Jinja2 = ">=3.0.1,<4.0.0"
-google-cloud-aiplatform = "1.24.1"
+google-cloud-aiplatform = "1.30.1"
 google-cloud-pipeline-components = "^2.1.0"
 bigquery-components = { path = "../components/bigquery-components", develop = true }
 vertex-components = { path = "../components/vertex-components", develop = true }
diff --git a/terraform/modules/cloudfunction/src/requirements.txt b/terraform/modules/cloudfunction/src/requirements.txt
index 75056d44..85105362 100644
--- a/terraform/modules/cloudfunction/src/requirements.txt
+++ b/terraform/modules/cloudfunction/src/requirements.txt
@@ -12,4 +12,4 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-google-cloud-aiplatform==1.24.1
+google-cloud-aiplatform[pipelines]==1.24.1

From 438c01e874d082160dbad89a34a06396cc92e93e Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 14 Aug 2023 11:41:42 +0100
Subject: [PATCH 149/238] fix: terraform variables file

---
 .../scheduled_pipelines/scheduled_jobs.auto.tfvars.example    | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
index 54c25bb4..22dc5dca 100644
--- a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
+++ b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
@@ -27,7 +27,6 @@ cloud_schedulers_config = {
       project_location = "europe-west2"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
-      model_label = "label_name"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
@@ -43,10 +42,9 @@ cloud_schedulers_config = {
     enable_caching = null
     pipeline_parameters = {
       project_id = "my-project-id"
-      project_location = "europe-west4"
+      project_location = "europe-west2"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
-      model_label = "label_name"
       dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"

From 2c8ce1ef712477b6169db37cce1ed4cc73620b61 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 14 Aug 2023 12:04:04 +0100
Subject: [PATCH 150/238] fix: add more permissions to CF service account

---
 terraform/modules/vertex_deployment/iam.tf | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/terraform/modules/vertex_deployment/iam.tf b/terraform/modules/vertex_deployment/iam.tf
index 2d58475a..1df87314 100644
--- a/terraform/modules/vertex_deployment/iam.tf
+++ b/terraform/modules/vertex_deployment/iam.tf
@@ -33,6 +33,22 @@ resource "google_service_account_iam_member" "cloudfunction_sa_can_use_pipelines
   member             = google_service_account.vertex_cloudfunction_sa.member
 }
 
+# Give cloud functions SA access to KFP Artifact Registry to access compiled pipelines
+resource "google_artifact_registry_repository_iam_member" "cloudfunction_sa_can_access_ar" {
+  project    = google_artifact_registry_repository.vertex-pipelines.project
+  location   = google_artifact_registry_repository.vertex-pipelines.location
+  repository = google_artifact_registry_repository.vertex-pipelines.name
+  role       = "roles/artifactregistry.reader"
+  member     = google_service_account.vertex_cloudfunction_sa.member
+}
+
+# Give cloud functions SA access to pipeline root bucket to check it exists
+resource "google_storage_bucket_iam_member" "cloudfunction_sa_can_get_pl_root_bucket" {
+  bucket = google_storage_bucket.pipeline_root_bucket.name
+  role   = "roles/storage.legacyBucketReader"
+  member = google_service_account.vertex_cloudfunction_sa.member
+}
+
 ## Project IAM roles ##
 
 # Vertex Pipelines SA project roles

From 72c78603bf9b829bb2433d53ab04e4a6b2f52cb0 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 14 Aug 2023 12:14:18 +0100
Subject: [PATCH 151/238] docs: fix example terraform config

---
 .../scheduled_pipelines/scheduled_jobs.auto.tfvars.example       | 1 -
 1 file changed, 1 deletion(-)

diff --git a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
index 22dc5dca..f864e7e9 100644
--- a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
+++ b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
@@ -45,7 +45,6 @@ cloud_schedulers_config = {
       project_location = "europe-west2"
       ingestion_project_id = "my-project-id"
       model_name = "xgboost_with_preprocessing"
-      dataset_id = "preprocessing"
       dataset_location = "europe-west2"
       ingestion_dataset_id = "chicago_taxi_trips"
       timestamp = "2022-12-01 00:00:00"

From e61c53935062c58980b8e50dce6cdd953409fb18 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Mon, 14 Aug 2023 17:25:27 +0100
Subject: [PATCH 152/238] fix: add workaround for Vertex Pipelines bug

---
 terraform/modules/cloudfunction/src/main.py   | 22 ++++++
 .../cloudfunction/src/requirements.txt        |  1 +
 .../modules/cloudfunction/test/test_main.py   | 69 ++++++++++++++++++-
 3 files changed, 89 insertions(+), 3 deletions(-)

diff --git a/terraform/modules/cloudfunction/src/main.py b/terraform/modules/cloudfunction/src/main.py
index 9a283787..767e3e18 100644
--- a/terraform/modules/cloudfunction/src/main.py
+++ b/terraform/modules/cloudfunction/src/main.py
@@ -15,8 +15,10 @@
 import base64
 import json
 import os
+import re
 from distutils.util import strtobool
 from google.cloud import aiplatform
+from kfp.registry import RegistryClient
 
 
 def cf_handler(event, context):
@@ -59,6 +61,26 @@ def cf_handler(event, context):
     encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER") or None
     network = os.environ.get("VERTEX_NETWORK") or None
 
+    # If template_path is an AR URL and a tag is used, resolve to exact version
+    # Workaround for known issue
+    # https://github.com/googleapis/python-aiplatform/issues/2181
+    _VALID_AR_URL = re.compile(
+        r"https://([\w\-]+)-kfp\.pkg\.dev/([\w\-]+)/([\w\-]+)/([\w\-]+)/([\w\-.]+)",
+        re.IGNORECASE,
+    )
+    match = _VALID_AR_URL.match(template_path)
+    if match and "sha256:" not in template_path:
+        region = match.group(1)
+        project = match.group(2)
+        repo = match.group(3)
+        package_name = match.group(4)
+        tag = match.group(5)
+        host = f"https://{region}-kfp.pkg.dev/{project}/{repo}"
+        client = RegistryClient(host=host)
+        metadata = client.get_tag(package_name, tag)
+        version = metadata["version"][metadata["version"].find("sha256:") :]
+        template_path = f"{host}/{package_name}/{version}"
+
     # Instantiate PipelineJob object
     pl = aiplatform.pipeline_jobs.PipelineJob(
         project=project_id,
diff --git a/terraform/modules/cloudfunction/src/requirements.txt b/terraform/modules/cloudfunction/src/requirements.txt
index 85105362..76cbee80 100644
--- a/terraform/modules/cloudfunction/src/requirements.txt
+++ b/terraform/modules/cloudfunction/src/requirements.txt
@@ -13,3 +13,4 @@
 # limitations under the License.
 
 google-cloud-aiplatform[pipelines]==1.24.1
+kfp==2.1.2
diff --git a/terraform/modules/cloudfunction/test/test_main.py b/terraform/modules/cloudfunction/test/test_main.py
index c4cc06fa..4d54dbaf 100644
--- a/terraform/modules/cloudfunction/test/test_main.py
+++ b/terraform/modules/cloudfunction/test/test_main.py
@@ -18,8 +18,6 @@
 import base64
 import json
 
-from src.main import cf_handler
-
 
 @pytest.mark.parametrize(
     "test_enable_caching_input,enable_caching_expected",
@@ -34,7 +32,7 @@
     ],
 )
 @mock.patch("google.cloud.aiplatform.pipeline_jobs.PipelineJob")
-def test_trigger_pipeline(
+def test_trigger_pipeline_local_yaml(
     mock_pipelinejob, test_enable_caching_input, enable_caching_expected
 ):
 
@@ -74,6 +72,8 @@ def test_trigger_pipeline(
 
     with mock.patch.dict(os.environ, env_vars):
 
+        from src.main import cf_handler
+
         cf_handler(event, None)
 
         mock_pipelinejob.assert_called_with(
@@ -91,3 +91,66 @@ def test_trigger_pipeline(
             service_account=service_account,
             network=network,
         )
+
+
+@mock.patch("src.main.RegistryClient")
+@mock.patch("google.cloud.aiplatform.pipeline_jobs.PipelineJob")
+def test_trigger_pipeline_ar_yaml_with_tag(mock_pipelinejob, mock_registryclient):
+
+    template_path = "https://europe-west2-kfp.pkg.dev/project/repo/package_name/tag"
+    enable_caching = None
+    pipeline_root = "gs://my-pipeline-root/abc123"
+    encryption_spec_key_name = "dummy_encryption_spec_key_name"
+    project_id = "dummy_project_id"
+    region = "dummy_region"
+    service_account = "dummy_sa@dummy_project_id.iam.gserviceaccount.com"
+    network = "dummy_network"
+    display_name = "my first pipeline"
+
+    payload = {
+        "template_path": template_path,
+        "display_name": display_name,
+        "pipeline_parameters": {
+            "foo": "bar",
+            "abc": 123,
+        },
+    }
+
+    if enable_caching is not None:
+        payload["enable_pipeline_caching"] = enable_caching
+
+    # encode as base64 to feed into Cloud Function
+    event = {"data": base64.b64encode(json.dumps(payload).encode("utf-8"))}
+
+    env_vars = {
+        "VERTEX_PROJECT_ID": project_id,
+        "VERTEX_LOCATION": region,
+        "VERTEX_SA_EMAIL": service_account,
+        "VERTEX_NETWORK": network,
+        "VERTEX_CMEK_IDENTIFIER": encryption_spec_key_name,
+        "VERTEX_PIPELINE_ROOT": pipeline_root,
+    }
+
+    with mock.patch.dict(os.environ, env_vars):
+        from src.main import cf_handler
+
+        cf_handler(event, None)
+
+        mock_pipelinejob.assert_called_with(
+            project=project_id,
+            location=region,
+            display_name=display_name,
+            enable_caching=None,
+            template_path=(
+                f"https://europe-west2-kfp.pkg.dev/project/repo/package_name/"
+                f"{mock_registryclient.return_value.get_tag.return_value.__getitem__().__getitem__()}"  # noqa
+            ),
+            pipeline_root=pipeline_root,
+            encryption_spec_key_name=encryption_spec_key_name,
+            parameter_values=payload["pipeline_parameters"],
+        )
+
+        mock_pipelinejob.return_value.submit.assert_called_with(
+            service_account=service_account,
+            network=network,
+        )

From 0e37aba73f6a9979fd28ab5a6f80b7ccd094f169 Mon Sep 17 00:00:00 2001
From: "Jonny Browning (Datatonic)"
 <78856444+browningjp-datatonic@users.noreply.github.com>
Date: Tue, 15 Aug 2023 09:34:26 +0100
Subject: [PATCH 153/238] refactor: tidy regex group

Co-authored-by: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
---
 terraform/modules/cloudfunction/src/main.py | 6 +-----
 1 file changed, 1 insertion(+), 5 deletions(-)

diff --git a/terraform/modules/cloudfunction/src/main.py b/terraform/modules/cloudfunction/src/main.py
index 767e3e18..c9eceb7b 100644
--- a/terraform/modules/cloudfunction/src/main.py
+++ b/terraform/modules/cloudfunction/src/main.py
@@ -70,11 +70,7 @@ def cf_handler(event, context):
     )
     match = _VALID_AR_URL.match(template_path)
     if match and "sha256:" not in template_path:
-        region = match.group(1)
-        project = match.group(2)
-        repo = match.group(3)
-        package_name = match.group(4)
-        tag = match.group(5)
+        region, project, repo, package_name, tag = match.group(1,2,3,4,5)
         host = f"https://{region}-kfp.pkg.dev/{project}/{repo}"
         client = RegistryClient(host=host)
         metadata = client.get_tag(package_name, tag)

From 59bd7e6965b1eb1539ef77379d26db5df605ddf0 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 15 Aug 2023 09:37:25 +0100
Subject: [PATCH 154/238] fix: bump google-cloud-aiplatform version in cloud
 function

---
 terraform/modules/cloudfunction/src/requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/terraform/modules/cloudfunction/src/requirements.txt b/terraform/modules/cloudfunction/src/requirements.txt
index 76cbee80..3567f18a 100644
--- a/terraform/modules/cloudfunction/src/requirements.txt
+++ b/terraform/modules/cloudfunction/src/requirements.txt
@@ -12,5 +12,5 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-google-cloud-aiplatform[pipelines]==1.24.1
+google-cloud-aiplatform[pipelines]==1.30.1
 kfp==2.1.2

From 8b66dc0342655e9e39065e841bbde742feb83323 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 15 Aug 2023 09:41:49 +0100
Subject: [PATCH 155/238] fix: update ENABLE_PIPELINE_CACHING env var

---
 Makefile                                          | 4 ++--
 cloudbuild/e2e-test.yaml                          | 5 +++--
 pipelines/src/pipelines/utils/trigger_pipeline.py | 2 +-
 pipelines/tests/utils/test_trigger_pipeline.py    | 6 +++---
 4 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/Makefile b/Makefile
index 0db5ca45..d052d930 100644
--- a/Makefile
+++ b/Makefile
@@ -69,12 +69,12 @@ test-all-components-coverage: ## Run tests with coverage
 		$(MAKE) test-components-coverage GROUP=$$(basename $$component_group) ; \
 	done
 
-run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
+run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour)
 	@ $(MAKE) compile-pipeline && \
 	cd pipelines/src && \
 	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline}
 
-e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour).
+e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour).
 	@ cd pipelines && \
 	poetry run pytest --log-cli-level=INFO tests/$(pipeline)
 
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index b6724cec..c2e77696 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -45,9 +45,10 @@ steps:
         curl -sSL https://install.python-poetry.org | python3 - && \
         export PATH="/builder/home/.local/bin:$$PATH" && \
         make setup && \
-        make e2e-tests pipeline=training enable_pipeline_caching=False && \
-        make e2e-tests pipeline=prediction enable_pipeline_caching=False
+        make e2e-tests pipeline=training && \
+        make e2e-tests pipeline=prediction
     env:
+      - ENABLE_PIPELINE_CACHING=${_TEST_ENABLE_PIPELINE_CACHING}
       - VERTEX_LOCATION=${_TEST_VERTEX_LOCATION}
       - VERTEX_PROJECT_ID=${_TEST_VERTEX_PROJECT_ID}
       - VERTEX_SA_EMAIL=${_TEST_VERTEX_SA_EMAIL}
diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index 3984e40b..6a739421 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -36,7 +36,7 @@ def trigger_pipeline(
     pipeline_root = os.environ["VERTEX_PIPELINE_ROOT"]
     service_account = os.environ["VERTEX_SA_EMAIL"]
 
-    enable_caching = os.environ.get("enable_pipeline_caching", None)
+    enable_caching = os.environ.get("ENABLE_PIPELINE_CACHING", None)
     if enable_caching:
         enable_caching = bool(strtobool(enable_caching))
 
diff --git a/pipelines/tests/utils/test_trigger_pipeline.py b/pipelines/tests/utils/test_trigger_pipeline.py
index 7ba37f1e..7972a1b3 100644
--- a/pipelines/tests/utils/test_trigger_pipeline.py
+++ b/pipelines/tests/utils/test_trigger_pipeline.py
@@ -21,14 +21,14 @@
 
 @pytest.mark.parametrize(
     "test_enable_caching_input,enable_caching_expected",
-    # test for different values of "enable_pipeline_caching" env var (left)
+    # test for different values of "ENABLE_PIPELINE_CACHING" env var (left)
     # vs actual value passed to PipelineJob enable_caching (right)
     [
         ("True", True),
         ("true", True),
         ("False", False),
         ("false", False),
-        (None, None),  # enable_pipeline_caching env var not set
+        (None, None),  # ENABLE_PIPELINE_CACHING env var not set
     ],
 )
 @mock.patch("google.cloud.aiplatform.PipelineJob")
@@ -56,7 +56,7 @@ def test_trigger_pipeline(
     }
 
     if enable_caching is not None:
-        env_vars["enable_pipeline_caching"] = enable_caching
+        env_vars["ENABLE_PIPELINE_CACHING"] = enable_caching
 
     with mock.patch.dict(os.environ, env_vars):
 

From 4db1c2c170694e0456b5cc58a62d7c90c33f654b Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 15 Aug 2023 09:43:04 +0100
Subject: [PATCH 156/238] refactor: remove redundant default value

---
 pipelines/src/pipelines/utils/trigger_pipeline.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index 6a739421..78c800e2 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -36,7 +36,7 @@ def trigger_pipeline(
     pipeline_root = os.environ["VERTEX_PIPELINE_ROOT"]
     service_account = os.environ["VERTEX_SA_EMAIL"]
 
-    enable_caching = os.environ.get("ENABLE_PIPELINE_CACHING", None)
+    enable_caching = os.environ.get("ENABLE_PIPELINE_CACHING")
     if enable_caching:
         enable_caching = bool(strtobool(enable_caching))
 

From ce82e95ca403c0407132cea4cd3d2898f9b3a7f5 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Tue, 15 Aug 2023 09:50:43 +0100
Subject: [PATCH 157/238] test: tidy test imports

---
 pipelines/tests/utils/test_upload_pipeline.py     | 5 +----
 terraform/modules/cloudfunction/test/test_main.py | 4 +---
 2 files changed, 2 insertions(+), 7 deletions(-)

diff --git a/pipelines/tests/utils/test_upload_pipeline.py b/pipelines/tests/utils/test_upload_pipeline.py
index e7d93a8b..00830696 100644
--- a/pipelines/tests/utils/test_upload_pipeline.py
+++ b/pipelines/tests/utils/test_upload_pipeline.py
@@ -14,6 +14,7 @@
 
 from unittest import mock
 import pytest
+from pipelines.utils.upload_pipeline import main, upload_pipeline
 
 
 @pytest.mark.parametrize(
@@ -39,8 +40,6 @@ def test_main(mock_upload_pipeline, input_tags):
     if input_tags:
         args.extend([f"--tag={tag}" for tag in input_tags])
 
-    from pipelines.utils.upload_pipeline import main
-
     main(args)
 
     mock_upload_pipeline.assert_called_with(
@@ -58,8 +57,6 @@ def test_upload_pipeline(mock_registry_client):
 
     input_tags = ["dummy_tag1", "dummy_tag2"]
 
-    from pipelines.utils.upload_pipeline import upload_pipeline
-
     upload_pipeline(
         host=dest,
         file_name=yaml,
diff --git a/terraform/modules/cloudfunction/test/test_main.py b/terraform/modules/cloudfunction/test/test_main.py
index 4d54dbaf..42b546ff 100644
--- a/terraform/modules/cloudfunction/test/test_main.py
+++ b/terraform/modules/cloudfunction/test/test_main.py
@@ -17,6 +17,7 @@
 import os
 import base64
 import json
+from src.main import cf_handler
 
 
 @pytest.mark.parametrize(
@@ -72,8 +73,6 @@ def test_trigger_pipeline_local_yaml(
 
     with mock.patch.dict(os.environ, env_vars):
 
-        from src.main import cf_handler
-
         cf_handler(event, None)
 
         mock_pipelinejob.assert_called_with(
@@ -132,7 +131,6 @@ def test_trigger_pipeline_ar_yaml_with_tag(mock_pipelinejob, mock_registryclient
     }
 
     with mock.patch.dict(os.environ, env_vars):
-        from src.main import cf_handler
 
         cf_handler(event, None)
 

From c14c299a8d48d89ebc9efe2e3b83c5ce16db3341 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 15 Aug 2023 15:52:25 +0100
Subject: [PATCH 158/238] refactor(Makefile): simplify make commands

---
 Makefile | 123 ++++++++++++++++++++++++++++---------------------------
 1 file changed, 62 insertions(+), 61 deletions(-)

diff --git a/Makefile b/Makefile
index 13020ced..6c20a715 100644
--- a/Makefile
+++ b/Makefile
@@ -23,77 +23,78 @@ pre-commit: ## Runs the pre-commit checks over entire repo
 	cd pipelines && \
 	poetry run pre-commit run --all-files
 
-setup: ## Set up local environment for Python development on pipelines
-	@cd pipelines && \
-	poetry install --with dev
+env ?= dev
+deploy: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
+	@ cd terraform/envs/$(env) && \
+	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
+	terraform apply -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
+
+undeploy: ## DESTROY the Terraform infrastructure in your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
+	@ cd terraform/envs/$(env) && \
+	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
+	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
 
-test-trigger: ## Runs unit tests for the pipeline trigger code
+install: ## Set up local environment for Python development on pipelines
 	@cd pipelines && \
-	poetry run python -m pytest tests/trigger
+	poetry install --with dev && \
+	cd .. && \
+	for component_group in components/*/ ; do \
+		echo "Setup for $$component_group" && \
+		cd "$$component_group" && \
+		poetry install --with dev && \
+		cd ../.. ;\
+	done ; \
 
-compile-pipeline: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
+
+compile: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
 	@cd pipelines/src && \
 	poetry run kfp dsl compile --py pipelines/${pipeline}/pipeline.py --output pipelines/${pipeline}/pipeline.yaml --function pipeline
 
-setup-components: ## Run unit tests for a component group
-	@cd "components/${GROUP}" && \
-	poetry install --with dev
-
-setup-all-components: ## Run unit tests for all pipeline components
-	@set -e && \
-	for component_group in components/*/ ; do \
-		echo "Setup components under $$component_group" && \
-		$(MAKE) setup-components GROUP=$$(basename $$component_group) ; \
-	done
-
-test-components: ## Run unit tests for a component group
-	@cd "components/${GROUP}" && \
-	poetry run pytest
-
-test-all-components: ## Run unit tests for all pipeline components
-	@set -e && \
-	for component_group in components/*/ ; do \
-		echo "Test components under $$component_group" && \
-		$(MAKE) test-components GROUP=$$(basename $$component_group) ; \
-	done
+targets ?= training serving
+build: ## Build and push training/serving container image using Docker. Specify target=<training|serving>
+	@cd model && \
+	for target in $$targets ; do \
+		echo "Building $$target image" && \
+		gcloud builds submit . \
+		--region=${VERTEX_LOCATION} \
+		--project=${VERTEX_PROJECT_ID} \
+		--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source \
+		--substitutions=_DOCKER_TARGET=${target},_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/${target}:${RESOURCE_SUFFIX} ; \
+	done 
+
+
+compile ?=true
+build ?= true 
+run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
+	@if [ "${compile}" ]; then \
+		$(MAKE) compile ; \
+	fi && \
+	if [ "${build}" ]; then \
+		$(MAKE) build ; \
+	fi && \
+	cd pipelines/src  \
+	poetry run python -m pipelines.trigger --template_path=pipelines/${pipeline}/pipeline.yaml --enable_caching=$(enable_pipeline_caching)
 
-test-components-coverage: ## Run tests with coverage
-	@cd "components/${GROUP}" && \
-	poetry run coverage run -m pytest && \
-	poetry run coverage report -m
 
-test-all-components-coverage: ## Run tests with coverage
-	@set -e && \
-	for component_group in components/*/ ; do \
-		echo "Test components under $$component_group" && \
-		$(MAKE) test-components-coverage GROUP=$$(basename $$component_group) ; \
-	done
+test:
+	@if [ -n "${GROUP}" ]; then \
+		echo "Test components under components/${GROUP}" && \
+		cd components/${GROUP} && \
+		poetry run pytest ; \
+	else \
+		echo "Testing scripts" && \
+		cd pipelines && \
+		poetry run python -m pytest tests/trigger &&\
+		cd .. && \
+		for i in components/*/ ; do \
+			echo "Test components under $$i" && \
+			cd "$$i" && \
+			poetry run pytest && \
+			cd ../.. ;\
+		done ; \
+	fi
 
-run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
-	@ $(MAKE) compile-pipeline && \
-	cd pipelines/src && \
-	poetry run python -m pipelines.trigger --template_path=pipelines/${pipeline}/pipeline.yaml --enable_caching=$(enable_pipeline_caching)
 
 e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour).
 	@ cd pipelines && \
 	poetry run pytest --log-cli-level=INFO tests/$(pipeline) --enable_caching=$(enable_pipeline_caching)
-
-env ?= dev
-deploy-infra: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
-	@ cd terraform/envs/$(env) && \
-	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
-	terraform apply -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
-
-destroy-infra: ## DESTROY the Terraform infrastructure in your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
-	@ cd terraform/envs/$(env) && \
-	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
-	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
-
-target ?= training
-build-container: ## Build and push training/serving container image using Docker. Specify target=<training|serving>
-	@ cd model && \
-	gcloud builds submit . \
-	--region=${VERTEX_LOCATION} \
-	--project=${VERTEX_PROJECT_ID} \
-	--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source \
-	--substitutions=_DOCKER_TARGET=${target},_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/${target}:${RESOURCE_SUFFIX}

From 638bc90233fac4d7185e1e8644257a63751b2d5f Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Thu, 17 Aug 2023 09:49:26 +0100
Subject: [PATCH 159/238] style: pre-commit fixes

---
 terraform/modules/cloudfunction/src/main.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/terraform/modules/cloudfunction/src/main.py b/terraform/modules/cloudfunction/src/main.py
index c9eceb7b..bec77328 100644
--- a/terraform/modules/cloudfunction/src/main.py
+++ b/terraform/modules/cloudfunction/src/main.py
@@ -70,7 +70,7 @@ def cf_handler(event, context):
     )
     match = _VALID_AR_URL.match(template_path)
     if match and "sha256:" not in template_path:
-        region, project, repo, package_name, tag = match.group(1,2,3,4,5)
+        region, project, repo, package_name, tag = match.group(1, 2, 3, 4, 5)
         host = f"https://{region}-kfp.pkg.dev/{project}/{repo}"
         client = RegistryClient(host=host)
         metadata = client.get_tag(package_name, tag)

From 868b91c0645bb410cfd6a985b7a564f702370bec Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Thu, 17 Aug 2023 10:01:59 +0100
Subject: [PATCH 160/238] refactor: env var handling code

---
 .../src/pipelines/utils/trigger_pipeline.py   | 12 +++++--
 .../tests/utils/test_trigger_pipeline.py      | 33 +++++++++++++++++++
 2 files changed, 42 insertions(+), 3 deletions(-)

diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index 78c800e2..736bd760 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -14,7 +14,6 @@
 
 import argparse
 import os
-from distutils.util import strtobool
 from google.cloud import aiplatform
 
 
@@ -37,8 +36,15 @@ def trigger_pipeline(
     service_account = os.environ["VERTEX_SA_EMAIL"]
 
     enable_caching = os.environ.get("ENABLE_PIPELINE_CACHING")
-    if enable_caching:
-        enable_caching = bool(strtobool(enable_caching))
+    if enable_caching is not None:
+        true_ = ["1", "true"]
+        false_ = ["0", "false"]
+        if enable_caching.lower() not in true_ + false_:
+            raise ValueError(
+                "ENABLE_PIPELINE_CACHING env variable must be "
+                "'true', 'false', '1' or '0', or not set."
+            )
+        enable_caching = enable_caching.lower() in true_
 
     # For below options, we want an empty string to become None, so we add "or None"
     encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER") or None
diff --git a/pipelines/tests/utils/test_trigger_pipeline.py b/pipelines/tests/utils/test_trigger_pipeline.py
index 7972a1b3..7de8731c 100644
--- a/pipelines/tests/utils/test_trigger_pipeline.py
+++ b/pipelines/tests/utils/test_trigger_pipeline.py
@@ -28,6 +28,8 @@
         ("true", True),
         ("False", False),
         ("false", False),
+        ("1", True),
+        ("0", False),
         (None, None),  # ENABLE_PIPELINE_CACHING env var not set
     ],
 )
@@ -79,3 +81,34 @@ def test_trigger_pipeline(
             service_account=service_account,
             network=network,
         )
+
+
+@mock.patch("google.cloud.aiplatform.PipelineJob")
+def test_trigger_pipeline_invalid_caching_env_var(mock_pipelinejob):
+
+    template_path = "path/to/template.yaml"
+    enable_caching = "invalid_value"
+    pipeline_root = "gs://my-pipeline-root/abc123"
+    encryption_spec_key_name = "dummy_encryption_spec_key_name"
+    project_id = "dummy_project_id"
+    region = "dummy_region"
+    service_account = "dummy_sa@dummy_project_id.iam.gserviceaccount.com"
+    network = "dummy_network"
+    display_name = "my first pipeline"
+
+    env_vars = {
+        "VERTEX_PROJECT_ID": project_id,
+        "VERTEX_LOCATION": region,
+        "VERTEX_SA_EMAIL": service_account,
+        "VERTEX_NETWORK": network,
+        "VERTEX_CMEK_IDENTIFIER": encryption_spec_key_name,
+        "VERTEX_PIPELINE_ROOT": pipeline_root,
+        "ENABLE_PIPELINE_CACHING": enable_caching,
+    }
+
+    with mock.patch.dict(os.environ, env_vars), pytest.raises(ValueError):
+
+        trigger_pipeline(
+            template_path=template_path,
+            display_name=display_name,
+        )

From 4161e4e20361000ace88dd0da525da0b3bf64795 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Thu, 17 Aug 2023 13:06:22 +0100
Subject: [PATCH 161/238] build(cloudbuild): update make commands

---
 cloudbuild/e2e-test.yaml      | 2 +-
 cloudbuild/pr-checks.yaml     | 9 ++++-----
 cloudbuild/release.yaml       | 6 +++---
 cloudbuild/trigger-tests.yaml | 4 ++--
 4 files changed, 10 insertions(+), 11 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index b6724cec..6576f750 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -44,7 +44,7 @@ steps:
       - |
         curl -sSL https://install.python-poetry.org | python3 - && \
         export PATH="/builder/home/.local/bin:$$PATH" && \
-        make setup && \
+        make install && \
         make e2e-tests pipeline=training enable_pipeline_caching=False && \
         make e2e-tests pipeline=prediction enable_pipeline_caching=False
     env:
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index a7819caa..085a1324 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -24,14 +24,13 @@ steps:
       - |
         curl -sSL https://install.python-poetry.org | python3 - && \
         export PATH="/builder/home/.local/bin:$$PATH" && \
-        make setup && \
+        make install && \
         git init && \
         git add . && \
         make pre-commit && \
-        make compile-pipeline pipeline=training && \
-        make compile-pipeline pipeline=prediction && \
-        make setup-all-components && \
-        make test-all-components
+        make compile pipeline=training && \
+        make compile pipeline=prediction && \
+        make test
     env:
       - SKIP=terraform-fmt,git-dirty
       - CONTAINER_IMAGE_REGISTRY=dummy_value
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index c7e514b3..fc20bc75 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -39,11 +39,11 @@ steps:
       - |
         curl -sSL https://install.python-poetry.org | python3 - && \
         export PATH="/builder/home/.local/bin:$$PATH" && \
-        make setup && \
+        make install && \
         for proj in ${_DESTINATION_PROJECTS} ; do \
           CONTAINER_IMAGE_REGISTRY=${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images \
-          make compile-pipeline pipeline=training && \
-          make compile-pipeline pipeline=prediction && \
+          make compile pipeline=training && \
+          make compile pipeline=prediction && \
           cd pipelines && \
           poetry run python -m pipelines.utils.upload_pipeline \
           --dest=https://${_VERTEX_LOCATION}-kfp.pkg.dev/$$proj/vertex-pipelines \
diff --git a/cloudbuild/trigger-tests.yaml b/cloudbuild/trigger-tests.yaml
index 4778396c..d1864221 100644
--- a/cloudbuild/trigger-tests.yaml
+++ b/cloudbuild/trigger-tests.yaml
@@ -19,8 +19,8 @@ steps:
       - |
         curl -sSL https://install.python-poetry.org | python3 - && \
         export PATH="/builder/home/.local/bin:$$PATH" && \
-        make setup && \
-        make test-trigger
+        make install && \
+        make test
     entrypoint: /bin/sh
 
 options:

From 9cf60f54573bf9419cbc63d4e465662b13636417 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Mon, 21 Aug 2023 12:43:09 +0100
Subject: [PATCH 162/238] refactor(Makefile): fix targets list with training
 and serving commands

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 6c20a715..93ebe9b4 100644
--- a/Makefile
+++ b/Makefile
@@ -50,7 +50,7 @@ compile: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<traini
 	@cd pipelines/src && \
 	poetry run kfp dsl compile --py pipelines/${pipeline}/pipeline.py --output pipelines/${pipeline}/pipeline.yaml --function pipeline
 
-targets ?= training serving
+targets ?= "training serving"
 build: ## Build and push training/serving container image using Docker. Specify target=<training|serving>
 	@cd model && \
 	for target in $$targets ; do \

From b45c50aaf2498c051e1891cea251c3d6db088534 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Mon, 21 Aug 2023 12:53:37 +0100
Subject: [PATCH 163/238] docs(Makefile): add and update doc strings

---
 Makefile | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/Makefile b/Makefile
index 93ebe9b4..e52f7590 100644
--- a/Makefile
+++ b/Makefile
@@ -51,7 +51,7 @@ compile: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<traini
 	poetry run kfp dsl compile --py pipelines/${pipeline}/pipeline.py --output pipelines/${pipeline}/pipeline.yaml --function pipeline
 
 targets ?= "training serving"
-build: ## Build and push training/serving container image using Docker. Specify target=<training|serving>
+build: ## Build and push training and/or serving container(s) image using Docker. Specify targets=<training serving> e.g. targets=training or targets=training serving (default)
 	@cd model && \
 	for target in $$targets ; do \
 		echo "Building $$target image" && \
@@ -76,7 +76,7 @@ run: ## Compile pipeline and run pipeline in sandbox environment. Must specify p
 	poetry run python -m pipelines.trigger --template_path=pipelines/${pipeline}/pipeline.yaml --enable_caching=$(enable_pipeline_caching)
 
 
-test:
+test: ## Run unit tests for a component group or for all component groups and the pipeline trigger code.
 	@if [ -n "${GROUP}" ]; then \
 		echo "Test components under components/${GROUP}" && \
 		cd components/${GROUP} && \

From 5fb0503599d831520a4f8ac3fe0bfd0f721d3e97 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 22 Aug 2023 01:00:40 +0100
Subject: [PATCH 164/238] refactor(Makefile): add doc string to the run command

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index e52f7590..f0986df2 100644
--- a/Makefile
+++ b/Makefile
@@ -65,7 +65,7 @@ build: ## Build and push training and/or serving container(s) image using Docker
 
 compile ?=true
 build ?= true 
-run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour)
+run: ## Compile or build pipeline and run pipeline in sandbox environment. Compile and build set to true by default
 	@if [ "${compile}" ]; then \
 		$(MAKE) compile ; \
 	fi && \

From 38c94d99b25351ad5423e930ef9e36585ab392d2 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 22 Aug 2023 01:11:21 +0100
Subject: [PATCH 165/238] refactor: fix rebase issues

---
 Makefile | 57 +-------------------------------------------------------
 1 file changed, 1 insertion(+), 56 deletions(-)

diff --git a/Makefile b/Makefile
index e5e9c49b..f0986df2 100644
--- a/Makefile
+++ b/Makefile
@@ -1,4 +1,4 @@
-# Copyright 2023 Google LLC
+# Copyright 2022 Google LLC
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -23,61 +23,6 @@ pre-commit: ## Runs the pre-commit checks over entire repo
 	cd pipelines && \
 	poetry run pre-commit run --all-files
 
-setup: ## Set up local environment for Python development on pipelines
-	@cd pipelines && \
-	poetry install --with dev
-
-test-utils: ## Runs unit tests for the util scripts
-	@cd pipelines && \
-	poetry run python -m pytest tests/utils
-
-compile-pipeline: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
-	@cd pipelines/src && \
-	poetry run kfp dsl compile --py pipelines/${pipeline}/pipeline.py --output pipelines/${pipeline}/pipeline.yaml --function pipeline
-
-setup-components: ## Run unit tests for a component group
-	@cd "components/${GROUP}" && \
-	poetry install --with dev
-
-setup-all-components: ## Run unit tests for all pipeline components
-	@set -e && \
-	for component_group in components/*/ ; do \
-		echo "Setup components under $$component_group" && \
-		$(MAKE) setup-components GROUP=$$(basename $$component_group) ; \
-	done
-
-test-components: ## Run unit tests for a component group
-	@cd "components/${GROUP}" && \
-	poetry run pytest
-
-test-all-components: ## Run unit tests for all pipeline components
-	@set -e && \
-	for component_group in components/*/ ; do \
-		echo "Test components under $$component_group" && \
-		$(MAKE) test-components GROUP=$$(basename $$component_group) ; \
-	done
-
-test-components-coverage: ## Run tests with coverage
-	@cd "components/${GROUP}" && \
-	poetry run coverage run -m pytest && \
-	poetry run coverage report -m
-
-test-all-components-coverage: ## Run tests with coverage
-	@set -e && \
-	for component_group in components/*/ ; do \
-		echo "Test components under $$component_group" && \
-		$(MAKE) test-components-coverage GROUP=$$(basename $$component_group) ; \
-	done
-
-run: ## Compile pipeline and run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour)
-	@ $(MAKE) compile-pipeline && \
-	cd pipelines/src && \
-	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline}
-
-e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour).
-	@ cd pipelines && \
-	poetry run pytest --log-cli-level=INFO tests/$(pipeline)
-
 env ?= dev
 deploy: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
 	@ cd terraform/envs/$(env) && \

From 3bb06ff54463749409cc81d4be444d881575fc13 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Tue, 22 Aug 2023 12:15:16 +0100
Subject: [PATCH 166/238] build: update make commands in cloudbuild files

---
 Makefile                  | 10 +++++-----
 cloudbuild/e2e-test.yaml  |  2 +-
 cloudbuild/pr-checks.yaml |  8 +++-----
 3 files changed, 9 insertions(+), 11 deletions(-)

diff --git a/Makefile b/Makefile
index f0986df2..993e76cd 100644
--- a/Makefile
+++ b/Makefile
@@ -65,7 +65,7 @@ build: ## Build and push training and/or serving container(s) image using Docker
 
 compile ?=true
 build ?= true 
-run: ## Compile or build pipeline and run pipeline in sandbox environment. Compile and build set to true by default
+run: ## Compile or build pipeline and run pipeline in sandbox environment. Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
 	@if [ "${compile}" ]; then \
 		$(MAKE) compile ; \
 	fi && \
@@ -73,7 +73,7 @@ run: ## Compile or build pipeline and run pipeline in sandbox environment. Compi
 		$(MAKE) build ; \
 	fi && \
 	cd pipelines/src  \
-	poetry run python -m pipelines.trigger --template_path=pipelines/${pipeline}/pipeline.yaml --enable_caching=$(enable_pipeline_caching)
+	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline}
 
 
 test: ## Run unit tests for a component group or for all component groups and the pipeline trigger code.
@@ -84,7 +84,7 @@ test: ## Run unit tests for a component group or for all component groups and th
 	else \
 		echo "Testing scripts" && \
 		cd pipelines && \
-		poetry run python -m pytest tests/trigger &&\
+		poetry run python -m pytest tests/utils &&\
 		cd .. && \
 		for i in components/*/ ; do \
 			echo "Test components under $$i" && \
@@ -95,6 +95,6 @@ test: ## Run unit tests for a component group or for all component groups and th
 	fi
 
 
-e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify enable_pipeline_caching=<true|false> (defaults to default Vertex caching behaviour).
+e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour).
 	@ cd pipelines && \
-	poetry run pytest --log-cli-level=INFO tests/$(pipeline) --enable_caching=$(enable_pipeline_caching)
+	poetry run pytest --log-cli-level=INFO tests/$(pipeline)
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index c2e77696..e225fcb9 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -44,7 +44,7 @@ steps:
       - |
         curl -sSL https://install.python-poetry.org | python3 - && \
         export PATH="/builder/home/.local/bin:$$PATH" && \
-        make setup && \
+        make install && \
         make e2e-tests pipeline=training && \
         make e2e-tests pipeline=prediction
     env:
diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 40c1b9f3..085a1324 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -28,11 +28,9 @@ steps:
         git init && \
         git add . && \
         make pre-commit && \
-        make test-utils && \
-        make compile-pipeline pipeline=training && \
-        make compile-pipeline pipeline=prediction && \
-        make setup-all-components && \
-        make test-all-components
+        make compile pipeline=training && \
+        make compile pipeline=prediction && \
+        make test
     env:
       - SKIP=terraform-fmt,git-dirty
       - CONTAINER_IMAGE_REGISTRY=dummy_value

From 79d5f9929db8a157732b7b6c8ea08d3f59050542 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Wed, 23 Aug 2023 11:31:46 +0100
Subject: [PATCH 167/238] style: change copyright to 2023

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 993e76cd..fd0be165 100644
--- a/Makefile
+++ b/Makefile
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

From e088d52b041d8b07cbb0f2f15a544059dcbbc386 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Wed, 23 Aug 2023 11:52:27 +0100
Subject: [PATCH 168/238] style: add quotes to doc strings

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index fd0be165..a330fd00 100644
--- a/Makefile
+++ b/Makefile
@@ -51,7 +51,7 @@ compile: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<traini
 	poetry run kfp dsl compile --py pipelines/${pipeline}/pipeline.py --output pipelines/${pipeline}/pipeline.yaml --function pipeline
 
 targets ?= "training serving"
-build: ## Build and push training and/or serving container(s) image using Docker. Specify targets=<training serving> e.g. targets=training or targets=training serving (default)
+build: ## Build and push training and/or serving container(s) image using Docker. Specify targets=<training serving> e.g. targets=training or targets="training serving" (default)
 	@cd model && \
 	for target in $$targets ; do \
 		echo "Building $$target image" && \

From 9dc734ebc01cb12f9310a87940099bd127dbaaab Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Wed, 23 Aug 2023 15:11:12 +0100
Subject: [PATCH 169/238] docs: update README with new make commands

---
 README.md           | 38 ++++++++++++++++++--------------------
 pipelines/README.md |  4 ++--
 2 files changed, 20 insertions(+), 22 deletions(-)

diff --git a/README.md b/README.md
index 59169d5a..20de5baf 100644
--- a/README.md
+++ b/README.md
@@ -70,10 +70,9 @@ How to deploy this infrastructure is covered in a [later section](#deploying-inf
 1. Install the correct Python version: `pyenv install`
 1. Install poetry - follow the instructions in the [poetry documentation](https://python-poetry.org/docs/#installation)
 1. Configure poetry to use the Python version from pyenv: `poetry config virtualenvs.prefer-active-python true`
-1. Install poetry dependencies for ML pipelines: `make setup`
+1. Install poetry dependencies for ML pipelines: `make install`
 1. Install pre-commit hooks: `cd pipelines && poetry run pre-commit install`
 1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh` for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)
-1. (Optional) If you want to make changes to the KFP components under [/components](/components/), set up the Python virtual environments for these by running `make setup-all-components`
 1. Authenticate to Google Cloud
     1. `gcloud auth login`
     1. `gcloud auth application-default login`
@@ -111,9 +110,9 @@ Install Terraform on your local machine. We recommend using [`tfswitch`](https:/
 Now you can deploy the infrastructure using Terraform:
 
 ```bash
-make deploy-infra env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
-make deploy-infra env=test VERTEX_PROJECT_ID=<TEST PROJECT ID>
-make deploy-infra env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
+make deploy env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
+make deploy env=test VERTEX_PROJECT_ID=<TEST PROJECT ID>
+make deploy env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
 ```
 
 #### Optional - Tearing down infrastructure
@@ -121,9 +120,9 @@ make deploy-infra env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
 To tear down the infrastructure you have created with Terraform, run these commands:
 
 ```bash
-make destroy-infra env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
-make destroy-infra env=test VERTEX_PROJECT_ID=<TEST PROJECT ID>
-make destroy-infra env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
+make undeploy env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
+make undeploy env=test VERTEX_PROJECT_ID=<TEST PROJECT ID>
+make undeploy env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
 ```
 
 ### Example ML pipelines
@@ -161,16 +160,16 @@ bq mk --transfer_config \
 
 The [model/](/model/) directory contains the code for custom training and serving container images, including the model training script at [model/training/train.py](model/training/train.py). You can modify this to suit your own use case.
 
-Build the training container image and push it to Artifact Registry with:
+Build the training and serving container image and push to Artifact Registry with:
 
 ```bash
-make build-container target=training
+make build
 ```
 
-Do the same for the serving container image:
+Do this to only build one image (for example):
 
 ```bash
-make build-container target=serving
+make build target=serving
 ```
 
 ### Running Pipelines
@@ -178,7 +177,7 @@ make build-container target=serving
 You can run the training pipeline (for example) with:
 
 ```bash
-make run pipeline=training
+make run pipeline=training 
 ```
 
 This will execute the pipeline using the chosen template on Vertex AI, namely it will:
@@ -198,26 +197,25 @@ Unit tests and end-to-end (E2E) pipeline tests are performed using [pytest](http
 The unit tests for custom KFP components are run on each pull request, as well as the E2E tests. To run them on your local machine:
 
 ```
-make setup-all-components
-make test-all-components
+make install
+make test
 ```
 
-Alternatively, only setup and install one of the component groups by running:
+Alternatively, only test one of the component groups by running:
 ```
-make setup-components GROUP=vertex-components
-make test-components GROUP=vertex-components
+make test GROUP=vertex-components
 ```
 
 To run end-to-end tests of a single pipeline, you can use:
 
 ```
-make e2e-tests pipeline=<training|prediction> [ enable_caching=<true|false> ]
+make e2e-tests pipeline=<training|prediction>
 ```
 
 There are also unit tests for the utility scripts in [pipelines/src/pipelines/utils](/pipelines/src/pipelines/utils/). To run them on your local machine:
 
 ```
-make test-utils
+make test
 ```
 
 ## Customize pipelines
diff --git a/pipelines/README.md b/pipelines/README.md
index ec328036..dccf64be 100644
--- a/pipelines/README.md
+++ b/pipelines/README.md
@@ -49,7 +49,7 @@ This step is performed using a custom KFP component located in [components/bigqu
 
 The training step is defined as a [KFP container component](https://www.kubeflow.org/docs/components/pipelines/v2/components/container-components/) in the [pipeline.py](/pipelines/src/pipelines/training/pipeline.py) file.
 
-The container image used for this component is built using CI/CD (or the `make build-container target=training` command if you want to build it during development).
+The container image used for this component is built using CI/CD (or the `make build target=training` command if you want to build it during development).
 
 The source code for this container image (and the serving container image) can be found in the [model](/model/) directory. Dependencies are managed using Poetry. The model training script can be found at [model/training/train.py](/model/training/train.py) and can be modified to suit your use case.
 
@@ -115,5 +115,5 @@ If the component is exactly the same and the arguments are exactly the same as i
 Since most of the ML projects take a long time and expensive computation resources, it is cost-effective to use cache when you are sure that the output of components is correct. 
 In terms of [how to control cache reuse behavior](https://cloud.google.com/vertex-ai/docs/pipelines/configure-caching), in generally, you can do it for either a component or the entire pipeline (for all components). 
 If you want to control caching behavior for individual components, add `.set_caching_options(<True|False>)` after each component when building a pipeline.
-To change the caching behaviour of ALL components within a pipeline, you can specify this when you trigger the pipeline like so: `make run pipeline=<training|prediction> enable_caching=<true|false>`
+To change the caching behaviour of ALL components within a pipeline, you can specify this when you trigger the pipeline like so: `make run pipeline=<training|prediction>`
 It is suggested to start by disabling caching of components during development, until you have a good idea of how the caching behaviour works, as it can lead to unexpected results.

From 9819d0236d875d3714a17396e681c60df061086b Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Wed, 23 Aug 2023 15:22:46 +0100
Subject: [PATCH 170/238] docs: README tweaks

---
 README.md | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 20de5baf..e2c54ab8 100644
--- a/README.md
+++ b/README.md
@@ -160,13 +160,13 @@ bq mk --transfer_config \
 
 The [model/](/model/) directory contains the code for custom training and serving container images, including the model training script at [model/training/train.py](model/training/train.py). You can modify this to suit your own use case.
 
-Build the training and serving container image and push to Artifact Registry with:
+Build the training and serving container images and push them to Artifact Registry with:
 
 ```bash
 make build
 ```
 
-Do this to only build one image (for example):
+Optionally specify the `target` variable to only build one of the images. For example, to build only the serving image:
 
 ```bash
 make build target=serving
@@ -177,7 +177,7 @@ make build target=serving
 You can run the training pipeline (for example) with:
 
 ```bash
-make run pipeline=training 
+make run pipeline=training
 ```
 
 This will execute the pipeline using the chosen template on Vertex AI, namely it will:
@@ -197,7 +197,6 @@ Unit tests and end-to-end (E2E) pipeline tests are performed using [pytest](http
 The unit tests for custom KFP components are run on each pull request, as well as the E2E tests. To run them on your local machine:
 
 ```
-make install
 make test
 ```
 

From 914aa9e54d3d59c9eb7cc8a3151b042c529e210a Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Mon, 21 Aug 2023 12:15:40 +0100
Subject: [PATCH 171/238] add wait param to MAKEFILE to wait until pipeline
 ends in make run

---
 Makefile                                          |  5 -----
 cloudbuild/e2e-test.yaml                          |  4 ++--
 pipelines/src/pipelines/utils/trigger_pipeline.py | 11 +++++++++++
 3 files changed, 13 insertions(+), 7 deletions(-)

diff --git a/Makefile b/Makefile
index a330fd00..fb6f9a1d 100644
--- a/Makefile
+++ b/Makefile
@@ -93,8 +93,3 @@ test: ## Run unit tests for a component group or for all component groups and th
 			cd ../.. ;\
 		done ; \
 	fi
-
-
-e2e-tests: ## Perform end-to-end (E2E) pipeline tests. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour).
-	@ cd pipelines && \
-	poetry run pytest --log-cli-level=INFO tests/$(pipeline)
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index e225fcb9..e59e8f30 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -45,8 +45,8 @@ steps:
         curl -sSL https://install.python-poetry.org | python3 - && \
         export PATH="/builder/home/.local/bin:$$PATH" && \
         make install && \
-        make e2e-tests pipeline=training && \
-        make e2e-tests pipeline=prediction
+        make run pipeline=training wait=true && \
+        make run pipeline=prediction wait=true
     env:
       - ENABLE_PIPELINE_CACHING=${_TEST_ENABLE_PIPELINE_CACHING}
       - VERTEX_LOCATION=${_TEST_VERTEX_LOCATION}
diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index 736bd760..d75e9658 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -20,12 +20,14 @@
 def trigger_pipeline(
     template_path: str,
     display_name: str,
+    wait: bool,
 ) -> aiplatform.PipelineJob:
     """Trigger a Vertex Pipeline run from a (local) compiled pipeline definition.
 
     Args:
         template_path (str): file path to the compiled YAML pipeline
         display_name (str): Display name to use for the PipelineJob
+        wait (bool): Wait for the pipeline to finish running
 
     Returns:
         aiplatform.PipelineJob: the Vertex PipelineJob object
@@ -67,6 +69,9 @@ def trigger_pipeline(
         network=network,
     )
 
+    if wait:
+        pl.wait()
+
     return pl
 
 
@@ -84,10 +89,16 @@ def trigger_pipeline(
         type=str,
     )
 
+    parser.add_argument(
+        "--wait",
+        help="Wait for the pipeline to finish running",
+        type=bool,
+    )
     # Get commandline args
     args = parser.parse_args()
 
     trigger_pipeline(
         template_path=args.template_path,
         display_name=args.display_name,
+        wait=args.wait,
     )

From d03d07e7af5d8e619e7024356fe3a7cbffdf8dac Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Mon, 21 Aug 2023 14:52:20 +0100
Subject: [PATCH 172/238] removed old pytest e2e tests

---
 Makefile                               |   7 +-
 pipelines/tests/e2e/test_e2e.py        | 305 -------------------------
 pipelines/tests/prediction/test_e2e.py |  38 ---
 pipelines/tests/training/test_e2e.py   |  36 ---
 4 files changed, 4 insertions(+), 382 deletions(-)
 delete mode 100644 pipelines/tests/e2e/test_e2e.py
 delete mode 100644 pipelines/tests/prediction/test_e2e.py
 delete mode 100644 pipelines/tests/training/test_e2e.py

diff --git a/Makefile b/Makefile
index fb6f9a1d..3ed168c3 100644
--- a/Makefile
+++ b/Makefile
@@ -63,8 +63,9 @@ build: ## Build and push training and/or serving container(s) image using Docker
 	done 
 
 
-compile ?=true
-build ?= true 
+compile ?= true
+build ?= true
+wait ?= false
 run: ## Compile or build pipeline and run pipeline in sandbox environment. Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
 	@if [ "${compile}" ]; then \
 		$(MAKE) compile ; \
@@ -73,7 +74,7 @@ run: ## Compile or build pipeline and run pipeline in sandbox environment. Set c
 		$(MAKE) build ; \
 	fi && \
 	cd pipelines/src  \
-	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline}
+	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline} --wait=${wait}
 
 
 test: ## Run unit tests for a component group or for all component groups and the pipeline trigger code.
diff --git a/pipelines/tests/e2e/test_e2e.py b/pipelines/tests/e2e/test_e2e.py
deleted file mode 100644
index e9b84525..00000000
--- a/pipelines/tests/e2e/test_e2e.py
+++ /dev/null
@@ -1,305 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import logging
-
-import pytest
-import os
-from google.cloud import storage
-from kfp import compiler
-from kfp.components import BaseComponent
-
-from pipelines.utils.trigger_pipeline import trigger_pipeline
-
-project_id = os.environ["VERTEX_PROJECT_ID"]
-project_location = os.environ["VERTEX_LOCATION"]
-
-
-def split_output_uri(output_uri: str):
-    """
-    Splits an output uri into its bucket name and blob path
-    Args: output_uri: (str) The output uri to split
-    Returns: A tuple of (bucket_name, blob_path)
-    """
-    output_uri_noprefix = output_uri[5:]  # remove the gs://
-    output_uri_noprefix_split = output_uri_noprefix.split("/")
-    bucket_name = output_uri_noprefix_split[0]
-    blob_path = "/".join(output_uri_noprefix_split[1:])
-    return (bucket_name, blob_path)
-
-
-def test_gcs_uri(output_uri: str, storage_client):
-    """
-    Tests whether a uri exists on GCS. If not, check whether it is a folder path.
-    Args:
-        output_uri: (str) The output_uri to test existence of
-        storage_client: (GCS client object) The GCS client for the project
-    Returns: (int)
-        None if the output_uri is not a file or a folder and therefore does not exist,
-        The uri's size otherwise (folder size if it is a folder)
-    """
-    bucket_name, blob_path = split_output_uri(output_uri)
-    bucket = storage_client.get_bucket(bucket_name)
-    blob = bucket.get_blob(blob_path)
-    # If not a file, assume its a folder and sum the size of the blobs inside it
-    if not blob:
-        # All files in the folder would have a prefix of the folder path
-        blob_contents = storage_client.list_blobs(bucket_name, prefix=blob_path)
-        if not blob_contents:
-            return None
-        else:
-            folder_size = 0
-            for blob in blob_contents:
-                folder_size += blob.size
-            return folder_size
-    return blob.size
-
-
-def test_vertex_model_uri(
-    model_id: str,
-    model_location: str,
-) -> bool:
-    """
-    Tests whether model artifact exist in Vertex AI.
-
-    Args:
-        model_id (str): Vertex model id
-        model_location (str) : Vertex model location
-
-    Returns:
-        bool: True, if the model exists in Vertex AI.
-             Otherwises, False
-    """
-    from google.cloud.aiplatform import Model
-
-    try:
-        Model(
-            model_name=model_id,
-            project=project_id,
-            location=model_location,
-        )
-        return True
-    except Exception:
-        return False
-
-
-def test_vertex_endpoint_uri(
-    endpoint_id: str,
-    endpoint_location: str,
-) -> bool:
-    """
-    Tests whether endpoint artifact exist in Vertex AI.
-
-    Args:
-        endpoint_id (str): Vertex endpoint id
-        endpoint_location (str) : Vertex endpoint location
-
-    Returns:
-        bool: True, if the endpoint exists in Vertex AI.
-             Otherwises, False
-    """
-    from google.cloud.aiplatform import Endpoint
-
-    try:
-        Endpoint(
-            endpoint_name=endpoint_id,
-            project=project_id,
-            location=endpoint_location,
-        )
-        return True
-    except Exception:
-        return False
-
-
-def test_batch_prediction_job_uri(
-    job_id: str,
-    job_location: str,
-) -> bool:
-    """
-    Tests whether endpoint artifact exist in Vertex AI.
-
-    Args:
-       job_id (str): Vertex batch prediction job id
-       job_location (str) : Vertex batch prediction  location
-
-    Returns:
-        bool: True, if the prediction job exists in Vertex AI.
-             Otherwises, False
-    """
-    from google.cloud.aiplatform import BatchPredictionJob
-
-    try:
-        BatchPredictionJob(
-            batch_prediction_job_name=job_id,
-            project=project_id,
-            location=job_location,
-        )
-        return True
-    except Exception:
-        return False
-
-
-def pipeline_e2e_test(
-    pipeline_func: BaseComponent,
-    common_tasks: dict,
-    **kwargs: dict,
-):
-    """
-    Test pipeline e2e for all expected tasks
-    1. Check all expected tasks occured in the pipeline
-    2. Check if these tasks output the correct artifacts and they are all accessible
-
-    Args:
-        pipeline_func (Callable): KFP pipeline function to test
-        enable_caching (bool): enable pipeline caching
-        common_tasks (dict): tasks in pipline that are executed everytime
-        **kwargs (dict): conditional tasks groups in dictionary
-    """
-
-    template_path = f"{pipeline_func.name}.yaml"
-
-    compiler.Compiler().compile(
-        pipeline_func=pipeline_func,
-        package_path=template_path,
-        type_check=False,
-    )
-
-    try:
-        pl = trigger_pipeline(
-            template_path=template_path,
-            display_name=f"{pipeline_func.name}-E2E-test",
-        )
-
-        pl.wait()
-
-    except Exception:
-        pytest.fail("pipeline not completed")
-
-    # Tests
-    # 1. Check all expected tasks occured in the pipeline
-    # 2-1. Check if these tasks output the correct artifacts
-    # 2-2. Check if these artifacts are accessible
-    details = pl.to_dict()
-    tasks = details["jobDetail"]["taskDetails"]
-
-    # check common tasks
-    if len(common_tasks):
-        test_pipeline_tasks(
-            tasks=tasks,
-            expected_tasks=common_tasks,
-            allow_tasks_missing=False,
-        )
-
-    # check conditioanl tasks
-    for _, conditional_tasks in kwargs.items():
-        test_pipeline_tasks(
-            tasks=tasks,
-            expected_tasks=conditional_tasks,
-            allow_tasks_missing=True,
-        )
-
-
-def test_pipeline_tasks(tasks: list, expected_tasks: dict, allow_tasks_missing: bool):
-    """
-    Test if expected_task meets all the requirements:
-    1. if expected tasks occured in the pipeline
-    2. if these tasks output the correct artifacts
-
-    Args:
-        tasks (list): all pipeline tasks
-        expected_tasks (dict): tasks for check
-        allow_tasks_missing (bool): if missing tasks in one task group is allowed
-            Only allow missing tasks in conditional task groups as sometimes they are
-            not executed.
-    """
-    # Tests
-
-    actual_tasks_expected = {
-        # Create a dict key for a task, where the corresponding value is another dict
-        # This corresponding dict will contain output_names and their output_uri
-        task["taskName"]: {
-            # Create a key/value pair of output_name and output_uri
-            # Do this for every output name
-            output_name: output_dict["artifacts"][0]["uri"]
-            if output_dict["artifacts"][0].get("uri") is not None
-            else None
-            for output_name, output_dict in task.get("outputs", {}).items()
-        }
-        # Create the above task dictionary for each task in the pipeline's tasks
-        # But only if the task is in expected tasks
-        for task in tasks
-        if task["taskName"] in list(expected_tasks.keys())
-    }
-
-    # 1. Missing task check
-    # If all of tasks in a group are not executed,
-    # the remaining check logic will be skipped.
-    # Otherwise, it will check if there are missing tasks.
-    if (len(actual_tasks_expected) == 0) and allow_tasks_missing:
-        logging.info(f"task: {expected_tasks} are not executed")
-        return None
-    else:
-        missing_tasks = [
-            task_name
-            for task_name in expected_tasks.keys()
-            if task_name not in actual_tasks_expected.keys()
-        ]
-        assert len(missing_tasks) == 0, f"expected but missing tasks: {missing_tasks}"
-
-    # test functions mappiing
-    test_functions = {
-        "models": test_vertex_model_uri,
-        "endpoints": test_vertex_endpoint_uri,
-        "batchPredictionJobs": test_batch_prediction_job_uri,
-    }
-
-    # initialise GCS client for the project
-    storage_client = storage.Client(project=project_id)
-
-    # 2. Outputs check
-    for task_name, expected_output in expected_tasks.items():
-        actual_outputs = actual_tasks_expected[task_name]
-        # 2-1. if the output artifact are as expected
-        diff = set(expected_output).symmetric_difference(actual_outputs.keys())
-        assert (
-            len(diff) == 0
-        ), f"task: {task_name}, \
-            expected_output {expected_output}, \
-            actual_outputs: {actual_outputs.keys()}"
-        for output_artifact in expected_output:
-            output_uri = actual_outputs[output_artifact]
-
-            # 2-2. if output is generated successfully
-            # if there is no output uri, skip
-            if output_uri is None:
-                continue
-            # if the output uri is a gcs path, fetch the file
-            elif output_uri.startswith("gs://"):
-                file_size = test_gcs_uri(output_uri, storage_client)
-                assert (
-                    file_size > 0
-                ), f"{output_artifact} in task {task_name} is not accessible"
-            # for Vertex resource check if the resource exists
-            else:
-                # all Vertex AI resource uri following this pattern:
-                # ‘projects/<my-project>/locations/<location>/<resource_type>/<resource_name>’
-                artifact_type = output_uri.split("/")[-2]
-                object_existence = test_functions[artifact_type](
-                    output_uri.split("/")[-1],  # id
-                    output_uri.split("/")[-3],  # location
-                )
-                assert (
-                    object_existence
-                ), f"{output_artifact} in task {task_name} is not accessible \
-                    with {output_uri.split('/')[-1]}"
diff --git a/pipelines/tests/prediction/test_e2e.py b/pipelines/tests/prediction/test_e2e.py
deleted file mode 100644
index e1fa5f1f..00000000
--- a/pipelines/tests/prediction/test_e2e.py
+++ /dev/null
@@ -1,38 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from pipelines.prediction.pipeline import pipeline
-from tests.e2e.test_e2e import pipeline_e2e_test
-
-
-def test_pipeline_run() -> None:
-    """
-    Tests if pipeline is run successfully
-    Triggers pipeline synchronously.
-    Tests will fail if:
-    - Any errors are thrown during execution
-    - Any of the expected component outputs are empty (size == 0kb)
-
-    Arguments:
-        None
-
-    Returns:
-        None
-    """
-
-    # tasks (components) and outputs for tasks which occur unconditionally
-    pipeline_e2e_test(
-        pipeline,
-        common_tasks={},
-    )
diff --git a/pipelines/tests/training/test_e2e.py b/pipelines/tests/training/test_e2e.py
deleted file mode 100644
index 72efa4fa..00000000
--- a/pipelines/tests/training/test_e2e.py
+++ /dev/null
@@ -1,36 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from pipelines.training.pipeline import pipeline
-from tests.e2e.test_e2e import pipeline_e2e_test
-
-
-def test_pipeline_run() -> None:
-    """
-    Tests if pipeline is run successfully
-    Triggers pipeline synchronously.
-    Tests will fail if:
-    - Any errors are thrown during execution
-    - Any of the expected component outputs are empty (size == 0kb)
-
-    Arguments:
-        None
-
-    Returns:
-        None
-    """
-    pipeline_e2e_test(
-        pipeline,
-        common_tasks={},
-    )

From acca598b885652bbbae1ea59ede19919378cf3d2 Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Tue, 22 Aug 2023 09:53:21 +0100
Subject: [PATCH 173/238] added default wait value to trigger_pipeline

---
 pipelines/src/pipelines/utils/trigger_pipeline.py | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index d75e9658..98ca88da 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -20,14 +20,14 @@
 def trigger_pipeline(
     template_path: str,
     display_name: str,
-    wait: bool,
+    wait: str = "True",
 ) -> aiplatform.PipelineJob:
     """Trigger a Vertex Pipeline run from a (local) compiled pipeline definition.
 
     Args:
         template_path (str): file path to the compiled YAML pipeline
         display_name (str): Display name to use for the PipelineJob
-        wait (bool): Wait for the pipeline to finish running
+        wait (str): Wait for the pipeline to finish running
 
     Returns:
         aiplatform.PipelineJob: the Vertex PipelineJob object
@@ -69,9 +69,10 @@ def trigger_pipeline(
         network=network,
     )
 
-    if wait:
+    if wait.lower() == "true":
         pl.wait()
-
+    elif wait.lower() != "false":
+        raise ValueError("wait variable must be 'true', 'false', or not set.")
     return pl
 
 
@@ -92,7 +93,7 @@ def trigger_pipeline(
     parser.add_argument(
         "--wait",
         help="Wait for the pipeline to finish running",
-        type=bool,
+        type=str,
     )
     # Get commandline args
     args = parser.parse_args()

From 81b37ad313f51bdf409af35007b1ebee6c9e4cd9 Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Tue, 22 Aug 2023 12:01:36 +0100
Subject: [PATCH 174/238] added comments and updated README

---
 README.md                                       | 17 ++++++-----------
 .../src/pipelines/utils/trigger_pipeline.py     |  3 ++-
 2 files changed, 8 insertions(+), 12 deletions(-)

diff --git a/README.md b/README.md
index e2c54ab8..35d737d9 100644
--- a/README.md
+++ b/README.md
@@ -177,13 +177,14 @@ make build target=serving
 You can run the training pipeline (for example) with:
 
 ```bash
-make run pipeline=training
+make run pipeline=training [ wait=<true|false> ]
 ```
 
 This will execute the pipeline using the chosen template on Vertex AI, namely it will:
 
 1. Compile the pipeline using the Kubeflow Pipelines SDK
-1. Trigger the pipeline with the help of `pipelines/trigger/main.py`
+2. Trigger the pipeline with the help of `pipelines/trigger/main.py`
+3. (optional) Wait for pipeline to finish before returning if `wait` is set to `true` (default is true)
 
 #### Pipeline input parameters
 
@@ -193,7 +194,7 @@ When triggering ad hoc runs in your dev/sandbox environment, or when running the
 
 ## Testing
 
-Unit tests and end-to-end (E2E) pipeline tests are performed using [pytest](https://docs.pytest.org). 
+Unit tests and end-to-end (E2E) pipeline tests are performed using [pytest](https://docs.pytest.org).
 The unit tests for custom KFP components are run on each pull request, as well as the E2E tests. To run them on your local machine:
 
 ```
@@ -205,12 +206,6 @@ Alternatively, only test one of the component groups by running:
 make test GROUP=vertex-components
 ```
 
-To run end-to-end tests of a single pipeline, you can use:
-
-```
-make e2e-tests pipeline=<training|prediction>
-```
-
 There are also unit tests for the utility scripts in [pipelines/src/pipelines/utils](/pipelines/src/pipelines/utils/). To run them on your local machine:
 
 ```
@@ -241,10 +236,10 @@ vertex-pipelines-end-to-end-samples
 
 Make sure that you give the ML pipeline a unique name in the `@pipeline` decorator.
 
-To run your pipeline, use `make run` as before:
+To run your pipeline, use `make run` as before (optionally adding parameter to wait until pipeline is finished before returning - defaults to true):
 
 ```bash
-make run pipeline=your_new_pipeline
+make run pipeline=your_new_pipeline [ wait=<true|false> ]
 ```
 
 You will also need to add an E2E test - copy and paste the `training` or `prediction` example in [pipelines/tests/](/pipelines/tests/).
diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index 98ca88da..b1d42000 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -20,7 +20,7 @@
 def trigger_pipeline(
     template_path: str,
     display_name: str,
-    wait: str = "True",
+    wait: str = "true",
 ) -> aiplatform.PipelineJob:
     """Trigger a Vertex Pipeline run from a (local) compiled pipeline definition.
 
@@ -70,6 +70,7 @@ def trigger_pipeline(
     )
 
     if wait.lower() == "true":
+        # Wait for pipeline to finish running before returning
         pl.wait()
     elif wait.lower() != "false":
         raise ValueError("wait variable must be 'true', 'false', or not set.")

From af5a003882ec281474713aa33a5949690f96308b Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Tue, 22 Aug 2023 13:29:09 +0100
Subject: [PATCH 175/238] wait defaults to false and moved logic out of
 trigger_pipeline func

---
 README.md                                       |  4 ++--
 .../src/pipelines/utils/trigger_pipeline.py     | 17 +++++++++++------
 2 files changed, 13 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index 35d737d9..0a6b33c4 100644
--- a/README.md
+++ b/README.md
@@ -184,7 +184,7 @@ This will execute the pipeline using the chosen template on Vertex AI, namely it
 
 1. Compile the pipeline using the Kubeflow Pipelines SDK
 2. Trigger the pipeline with the help of `pipelines/trigger/main.py`
-3. (optional) Wait for pipeline to finish before returning if `wait` is set to `true` (default is true)
+3. (optional) Wait for pipeline to finish before returning if `wait` is set to `true` (default is false)
 
 #### Pipeline input parameters
 
@@ -236,7 +236,7 @@ vertex-pipelines-end-to-end-samples
 
 Make sure that you give the ML pipeline a unique name in the `@pipeline` decorator.
 
-To run your pipeline, use `make run` as before (optionally adding parameter to wait until pipeline is finished before returning - defaults to true):
+To run your pipeline, use `make run` as before (optionally adding parameter to wait until pipeline is finished before returning - defaults to false):
 
 ```bash
 make run pipeline=your_new_pipeline [ wait=<true|false> ]
diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index b1d42000..4e4938c6 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -20,14 +20,14 @@
 def trigger_pipeline(
     template_path: str,
     display_name: str,
-    wait: str = "true",
+    wait: bool = False,
 ) -> aiplatform.PipelineJob:
     """Trigger a Vertex Pipeline run from a (local) compiled pipeline definition.
 
     Args:
         template_path (str): file path to the compiled YAML pipeline
         display_name (str): Display name to use for the PipelineJob
-        wait (str): Wait for the pipeline to finish running
+        wait (bool): Wait for the pipeline to finish running
 
     Returns:
         aiplatform.PipelineJob: the Vertex PipelineJob object
@@ -69,11 +69,10 @@ def trigger_pipeline(
         network=network,
     )
 
-    if wait.lower() == "true":
+    if wait:
         # Wait for pipeline to finish running before returning
         pl.wait()
-    elif wait.lower() != "false":
-        raise ValueError("wait variable must be 'true', 'false', or not set.")
+
     return pl
 
 
@@ -99,8 +98,14 @@ def trigger_pipeline(
     # Get commandline args
     args = parser.parse_args()
 
+    if args.wait.lower() == "true":
+        wait = True
+    elif args.wait.lower() != "false":
+        raise ValueError("wait variable must be 'true' or 'false'")
+    wait = False
+
     trigger_pipeline(
         template_path=args.template_path,
         display_name=args.display_name,
-        wait=args.wait,
+        wait=wait,
     )

From a9a5c83983dcf355b6249cdeff1eb13f721bb49e Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Tue, 22 Aug 2023 14:50:51 +0100
Subject: [PATCH 176/238] removed ref to e2e tests in README

---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 0a6b33c4..74485588 100644
--- a/README.md
+++ b/README.md
@@ -194,7 +194,7 @@ When triggering ad hoc runs in your dev/sandbox environment, or when running the
 
 ## Testing
 
-Unit tests and end-to-end (E2E) pipeline tests are performed using [pytest](https://docs.pytest.org).
+Unit tests are performed using [pytest](https://docs.pytest.org).
 The unit tests for custom KFP components are run on each pull request, as well as the E2E tests. To run them on your local machine:
 
 ```

From 3e9f63b28315ee5f29e5c571b5444f22afc5cc88 Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Tue, 22 Aug 2023 14:59:08 +0100
Subject: [PATCH 177/238] more formatting of numbers in readme

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 74485588..3f4e7411 100644
--- a/README.md
+++ b/README.md
@@ -183,8 +183,8 @@ make run pipeline=training [ wait=<true|false> ]
 This will execute the pipeline using the chosen template on Vertex AI, namely it will:
 
 1. Compile the pipeline using the Kubeflow Pipelines SDK
-2. Trigger the pipeline with the help of `pipelines/trigger/main.py`
-3. (optional) Wait for pipeline to finish before returning if `wait` is set to `true` (default is false)
+1. Trigger the pipeline with the help of `pipelines/trigger/main.py`
+1. (optional) Wait for pipeline to finish before returning if `wait` is set to `true` (default is false)
 
 #### Pipeline input parameters
 

From 362ad8a4586feb46408eca38c8c11632e392deca Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Wed, 23 Aug 2023 15:21:16 +0100
Subject: [PATCH 178/238] removed mention of deleted e2e tests

---
 README.md          | 4 +---
 docs/PRODUCTION.md | 2 +-
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 3f4e7411..f2f7e556 100644
--- a/README.md
+++ b/README.md
@@ -195,7 +195,7 @@ When triggering ad hoc runs in your dev/sandbox environment, or when running the
 ## Testing
 
 Unit tests are performed using [pytest](https://docs.pytest.org).
-The unit tests for custom KFP components are run on each pull request, as well as the E2E tests. To run them on your local machine:
+The unit tests for custom KFP components are run on each pull request. To run them on your local machine:
 
 ```
 make test
@@ -242,8 +242,6 @@ To run your pipeline, use `make run` as before (optionally adding parameter to w
 make run pipeline=your_new_pipeline [ wait=<true|false> ]
 ```
 
-You will also need to add an E2E test - copy and paste the `training` or `prediction` example in [pipelines/tests/](/pipelines/tests/).
-
 Some of the scripts e.g. CI/CD pipelines assume only a training and prediction pipeline. You will need to adapt these to add in the compile, run and upload steps for your new pipeline in [cloudbuild/pr-checks.yaml](/cloudbuild/pr-checks.yaml), [cloudbuild/e2e-test.yaml](/cloudbuild/e2e-test.yaml) and [cloudbuild/release.yaml](/cloudbuild/release.yaml).
 
 ### Scheduling pipelines
diff --git a/docs/PRODUCTION.md b/docs/PRODUCTION.md
index a14db1fd..8302f902 100644
--- a/docs/PRODUCTION.md
+++ b/docs/PRODUCTION.md
@@ -38,7 +38,7 @@ When you open the Pull Request, the CI pipeline (`pr-checks.yaml`) should be tri
 
 | :bulb: Remember    |
 |:-------------------|
-| Make sure to update any unit tests and end-to-end tests in line with your changes to the pipelines |
+| Make sure to update any unit tests in line with your changes to the pipelines |
 
 | :exclamation: IMPORTANT    |
 |:---------------------------|

From 99072645c8dc198d7bbead3c908d491800f5a83b Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Wed, 23 Aug 2023 15:32:11 +0100
Subject: [PATCH 179/238] fix: update docstring in Makefile

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 3ed168c3..bc1d3f19 100644
--- a/Makefile
+++ b/Makefile
@@ -66,7 +66,7 @@ build: ## Build and push training and/or serving container(s) image using Docker
 compile ?= true
 build ?= true
 wait ?= false
-run: ## Compile or build pipeline and run pipeline in sandbox environment. Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
+run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour) and wait=<true|false> (default = false). Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
 	@if [ "${compile}" ]; then \
 		$(MAKE) compile ; \
 	fi && \

From 6951b4734047c5f9ccbe648a0e2749f8effd306f Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Wed, 23 Aug 2023 15:38:41 +0100
Subject: [PATCH 180/238] ci: skip image build in ci pipeline step

---
 cloudbuild/e2e-test.yaml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index e59e8f30..8c5c51d0 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -45,8 +45,8 @@ steps:
         curl -sSL https://install.python-poetry.org | python3 - && \
         export PATH="/builder/home/.local/bin:$$PATH" && \
         make install && \
-        make run pipeline=training wait=true && \
-        make run pipeline=prediction wait=true
+        make run pipeline=training build=false wait=true && \
+        make run pipeline=prediction build=false wait=true
     env:
       - ENABLE_PIPELINE_CACHING=${_TEST_ENABLE_PIPELINE_CACHING}
       - VERTEX_LOCATION=${_TEST_VERTEX_LOCATION}

From 01abc17fb89bbe8353fa6f1ed694d4756d90522e Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Wed, 23 Aug 2023 15:57:16 +0100
Subject: [PATCH 181/238] fix: fix Makefile after previous PR

---
 Makefile | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/Makefile b/Makefile
index bc1d3f19..93cd7e1f 100644
--- a/Makefile
+++ b/Makefile
@@ -50,7 +50,7 @@ compile: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<traini
 	@cd pipelines/src && \
 	poetry run kfp dsl compile --py pipelines/${pipeline}/pipeline.py --output pipelines/${pipeline}/pipeline.yaml --function pipeline
 
-targets ?= "training serving"
+targets ?= training serving
 build: ## Build and push training and/or serving container(s) image using Docker. Specify targets=<training serving> e.g. targets=training or targets="training serving" (default)
 	@cd model && \
 	for target in $$targets ; do \
@@ -67,13 +67,13 @@ compile ?= true
 build ?= true
 wait ?= false
 run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour) and wait=<true|false> (default = false). Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
-	@if [ "${compile}" ]; then \
+	@if [ $(compile) = "true" ]; then \
 		$(MAKE) compile ; \
 	fi && \
-	if [ "${build}" ]; then \
+	if [ $(build) = "true" ]; then \
 		$(MAKE) build ; \
 	fi && \
-	cd pipelines/src  \
+	cd pipelines/src && \
 	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline} --wait=${wait}
 
 

From 15afe3a70193cd6d8b76b11dc400adf5747fbbc9 Mon Sep 17 00:00:00 2001
From: roberta-dt <roberta.nwokonko@datatonic.com>
Date: Thu, 24 Aug 2023 10:31:37 +0100
Subject: [PATCH 182/238] fix: update docs strings for test command in Makefile

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 93cd7e1f..cdb82930 100644
--- a/Makefile
+++ b/Makefile
@@ -77,7 +77,7 @@ run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|pre
 	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline} --wait=${wait}
 
 
-test: ## Run unit tests for a component group or for all component groups and the pipeline trigger code.
+test: ## Run unit tests for a specific component group or for all component groups and the pipeline trigger code. Specify GROUP=<vertex-components|bigquery-components>
 	@if [ -n "${GROUP}" ]; then \
 		echo "Test components under components/${GROUP}" && \
 		cd components/${GROUP} && \

From 1393bc62b59930fa2fc2a00b6689f9488f9a4904 Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Thu, 24 Aug 2023 11:18:14 +0100
Subject: [PATCH 183/238] fixed logic error in trigger_pipeline.py

---
 pipelines/src/pipelines/utils/trigger_pipeline.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index 4e4938c6..9ea5d8e2 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -100,9 +100,10 @@ def trigger_pipeline(
 
     if args.wait.lower() == "true":
         wait = True
-    elif args.wait.lower() != "false":
+    elif args.wait.lower() == "false":
+        wait = False
+    else:
         raise ValueError("wait variable must be 'true' or 'false'")
-    wait = False
 
     trigger_pipeline(
         template_path=args.template_path,

From 77f25847226ed223609d4c5af2a3c4c150f59f1c Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Thu, 24 Aug 2023 13:58:59 +0100
Subject: [PATCH 184/238] added logic to makefile to check true/false input

---
 Makefile | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index cdb82930..ab15bcff 100644
--- a/Makefile
+++ b/Makefile
@@ -69,14 +69,19 @@ wait ?= false
 run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour) and wait=<true|false> (default = false). Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
 	@if [ $(compile) = "true" ]; then \
 		$(MAKE) compile ; \
+	elif [ $(compile) != "false" ]; then \
+		echo "ValueError: compile must be either true or false" ; \
+		exit ; \
 	fi && \
 	if [ $(build) = "true" ]; then \
 		$(MAKE) build ; \
+	elif [ $(build) != "false" ]; then \
+		echo "ValueError: build must be either true or false" ; \
+		exit ; \
 	fi && \
 	cd pipelines/src && \
 	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline} --wait=${wait}
 
-
 test: ## Run unit tests for a specific component group or for all component groups and the pipeline trigger code. Specify GROUP=<vertex-components|bigquery-components>
 	@if [ -n "${GROUP}" ]; then \
 		echo "Test components under components/${GROUP}" && \

From 59305a687c6a1e17392405176dfd891cd20999c8 Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Thu, 24 Aug 2023 15:44:08 +0100
Subject: [PATCH 185/238] removed .lower() from trigger_pipeline for wait param

---
 Makefile                                          | 2 +-
 pipelines/src/pipelines/utils/trigger_pipeline.py | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/Makefile b/Makefile
index ab15bcff..bd6ab177 100644
--- a/Makefile
+++ b/Makefile
@@ -66,7 +66,7 @@ build: ## Build and push training and/or serving container(s) image using Docker
 compile ?= true
 build ?= true
 wait ?= false
-run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify ENABLE_PIPELINE_CACHING=<true|false> (defaults to default Vertex caching behaviour) and wait=<true|false> (default = false). Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
+run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify wait=<true|false> (default = false). Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
 	@if [ $(compile) = "true" ]; then \
 		$(MAKE) compile ; \
 	elif [ $(compile) != "false" ]; then \
diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index 9ea5d8e2..6d217020 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -98,9 +98,9 @@ def trigger_pipeline(
     # Get commandline args
     args = parser.parse_args()
 
-    if args.wait.lower() == "true":
+    if args.wait == "true":
         wait = True
-    elif args.wait.lower() == "false":
+    elif args.wait == "false":
         wait = False
     else:
         raise ValueError("wait variable must be 'true' or 'false'")

From be7cc575f397d60261660699a459040fa6064938 Mon Sep 17 00:00:00 2001
From: Jonny Browning <jonathan.browning@datatonic.com>
Date: Fri, 25 Aug 2023 10:19:41 +0100
Subject: [PATCH 186/238] docs: tweak docstring in Makefile

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index bd6ab177..064500e0 100644
--- a/Makefile
+++ b/Makefile
@@ -82,7 +82,7 @@ run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|pre
 	cd pipelines/src && \
 	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline} --wait=${wait}
 
-test: ## Run unit tests for a specific component group or for all component groups and the pipeline trigger code. Specify GROUP=<vertex-components|bigquery-components>
+test: ## Run unit tests for a specific component group or for all component groups and the pipeline trigger code. Optionally specify GROUP=<component group e.g. vertex-components>
 	@if [ -n "${GROUP}" ]; then \
 		echo "Test components under components/${GROUP}" && \
 		cd components/${GROUP} && \

From 84dd5cb1ce82bb4d46f523efb0090d6c62fd86d5 Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Tue, 5 Sep 2023 10:19:31 +0100
Subject: [PATCH 187/238] Added tutorial notebook

---
 tutorial.ipynb | 692 +++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 692 insertions(+)
 create mode 100644 tutorial.ipynb

diff --git a/tutorial.ipynb b/tutorial.ipynb
new file mode 100644
index 00000000..4d73daac
--- /dev/null
+++ b/tutorial.ipynb
@@ -0,0 +1,692 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "ur8xi4C7S06n"
+      },
+      "outputs": [],
+      "source": [
+        "# Copyright 2023 Google LLC\n",
+        "#\n",
+        "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+        "# you may not use this file except in compliance with the License.\n",
+        "# You may obtain a copy of the License at\n",
+        "#\n",
+        "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+        "#\n",
+        "# Unless required by applicable law or agreed to in writing, software\n",
+        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+        "# See the License for the specific language governing permissions and\n",
+        "# limitations under the License."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "JAPoU8Sm5E6e"
+      },
+      "source": [
+        "# [TODO] Add your H1 title heading here\n",
+        "\n",
+        "{TODO: Update the links below.} \n",
+        "\n",
+        "<table align=\"left\">\n",
+        "\n",
+        "  <td>\n",
+        "    <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb\">\n",
+        "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
+        "    </a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb\">\n",
+        "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
+        "      View on GitHub\n",
+        "    </a>\n",
+        "  </td>\n",
+        "  <td>\n",
+        "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/notebook_template.ipynb\">\n",
+        "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
+        "      Open in Vertex AI Workbench\n",
+        "    </a>\n",
+        "  </td>                                                                                               \n",
+        "</table>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "24743cf4a1e1"
+      },
+      "source": [
+        "**_NOTE_**: This notebook has been tested in the following environment:\n",
+        "\n",
+        "* Python version = 3.9"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "tvgnzT1CKxrO"
+      },
+      "source": [
+        "## Overview\n",
+        "\n",
+        "{TODO: Include a paragraph or two explaining what this example demonstrates, who should be interested in it, and what you need to know before you get started.}\n",
+        "\n",
+        "Learn more about [web-doc-title](linkback-to-webdoc-page). {TODO: if more than one primary feature, add tag/linkback for each one}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "d975e698c9a4"
+      },
+      "source": [
+        "### Objective\n",
+        "\n",
+        "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
+        "\n",
+        "This tutorial uses the following Google Cloud ML services and resources:\n",
+        "\n",
+        "- *{TODO: Add high level bullets for the services/resources demonstrated; e.g., Vertex AI Training}*\n",
+        "\n",
+        "\n",
+        "The steps performed include:\n",
+        "\n",
+        "- *{TODO: Add high level bullets for the steps of performed in the notebook}*"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "08d289fa873f"
+      },
+      "source": [
+        "### Dataset\n",
+        "\n",
+        "{TODO: Include a paragraph with Dataset information and where to obtain it.} \n",
+        "\n",
+        "{TODO: Make sure the dataset is accessible to the public. **Googlers**: Add your dataset to the [public samples bucket](http://goto/cloudsamples#sample-storage-bucket) within gs://cloud-samples-data/vertex-ai, if it doesn't already exist there.}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "aed92deeb4a0"
+      },
+      "source": [
+        "### Costs \n",
+        "\n",
+        "{TODO: Update the list of billable products that your tutorial uses.}\n",
+        "\n",
+        "This tutorial uses billable components of Google Cloud:\n",
+        "\n",
+        "* Vertex AI\n",
+        "* {TODO: BigQuery}\n",
+        "* Cloud Storage\n",
+        "\n",
+        "{TODO: Include links to pricing documentation for each product you listed above.\n",
+        " NOTE: If you use BigQuery or Dataflow, you need to add this to the pricing.\n",
+        "}\n",
+        "\n",
+        "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
+        "{ TODO: [BigQuery pricing](https://cloud.google.com/bigquery/pricing), }\n",
+        "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing), \n",
+        "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
+        "to generate a cost estimate based on your projected usage."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "i7EUnXsZhAGF"
+      },
+      "source": [
+        "## Installation\n",
+        "\n",
+        "Install the following packages required to execute this notebook. \n",
+        "\n",
+        "{TODO: Suggest using the latest major GA version of each package; i.e., --upgrade}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "2b4ef9b72d43"
+      },
+      "outputs": [],
+      "source": [
+        "# Install the correct Python version\n",
+        "! pyenv install \n",
+        "\n",
+        "# Install poetry\n",
+        "\n",
+        "# configure poetry \n",
+        "! poetry config virtualenvs.prefer-active-python true\n",
+        "\n",
+        "#Install poetry dependencies for ML pipelines\n",
+        "! make install\n",
+        "\n",
+        "# Install pre-commit hooks\n",
+        "! cd pipelines && poetry run pre-commit install\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "58707a750154"
+      },
+      "source": [
+        "### Colab only: Uncomment the following cell to restart the kernel."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "f200f10a1da3"
+      },
+      "outputs": [],
+      "source": [
+        "# # Automatically restart kernel after installs so that your environment can access the new packages\n",
+        "# import IPython\n",
+        "\n",
+        "# app = IPython.Application.instance()\n",
+        "# app.kernel.do_shutdown(True)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "BF1j6f9HApxa"
+      },
+      "source": [
+        "## Before you begin\n",
+        "\n",
+        "### Set up your Google Cloud project\n",
+        "\n",
+        "**The following steps are required, regardless of your notebook environment.**\n",
+        "\n",
+        "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+        "\n",
+        "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
+        "\n",
+        "3. [Enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com). {TODO: Update the APIs needed for your tutorial. Edit the API names, and update the link to append the API IDs, separating each one with a comma. For example, container.googleapis.com,cloudbuild.googleapis.com}\n",
+        "\n",
+        "4. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "WReHDGG5g0XY"
+      },
+      "source": [
+        "#### Set your project ID\n",
+        "\n",
+        "**If you don't know your project ID**, try the following:\n",
+        "* Run `gcloud config list`.\n",
+        "* Run `gcloud projects list`.\n",
+        "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "oM1iC_MfAts1"
+      },
+      "outputs": [],
+      "source": [
+        "vertex_project_id = \"[your-project-id]\"  # @param {type:\"string\"}\n",
+        "\n",
+        "# Set the project id\n",
+        "! gcloud config set project {vertex_project_id}\n",
+        "\n",
+        "# Set the environment variable\n",
+        "% env VERTEX_PROJECT_ID = {vertex_project_id}"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "region"
+      },
+      "source": [
+        "#### Location\n",
+        "\n",
+        "You can also change the `VERTEX_LOCATION` variable used by Vertex AI. Learn more about [Vertex AI locations](https://cloud.google.com/vertex-ai/docs/general/locations)."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 42,
+      "metadata": {
+        "id": "region"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "env: VERTEX_LOCATION=europe-west2\n"
+          ]
+        }
+      ],
+      "source": [
+        "vertex_location = \"europe-west2\"  # @param {type: \"string\"}\n",
+        "\n",
+        "# Set the environment variable\n",
+        "%env VERTEX_LOCATION={vertex_location}"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "#### Resource suffix\n",
+        "\n",
+        "Specify the `RESOURCE_SUFFIX` (e.g. `<your name>`) to facilitate running concurrent pipelines in the same Google Cloud project. \n",
+        "This is important to change if you are working in a team to avoid overwriting resources during development "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "resource_suffix=\"default\" # @param {type: \"string\"}\n",
+        "\n",
+        "# Set the environment variable\n",
+        "%env RESOUCE_SUFFIX=resource_suffix"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "#### Vertex pipelines service account\n",
+        "\n",
+        "We need to set the `VERTEX_SA_EMAIL` that is in the Google Cloud project so that this service account can run the pipelines for us."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 62,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "env: TEMP=vertex-pipelines@europe-west2.iam.gserviceaccount.com\n",
+            "env: VERTEX_SA_EMAIL=${TEMP}\n"
+          ]
+        }
+      ],
+      "source": [
+        "vertex_sa_email=f\"vertex-pipelines@{vertex_location}.iam.gserviceaccount.com\" #TODO: vertex_location should be vertex_project_id\n",
+        "\n",
+        "%env TEMP={vertex_sa_email}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 52,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "env: TEST=vertex-pipelines@europe-west2.iam.gserviceaccount.com\n"
+          ]
+        }
+      ],
+      "source": [
+        "%env TEST={vertex_sa_email}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 64,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "${TEMP}\n",
+            "vertex-pipelines@europe-west2.iam.gserviceaccount.com\n"
+          ]
+        }
+      ],
+      "source": [
+        "! echo ${VERTEX_SA_EMAIL} && echo ${TEST}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 24,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "-pipelines@testing.iam.gserviceaccount.com\n",
+            "testing\n",
+            "569Xpipelines@testing.iam.gserviceaccount.com\n"
+          ]
+        }
+      ],
+      "source": [
+        "! echo {VERTEX_SA_EMAIL} && echo {VERTEX_PROJECT_ID} && echo ${VERTEX_SA_EMAIL}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "sBCra4QMA2wR"
+      },
+      "source": [
+        "### Authenticate your Google Cloud account\n",
+        "\n",
+        "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "74ccc9e52986"
+      },
+      "source": [
+        "**1. Vertex AI Workbench**\n",
+        "* Do nothing as you are already authenticated."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "de775a3773ba"
+      },
+      "source": [
+        "**2. Local JupyterLab instance, uncomment and run:**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "254614fa0c46"
+      },
+      "outputs": [],
+      "source": [
+        "# ! gcloud auth login"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ef21552ccea8"
+      },
+      "source": [
+        "**3. Colab, uncomment and run:**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "id": "603adbbf0532"
+      },
+      "outputs": [],
+      "source": [
+        "# from google.colab import auth\n",
+        "# auth.authenticate_user()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "f6b2ccc891ed"
+      },
+      "source": [
+        "**4. Service account or other**\n",
+        "* See how to grant Cloud Storage permissions to your service account at https://cloud.google.com/storage/docs/gsutil/commands/iam#ch-examples."
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## xgboost example"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "TESTVAR=\"test\""
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "echo \n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "! make becky-test"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "! make run pipeline=training wait=true"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {},
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Configuration file exists at /Users/beckyinkpen/Library/Preferences/pypoetry, reusing this directory.\n",
+            "\n",
+            "Consider moving TOML configuration files to /Users/beckyinkpen/Library/Application Support/pypoetry, as support for the legacy directory will be removed in an upcoming release.\n",
+            "/Users/beckyinkpen/Code/vertex-pipelines-end-to-end-samples/pipelines/src/pipelines/prediction/pipeline.yaml\n",
+            "Building training image\n",
+            "\u001b[1;31mERROR:\u001b[0m (gcloud.builds.submit) The user is forbidden from accessing the bucket [dt-turbo-templates-dev-staging]. Please check your organization's policy or if the user has the \"serviceusage.services.use\" permission. Giving the user Owner, Editor, or Viewer roles may also fix this issue. Alternatively, use the --no-source option and access your source code via a different method.\n",
+            "Building serving image\n",
+            "\u001b[1;31mERROR:\u001b[0m (gcloud.builds.submit) The user is forbidden from accessing the bucket [dt-turbo-templates-dev-staging]. Please check your organization's policy or if the user has the \"serviceusage.services.use\" permission. Giving the user Owner, Editor, or Viewer roles may also fix this issue. Alternatively, use the --no-source option and access your source code via a different method.\n",
+            "make[1]: *** [build] Error 1\n",
+            "make: *** [run] Error 2\n"
+          ]
+        }
+      ],
+      "source": [
+        "! make run pipeline=prediction wait=false"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "zgPO1eR3CYjk"
+      },
+      "source": [
+        "### Create a Cloud Storage bucket\n",
+        "\n",
+        "Create a storage bucket to store intermediate artifacts such as datasets.\n",
+        "\n",
+        "- *{Note to notebook author: For any user-provided strings that need to be unique (like bucket names or model ID's), append \"-unique\" to the end so proper testing can occur}*"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "MzGDU7TWdts_"
+      },
+      "outputs": [],
+      "source": [
+        "BUCKET_URI = f\"gs://your-bucket-name-{PROJECT_ID}-unique\"  # @param {type:\"string\"}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "-EcIXiGsCePi"
+      },
+      "source": [
+        "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "NIq7R4HZCfIc"
+      },
+      "outputs": [],
+      "source": [
+        "! gsutil mb -l {REGION} -p {PROJECT_ID} {BUCKET_URI}"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "960505627ddf"
+      },
+      "source": [
+        "### Import libraries"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "PyQmSRbKA8r-"
+      },
+      "outputs": [],
+      "source": [
+        "from google.cloud import aiplatform"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "init_aip:mbsdk,all"
+      },
+      "source": [
+        "### Initialize Vertex AI SDK for Python\n",
+        "\n",
+        "Initialize the Vertex AI SDK for Python for your project."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "init_aip:mbsdk,all"
+      },
+      "outputs": [],
+      "source": [
+        "aiplatform.init(project=PROJECT_ID, location=REGION, staging_bucket=BUCKET_URI)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "TpV-iwP9qw9c"
+      },
+      "source": [
+        "## Cleaning up\n",
+        "\n",
+        "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
+        "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+        "\n",
+        "Otherwise, you can delete the individual resources you created in this tutorial:\n",
+        "\n",
+        "{TODO: Include commands to delete individual resources below}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "sx_vKniMq9ZX"
+      },
+      "outputs": [],
+      "source": [
+        "import os\n",
+        "\n",
+        "# Delete endpoint resource\n",
+        "# e.g. `endpoint.delete()`\n",
+        "\n",
+        "# Delete model resource\n",
+        "# e.g. `model.delete()`\n",
+        "\n",
+        "# Delete Cloud Storage objects that were created\n",
+        "delete_bucket = False\n",
+        "if delete_bucket or os.getenv(\"IS_TESTING\"):\n",
+        "    ! gsutil -m rm -r $BUCKET_URI"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "collapsed_sections": [],
+      "name": "notebook_template.ipynb",
+      "toc_visible": true
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.11.2"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

From 345690f0f8dc4f1db9ad317e3d8f3812f022f657 Mon Sep 17 00:00:00 2001
From: becky-dt <rebecca.inkpen@datatonic.com>
Date: Tue, 5 Sep 2023 10:20:17 +0100
Subject: [PATCH 188/238] Added comment to notebook

---
 tutorial.ipynb | 181 ++++++++-----------------------------------------
 1 file changed, 30 insertions(+), 151 deletions(-)

diff --git a/tutorial.ipynb b/tutorial.ipynb
index 4d73daac..0b7ba689 100644
--- a/tutorial.ipynb
+++ b/tutorial.ipynb
@@ -163,7 +163,7 @@
         "# Install the correct Python version\n",
         "! pyenv install \n",
         "\n",
-        "# Install poetry\n",
+        "# Install poetry #TODO: Fill this section!!\n",
         "\n",
         "# configure poetry \n",
         "! poetry config virtualenvs.prefer-active-python true\n",
@@ -200,12 +200,13 @@
       ]
     },
     {
+      "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "BF1j6f9HApxa"
       },
       "source": [
-        "## Before you begin\n",
+        "## 1. Setup\n",
         "\n",
         "### Set up your Google Cloud project\n",
         "\n",
@@ -265,19 +266,11 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 42,
+      "execution_count": null,
       "metadata": {
         "id": "region"
       },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "env: VERTEX_LOCATION=europe-west2\n"
-          ]
-        }
-      ],
+      "outputs": [],
       "source": [
         "vertex_location = \"europe-west2\"  # @param {type: \"string\"}\n",
         "\n",
@@ -320,76 +313,14 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 62,
+      "execution_count": null,
       "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "env: TEMP=vertex-pipelines@europe-west2.iam.gserviceaccount.com\n",
-            "env: VERTEX_SA_EMAIL=${TEMP}\n"
-          ]
-        }
-      ],
+      "outputs": [],
       "source": [
         "vertex_sa_email=f\"vertex-pipelines@{vertex_location}.iam.gserviceaccount.com\" #TODO: vertex_location should be vertex_project_id\n",
         "\n",
-        "%env TEMP={vertex_sa_email}"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 52,
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "env: TEST=vertex-pipelines@europe-west2.iam.gserviceaccount.com\n"
-          ]
-        }
-      ],
-      "source": [
-        "%env TEST={vertex_sa_email}"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 64,
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "${TEMP}\n",
-            "vertex-pipelines@europe-west2.iam.gserviceaccount.com\n"
-          ]
-        }
-      ],
-      "source": [
-        "! echo ${VERTEX_SA_EMAIL} && echo ${TEST}"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 24,
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "-pipelines@testing.iam.gserviceaccount.com\n",
-            "testing\n",
-            "569Xpipelines@testing.iam.gserviceaccount.com\n"
-          ]
-        }
-      ],
-      "source": [
-        "! echo {VERTEX_SA_EMAIL} && echo {VERTEX_PROJECT_ID} && echo ${VERTEX_SA_EMAIL}"
+        "# Set the environment variable\n",
+        "%env VERTEX_SA_EMAIL={vertex_sa_email}"
       ]
     },
     {
@@ -424,7 +355,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 2,
+      "execution_count": null,
       "metadata": {
         "id": "254614fa0c46"
       },
@@ -444,7 +375,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 3,
+      "execution_count": null,
       "metadata": {
         "id": "603adbbf0532"
       },
@@ -464,75 +395,6 @@
         "* See how to grant Cloud Storage permissions to your service account at https://cloud.google.com/storage/docs/gsutil/commands/iam#ch-examples."
       ]
     },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## xgboost example"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 3,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "TESTVAR=\"test\""
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 5,
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "echo \n",
-            "\n"
-          ]
-        }
-      ],
-      "source": [
-        "! make becky-test"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "! make run pipeline=training wait=true"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 2,
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Configuration file exists at /Users/beckyinkpen/Library/Preferences/pypoetry, reusing this directory.\n",
-            "\n",
-            "Consider moving TOML configuration files to /Users/beckyinkpen/Library/Application Support/pypoetry, as support for the legacy directory will be removed in an upcoming release.\n",
-            "/Users/beckyinkpen/Code/vertex-pipelines-end-to-end-samples/pipelines/src/pipelines/prediction/pipeline.yaml\n",
-            "Building training image\n",
-            "\u001b[1;31mERROR:\u001b[0m (gcloud.builds.submit) The user is forbidden from accessing the bucket [dt-turbo-templates-dev-staging]. Please check your organization's policy or if the user has the \"serviceusage.services.use\" permission. Giving the user Owner, Editor, or Viewer roles may also fix this issue. Alternatively, use the --no-source option and access your source code via a different method.\n",
-            "Building serving image\n",
-            "\u001b[1;31mERROR:\u001b[0m (gcloud.builds.submit) The user is forbidden from accessing the bucket [dt-turbo-templates-dev-staging]. Please check your organization's policy or if the user has the \"serviceusage.services.use\" permission. Giving the user Owner, Editor, or Viewer roles may also fix this issue. Alternatively, use the --no-source option and access your source code via a different method.\n",
-            "make[1]: *** [build] Error 1\n",
-            "make: *** [run] Error 2\n"
-          ]
-        }
-      ],
-      "source": [
-        "! make run pipeline=prediction wait=false"
-      ]
-    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -620,12 +482,29 @@
       ]
     },
     {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 2. Training Pipeline"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## 3. Prediction Pipeline"
+      ]
+    },
+    {
+      "attachments": {},
       "cell_type": "markdown",
       "metadata": {
         "id": "TpV-iwP9qw9c"
       },
       "source": [
-        "## Cleaning up\n",
+        "## 4. Cleaning up\n",
         "\n",
         "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
         "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
@@ -637,7 +516,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 1,
+      "execution_count": null,
       "metadata": {
         "id": "sx_vKniMq9ZX"
       },

From 6894f6503c2447b528e52822a211571ade4f6630 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 5 Sep 2023 17:46:43 +0100
Subject: [PATCH 189/238] fix: make build variable substitution fix

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 064500e0..344a02a6 100644
--- a/Makefile
+++ b/Makefile
@@ -59,7 +59,7 @@ build: ## Build and push training and/or serving container(s) image using Docker
 		--region=${VERTEX_LOCATION} \
 		--project=${VERTEX_PROJECT_ID} \
 		--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source \
-		--substitutions=_DOCKER_TARGET=${target},_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/${target}:${RESOURCE_SUFFIX} ; \
+		--substitutions=_DOCKER_TARGET=$$target,_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/$$target:${RESOURCE_SUFFIX} ; \
 	done 
 
 

From 9d95143a753327ca05f092ba7f03cb3611b274b0 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 5 Sep 2023 18:00:05 +0100
Subject: [PATCH 190/238] feat: example notebook

---
 examples/try_it_yourself.ipynb | 266 +++++++++++++++++++++++++++++++++
 1 file changed, 266 insertions(+)
 create mode 100644 examples/try_it_yourself.ipynb

diff --git a/examples/try_it_yourself.ipynb b/examples/try_it_yourself.ipynb
new file mode 100644
index 00000000..0c902d80
--- /dev/null
+++ b/examples/try_it_yourself.ipynb
@@ -0,0 +1,266 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d1969712-ce0a-4ca5-8581-fe0f817e5d13",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Clone a Git repository\n",
+    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d4979f79-2c58-4554-bd93-db89a6367098",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "435fb56c-7b27-4c7f-8d96-751bc9ba0324",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "PROJECT_ID = \"my-project-id\"  # @param {type:\"string\"}\n",
+    "LOCATION = \"europe-west2\" # @param {type:\"string\"}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9853f0e0-c712-4e41-92b3-edfdadb34593",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set the project id\n",
+    "!gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a43743b5-b750-4ffe-924e-f19b75a20570",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!gcloud auth application-default login"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "18f3b0f6-ff25-4436-a604-4d694e758d16",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ['PIPELINE_TEMPLATE'] = 'xgboost'\n",
+    "os.environ['VERTEX_CMEK_IDENTIFIER'] = ''\n",
+    "os.environ['VERTEX_LOCATION'] = LOCATION\n",
+    "os.environ['VERTEX_NETWORK'] = ''\n",
+    "os.environ['VERTEX_PROJECT_ID'] = PROJECT_ID\n",
+    "os.environ['RESOURCE_SUFFIX']='default'\n",
+    "\n",
+    "# Calculate the value of VERTEX_SA_EMAIL based on VERTEX_PROJECT_ID\n",
+    "os.environ['VERTEX_SA_EMAIL'] = f'vertex-pipelines@{os.environ[\"VERTEX_PROJECT_ID\"]}.iam.gserviceaccount.com'\n",
+    "os.environ['PIPELINE_FILES_GCS_PATH'] = f'gs://{os.environ[\"VERTEX_PROJECT_ID\"]}-pl-root'\n",
+    "os.environ['CONTAINER_IMAGE_REGISTRY']=f'{os.environ[\"VERTEX_LOCATION\"]}-docker.pkg.dev/{os.environ[\"VERTEX_PROJECT_ID\"]}/vertex-images'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fcf5ce7a-ef56-4e55-877c-697c4e8b2fb8",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!gcloud services enable cloudresourcemanager.googleapis.com --project={PROJECT_ID}\n",
+    "!gcloud services enable serviceusage.googleapis.com --project={PROJECT_ID}\n",
+    "!gcloud storage buckets create gs://{PROJECT_ID}-tfstate --project={PROJECT_ID} --location={LOCATION} --uniform-bucket-level-access"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "798f98ee-3cdc-4dbe-9e3e-a7e9c1d8d1cd",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!make install"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7963e7b2-aa51-46fd-b7e5-8f356f8beeec",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "#Make deploy needs approval (i.e. -auto-approve flag) MAKE FILE WOULD NEED SOME CHANGES\n",
+    "!make deploy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "95726e43-1bc1-4de5-a463-0fae31a5256c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!bq --location={LOCATION} mk --dataset \"{PROJECT_ID}:chicago_taxi_trips\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "83ed96eb-3a12-4d07-8b00-701708e9f823",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!bq --location={LOCATION} mk --dataset \"{PROJECT_ID}:preprocessing\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bc01d526-c528-4f82-9541-6a8319fbedaf",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# TO TRANSFER DATA USED CONSOLE TO CREATE DATA TRANSFER\n",
+    "\n",
+    "\n",
+    "#ERRORS\n",
+    "# bq mk asks for code to be pasted from generated link to authenticate data transfer. Cant be done in jupyter?\n",
+    "\n",
+    "# python code below gives \"Request contains an invalid argument. error\n",
+    "\n",
+    "\n",
+    "#!pip install google-cloud-bigquery-datatransfer\n",
+    "# from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "# transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "# destination_project_id = \"dt-donatas-sandbox-dev\"\n",
+    "# destination_dataset_id = \"dt-donatas-sandbox-dev:chicago_taxi_trips\"\n",
+    "# source_project_id = \"bigquery-public-data\"\n",
+    "# source_dataset_id = \"chicago_taxi_trips\"\n",
+    "# transfer_config = bigquery_datatransfer.TransferConfig(\n",
+    "#     destination_dataset_id=destination_dataset_id,\n",
+    "#     display_name=\"Chicago taxi trip mirror\",\n",
+    "#     data_source_id=\"cross_region_copy\",\n",
+    "#     params={\n",
+    "#         \"source_project_id\": source_project_id,\n",
+    "#         \"source_dataset_id\": source_dataset_id,\n",
+    "#     },\n",
+    "#     schedule=\"every 24 hours\",\n",
+    "# )\n",
+    "# transfer_config = transfer_client.create_transfer_config(\n",
+    "#     parent=transfer_client.common_project_path(destination_project_id),\n",
+    "#     transfer_config=transfer_config,\n",
+    "# )\n",
+    "# print(f\"Created transfer config: {transfer_config.name}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d69779bd-47a3-4075-8c58-48f2dea2a6da",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!make build"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3e8f1804-72ae-4964-a00c-9d60f70f97a6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "!make run pipeline=training build=false"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "96a8c160-415c-45b6-81b6-845cfcd9501d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!make run pipeline=prediction build=false"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "61504b1b-f988-43f2-9dc1-385afdc83d97",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!make undeploy"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.5"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From 9c963fb0209dcfcb21b8b438c9dfb1fe6c844acb Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 5 Sep 2023 18:06:08 +0100
Subject: [PATCH 191/238] feat: comments

---
 examples/try_it_yourself.ipynb | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/examples/try_it_yourself.ipynb b/examples/try_it_yourself.ipynb
index 0c902d80..d79e5fc6 100644
--- a/examples/try_it_yourself.ipynb
+++ b/examples/try_it_yourself.ipynb
@@ -163,6 +163,14 @@
     "#ERRORS\n",
     "# bq mk asks for code to be pasted from generated link to authenticate data transfer. Cant be done in jupyter?\n",
     "\n",
+    "# bq mk --transfer_config \\\n",
+    "#   --project_id=${VERTEX_PROJECT_ID} \\\n",
+    "#   --data_source=\"cross_region_copy\" \\\n",
+    "#   --target_dataset=\"chicago_taxi_trips\" \\\n",
+    "#   --display_name=\"Chicago taxi trip mirror\" \\\n",
+    "#   --params='{\"source_dataset_id\":\"'\"chicago_taxi_trips\"'\",\"source_project_id\":\"'\"bigquery-public-data\"'\"}'\n",
+    "\n",
+    "\n",
     "# python code below gives \"Request contains an invalid argument. error\n",
     "\n",
     "\n",

From 6ff532fd31bf5af969ff1f6c0ed3368381ce1b2b Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 6 Sep 2023 12:02:50 +0100
Subject: [PATCH 192/238] feat: deployt chdir

---
 examples/try_it_yourself.ipynb | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/examples/try_it_yourself.ipynb b/examples/try_it_yourself.ipynb
index d79e5fc6..b0ebf471 100644
--- a/examples/try_it_yourself.ipynb
+++ b/examples/try_it_yourself.ipynb
@@ -94,8 +94,8 @@
    },
    "outputs": [],
    "source": [
-    "!gcloud services enable cloudresourcemanager.googleapis.com --project={PROJECT_ID}\n",
-    "!gcloud services enable serviceusage.googleapis.com --project={PROJECT_ID}\n",
+    "# !gcloud services enable cloudresourcemanager.googleapis.com --project={PROJECT_ID}\n",
+    "# !gcloud services enable serviceusage.googleapis.com --project={PROJECT_ID}\n",
     "!gcloud storage buckets create gs://{PROJECT_ID}-tfstate --project={PROJECT_ID} --location={LOCATION} --uniform-bucket-level-access"
    ]
   },
@@ -121,7 +121,10 @@
    "outputs": [],
    "source": [
     "#Make deploy needs approval (i.e. -auto-approve flag) MAKE FILE WOULD NEED SOME CHANGES\n",
-    "!make deploy"
+    "#!make deploy\n",
+    "! terraform -chdir=terraform/envs/dev init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' \n",
+    "! terraform -chdir=terraform/envs/dev plan -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'\n",
+    "# ! terraform -chdir=terraform/envs/dev apply -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}' -auto-approve"
    ]
   },
   {

From 87f3c65dc916525ecdfd2d9ffe796e463e6b3af9 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 6 Sep 2023 15:20:38 +0100
Subject: [PATCH 193/238] feat: Updated notebook

---
 examples/try_it_yourself.ipynb | 3759 +++++++++++++++++++++++++++++++-
 1 file changed, 3654 insertions(+), 105 deletions(-)

diff --git a/examples/try_it_yourself.ipynb b/examples/try_it_yourself.ipynb
index b0ebf471..53c74abf 100644
--- a/examples/try_it_yourself.ipynb
+++ b/examples/try_it_yourself.ipynb
@@ -3,11 +3,186 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d1969712-ce0a-4ca5-8581-fe0f817e5d13",
    "metadata": {
-    "tags": []
+    "id": "ur8xi4C7S06n"
    },
    "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# [TODO] Add your H1 title heading here\n",
+    "\n",
+    "{TODO: Update the links below.} \n",
+    "\n",
+    "<table align=\"left\">\n",
+    "\n",
+    "  <td>\n",
+    "    <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
+    "    </a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
+    "      View on GitHub\n",
+    "    </a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/notebook_template.ipynb\">\n",
+    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
+    "      Open in Vertex AI Workbench\n",
+    "    </a>\n",
+    "  </td>                                                                                               \n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "24743cf4a1e1"
+   },
+   "source": [
+    "**_NOTE_**: This notebook has been tested in the following environment:\n",
+    "\n",
+    "* Python version = 3.9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tvgnzT1CKxrO"
+   },
+   "source": [
+    "## Overview\n",
+    "\n",
+    "{TODO: Include a paragraph or two explaining what this example demonstrates, who should be interested in it, and what you need to know before you get started.}\n",
+    "\n",
+    "Learn more about [web-doc-title](linkback-to-webdoc-page). {TODO: if more than one primary feature, add tag/linkback for each one}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d975e698c9a4"
+   },
+   "source": [
+    "### Objective\n",
+    "\n",
+    "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
+    "\n",
+    "This tutorial uses the following Google Cloud ML services and resources:\n",
+    "\n",
+    "- *{TODO: Add high level bullets for the services/resources demonstrated; e.g., Vertex AI Training}*\n",
+    "\n",
+    "\n",
+    "The steps performed include:\n",
+    "\n",
+    "- *{TODO: Add high level bullets for the steps of performed in the notebook}*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "08d289fa873f"
+   },
+   "source": [
+    "### Dataset\n",
+    "\n",
+    "{TODO: Include a paragraph with Dataset information and where to obtain it.} \n",
+    "\n",
+    "{TODO: Make sure the dataset is accessible to the public. **Googlers**: Add your dataset to the [public samples bucket](http://goto/cloudsamples#sample-storage-bucket) within gs://cloud-samples-data/vertex-ai, if it doesn't already exist there.}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "aed92deeb4a0"
+   },
+   "source": [
+    "### Costs \n",
+    "\n",
+    "{TODO: Update the list of billable products that your tutorial uses.}\n",
+    "\n",
+    "This tutorial uses billable components of Google Cloud:\n",
+    "\n",
+    "* Vertex AI\n",
+    "* {TODO: BigQuery}\n",
+    "* Cloud Storage\n",
+    "\n",
+    "{TODO: Include links to pricing documentation for each product you listed above.\n",
+    " NOTE: If you use BigQuery or Dataflow, you need to add this to the pricing.\n",
+    "}\n",
+    "\n",
+    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
+    "{ TODO: [BigQuery pricing](https://cloud.google.com/bigquery/pricing), }\n",
+    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing), \n",
+    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
+    "to generate a cost estimate based on your projected usage."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Poetry](https://python-poetry.org)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Clone Turbo Templates repository"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cloning into 'vertex-pipelines-end-to-end-samples'...\n",
+      "remote: Enumerating objects: 3866, done.\u001b[K\n",
+      "remote: Counting objects: 100% (2156/2156), done.\u001b[K\n",
+      "remote: Compressing objects: 100% (843/843), done.\u001b[K\n",
+      "remote: Total 3866 (delta 1311), reused 1807 (delta 1202), pack-reused 1710\u001b[K\n",
+      "Receiving objects: 100% (3866/3866), 3.05 MiB | 3.94 MiB/s, done.\n",
+      "Resolving deltas: 100% (2173/2173), done.\n"
+     ]
+    }
+   ],
    "source": [
     "# Clone a Git repository\n",
     "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
@@ -15,242 +190,3616 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "d4979f79-2c58-4554-bd93-db89a6367098",
+   "execution_count": 2,
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples\n"
+     ]
+    }
+   ],
    "source": [
-    "%cd vertex-pipelines-end-to-end-samples"
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "i7EUnXsZhAGF"
+   },
+   "source": [
+    "## Installation\n",
+    "\n",
+    "Install the following packages required to execute this notebook. \n",
+    "\n",
+    "{TODO: Suggest using the latest major GA version of each package; i.e., --upgrade}"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "435fb56c-7b27-4c7f-8d96-751bc9ba0324",
+   "execution_count": 3,
    "metadata": {
+    "collapsed": true,
+    "id": "2b4ef9b72d43",
+    "jupyter": {
+     "outputs_hidden": true
+    },
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Usage: pyenv install [-f] [-kvp] <version>...\n",
+      "       pyenv install [-f] [-kvp] <definition-file>\n",
+      "       pyenv install -l|--list\n",
+      "       pyenv install --version\n",
+      "\n",
+      "  -l/--list          List all available versions\n",
+      "  -f/--force         Install even if the version appears to be installed already\n",
+      "  -s/--skip-existing Skip if the version appears to be installed already\n",
+      "\n",
+      "  python-build options:\n",
+      "\n",
+      "  -k/--keep          Keep source tree in $PYENV_BUILD_ROOT after installation\n",
+      "                     (defaults to $PYENV_ROOT/sources)\n",
+      "  -p/--patch         Apply a patch from stdin before building\n",
+      "  -v/--verbose       Verbose mode: print compilation status to stdout\n",
+      "  --version          Show version of python-build\n",
+      "  -g/--debug         Build a debug version\n",
+      "\n",
+      "For detailed information on installing Python versions with\n",
+      "python-build, including a list of environment variables for adjusting\n",
+      "compilation, see: https://github.com/pyenv/pyenv#readme\n",
+      "\n",
+      "Creating virtualenv \u001b[36mpipelines\u001b[39m in /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/pipelines/.venv\n",
+      "\u001b[34mInstalling dependencies from lock file\u001b[39m\n",
+      "\n",
+      "\u001b[39;1mPackage operations\u001b[39;22m: \u001b[34m59\u001b[39m installs, \u001b[34m0\u001b[39m updates, \u001b[34m0\u001b[39m removals\n",
+      "\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2023.7.22\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.22.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.22.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.22.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.60.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.57.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.11.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.3.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[12A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "Connection pool is full, discarding connection: pypi.org. Connection pool size: 10\n",
+      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[14A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[13A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[32m8.1.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[12A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "Connection pool is full, discarding connection: pypi.org. Connection pool size: 10\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[13A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[12A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.7\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.11.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.10.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[32m26.1.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcfgv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcfgv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcfgv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "Connection pool is full, discarding connection: pypi.org. Connection pool size: 10\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.30.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcoverage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.2.5\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcoverage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.2.5\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcoverage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.2.5\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.21.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.21.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.21.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mBuilding...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPreparing...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mBuilding...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPreparing...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\n",
+      "\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mpipelines\u001b[39m (\u001b[39;1m0.1.0\u001b[39;22m)\u001b[1G\u001b[2K\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mpipelines\u001b[39m (\u001b[32m0.1.0\u001b[39m)\n",
+      "Setup for components/bigquery-components/\n",
+      "Creating virtualenv \u001b[36mbigquery-components\u001b[39m in /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components/.venv\n",
+      "\u001b[34mInstalling dependencies from lock file\u001b[39m\n",
+      "\u001b[33mWarning: poetry.lock is not consistent with pyproject.toml. You may be getting improper dependencies. Run `poetry lock [--no-update]` to fix it.\u001b[39m\n",
+      "\n",
+      "\u001b[39;1mPackage operations\u001b[39;22m: \u001b[34m41\u001b[39m installs, \u001b[34m1\u001b[39m update, \u001b[34m0\u001b[39m removals\n",
+      "\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2023.5.7\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.19.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.19.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.19.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.59.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.11.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.54.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.3.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[32m67.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[12A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[13A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[12A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[12A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[14A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[13A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[32m8.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[32m25.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.30.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.30.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.30.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\n",
+      "\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mbigquery-components\u001b[39m (\u001b[39;1m0.1.0\u001b[39;22m)\u001b[1G\u001b[2K\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mbigquery-components\u001b[39m (\u001b[32m0.1.0\u001b[39m)\n",
+      "Setup for components/vertex-components/\n",
+      "Creating virtualenv \u001b[36mvertex-components\u001b[39m in /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components/.venv\n",
+      "\u001b[34mInstalling dependencies from lock file\u001b[39m\n",
+      "\n",
+      "\u001b[39;1mPackage operations\u001b[39;22m: \u001b[34m46\u001b[39m installs, \u001b[34m0\u001b[39m updates, \u001b[34m0\u001b[39m removals\n",
+      "\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2023.7.22\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.22.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.22.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.22.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.60.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.57.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.11.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.3.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[10A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[32m8.1.6\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.11.4\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.10.3\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[32m26.1.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.30.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
+      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
+      "\n",
+      "\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mvertex-components\u001b[39m (\u001b[39;1m0.1.0\u001b[39;22m)\u001b[1G\u001b[2K\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mvertex-components\u001b[39m (\u001b[32m0.1.0\u001b[39m)\n",
+      "pre-commit installed at .git/hooks/pre-commit\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Install the correct Python version\n",
+    "! pyenv install -skip-existing\n",
+    "\n",
+    "# configure poetry \n",
+    "! poetry config virtualenvs.prefer-active-python true\n",
+    "\n",
+    "#Install poetry dependencies for ML pipelines\n",
+    "! make install\n",
+    "\n",
+    "# Install pre-commit hooks\n",
+    "! cd pipelines && poetry run pre-commit install\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "58707a750154"
+   },
    "source": [
-    "PROJECT_ID = \"my-project-id\"  # @param {type:\"string\"}\n",
-    "LOCATION = \"europe-west2\" # @param {type:\"string\"}"
+    "### Colab only: Uncomment the following cell to restart the kernel."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "9853f0e0-c712-4e41-92b3-edfdadb34593",
-   "metadata": {},
+   "execution_count": 4,
+   "metadata": {
+    "id": "f200f10a1da3",
+    "tags": []
+   },
    "outputs": [],
    "source": [
+    "# Automatically restart kernel after installs so that your environment can access the new packages\n",
+    "# import IPython\n",
+    "\n",
+    "# app = IPython.Application.instance()\n",
+    "# app.kernel.do_shutdown(True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "BF1j6f9HApxa"
+   },
+   "source": [
+    "## 1. Setup\n",
+    "\n",
+    "### Set up your Google Cloud project\n",
+    "\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
+    "\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+    "\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
+    "\n",
+    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WReHDGG5g0XY"
+   },
+   "source": [
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "id": "oM1iC_MfAts1",
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Updated property [core/project].\n",
+      "\n",
+      "\n",
+      "Updates are available for some Google Cloud CLI components.  To install them,\n",
+      "please run:\n",
+      "  $ gcloud components update\n",
+      "\n",
+      "env: VERTEX_PROJECT_ID=dt-donatas-sandbox-dev\n"
+     ]
+    }
+   ],
+   "source": [
+    "vertex_project_id = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "\n",
     "# Set the project id\n",
-    "!gcloud config set project {PROJECT_ID}"
+    "! gcloud config set project {vertex_project_id}\n",
+    "\n",
+    "# Set the environment variable\n",
+    "%env VERTEX_PROJECT_ID = {vertex_project_id}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "region"
+   },
+   "source": [
+    "#### Location\n",
+    "\n",
+    "You can also change the `VERTEX_LOCATION` variable used by Vertex AI. Learn more about [Vertex AI locations](https://cloud.google.com/vertex-ai/docs/general/locations)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "a43743b5-b750-4ffe-924e-f19b75a20570",
+   "execution_count": 6,
    "metadata": {
+    "id": "region",
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: VERTEX_LOCATION=europe-west2\n"
+     ]
+    }
+   ],
+   "source": [
+    "vertex_location = \"europe-west2\"  # @param {type: \"string\"}\n",
+    "\n",
+    "# Set the environment variable\n",
+    "%env VERTEX_LOCATION={vertex_location}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
-    "!gcloud auth application-default login"
+    "#### Resource Suffix\n",
+    "\n",
+    "Specify the `RESOURCE_SUFFIX` (e.g. `<your name>`) to facilitate running concurrent pipelines in the same Google Cloud project. \n",
+    "This is important to change if you are working in a team to avoid overwriting resources during development "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "18f3b0f6-ff25-4436-a604-4d694e758d16",
+   "execution_count": 7,
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: RESOUCE_SUFFIX=resource_suffix\n"
+     ]
+    }
+   ],
    "source": [
-    "import os\n",
+    "resource_suffix=\"default\" # @param {type: \"string\"}\n",
     "\n",
-    "os.environ['PIPELINE_TEMPLATE'] = 'xgboost'\n",
-    "os.environ['VERTEX_CMEK_IDENTIFIER'] = ''\n",
-    "os.environ['VERTEX_LOCATION'] = LOCATION\n",
-    "os.environ['VERTEX_NETWORK'] = ''\n",
-    "os.environ['VERTEX_PROJECT_ID'] = PROJECT_ID\n",
-    "os.environ['RESOURCE_SUFFIX']='default'\n",
+    "# Set the environment variable\n",
+    "%env RESOUCE_SUFFIX=resource_suffix"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Vertex Pipelines Service Account\n",
     "\n",
-    "# Calculate the value of VERTEX_SA_EMAIL based on VERTEX_PROJECT_ID\n",
-    "os.environ['VERTEX_SA_EMAIL'] = f'vertex-pipelines@{os.environ[\"VERTEX_PROJECT_ID\"]}.iam.gserviceaccount.com'\n",
-    "os.environ['PIPELINE_FILES_GCS_PATH'] = f'gs://{os.environ[\"VERTEX_PROJECT_ID\"]}-pl-root'\n",
-    "os.environ['CONTAINER_IMAGE_REGISTRY']=f'{os.environ[\"VERTEX_LOCATION\"]}-docker.pkg.dev/{os.environ[\"VERTEX_PROJECT_ID\"]}/vertex-images'"
+    "We need to set the `VERTEX_SA_EMAIL` that is in the Google Cloud project so that this service account can run the pipelines for us."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "fcf5ce7a-ef56-4e55-877c-697c4e8b2fb8",
+   "execution_count": 8,
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: VERTEX_SA_EMAIL=vertex-pipelines@dt-donatas-sandbox-dev.iam.gserviceaccount.com\n"
+     ]
+    }
+   ],
    "source": [
-    "# !gcloud services enable cloudresourcemanager.googleapis.com --project={PROJECT_ID}\n",
-    "# !gcloud services enable serviceusage.googleapis.com --project={PROJECT_ID}\n",
-    "!gcloud storage buckets create gs://{PROJECT_ID}-tfstate --project={PROJECT_ID} --location={LOCATION} --uniform-bucket-level-access"
+    "vertex_sa_email=f\"vertex-pipelines@{vertex_project_id}.iam.gserviceaccount.com\"\n",
+    "\n",
+    "# Set the environment variable\n",
+    "%env VERTEX_SA_EMAIL={vertex_sa_email}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "#### Vertex Pipelines Root Bucket\n",
+    "\n",
+    "We need to set the `VERTEX_PIPELINE_ROOT` that is in the Google Cloud project which is used to stage pipeline artifacts."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "798f98ee-3cdc-4dbe-9e3e-a7e9c1d8d1cd",
+   "execution_count": 9,
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: VERTEX_PIPELINE_ROOT=gs://$dt-donatas-sandbox-dev-pl-root\n"
+     ]
+    }
+   ],
    "source": [
-    "!make install"
+    "vertex_pipeline_root=f\"gs://${vertex_project_id}-pl-root\"\n",
+    "\n",
+    "# Set the environment variable\n",
+    "%env VERTEX_PIPELINE_ROOT={vertex_pipeline_root}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Container Image Registry\n",
+    "\n",
+    "We need to set the `CONTAINER_IMAGE_REGISTRY` that is container image repository for training/serving container images."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "env: CONTAINER_IMAGE_REGISTRY=europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images\n"
+     ]
+    }
+   ],
+   "source": [
+    "container_image_registry=f\"{vertex_location}-docker.pkg.dev/{vertex_project_id}/vertex-images\"\n",
+    "\n",
+    "# Set the environment variable\n",
+    "%env CONTAINER_IMAGE_REGISTRY={container_image_registry}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "sBCra4QMA2wR"
+   },
+   "source": [
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "74ccc9e52986"
+   },
+   "source": [
+    "**1. Vertex AI Workbench**\n",
+    "* Do nothing as you are already authenticated."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "de775a3773ba"
+   },
+   "source": [
+    "**2. Local JupyterLab instance, uncomment and run:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "id": "254614fa0c46",
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Your browser has been opened to visit:\n",
+      "\n",
+      "    https://accounts.google.com/o/oauth2/auth?response_type=code&client_id=32555940559.apps.googleusercontent.com&redirect_uri=http%3A%2F%2Flocalhost%3A8085%2F&scope=openid+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fuserinfo.email+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fcloud-platform+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fappengine.admin+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fsqlservice.login+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fcompute+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Faccounts.reauth&state=k6jMTq96cILXIHTYaj26JHwqvHn6Ey&access_type=offline&code_challenge=whoq3ZN3MktqtUR1PwXG5jV0GljumM8qPT6GQpl-l5w&code_challenge_method=S256\n",
+      "\n",
+      "\n",
+      "You are now logged in as [donatas.mickevicius@datatonic.com].\n",
+      "Your current project is [dt-donatas-sandbox-dev].  You can change this setting by running:\n",
+      "  $ gcloud config set project PROJECT_ID\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ! gcloud auth login"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ef21552ccea8"
+   },
+   "source": [
+    "**3. Colab, uncomment and run:**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7963e7b2-aa51-46fd-b7e5-8f356f8beeec",
    "metadata": {
+    "id": "603adbbf0532"
+   },
+   "outputs": [],
+   "source": [
+    "# from google.colab import auth\n",
+    "# auth.authenticate_user()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "f6b2ccc891ed"
+   },
+   "source": [
+    "**4. Service account or other**\n",
+    "* See how to grant Cloud Storage permissions to your service account at https://cloud.google.com/storage/docs/gsutil/commands/iam#ch-examples."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zgPO1eR3CYjk"
+   },
+   "source": [
+    "### Infrastructure deployment using terraform.\n",
+    "\n",
+    "Install Terraform on your local machine. We recommend using [`tfswitch`](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version for you (run `tfswitch` from the [`terraform/envs/dev`](terraform/envs/dev/) directory).\n",
+    "\n",
+    "Now you can deploy the infrastructure using Terraform:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Create tfstate bucket\n",
+    "\n",
+    "Before provisioning our infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the state files for Terraform deployments.\n",
+    "\n",
+    "- *{Note to notebook author: For any user-provided strings that need to be unique (like bucket names or model ID's), append \"-unique\" to the end so proper testing can occur}*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "id": "MzGDU7TWdts_",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "#Make deploy needs approval (i.e. -auto-approve flag) MAKE FILE WOULD NEED SOME CHANGES\n",
-    "#!make deploy\n",
-    "! terraform -chdir=terraform/envs/dev init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' \n",
-    "! terraform -chdir=terraform/envs/dev plan -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'\n",
-    "# ! terraform -chdir=terraform/envs/dev apply -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}' -auto-approve"
+    "tf_state_bucket_uri = f\"gs://{vertex_project_id}-tfstate\"  # @param {type:\"string\"}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "-EcIXiGsCePi"
+   },
+   "source": [
+    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "id": "NIq7R4HZCfIc",
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Creating gs://dt-donatas-sandbox-dev-tfstate/...\n",
+      "ServiceException: 409 A Cloud Storage bucket named 'dt-donatas-sandbox-dev-tfstate' already exists. Try another name. Bucket names must be globally unique across all Google Cloud projects, including those outside of your organization.\n"
+     ]
+    }
+   ],
+   "source": [
+    "! gsutil mb -l {vertex_location} -p {vertex_project_id} {tf_state_bucket_uri}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "960505627ddf"
+   },
+   "source": [
+    "### Deploy required infrastructure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dt-donatas-sandbox-dev\n"
+     ]
+    }
+   ],
+   "source": [
+    "!echo ${VERTEX_PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Initialize Backend**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "95726e43-1bc1-4de5-a463-0fae31a5256c",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
-    "!bq --location={LOCATION} mk --dataset \"{PROJECT_ID}:chicago_taxi_trips\""
+    "! terraform -chdir=terraform/envs/dev init -backend-config=\"bucket=${VERTEX_PROJECT_ID}-tfstate\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Terraform Plan**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "83ed96eb-3a12-4d07-8b00-701708e9f823",
    "metadata": {
+    "id": "PyQmSRbKA8r-",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "!bq --location={LOCATION} mk --dataset \"{PROJECT_ID}:preprocessing\""
+    "! terraform -chdir=terraform/envs/dev plan -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Terraform Apply** Please check tf plan output to see what infrastructure will be provisioned. If everything looks ok uncomment and run cell below."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bc01d526-c528-4f82-9541-6a8319fbedaf",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# TO TRANSFER DATA USED CONSOLE TO CREATE DATA TRANSFER\n",
-    "\n",
-    "\n",
-    "#ERRORS\n",
-    "# bq mk asks for code to be pasted from generated link to authenticate data transfer. Cant be done in jupyter?\n",
-    "\n",
-    "# bq mk --transfer_config \\\n",
-    "#   --project_id=${VERTEX_PROJECT_ID} \\\n",
-    "#   --data_source=\"cross_region_copy\" \\\n",
-    "#   --target_dataset=\"chicago_taxi_trips\" \\\n",
-    "#   --display_name=\"Chicago taxi trip mirror\" \\\n",
-    "#   --params='{\"source_dataset_id\":\"'\"chicago_taxi_trips\"'\",\"source_project_id\":\"'\"bigquery-public-data\"'\"}'\n",
+    "# ! terraform -chdir=terraform/envs/dev apply -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" -auto-approve -lock=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Example ML Pipelines"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This repository contains example ML training and prediction pipelines for two popular frameworks (XGBoost/sklearn and Tensorflow) using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips). The details of these can be found in the [separate README](pipelines/README.md).\n",
     "\n",
+    "#### Pre-requisites\n",
     "\n",
-    "# python code below gives \"Request contains an invalid argument. error\n",
+    "Before you can run these example pipelines successfully there are a few additional things you will need to deploy (they have not been included in the Terraform code as they are specific to these pipelines)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "1. Create a new BigQuery dataset for the Chicago Taxi data:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "BigQuery error in mk operation: Dataset 'dt-donatas-sandbox-\n",
+      "dev:chicago_taxi_trips' already exists.\n"
+     ]
+    }
+   ],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "2. Create a new BigQuery dataset for data processing during the pipelines:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "BigQuery error in mk operation: Dataset 'dt-donatas-sandbox-dev:preprocessing'\n",
+      "already exists.\n"
+     ]
+    }
+   ],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "https://www.gstatic.com/bigquerydatatransfer/oauthz/auth?client_id=433065040935-uvs8ptbn0udhuartdhl4nn1l27t5v3qg.apps.googleusercontent.com&scope=https://www.googleapis.com/auth/bigquery&redirect_uri=urn:ietf:wg:oauth:2.0:oob&response_type=version_info\n",
+      "Please copy and paste the above URL into your web browser and follow the instructions to retrieve a version_info.\n",
+      "Enter your version_info here: ^C\n"
+     ]
+    }
+   ],
+   "source": [
+    "! bq mk --transfer_config \\\n",
+    "  --project_id=${VERTEX_PROJECT_ID} \\\n",
+    "  --data_source=\"cross_region_copy\" \\\n",
+    "  --target_dataset=\"chicago_taxi_trips\" \\\n",
+    "  --display_name=\"Chicago taxi trip mirror\" \\\n",
+    "  --params='{\"source_dataset_id\":\"'\"chicago_taxi_trips\"'\",\"source_project_id\":\"'\"bigquery-public-data\"'\"}' \\\n",
+    "  --quiet=true"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\"source_project_id\":\"'\"bigquery-public-data\"'\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install google-cloud-bigquery-datatransfer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "!echo $GOOGLE_APPLICATION_CREDENTIALS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Your browser has been opened to visit:\n",
+      "\n",
+      "    https://accounts.google.com/o/oauth2/auth?response_type=code&client_id=764086051850-6qr4p6gpi6hn506pt8ejuq83di341hur.apps.googleusercontent.com&redirect_uri=http%3A%2F%2Flocalhost%3A8085%2F&scope=openid+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fuserinfo.email+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fcloud-platform+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fsqlservice.login+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Faccounts.reauth&state=5HwStYisqE4FHgRbPiNDCIMrtmmJ4o&access_type=offline&code_challenge=4d8hOLhGRdD86uNzFAM_NpHkz6S70HIqB0E5XQhXpBs&code_challenge_method=S256\n",
+      "\n",
+      "\n",
+      "Credentials saved to file: [/Users/donatasmickevicius/.config/gcloud/application_default_credentials.json]\n",
+      "\n",
+      "These credentials will be used by any library that requests Application Default Credentials (ADC).\n",
+      "\n",
+      "Quota project \"dt-donatas-sandbox-dev\" was added to ADC which can be used by Google client libraries for billing and quota. Note that some services may still bill the project owning the resource.\n"
+     ]
+    }
+   ],
+   "source": [
+    "! gcloud auth application-default login "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Created transfer config: projects/529423390811/locations/europe-west2/transferConfigs/64ff46a0-0000-2d9c-b971-089e0820ebe0\n"
+     ]
+    }
+   ],
+   "source": [
+    "from google.cloud import bigquery_datatransfer\n",
     "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
     "\n",
-    "#!pip install google-cloud-bigquery-datatransfer\n",
-    "# from google.cloud import bigquery_datatransfer\n",
+    "destination_project_id = vertex_project_id\n",
+    "destination_dataset_id = \"chicago_taxi_trips\"\n",
+    "source_project_id = \"bigquery-public-data\"\n",
+    "source_dataset_id = \"chicago_taxi_trips\"\n",
+    "transfer_config = bigquery_datatransfer.TransferConfig(\n",
+    "    destination_dataset_id=destination_dataset_id,\n",
+    "    display_name=\"Chicago taxi trip mirror\",\n",
+    "    data_source_id=\"cross_region_copy\",\n",
+    "    params={\n",
+    "        \"source_project_id\": source_project_id,\n",
+    "        \"source_dataset_id\": source_dataset_id,\n",
+    "    },\n",
+    "    schedule=\"every 24 hours\",\n",
+    ")\n",
+    "transfer_config = transfer_client.create_transfer_config(\n",
+    "    parent=transfer_client.common_project_path(destination_project_id),\n",
+    "    transfer_config=transfer_config,\n",
+    ")\n",
+    "print(f\"Created transfer config: {transfer_config.name}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Building the container images\n",
     "\n",
-    "# transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "The [model/](/model/) directory contains the code for custom training and serving container images [model/training/train.py](model/training/train.py).\n",
     "\n",
-    "# destination_project_id = \"dt-donatas-sandbox-dev\"\n",
-    "# destination_dataset_id = \"dt-donatas-sandbox-dev:chicago_taxi_trips\"\n",
-    "# source_project_id = \"bigquery-public-data\"\n",
-    "# source_dataset_id = \"chicago_taxi_trips\"\n",
-    "# transfer_config = bigquery_datatransfer.TransferConfig(\n",
-    "#     destination_dataset_id=destination_dataset_id,\n",
-    "#     display_name=\"Chicago taxi trip mirror\",\n",
-    "#     data_source_id=\"cross_region_copy\",\n",
-    "#     params={\n",
-    "#         \"source_project_id\": source_project_id,\n",
-    "#         \"source_dataset_id\": source_dataset_id,\n",
-    "#     },\n",
-    "#     schedule=\"every 24 hours\",\n",
-    "# )\n",
-    "# transfer_config = transfer_client.create_transfer_config(\n",
-    "#     parent=transfer_client.common_project_path(destination_project_id),\n",
-    "#     transfer_config=transfer_config,\n",
-    "# )\n",
-    "# print(f\"Created transfer config: {transfer_config.name}\")"
+    "Build the training and serving container images and push them to Artifact Registry."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d69779bd-47a3-4075-8c58-48f2dea2a6da",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Building training image\n",
+      "Creating temporary tarball archive of 7 file(s) totalling 87.1 KiB before compression.\n",
+      "Uploading tarball of [.] to [gs://dt-donatas-sandbox-dev-staging/source/1694009873.552364-fb32142e7a9740909e0a330ba3cfe17c.tgz]\n",
+      "Created [https://cloudbuild.googleapis.com/v1/projects/dt-donatas-sandbox-dev/locations/europe-west2/builds/8186df5e-46d3-4ff7-909b-1d5fb539e3a1].\n",
+      "Logs are available at [ https://console.cloud.google.com/cloud-build/builds;region=europe-west2/8186df5e-46d3-4ff7-909b-1d5fb539e3a1?project=529423390811 ].\n",
+      "----------------------------- REMOTE BUILD OUTPUT ------------------------------\n",
+      "starting build \"8186df5e-46d3-4ff7-909b-1d5fb539e3a1\"\n",
+      "\n",
+      "FETCHSOURCE\n",
+      "Fetching storage object: gs://dt-donatas-sandbox-dev-staging/source/1694009873.552364-fb32142e7a9740909e0a330ba3cfe17c.tgz#1694009874031650\n",
+      "Copying gs://dt-donatas-sandbox-dev-staging/source/1694009873.552364-fb32142e7a9740909e0a330ba3cfe17c.tgz#1694009874031650...\n",
+      "/ [1 files][ 28.4 KiB/ 28.4 KiB]                                                \n",
+      "Operation completed over 1 objects/28.4 KiB.                                     \n",
+      "BUILD\n",
+      "Pulling image: gcr.io/kaniko-project/executor:latest\n",
+      "latest: Pulling from kaniko-project/executor\n",
+      "24b9c0f43324: Already exists\n",
+      "0d0cf3a75faa: Already exists\n",
+      "a13620305055: Already exists\n",
+      "3c02b8d0f8d0: Pulling fs layer\n",
+      "f2ed186425e5: Pulling fs layer\n",
+      "c113a25f71a0: Pulling fs layer\n",
+      "e600f5fdfda3: Pulling fs layer\n",
+      "41ac909a10bf: Pulling fs layer\n",
+      "3eb8d55ab910: Pulling fs layer\n",
+      "e600f5fdfda3: Waiting\n",
+      "41ac909a10bf: Waiting\n",
+      "3eb8d55ab910: Waiting\n",
+      "3c02b8d0f8d0: Verifying Checksum\n",
+      "3c02b8d0f8d0: Download complete\n",
+      "f2ed186425e5: Verifying Checksum\n",
+      "f2ed186425e5: Download complete\n",
+      "c113a25f71a0: Verifying Checksum\n",
+      "c113a25f71a0: Download complete\n",
+      "e600f5fdfda3: Download complete\n",
+      "41ac909a10bf: Verifying Checksum\n",
+      "41ac909a10bf: Download complete\n",
+      "3c02b8d0f8d0: Pull complete\n",
+      "f2ed186425e5: Pull complete\n",
+      "c113a25f71a0: Pull complete\n",
+      "e600f5fdfda3: Pull complete\n",
+      "41ac909a10bf: Pull complete\n",
+      "3eb8d55ab910: Verifying Checksum\n",
+      "3eb8d55ab910: Download complete\n",
+      "3eb8d55ab910: Pull complete\n",
+      "Digest: sha256:6aace7210ad8bf0da4b1aa707a1c0ea962d0e871bb1921504c1a5e690d5f6a2a\n",
+      "Status: Downloaded newer image for gcr.io/kaniko-project/executor:latest\n",
+      "gcr.io/kaniko-project/executor:latest\n",
+      "\u001b[36mINFO\u001b[0m[0000] Resolved base name python:3.9.16-slim to builder \n",
+      "\u001b[36mINFO\u001b[0m[0000] Resolved base name builder to training       \n",
+      "\u001b[36mINFO\u001b[0m[0000] Retrieving image manifest python:3.9.16-slim \n",
+      "\u001b[36mINFO\u001b[0m[0000] Retrieving image python:3.9.16-slim from registry index.docker.io\n",
+      "\u001b[36mINFO\u001b[0m[0000] Retrieving image manifest python:3.9.16-slim \n",
+      "\u001b[36mINFO\u001b[0m[0000] Returning cached image manifest              \n",
+      "\u001b[36mINFO\u001b[0m[0001] Built cross stage deps: map[]                \n",
+      "\u001b[36mINFO\u001b[0m[0001] Retrieving image manifest python:3.9.16-slim \n",
+      "\u001b[36mINFO\u001b[0m[0001] Returning cached image manifest              \n",
+      "\u001b[36mINFO\u001b[0m[0001] Retrieving image manifest python:3.9.16-slim \n",
+      "\u001b[36mINFO\u001b[0m[0001] Returning cached image manifest              \n",
+      "\u001b[36mINFO\u001b[0m[0001] Executing 0 build triggers                   \n",
+      "\u001b[36mINFO\u001b[0m[0001] Building stage 'python:3.9.16-slim' [idx: '0', base-idx: '-1'] \n",
+      "\u001b[36mINFO\u001b[0m[0001] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/training/cache:c11a5eafecf1c87b200f99fd974266d08cea862d33779292584b49d00403d0d0... \n",
+      "\u001b[36mINFO\u001b[0m[0001] Using caching version of cmd: RUN pip install poetry==${POETRY_VERSION} \n",
+      "\u001b[36mINFO\u001b[0m[0001] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/training/cache:3a4748cb15c98dbea0a12531d8158c54644335412df8f535d6bfb31666ad92e5... \n",
+      "\u001b[36mINFO\u001b[0m[0001] Using caching version of cmd: RUN poetry config virtualenvs.create false && poetry install \n",
+      "\u001b[36mINFO\u001b[0m[0001] Unpacking rootfs as cmd COPY pyproject.toml pyproject.toml requires it.\n",
+      "\u001b[36mINFO\u001b[0m[0004] ENV PIP_NO_CACHE_DIR=off     PIP_DISABLE_PIP_VERSION_CHECK=on     PIP_DEFAULT_TIMEOUT=100 \n",
+      "\u001b[36mINFO\u001b[0m[0004] No files changed in this command, skipping snapshotting. \n",
+      "\u001b[36mINFO\u001b[0m[0004] ARG POETRY_VERSION=1.5.1                     \n",
+      "\u001b[36mINFO\u001b[0m[0004] No files changed in this command, skipping snapshotting. \n",
+      "\u001b[36mINFO\u001b[0m[0004] COPY pyproject.toml pyproject.toml           \n",
+      "\u001b[36mINFO\u001b[0m[0004] Taking snapshot of files...                  \n",
+      "\u001b[36mINFO\u001b[0m[0004] COPY poetry.lock poetry.lock                 \n",
+      "\u001b[36mINFO\u001b[0m[0004] Taking snapshot of files...                  \n",
+      "\u001b[36mINFO\u001b[0m[0004] RUN pip install poetry==${POETRY_VERSION}    \n",
+      "\u001b[36mINFO\u001b[0m[0004] Found cached layer, extracting to filesystem\n",
+      "\u001b[36mINFO\u001b[0m[0006] RUN poetry config virtualenvs.create false && poetry install \n",
+      "\u001b[36mINFO\u001b[0m[0006] Found cached layer, extracting to filesystem\n",
+      "\u001b[36mINFO\u001b[0m[0026] Storing source image from stage 0 at path /kaniko/stages/0\n"
+     ]
+    }
+   ],
    "source": [
-    "!make build"
+    "! make build"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3e8f1804-72ae-4964-a00c-9d60f70f97a6",
+   "cell_type": "markdown",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
    "source": [
-    "!make run pipeline=training build=false"
+    "### Running Pipelines\n",
+    "\n",
+    "You can run the training pipeline (for example) with:\n",
+    "\n",
+    "This will execute the pipeline using the chosen template on Vertex AI, namely it will:\n",
+    "\n",
+    "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
+    "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Run Training Pipeline**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "96a8c160-415c-45b6-81b6-845cfcd9501d",
    "metadata": {},
    "outputs": [],
    "source": [
-    "!make run pipeline=prediction build=false"
+    "! make run pipeline=training build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Run Prediction Pipeline** \n",
+    "\n",
+    "After successful training run you can try prediction pipeline."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "61504b1b-f988-43f2-9dc1-385afdc83d97",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#!make undeploy"
+    "! make run pipeline=prediction build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "TpV-iwP9qw9c"
+   },
+   "source": [
+    "## 4. Cleaning up\n",
+    "\n",
+    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
+    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+    "\n",
+    "Otherwise, you can delete the individual resources you created in this tutorial:\n",
+    "\n",
+    "{TODO: Include infrastructure cleanup}"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "sx_vKniMq9ZX"
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -264,14 +3813,14 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.9.6"
   },
   "vscode": {
    "interpreter": {
-    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
    }
   }
  },
  "nbformat": 4,
- "nbformat_minor": 5
+ "nbformat_minor": 4
 }

From 3ee90896d6fda7f5d0c9a6a94c057c95061396e7 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 6 Sep 2023 15:26:08 +0100
Subject: [PATCH 194/238] feat: Updated Tutorial

---
 ...{try_it_yourself.ipynb => pipelines.ipynb} | 156 +++++++++++++++++-
 1 file changed, 147 insertions(+), 9 deletions(-)
 rename examples/{try_it_yourself.ipynb => pipelines.ipynb} (98%)

diff --git a/examples/try_it_yourself.ipynb b/examples/pipelines.ipynb
similarity index 98%
rename from examples/try_it_yourself.ipynb
rename to examples/pipelines.ipynb
index 53c74abf..af05d7cc 100644
--- a/examples/try_it_yourself.ipynb
+++ b/examples/pipelines.ipynb
@@ -2988,7 +2988,7 @@
     }
    ],
    "source": [
-    "vertex_project_id = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "vertex_project_id = \"[my-project-id]\"  # @param {type:\"string\"}\n",
     "\n",
     "# Set the project id\n",
     "! gcloud config set project {vertex_project_id}\n",
@@ -3107,7 +3107,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 50,
    "metadata": {
     "tags": []
    },
@@ -3116,12 +3116,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "env: VERTEX_PIPELINE_ROOT=gs://$dt-donatas-sandbox-dev-pl-root\n"
+      "env: VERTEX_PIPELINE_ROOT=gs://dt-donatas-sandbox-dev-pl-root\n"
      ]
     }
    ],
    "source": [
-    "vertex_pipeline_root=f\"gs://${vertex_project_id}-pl-root\"\n",
+    "vertex_pipeline_root=f\"gs://{vertex_project_id}-pl-root\"\n",
     "\n",
     "# Set the environment variable\n",
     "%env VERTEX_PIPELINE_ROOT={vertex_pipeline_root}"
@@ -3621,7 +3621,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {
     "tags": []
    },
@@ -3708,7 +3708,129 @@
       "\u001b[36mINFO\u001b[0m[0004] Found cached layer, extracting to filesystem\n",
       "\u001b[36mINFO\u001b[0m[0006] RUN poetry config virtualenvs.create false && poetry install \n",
       "\u001b[36mINFO\u001b[0m[0006] Found cached layer, extracting to filesystem\n",
-      "\u001b[36mINFO\u001b[0m[0026] Storing source image from stage 0 at path /kaniko/stages/0\n"
+      "\u001b[36mINFO\u001b[0m[0026] Storing source image from stage 0 at path /kaniko/stages/0\n",
+      "\u001b[36mINFO\u001b[0m[0036] Deleting filesystem...\n",
+      "\u001b[36mINFO\u001b[0m[0036] Base image from previous stage 0 found, using saved tar at path /kaniko/stages/0 \n",
+      "\u001b[36mINFO\u001b[0m[0036] Executing 0 build triggers\n",
+      "\u001b[36mINFO\u001b[0m[0040] Building stage 'builder' [idx: '1', base-idx: '0'] \n",
+      "\u001b[36mINFO\u001b[0m[0040] Unpacking rootfs as cmd COPY training/train.py training/train.py requires it.\n",
+      "\u001b[36mINFO\u001b[0m[0052] COPY training/train.py training/train.py     \n",
+      "\u001b[36mINFO\u001b[0m[0052] Taking snapshot of files...                  \n",
+      "\u001b[36mINFO\u001b[0m[0052] Pushing image to europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/training: \n",
+      "\u001b[36mINFO\u001b[0m[0052] Pushed europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/training@sha256:a9635753244b1d46a825feff9270588dde7545418d044727524b129c378b4fba\n",
+      "PUSH\n",
+      "DONE\n",
+      "--------------------------------------------------------------------------------\n",
+      "ID                                    CREATE_TIME                DURATION  SOURCE                                                                                             IMAGES  STATUS\n",
+      "8186df5e-46d3-4ff7-909b-1d5fb539e3a1  2023-09-06T14:17:54+00:00  1M13S     gs://dt-donatas-sandbox-dev-staging/source/1694009873.552364-fb32142e7a9740909e0a330ba3cfe17c.tgz  -       SUCCESS\n",
+      "Building serving image\n",
+      "Creating temporary tarball archive of 7 file(s) totalling 87.1 KiB before compression.\n",
+      "Uploading tarball of [.] to [gs://dt-donatas-sandbox-dev-staging/source/1694009951.638785-186144ba8771421c998171d12fc788c2.tgz]\n",
+      "Created [https://cloudbuild.googleapis.com/v1/projects/dt-donatas-sandbox-dev/locations/europe-west2/builds/378f1da1-8eef-4cf6-85e6-27738a9bd038].\n",
+      "Logs are available at [ https://console.cloud.google.com/cloud-build/builds;region=europe-west2/378f1da1-8eef-4cf6-85e6-27738a9bd038?project=529423390811 ].\n",
+      "----------------------------- REMOTE BUILD OUTPUT ------------------------------\n",
+      "starting build \"378f1da1-8eef-4cf6-85e6-27738a9bd038\"\n",
+      "\n",
+      "FETCHSOURCE\n",
+      "Fetching storage object: gs://dt-donatas-sandbox-dev-staging/source/1694009951.638785-186144ba8771421c998171d12fc788c2.tgz#1694009952285513\n",
+      "Copying gs://dt-donatas-sandbox-dev-staging/source/1694009951.638785-186144ba8771421c998171d12fc788c2.tgz#1694009952285513...\n",
+      "/ [1 files][ 28.4 KiB/ 28.4 KiB]                                                \n",
+      "Operation completed over 1 objects/28.4 KiB.\n",
+      "BUILD\n",
+      "Pulling image: gcr.io/kaniko-project/executor:latest\n",
+      "latest: Pulling from kaniko-project/executor\n",
+      "24b9c0f43324: Already exists\n",
+      "0d0cf3a75faa: Already exists\n",
+      "a13620305055: Already exists\n",
+      "3c02b8d0f8d0: Pulling fs layer\n",
+      "f2ed186425e5: Pulling fs layer\n",
+      "c113a25f71a0: Pulling fs layer\n",
+      "e600f5fdfda3: Pulling fs layer\n",
+      "41ac909a10bf: Pulling fs layer\n",
+      "3eb8d55ab910: Pulling fs layer\n",
+      "e600f5fdfda3: Waiting\n",
+      "41ac909a10bf: Waiting\n",
+      "3eb8d55ab910: Waiting\n",
+      "3c02b8d0f8d0: Verifying Checksum\n",
+      "3c02b8d0f8d0: Download complete\n",
+      "f2ed186425e5: Verifying Checksum\n",
+      "f2ed186425e5: Download complete\n",
+      "c113a25f71a0: Verifying Checksum\n",
+      "c113a25f71a0: Download complete\n",
+      "e600f5fdfda3: Verifying Checksum\n",
+      "e600f5fdfda3: Download complete\n",
+      "41ac909a10bf: Verifying Checksum\n",
+      "41ac909a10bf: Download complete\n",
+      "3c02b8d0f8d0: Pull complete\n",
+      "f2ed186425e5: Pull complete\n",
+      "c113a25f71a0: Pull complete\n",
+      "e600f5fdfda3: Pull complete\n",
+      "41ac909a10bf: Pull complete\n",
+      "3eb8d55ab910: Verifying Checksum\n",
+      "3eb8d55ab910: Download complete\n",
+      "3eb8d55ab910: Pull complete\n",
+      "Digest: sha256:6aace7210ad8bf0da4b1aa707a1c0ea962d0e871bb1921504c1a5e690d5f6a2a\n",
+      "Status: Downloaded newer image for gcr.io/kaniko-project/executor:latest\n",
+      "gcr.io/kaniko-project/executor:latest\n",
+      "\u001b[36mINFO\u001b[0m[0000] Resolved base name python:3.9.16-slim to builder \n",
+      "\u001b[36mINFO\u001b[0m[0000] Resolved base name builder to training       \n",
+      "\u001b[36mINFO\u001b[0m[0000] Resolved base name builder to serving        \n",
+      "\u001b[36mINFO\u001b[0m[0000] Retrieving image manifest python:3.9.16-slim \n",
+      "\u001b[36mINFO\u001b[0m[0000] Retrieving image python:3.9.16-slim from registry index.docker.io\n",
+      "\u001b[36mINFO\u001b[0m[0000] Retrieving image manifest python:3.9.16-slim \n",
+      "\u001b[36mINFO\u001b[0m[0000] Returning cached image manifest              \n",
+      "\u001b[36mINFO\u001b[0m[0001] Built cross stage deps: map[]                \n",
+      "\u001b[36mINFO\u001b[0m[0001] Retrieving image manifest python:3.9.16-slim \n",
+      "\u001b[36mINFO\u001b[0m[0001] Returning cached image manifest              \n",
+      "\u001b[36mINFO\u001b[0m[0001] Retrieving image manifest python:3.9.16-slim \n",
+      "\u001b[36mINFO\u001b[0m[0001] Returning cached image manifest              \n",
+      "\u001b[36mINFO\u001b[0m[0001] Executing 0 build triggers                   \n",
+      "\u001b[36mINFO\u001b[0m[0001] Building stage 'python:3.9.16-slim' [idx: '0', base-idx: '-1'] \n",
+      "\u001b[36mINFO\u001b[0m[0001] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving/cache:c11a5eafecf1c87b200f99fd974266d08cea862d33779292584b49d00403d0d0...\n",
+      "\u001b[36mINFO\u001b[0m[0001] Using caching version of cmd: RUN pip install poetry==${POETRY_VERSION} \n",
+      "\u001b[36mINFO\u001b[0m[0001] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving/cache:3a4748cb15c98dbea0a12531d8158c54644335412df8f535d6bfb31666ad92e5... \n",
+      "\u001b[36mINFO\u001b[0m[0001] Using caching version of cmd: RUN poetry config virtualenvs.create false && poetry install \n",
+      "\u001b[36mINFO\u001b[0m[0001] Unpacking rootfs as cmd COPY pyproject.toml pyproject.toml requires it.\n",
+      "\u001b[36mINFO\u001b[0m[0005] ENV PIP_NO_CACHE_DIR=off     PIP_DISABLE_PIP_VERSION_CHECK=on     PIP_DEFAULT_TIMEOUT=100 \n",
+      "\u001b[36mINFO\u001b[0m[0005] No files changed in this command, skipping snapshotting. \n",
+      "\u001b[36mINFO\u001b[0m[0005] ARG POETRY_VERSION=1.5.1                     \n",
+      "\u001b[36mINFO\u001b[0m[0005] No files changed in this command, skipping snapshotting. \n",
+      "\u001b[36mINFO\u001b[0m[0005] COPY pyproject.toml pyproject.toml           \n",
+      "\u001b[36mINFO\u001b[0m[0005] Taking snapshot of files...                  \n",
+      "\u001b[36mINFO\u001b[0m[0005] COPY poetry.lock poetry.lock                 \n",
+      "\u001b[36mINFO\u001b[0m[0005] Taking snapshot of files...                  \n",
+      "\u001b[36mINFO\u001b[0m[0005] RUN pip install poetry==${POETRY_VERSION}    \n",
+      "\u001b[36mINFO\u001b[0m[0005] Found cached layer, extracting to filesystem\n",
+      "\u001b[36mINFO\u001b[0m[0006] RUN poetry config virtualenvs.create false && poetry install \n",
+      "\u001b[36mINFO\u001b[0m[0006] Found cached layer, extracting to filesystem\n",
+      "\u001b[36mINFO\u001b[0m[0026] Storing source image from stage 0 at path /kaniko/stages/0\n",
+      "\u001b[36mINFO\u001b[0m[0034] Deleting filesystem...\n",
+      "\u001b[36mINFO\u001b[0m[0035] Base image from previous stage 0 found, using saved tar at path /kaniko/stages/0 \n",
+      "\u001b[36mINFO\u001b[0m[0035] Executing 0 build triggers\n",
+      "\u001b[36mINFO\u001b[0m[0038] Building stage 'builder' [idx: '1', base-idx: '0'] \n",
+      "\u001b[36mINFO\u001b[0m[0038] Unpacking rootfs as cmd COPY training/train.py training/train.py requires it.\n",
+      "\u001b[36mINFO\u001b[0m[0050] COPY training/train.py training/train.py     \n",
+      "\u001b[36mINFO\u001b[0m[0050] Taking snapshot of files...                  \n",
+      "\u001b[36mINFO\u001b[0m[0050] Deleting filesystem...\n",
+      "\u001b[36mINFO\u001b[0m[0051] Base image from previous stage 0 found, using saved tar at path /kaniko/stages/0 \n",
+      "\u001b[36mINFO\u001b[0m[0051] Executing 0 build triggers\n",
+      "\u001b[36mINFO\u001b[0m[0054] Building stage 'builder' [idx: '2', base-idx: '0'] \n",
+      "\u001b[36mINFO\u001b[0m[0054] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving/cache:440ff423928e582f8e1aebbb700d6abb6bd659cd07668be714ab9441e42cc2e3... \n",
+      "\u001b[36mINFO\u001b[0m[0054] Using caching version of cmd: RUN poetry install --with serving \n",
+      "\u001b[36mINFO\u001b[0m[0054] Unpacking rootfs as cmd COPY serving/main.py serving/main.py requires it.\n",
+      "\u001b[36mINFO\u001b[0m[0066] RUN poetry install --with serving            \n",
+      "\u001b[36mINFO\u001b[0m[0066] Found cached layer, extracting to filesystem \n",
+      "\u001b[36mINFO\u001b[0m[0067] COPY serving/main.py serving/main.py         \n",
+      "\u001b[36mINFO\u001b[0m[0067] Taking snapshot of files...                  \n",
+      "\u001b[36mINFO\u001b[0m[0067] CMD exec uvicorn serving.main:app --host \"0.0.0.0\" --port \"$AIP_HTTP_PORT\" \n",
+      "\u001b[36mINFO\u001b[0m[0067] No files changed in this command, skipping snapshotting. \n",
+      "\u001b[36mINFO\u001b[0m[0067] Pushing image to europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving:\n",
+      "\u001b[36mINFO\u001b[0m[0067] Pushed europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving@sha256:b85a7e4707a61ab47b92c87bdf6954bf402a7ef57a83481baf18948f8ca99ee3\n",
+      "PUSH\n",
+      "DONE\n",
+      "--------------------------------------------------------------------------------\n",
+      "ID                                    CREATE_TIME                DURATION  SOURCE                                                                                             IMAGES  STATUS\n",
+      "378f1da1-8eef-4cf6-85e6-27738a9bd038  2023-09-06T14:19:12+00:00  1M25S     gs://dt-donatas-sandbox-dev-staging/source/1694009951.638785-186144ba8771421c998171d12fc788c2.tgz  -       SUCCESS\n"
      ]
     }
    ],
@@ -3741,9 +3863,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 51,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "/Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/pipelines/src/pipelines/training/pipeline.yaml\n",
+      "Creating PipelineJob\n",
+      "PipelineJob created. Resource name: projects/529423390811/locations/europe-west2/pipelineJobs/xgboost-train-pipeline-20230906152310\n",
+      "To use this PipelineJob in another session:\n",
+      "pipeline_job = aiplatform.PipelineJob.get('projects/529423390811/locations/europe-west2/pipelineJobs/xgboost-train-pipeline-20230906152310')\n",
+      "View Pipeline Job:\n",
+      "https://console.cloud.google.com/vertex-ai/locations/europe-west2/pipelines/runs/xgboost-train-pipeline-20230906152310?project=529423390811\n"
+     ]
+    }
+   ],
    "source": [
     "! make run pipeline=training build=false"
    ]

From 0c4ea34c9bd6cf027e471b3aa04a0748d9e092af Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 6 Sep 2023 15:29:49 +0100
Subject: [PATCH 195/238] feat: Remove outputs

---
 examples/pipelines.ipynb | 3141 +-------------------------------------
 1 file changed, 42 insertions(+), 3099 deletions(-)

diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index af05d7cc..5cd7c4f0 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -164,25 +164,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Cloning into 'vertex-pipelines-end-to-end-samples'...\n",
-      "remote: Enumerating objects: 3866, done.\u001b[K\n",
-      "remote: Counting objects: 100% (2156/2156), done.\u001b[K\n",
-      "remote: Compressing objects: 100% (843/843), done.\u001b[K\n",
-      "remote: Total 3866 (delta 1311), reused 1807 (delta 1202), pack-reused 1710\u001b[K\n",
-      "Receiving objects: 100% (3866/3866), 3.05 MiB | 3.94 MiB/s, done.\n",
-      "Resolving deltas: 100% (2173/2173), done.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Clone a Git repository\n",
     "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
@@ -190,19 +176,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "/Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%cd vertex-pipelines-end-to-end-samples/"
    ]
@@ -222,2676 +200,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
-    "collapsed": true,
     "id": "2b4ef9b72d43",
-    "jupyter": {
-     "outputs_hidden": true
-    },
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Usage: pyenv install [-f] [-kvp] <version>...\n",
-      "       pyenv install [-f] [-kvp] <definition-file>\n",
-      "       pyenv install -l|--list\n",
-      "       pyenv install --version\n",
-      "\n",
-      "  -l/--list          List all available versions\n",
-      "  -f/--force         Install even if the version appears to be installed already\n",
-      "  -s/--skip-existing Skip if the version appears to be installed already\n",
-      "\n",
-      "  python-build options:\n",
-      "\n",
-      "  -k/--keep          Keep source tree in $PYENV_BUILD_ROOT after installation\n",
-      "                     (defaults to $PYENV_ROOT/sources)\n",
-      "  -p/--patch         Apply a patch from stdin before building\n",
-      "  -v/--verbose       Verbose mode: print compilation status to stdout\n",
-      "  --version          Show version of python-build\n",
-      "  -g/--debug         Build a debug version\n",
-      "\n",
-      "For detailed information on installing Python versions with\n",
-      "python-build, including a list of environment variables for adjusting\n",
-      "compilation, see: https://github.com/pyenv/pyenv#readme\n",
-      "\n",
-      "Creating virtualenv \u001b[36mpipelines\u001b[39m in /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/pipelines/.venv\n",
-      "\u001b[34mInstalling dependencies from lock file\u001b[39m\n",
-      "\n",
-      "\u001b[39;1mPackage operations\u001b[39;22m: \u001b[34m59\u001b[39m installs, \u001b[34m0\u001b[39m updates, \u001b[34m0\u001b[39m removals\n",
-      "\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2023.7.22\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.22.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.22.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.22.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.60.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.57.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.11.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.3.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[12A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "Connection pool is full, discarding connection: pypi.org. Connection pool size: 10\n",
-      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.12.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[14A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[13A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[32m8.1.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[12A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "Connection pool is full, discarding connection: pypi.org. Connection pool size: 10\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[13A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[12A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdistlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.7\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mfilelock\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.12.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.11.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.10.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[32m26.1.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mplatformdirs\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcfgv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcfgv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcfgv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.26\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "Connection pool is full, discarding connection: pypi.org. Connection pool size: 10\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m20.24.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.30.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midentify\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.26\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mmarkupsafe\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mnodeenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvirtualenv\u001b[39m\u001b[39m (\u001b[39m\u001b[32m20.24.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcoverage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.2.5\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcoverage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.2.5\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcoverage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.2.5\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.21.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.21.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.21.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mjinja2\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpre-commit\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.21.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mBuilding...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPreparing...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mbigquery-components\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mBuilding...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPreparing...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mvertex-components\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.1.0 /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\n",
-      "\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mpipelines\u001b[39m (\u001b[39;1m0.1.0\u001b[39;22m)\u001b[1G\u001b[2K\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mpipelines\u001b[39m (\u001b[32m0.1.0\u001b[39m)\n",
-      "Setup for components/bigquery-components/\n",
-      "Creating virtualenv \u001b[36mbigquery-components\u001b[39m in /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/bigquery-components/.venv\n",
-      "\u001b[34mInstalling dependencies from lock file\u001b[39m\n",
-      "\u001b[33mWarning: poetry.lock is not consistent with pyproject.toml. You may be getting improper dependencies. Run `poetry lock [--no-update]` to fix it.\u001b[39m\n",
-      "\n",
-      "\u001b[39;1mPackage operations\u001b[39;22m: \u001b[34m41\u001b[39m installs, \u001b[34m1\u001b[39m update, \u001b[34m0\u001b[39m removals\n",
-      "\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.5.7\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2023.5.7\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.1.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.19.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.19.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.19.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.59.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.59.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.11.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.54.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.54.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.4.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.3.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.4.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[39;1m67.8.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mUpdating \u001b[39m\u001b[36msetuptools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m68.0.0\u001b[39;22m\u001b[39m -> \u001b[39m\u001b[32m67.8.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[12A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[13A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[12A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[12A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[14A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[13A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[32m8.1.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m25.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[32m25.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.30.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.30.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.30.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\n",
-      "\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mbigquery-components\u001b[39m (\u001b[39;1m0.1.0\u001b[39;22m)\u001b[1G\u001b[2K\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mbigquery-components\u001b[39m (\u001b[32m0.1.0\u001b[39m)\n",
-      "Setup for components/vertex-components/\n",
-      "Creating virtualenv \u001b[36mvertex-components\u001b[39m in /Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/components/vertex-components/.venv\n",
-      "\u001b[34mInstalling dependencies from lock file\u001b[39m\n",
-      "\n",
-      "\u001b[39;1mPackage operations\u001b[39;22m: \u001b[34m46\u001b[39m installs, \u001b[34m0\u001b[39m updates, \u001b[34m0\u001b[39m removals\n",
-      "\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m5.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcachetools\u001b[39m\u001b[39m (\u001b[39m\u001b[32m5.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2023.7.22\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.16.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.26.16\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcertifi\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2023.7.22\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mcharset-normalizer\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36midna\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.20.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mprotobuf\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.20.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.3.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m4.9\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyasn1-modules\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.3.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrsa\u001b[39m\u001b[39m (\u001b[39m\u001b[32m4.9\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36msix\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.16.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36murllib3\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.26.16\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.22.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.22.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.31.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-auth\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.22.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.60.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogleapis-common-protos\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.60.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.57.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.57.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.31.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.11.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.48.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-api-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.11.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-crc32c\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpcio-status\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.48.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36moauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.3.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.5.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.12.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.3.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m23.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m6.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-core\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.3.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-resumable-media\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.5.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgrpc-google-iam-v1\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.12.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpackaging\u001b[39m\u001b[39m (\u001b[39m\u001b[32m23.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.22.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.6.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mproto-plus\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.22.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.8.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpython-dateutil\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.8.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpyyaml\u001b[39m\u001b[39m (\u001b[39m\u001b[32m6.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-oauthlib\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.3.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mwebsocket-client\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.6.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m8.1.6\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.15\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.2.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.9.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[11A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[10A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mclick\u001b[39m\u001b[39m (\u001b[39m\u001b[32m8.1.6\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mdocstring-parser\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.15\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m3.11.4\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.10.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m0.10.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[9A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-bigquery\u001b[39m\u001b[39m (\u001b[39m\u001b[32m3.11.4\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.10.3\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[8A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[7A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-resource-manager\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.10.3\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-storage\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.10.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-pipeline-spec\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.2.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp-server-api\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m26.1.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.8.5.post1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkubernetes\u001b[39m\u001b[39m (\u001b[39m\u001b[32m26.1.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mrequests-toolbelt\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.10.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mshapely\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.8.5.post1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtabulate\u001b[39m\u001b[39m (\u001b[39m\u001b[32m0.9.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.1.2\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[6A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mexceptiongroup\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.1.2\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.30.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.0.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m1.2.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[3A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[5A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[4A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-aiplatform\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.30.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36miniconfig\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mkfp\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpluggy\u001b[39m\u001b[39m (\u001b[39m\u001b[32m1.2.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mtomli\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.0.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mPending...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m2.1.1\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "  \u001b[34;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[39;1m7.4.0\u001b[39;22m\u001b[39m)\u001b[39m: \u001b[34mInstalling...\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[2A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\u001b[1A\u001b[0J  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mgoogle-cloud-pipeline-components\u001b[39m\u001b[39m (\u001b[39m\u001b[32m2.1.1\u001b[39m\u001b[39m)\u001b[39m\n",
-      "  \u001b[32;1m•\u001b[39;22m \u001b[39mInstalling \u001b[39m\u001b[36mpytest\u001b[39m\u001b[39m (\u001b[39m\u001b[32m7.4.0\u001b[39m\u001b[39m)\u001b[39m\n",
-      "\n",
-      "\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mvertex-components\u001b[39m (\u001b[39;1m0.1.0\u001b[39;22m)\u001b[1G\u001b[2K\u001b[39;1mInstalling\u001b[39;22m the current project: \u001b[36mvertex-components\u001b[39m (\u001b[32m0.1.0\u001b[39m)\n",
-      "pre-commit installed at .git/hooks/pre-commit\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Install the correct Python version\n",
     "! pyenv install -skip-existing\n",
@@ -2917,7 +231,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "id": "f200f10a1da3",
     "tags": []
@@ -2966,27 +280,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "id": "oM1iC_MfAts1",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Updated property [core/project].\n",
-      "\n",
-      "\n",
-      "Updates are available for some Google Cloud CLI components.  To install them,\n",
-      "please run:\n",
-      "  $ gcloud components update\n",
-      "\n",
-      "env: VERTEX_PROJECT_ID=dt-donatas-sandbox-dev\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vertex_project_id = \"[my-project-id]\"  # @param {type:\"string\"}\n",
     "\n",
@@ -3010,20 +309,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {
     "id": "region",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "env: VERTEX_LOCATION=europe-west2\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vertex_location = \"europe-west2\"  # @param {type: \"string\"}\n",
     "\n",
@@ -3043,19 +334,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "env: RESOUCE_SUFFIX=resource_suffix\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "resource_suffix=\"default\" # @param {type: \"string\"}\n",
     "\n",
@@ -3074,19 +357,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "env: VERTEX_SA_EMAIL=vertex-pipelines@dt-donatas-sandbox-dev.iam.gserviceaccount.com\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vertex_sa_email=f\"vertex-pipelines@{vertex_project_id}.iam.gserviceaccount.com\"\n",
     "\n",
@@ -3107,19 +382,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "env: VERTEX_PIPELINE_ROOT=gs://dt-donatas-sandbox-dev-pl-root\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vertex_pipeline_root=f\"gs://{vertex_project_id}-pl-root\"\n",
     "\n",
@@ -3138,19 +405,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "env: CONTAINER_IMAGE_REGISTRY=europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "container_image_registry=f\"{vertex_location}-docker.pkg.dev/{vertex_project_id}/vertex-images\"\n",
     "\n",
@@ -3190,27 +449,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {
     "id": "254614fa0c46",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Your browser has been opened to visit:\n",
-      "\n",
-      "    https://accounts.google.com/o/oauth2/auth?response_type=code&client_id=32555940559.apps.googleusercontent.com&redirect_uri=http%3A%2F%2Flocalhost%3A8085%2F&scope=openid+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fuserinfo.email+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fcloud-platform+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fappengine.admin+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fsqlservice.login+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fcompute+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Faccounts.reauth&state=k6jMTq96cILXIHTYaj26JHwqvHn6Ey&access_type=offline&code_challenge=whoq3ZN3MktqtUR1PwXG5jV0GljumM8qPT6GQpl-l5w&code_challenge_method=S256\n",
-      "\n",
-      "\n",
-      "You are now logged in as [donatas.mickevicius@datatonic.com].\n",
-      "Your current project is [dt-donatas-sandbox-dev].  You can change this setting by running:\n",
-      "  $ gcloud config set project PROJECT_ID\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# ! gcloud auth login"
    ]
@@ -3272,7 +516,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {
     "id": "MzGDU7TWdts_",
     "tags": []
@@ -3293,21 +537,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {
     "id": "NIq7R4HZCfIc",
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Creating gs://dt-donatas-sandbox-dev-tfstate/...\n",
-      "ServiceException: 409 A Cloud Storage bucket named 'dt-donatas-sandbox-dev-tfstate' already exists. Try another name. Bucket names must be globally unique across all Google Cloud projects, including those outside of your organization.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "! gsutil mb -l {vertex_location} -p {vertex_project_id} {tf_state_bucket_uri}"
    ]
@@ -3323,19 +558,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "dt-donatas-sandbox-dev\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "!echo ${VERTEX_PROJECT_ID}"
    ]
@@ -3422,20 +649,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "BigQuery error in mk operation: Dataset 'dt-donatas-sandbox-\n",
-      "dev:chicago_taxi_trips' already exists.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
    ]
@@ -3449,20 +667,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "BigQuery error in mk operation: Dataset 'dt-donatas-sandbox-dev:preprocessing'\n",
-      "already exists.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
    ]
@@ -3476,22 +685,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n",
-      "https://www.gstatic.com/bigquerydatatransfer/oauthz/auth?client_id=433065040935-uvs8ptbn0udhuartdhl4nn1l27t5v3qg.apps.googleusercontent.com&scope=https://www.googleapis.com/auth/bigquery&redirect_uri=urn:ietf:wg:oauth:2.0:oob&response_type=version_info\n",
-      "Please copy and paste the above URL into your web browser and follow the instructions to retrieve a version_info.\n",
-      "Enter your version_info here: ^C\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "! bq mk --transfer_config \\\n",
     "  --project_id=${VERTEX_PROJECT_ID} \\\n",
@@ -3522,66 +720,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "!echo $GOOGLE_APPLICATION_CREDENTIALS"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Your browser has been opened to visit:\n",
-      "\n",
-      "    https://accounts.google.com/o/oauth2/auth?response_type=code&client_id=764086051850-6qr4p6gpi6hn506pt8ejuq83di341hur.apps.googleusercontent.com&redirect_uri=http%3A%2F%2Flocalhost%3A8085%2F&scope=openid+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fuserinfo.email+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fcloud-platform+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fsqlservice.login+https%3A%2F%2Fwww.googleapis.com%2Fauth%2Faccounts.reauth&state=5HwStYisqE4FHgRbPiNDCIMrtmmJ4o&access_type=offline&code_challenge=4d8hOLhGRdD86uNzFAM_NpHkz6S70HIqB0E5XQhXpBs&code_challenge_method=S256\n",
-      "\n",
-      "\n",
-      "Credentials saved to file: [/Users/donatasmickevicius/.config/gcloud/application_default_credentials.json]\n",
-      "\n",
-      "These credentials will be used by any library that requests Application Default Credentials (ADC).\n",
-      "\n",
-      "Quota project \"dt-donatas-sandbox-dev\" was added to ADC which can be used by Google client libraries for billing and quota. Note that some services may still bill the project owning the resource.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "! gcloud auth application-default login "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Created transfer config: projects/529423390811/locations/europe-west2/transferConfigs/64ff46a0-0000-2d9c-b971-089e0820ebe0\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from google.cloud import bigquery_datatransfer\n",
     "\n",
@@ -3621,219 +786,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Building training image\n",
-      "Creating temporary tarball archive of 7 file(s) totalling 87.1 KiB before compression.\n",
-      "Uploading tarball of [.] to [gs://dt-donatas-sandbox-dev-staging/source/1694009873.552364-fb32142e7a9740909e0a330ba3cfe17c.tgz]\n",
-      "Created [https://cloudbuild.googleapis.com/v1/projects/dt-donatas-sandbox-dev/locations/europe-west2/builds/8186df5e-46d3-4ff7-909b-1d5fb539e3a1].\n",
-      "Logs are available at [ https://console.cloud.google.com/cloud-build/builds;region=europe-west2/8186df5e-46d3-4ff7-909b-1d5fb539e3a1?project=529423390811 ].\n",
-      "----------------------------- REMOTE BUILD OUTPUT ------------------------------\n",
-      "starting build \"8186df5e-46d3-4ff7-909b-1d5fb539e3a1\"\n",
-      "\n",
-      "FETCHSOURCE\n",
-      "Fetching storage object: gs://dt-donatas-sandbox-dev-staging/source/1694009873.552364-fb32142e7a9740909e0a330ba3cfe17c.tgz#1694009874031650\n",
-      "Copying gs://dt-donatas-sandbox-dev-staging/source/1694009873.552364-fb32142e7a9740909e0a330ba3cfe17c.tgz#1694009874031650...\n",
-      "/ [1 files][ 28.4 KiB/ 28.4 KiB]                                                \n",
-      "Operation completed over 1 objects/28.4 KiB.                                     \n",
-      "BUILD\n",
-      "Pulling image: gcr.io/kaniko-project/executor:latest\n",
-      "latest: Pulling from kaniko-project/executor\n",
-      "24b9c0f43324: Already exists\n",
-      "0d0cf3a75faa: Already exists\n",
-      "a13620305055: Already exists\n",
-      "3c02b8d0f8d0: Pulling fs layer\n",
-      "f2ed186425e5: Pulling fs layer\n",
-      "c113a25f71a0: Pulling fs layer\n",
-      "e600f5fdfda3: Pulling fs layer\n",
-      "41ac909a10bf: Pulling fs layer\n",
-      "3eb8d55ab910: Pulling fs layer\n",
-      "e600f5fdfda3: Waiting\n",
-      "41ac909a10bf: Waiting\n",
-      "3eb8d55ab910: Waiting\n",
-      "3c02b8d0f8d0: Verifying Checksum\n",
-      "3c02b8d0f8d0: Download complete\n",
-      "f2ed186425e5: Verifying Checksum\n",
-      "f2ed186425e5: Download complete\n",
-      "c113a25f71a0: Verifying Checksum\n",
-      "c113a25f71a0: Download complete\n",
-      "e600f5fdfda3: Download complete\n",
-      "41ac909a10bf: Verifying Checksum\n",
-      "41ac909a10bf: Download complete\n",
-      "3c02b8d0f8d0: Pull complete\n",
-      "f2ed186425e5: Pull complete\n",
-      "c113a25f71a0: Pull complete\n",
-      "e600f5fdfda3: Pull complete\n",
-      "41ac909a10bf: Pull complete\n",
-      "3eb8d55ab910: Verifying Checksum\n",
-      "3eb8d55ab910: Download complete\n",
-      "3eb8d55ab910: Pull complete\n",
-      "Digest: sha256:6aace7210ad8bf0da4b1aa707a1c0ea962d0e871bb1921504c1a5e690d5f6a2a\n",
-      "Status: Downloaded newer image for gcr.io/kaniko-project/executor:latest\n",
-      "gcr.io/kaniko-project/executor:latest\n",
-      "\u001b[36mINFO\u001b[0m[0000] Resolved base name python:3.9.16-slim to builder \n",
-      "\u001b[36mINFO\u001b[0m[0000] Resolved base name builder to training       \n",
-      "\u001b[36mINFO\u001b[0m[0000] Retrieving image manifest python:3.9.16-slim \n",
-      "\u001b[36mINFO\u001b[0m[0000] Retrieving image python:3.9.16-slim from registry index.docker.io\n",
-      "\u001b[36mINFO\u001b[0m[0000] Retrieving image manifest python:3.9.16-slim \n",
-      "\u001b[36mINFO\u001b[0m[0000] Returning cached image manifest              \n",
-      "\u001b[36mINFO\u001b[0m[0001] Built cross stage deps: map[]                \n",
-      "\u001b[36mINFO\u001b[0m[0001] Retrieving image manifest python:3.9.16-slim \n",
-      "\u001b[36mINFO\u001b[0m[0001] Returning cached image manifest              \n",
-      "\u001b[36mINFO\u001b[0m[0001] Retrieving image manifest python:3.9.16-slim \n",
-      "\u001b[36mINFO\u001b[0m[0001] Returning cached image manifest              \n",
-      "\u001b[36mINFO\u001b[0m[0001] Executing 0 build triggers                   \n",
-      "\u001b[36mINFO\u001b[0m[0001] Building stage 'python:3.9.16-slim' [idx: '0', base-idx: '-1'] \n",
-      "\u001b[36mINFO\u001b[0m[0001] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/training/cache:c11a5eafecf1c87b200f99fd974266d08cea862d33779292584b49d00403d0d0... \n",
-      "\u001b[36mINFO\u001b[0m[0001] Using caching version of cmd: RUN pip install poetry==${POETRY_VERSION} \n",
-      "\u001b[36mINFO\u001b[0m[0001] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/training/cache:3a4748cb15c98dbea0a12531d8158c54644335412df8f535d6bfb31666ad92e5... \n",
-      "\u001b[36mINFO\u001b[0m[0001] Using caching version of cmd: RUN poetry config virtualenvs.create false && poetry install \n",
-      "\u001b[36mINFO\u001b[0m[0001] Unpacking rootfs as cmd COPY pyproject.toml pyproject.toml requires it.\n",
-      "\u001b[36mINFO\u001b[0m[0004] ENV PIP_NO_CACHE_DIR=off     PIP_DISABLE_PIP_VERSION_CHECK=on     PIP_DEFAULT_TIMEOUT=100 \n",
-      "\u001b[36mINFO\u001b[0m[0004] No files changed in this command, skipping snapshotting. \n",
-      "\u001b[36mINFO\u001b[0m[0004] ARG POETRY_VERSION=1.5.1                     \n",
-      "\u001b[36mINFO\u001b[0m[0004] No files changed in this command, skipping snapshotting. \n",
-      "\u001b[36mINFO\u001b[0m[0004] COPY pyproject.toml pyproject.toml           \n",
-      "\u001b[36mINFO\u001b[0m[0004] Taking snapshot of files...                  \n",
-      "\u001b[36mINFO\u001b[0m[0004] COPY poetry.lock poetry.lock                 \n",
-      "\u001b[36mINFO\u001b[0m[0004] Taking snapshot of files...                  \n",
-      "\u001b[36mINFO\u001b[0m[0004] RUN pip install poetry==${POETRY_VERSION}    \n",
-      "\u001b[36mINFO\u001b[0m[0004] Found cached layer, extracting to filesystem\n",
-      "\u001b[36mINFO\u001b[0m[0006] RUN poetry config virtualenvs.create false && poetry install \n",
-      "\u001b[36mINFO\u001b[0m[0006] Found cached layer, extracting to filesystem\n",
-      "\u001b[36mINFO\u001b[0m[0026] Storing source image from stage 0 at path /kaniko/stages/0\n",
-      "\u001b[36mINFO\u001b[0m[0036] Deleting filesystem...\n",
-      "\u001b[36mINFO\u001b[0m[0036] Base image from previous stage 0 found, using saved tar at path /kaniko/stages/0 \n",
-      "\u001b[36mINFO\u001b[0m[0036] Executing 0 build triggers\n",
-      "\u001b[36mINFO\u001b[0m[0040] Building stage 'builder' [idx: '1', base-idx: '0'] \n",
-      "\u001b[36mINFO\u001b[0m[0040] Unpacking rootfs as cmd COPY training/train.py training/train.py requires it.\n",
-      "\u001b[36mINFO\u001b[0m[0052] COPY training/train.py training/train.py     \n",
-      "\u001b[36mINFO\u001b[0m[0052] Taking snapshot of files...                  \n",
-      "\u001b[36mINFO\u001b[0m[0052] Pushing image to europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/training: \n",
-      "\u001b[36mINFO\u001b[0m[0052] Pushed europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/training@sha256:a9635753244b1d46a825feff9270588dde7545418d044727524b129c378b4fba\n",
-      "PUSH\n",
-      "DONE\n",
-      "--------------------------------------------------------------------------------\n",
-      "ID                                    CREATE_TIME                DURATION  SOURCE                                                                                             IMAGES  STATUS\n",
-      "8186df5e-46d3-4ff7-909b-1d5fb539e3a1  2023-09-06T14:17:54+00:00  1M13S     gs://dt-donatas-sandbox-dev-staging/source/1694009873.552364-fb32142e7a9740909e0a330ba3cfe17c.tgz  -       SUCCESS\n",
-      "Building serving image\n",
-      "Creating temporary tarball archive of 7 file(s) totalling 87.1 KiB before compression.\n",
-      "Uploading tarball of [.] to [gs://dt-donatas-sandbox-dev-staging/source/1694009951.638785-186144ba8771421c998171d12fc788c2.tgz]\n",
-      "Created [https://cloudbuild.googleapis.com/v1/projects/dt-donatas-sandbox-dev/locations/europe-west2/builds/378f1da1-8eef-4cf6-85e6-27738a9bd038].\n",
-      "Logs are available at [ https://console.cloud.google.com/cloud-build/builds;region=europe-west2/378f1da1-8eef-4cf6-85e6-27738a9bd038?project=529423390811 ].\n",
-      "----------------------------- REMOTE BUILD OUTPUT ------------------------------\n",
-      "starting build \"378f1da1-8eef-4cf6-85e6-27738a9bd038\"\n",
-      "\n",
-      "FETCHSOURCE\n",
-      "Fetching storage object: gs://dt-donatas-sandbox-dev-staging/source/1694009951.638785-186144ba8771421c998171d12fc788c2.tgz#1694009952285513\n",
-      "Copying gs://dt-donatas-sandbox-dev-staging/source/1694009951.638785-186144ba8771421c998171d12fc788c2.tgz#1694009952285513...\n",
-      "/ [1 files][ 28.4 KiB/ 28.4 KiB]                                                \n",
-      "Operation completed over 1 objects/28.4 KiB.\n",
-      "BUILD\n",
-      "Pulling image: gcr.io/kaniko-project/executor:latest\n",
-      "latest: Pulling from kaniko-project/executor\n",
-      "24b9c0f43324: Already exists\n",
-      "0d0cf3a75faa: Already exists\n",
-      "a13620305055: Already exists\n",
-      "3c02b8d0f8d0: Pulling fs layer\n",
-      "f2ed186425e5: Pulling fs layer\n",
-      "c113a25f71a0: Pulling fs layer\n",
-      "e600f5fdfda3: Pulling fs layer\n",
-      "41ac909a10bf: Pulling fs layer\n",
-      "3eb8d55ab910: Pulling fs layer\n",
-      "e600f5fdfda3: Waiting\n",
-      "41ac909a10bf: Waiting\n",
-      "3eb8d55ab910: Waiting\n",
-      "3c02b8d0f8d0: Verifying Checksum\n",
-      "3c02b8d0f8d0: Download complete\n",
-      "f2ed186425e5: Verifying Checksum\n",
-      "f2ed186425e5: Download complete\n",
-      "c113a25f71a0: Verifying Checksum\n",
-      "c113a25f71a0: Download complete\n",
-      "e600f5fdfda3: Verifying Checksum\n",
-      "e600f5fdfda3: Download complete\n",
-      "41ac909a10bf: Verifying Checksum\n",
-      "41ac909a10bf: Download complete\n",
-      "3c02b8d0f8d0: Pull complete\n",
-      "f2ed186425e5: Pull complete\n",
-      "c113a25f71a0: Pull complete\n",
-      "e600f5fdfda3: Pull complete\n",
-      "41ac909a10bf: Pull complete\n",
-      "3eb8d55ab910: Verifying Checksum\n",
-      "3eb8d55ab910: Download complete\n",
-      "3eb8d55ab910: Pull complete\n",
-      "Digest: sha256:6aace7210ad8bf0da4b1aa707a1c0ea962d0e871bb1921504c1a5e690d5f6a2a\n",
-      "Status: Downloaded newer image for gcr.io/kaniko-project/executor:latest\n",
-      "gcr.io/kaniko-project/executor:latest\n",
-      "\u001b[36mINFO\u001b[0m[0000] Resolved base name python:3.9.16-slim to builder \n",
-      "\u001b[36mINFO\u001b[0m[0000] Resolved base name builder to training       \n",
-      "\u001b[36mINFO\u001b[0m[0000] Resolved base name builder to serving        \n",
-      "\u001b[36mINFO\u001b[0m[0000] Retrieving image manifest python:3.9.16-slim \n",
-      "\u001b[36mINFO\u001b[0m[0000] Retrieving image python:3.9.16-slim from registry index.docker.io\n",
-      "\u001b[36mINFO\u001b[0m[0000] Retrieving image manifest python:3.9.16-slim \n",
-      "\u001b[36mINFO\u001b[0m[0000] Returning cached image manifest              \n",
-      "\u001b[36mINFO\u001b[0m[0001] Built cross stage deps: map[]                \n",
-      "\u001b[36mINFO\u001b[0m[0001] Retrieving image manifest python:3.9.16-slim \n",
-      "\u001b[36mINFO\u001b[0m[0001] Returning cached image manifest              \n",
-      "\u001b[36mINFO\u001b[0m[0001] Retrieving image manifest python:3.9.16-slim \n",
-      "\u001b[36mINFO\u001b[0m[0001] Returning cached image manifest              \n",
-      "\u001b[36mINFO\u001b[0m[0001] Executing 0 build triggers                   \n",
-      "\u001b[36mINFO\u001b[0m[0001] Building stage 'python:3.9.16-slim' [idx: '0', base-idx: '-1'] \n",
-      "\u001b[36mINFO\u001b[0m[0001] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving/cache:c11a5eafecf1c87b200f99fd974266d08cea862d33779292584b49d00403d0d0...\n",
-      "\u001b[36mINFO\u001b[0m[0001] Using caching version of cmd: RUN pip install poetry==${POETRY_VERSION} \n",
-      "\u001b[36mINFO\u001b[0m[0001] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving/cache:3a4748cb15c98dbea0a12531d8158c54644335412df8f535d6bfb31666ad92e5... \n",
-      "\u001b[36mINFO\u001b[0m[0001] Using caching version of cmd: RUN poetry config virtualenvs.create false && poetry install \n",
-      "\u001b[36mINFO\u001b[0m[0001] Unpacking rootfs as cmd COPY pyproject.toml pyproject.toml requires it.\n",
-      "\u001b[36mINFO\u001b[0m[0005] ENV PIP_NO_CACHE_DIR=off     PIP_DISABLE_PIP_VERSION_CHECK=on     PIP_DEFAULT_TIMEOUT=100 \n",
-      "\u001b[36mINFO\u001b[0m[0005] No files changed in this command, skipping snapshotting. \n",
-      "\u001b[36mINFO\u001b[0m[0005] ARG POETRY_VERSION=1.5.1                     \n",
-      "\u001b[36mINFO\u001b[0m[0005] No files changed in this command, skipping snapshotting. \n",
-      "\u001b[36mINFO\u001b[0m[0005] COPY pyproject.toml pyproject.toml           \n",
-      "\u001b[36mINFO\u001b[0m[0005] Taking snapshot of files...                  \n",
-      "\u001b[36mINFO\u001b[0m[0005] COPY poetry.lock poetry.lock                 \n",
-      "\u001b[36mINFO\u001b[0m[0005] Taking snapshot of files...                  \n",
-      "\u001b[36mINFO\u001b[0m[0005] RUN pip install poetry==${POETRY_VERSION}    \n",
-      "\u001b[36mINFO\u001b[0m[0005] Found cached layer, extracting to filesystem\n",
-      "\u001b[36mINFO\u001b[0m[0006] RUN poetry config virtualenvs.create false && poetry install \n",
-      "\u001b[36mINFO\u001b[0m[0006] Found cached layer, extracting to filesystem\n",
-      "\u001b[36mINFO\u001b[0m[0026] Storing source image from stage 0 at path /kaniko/stages/0\n",
-      "\u001b[36mINFO\u001b[0m[0034] Deleting filesystem...\n",
-      "\u001b[36mINFO\u001b[0m[0035] Base image from previous stage 0 found, using saved tar at path /kaniko/stages/0 \n",
-      "\u001b[36mINFO\u001b[0m[0035] Executing 0 build triggers\n",
-      "\u001b[36mINFO\u001b[0m[0038] Building stage 'builder' [idx: '1', base-idx: '0'] \n",
-      "\u001b[36mINFO\u001b[0m[0038] Unpacking rootfs as cmd COPY training/train.py training/train.py requires it.\n",
-      "\u001b[36mINFO\u001b[0m[0050] COPY training/train.py training/train.py     \n",
-      "\u001b[36mINFO\u001b[0m[0050] Taking snapshot of files...                  \n",
-      "\u001b[36mINFO\u001b[0m[0050] Deleting filesystem...\n",
-      "\u001b[36mINFO\u001b[0m[0051] Base image from previous stage 0 found, using saved tar at path /kaniko/stages/0 \n",
-      "\u001b[36mINFO\u001b[0m[0051] Executing 0 build triggers\n",
-      "\u001b[36mINFO\u001b[0m[0054] Building stage 'builder' [idx: '2', base-idx: '0'] \n",
-      "\u001b[36mINFO\u001b[0m[0054] Checking for cached layer europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving/cache:440ff423928e582f8e1aebbb700d6abb6bd659cd07668be714ab9441e42cc2e3... \n",
-      "\u001b[36mINFO\u001b[0m[0054] Using caching version of cmd: RUN poetry install --with serving \n",
-      "\u001b[36mINFO\u001b[0m[0054] Unpacking rootfs as cmd COPY serving/main.py serving/main.py requires it.\n",
-      "\u001b[36mINFO\u001b[0m[0066] RUN poetry install --with serving            \n",
-      "\u001b[36mINFO\u001b[0m[0066] Found cached layer, extracting to filesystem \n",
-      "\u001b[36mINFO\u001b[0m[0067] COPY serving/main.py serving/main.py         \n",
-      "\u001b[36mINFO\u001b[0m[0067] Taking snapshot of files...                  \n",
-      "\u001b[36mINFO\u001b[0m[0067] CMD exec uvicorn serving.main:app --host \"0.0.0.0\" --port \"$AIP_HTTP_PORT\" \n",
-      "\u001b[36mINFO\u001b[0m[0067] No files changed in this command, skipping snapshotting. \n",
-      "\u001b[36mINFO\u001b[0m[0067] Pushing image to europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving:\n",
-      "\u001b[36mINFO\u001b[0m[0067] Pushed europe-west2-docker.pkg.dev/dt-donatas-sandbox-dev/vertex-images/serving@sha256:b85a7e4707a61ab47b92c87bdf6954bf402a7ef57a83481baf18948f8ca99ee3\n",
-      "PUSH\n",
-      "DONE\n",
-      "--------------------------------------------------------------------------------\n",
-      "ID                                    CREATE_TIME                DURATION  SOURCE                                                                                             IMAGES  STATUS\n",
-      "378f1da1-8eef-4cf6-85e6-27738a9bd038  2023-09-06T14:19:12+00:00  1M25S     gs://dt-donatas-sandbox-dev-staging/source/1694009951.638785-186144ba8771421c998171d12fc788c2.tgz  -       SUCCESS\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "! make build"
    ]
@@ -3863,25 +820,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "/Users/donatasmickevicius/code/vertex-pipelines-end-to-end-samples/vertex-pipelines-end-to-end-samples/pipelines/src/pipelines/training/pipeline.yaml\n",
-      "Creating PipelineJob\n",
-      "PipelineJob created. Resource name: projects/529423390811/locations/europe-west2/pipelineJobs/xgboost-train-pipeline-20230906152310\n",
-      "To use this PipelineJob in another session:\n",
-      "pipeline_job = aiplatform.PipelineJob.get('projects/529423390811/locations/europe-west2/pipelineJobs/xgboost-train-pipeline-20230906152310')\n",
-      "View Pipeline Job:\n",
-      "https://console.cloud.google.com/vertex-ai/locations/europe-west2/pipelines/runs/xgboost-train-pipeline-20230906152310?project=529423390811\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "! make run pipeline=training build=false"
    ]

From 181fd7895ed32196b5eb1bb7b05ecaa214797f80 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 6 Sep 2023 15:32:12 +0100
Subject: [PATCH 196/238] feat: Clean up

---
 examples/pipelines.ipynb | 59 ----------------------------------------
 1 file changed, 59 deletions(-)

diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index 5cd7c4f0..27afa9e1 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -556,17 +556,6 @@
     "### Deploy required infrastructure"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "!echo ${VERTEX_PROJECT_ID}"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -683,32 +672,6 @@
     "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq mk --transfer_config \\\n",
-    "  --project_id=${VERTEX_PROJECT_ID} \\\n",
-    "  --data_source=\"cross_region_copy\" \\\n",
-    "  --target_dataset=\"chicago_taxi_trips\" \\\n",
-    "  --display_name=\"Chicago taxi trip mirror\" \\\n",
-    "  --params='{\"source_dataset_id\":\"'\"chicago_taxi_trips\"'\",\"source_project_id\":\"'\"bigquery-public-data\"'\"}' \\\n",
-    "  --quiet=true"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\"source_project_id\":\"'\"bigquery-public-data\"'\""
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -718,28 +681,6 @@
     "! pip install google-cloud-bigquery-datatransfer"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "!echo $GOOGLE_APPLICATION_CREDENTIALS"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud auth application-default login "
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

From 0cfc402c650246e2918fd0a75b574b57e99a0519 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Fri, 8 Sep 2023 10:41:01 +0100
Subject: [PATCH 197/238] feat: Updates to notebook

---
 examples/pipelines.ipynb | 575 +++++++++++++++++++++++++++++++--------
 1 file changed, 454 insertions(+), 121 deletions(-)

diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index 27afa9e1..48929d96 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -29,10 +29,12 @@
     "id": "JAPoU8Sm5E6e"
    },
    "source": [
-    "# [TODO] Add your H1 title heading here\n",
+    "# Running Vertex Pipelines using End-to-end Samples repository.\n",
     "\n",
     "{TODO: Update the links below.} \n",
     "\n",
+    "{TODO: 🔴 Potentially remove colab and workbench as terraform installation could be difficult?}\n",
+    "\n",
     "<table align=\"left\">\n",
     "\n",
     "  <td>\n",
@@ -74,9 +76,9 @@
    "source": [
     "## Overview\n",
     "\n",
-    "{TODO: Include a paragraph or two explaining what this example demonstrates, who should be interested in it, and what you need to know before you get started.}\n",
+    "This notebook shows you how to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
     "\n",
-    "Learn more about [web-doc-title](linkback-to-webdoc-page). {TODO: if more than one primary feature, add tag/linkback for each one}"
+    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
    ]
   },
   {
@@ -89,14 +91,18 @@
     "\n",
     "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
     "\n",
-    "This tutorial uses the following Google Cloud ML services and resources:\n",
-    "\n",
-    "- *{TODO: Add high level bullets for the services/resources demonstrated; e.g., Vertex AI Training}*\n",
+    "This tutorial uses the following Google Cloud services and resources:\n",
     "\n",
+    "- *`Vertex Pipelines`*\n",
+    "- *`Google Cloud Storage`*\n",
+    "- *`Artifact Registry`*\n",
+    "- *`BigQuery`*\n",
+    "- *`Cloud Build`*\n",
     "\n",
     "The steps performed include:\n",
     "\n",
-    "- *{TODO: Add high level bullets for the steps of performed in the notebook}*"
+    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services.\n",
+    "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
    ]
   },
   {
@@ -107,9 +113,10 @@
    "source": [
     "### Dataset\n",
     "\n",
-    "{TODO: Include a paragraph with Dataset information and where to obtain it.} \n",
+    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
+    "\n",
     "\n",
-    "{TODO: Make sure the dataset is accessible to the public. **Googlers**: Add your dataset to the [public samples bucket](http://goto/cloudsamples#sample-storage-bucket) within gs://cloud-samples-data/vertex-ai, if it doesn't already exist there.}"
+    "This public dataset is hosted in Google BigQuery."
    ]
   },
   {
@@ -120,21 +127,21 @@
    "source": [
     "### Costs \n",
     "\n",
-    "{TODO: Update the list of billable products that your tutorial uses.}\n",
     "\n",
     "This tutorial uses billable components of Google Cloud:\n",
     "\n",
     "* Vertex AI\n",
-    "* {TODO: BigQuery}\n",
+    "* BigQuery\n",
     "* Cloud Storage\n",
+    "* Cloud Build\n",
+    "* Artifact Registry\n",
     "\n",
-    "{TODO: Include links to pricing documentation for each product you listed above.\n",
-    " NOTE: If you use BigQuery or Dataflow, you need to add this to the pricing.\n",
-    "}\n",
     "\n",
     "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
-    "{ TODO: [BigQuery pricing](https://cloud.google.com/bigquery/pricing), }\n",
-    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing), \n",
+    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
+    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
+    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
+    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
     "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
     "to generate a cost estimate based on your projected usage."
    ]
@@ -150,7 +157,8 @@
     "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
     "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
     "- Make\n",
-    "- [Poetry](https://python-poetry.org)"
+    "- [Poetry](https://python-poetry.org)\n",
+    "- [Terraform](https://www.terraform.io) (To install Terraform on your local machine we recommend using [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version.)"
    ]
   },
   {
@@ -191,11 +199,14 @@
     "id": "i7EUnXsZhAGF"
    },
    "source": [
-    "## Installation\n",
-    "\n",
-    "Install the following packages required to execute this notebook. \n",
-    "\n",
-    "{TODO: Suggest using the latest major GA version of each package; i.e., --upgrade}"
+    "## Installation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Install the packages required for executing this notebook."
    ]
   },
   {
@@ -214,10 +225,7 @@
     "! poetry config virtualenvs.prefer-active-python true\n",
     "\n",
     "#Install poetry dependencies for ML pipelines\n",
-    "! make install\n",
-    "\n",
-    "# Install pre-commit hooks\n",
-    "! cd pipelines && poetry run pre-commit install\n"
+    "! make install"
    ]
   },
   {
@@ -226,7 +234,7 @@
     "id": "58707a750154"
    },
    "source": [
-    "### Colab only: Uncomment the following cell to restart the kernel."
+    "### Colab only: Uncomment the following cell to restart the kernel. 🔴{TODO: Potentially remove colab as terraform installation could be difficult?}"
    ]
   },
   {
@@ -245,14 +253,21 @@
     "# app.kernel.do_shutdown(True)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Before You Begin"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
     "id": "BF1j6f9HApxa"
    },
    "source": [
-    "## 1. Setup\n",
-    "\n",
     "### Set up your Google Cloud project\n",
     "\n",
     "**The following steps are required, regardless of your notebook environment.**\n",
@@ -287,49 +302,58 @@
    },
    "outputs": [],
    "source": [
-    "vertex_project_id = \"[my-project-id]\"  # @param {type:\"string\"}\n",
-    "\n",
+    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
     "# Set the project id\n",
-    "! gcloud config set project {vertex_project_id}\n",
+    "! gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Authenticate your Google Cloud account {TODO: Potentially remove colab and workbench as terraform installation could be difficult?🔴🔴🔴}\n",
+    "\n",
     "\n",
-    "# Set the environment variable\n",
-    "%env VERTEX_PROJECT_ID = {vertex_project_id}"
+    "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "region"
+    "tags": []
    },
    "source": [
-    "#### Location\n",
-    "\n",
-    "You can also change the `VERTEX_LOCATION` variable used by Vertex AI. Learn more about [Vertex AI locations](https://cloud.google.com/vertex-ai/docs/general/locations)."
+    "**1. Vertex AI Workbench**\n",
+    "* Do nothing as you are already authenticated."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**2. Local JupyterLab instance, uncomment and run:**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "region",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "vertex_location = \"europe-west2\"  # @param {type: \"string\"}\n",
-    "\n",
-    "# Set the environment variable\n",
-    "%env VERTEX_LOCATION={vertex_location}"
+    "# ! gcloud auth login"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
-    "#### Resource Suffix\n",
-    "\n",
-    "Specify the `RESOURCE_SUFFIX` (e.g. `<your name>`) to facilitate running concurrent pipelines in the same Google Cloud project. \n",
-    "This is important to change if you are working in a team to avoid overwriting resources during development "
+    "**3. Colab, uncomment and run:**"
    ]
   },
   {
@@ -340,19 +364,31 @@
    },
    "outputs": [],
    "source": [
-    "resource_suffix=\"default\" # @param {type: \"string\"}\n",
-    "\n",
-    "# Set the environment variable\n",
-    "%env RESOUCE_SUFFIX=resource_suffix"
+    "# from google.colab import auth\n",
+    "# auth.authenticate_user()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "#### Vertex Pipelines Service Account\n",
-    "\n",
-    "We need to set the `VERTEX_SA_EMAIL` that is in the Google Cloud project so that this service account can run the pipelines for us."
+    "### Environment Setup {Work in progress}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to run make commands relevant environment variables need to be set. Please create `env.sh`, and update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "#### Using `os` library"
    ]
   },
   {
@@ -363,21 +399,41 @@
    },
    "outputs": [],
    "source": [
-    "vertex_sa_email=f\"vertex-pipelines@{vertex_project_id}.iam.gserviceaccount.com\"\n",
+    "import os\n",
     "\n",
-    "# Set the environment variable\n",
-    "%env VERTEX_SA_EMAIL={vertex_sa_email}"
+    "os.environ['VERTEX_PROJECT_ID'] = 'my-project-id'\n",
+    "os.environ['VERTEX_LOCATION'] = 'europe-west2'\n",
+    "\n",
+    "os.environ['VERTEX_CMEK_IDENTIFIER'] = ''  # optional\n",
+    "os.environ['VERTEX_NETWORK'] = ''  # optional\n",
+    "\n",
+    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project.\n",
+    "# Change if working in a team to avoid overwriting resources during development \n",
+    "os.environ['RESOURCE_SUFFIX'] = 'default'\n",
+    "\n",
+    "# Leave as-is\n",
+    "os.environ['VERTEX_SA_EMAIL'] = f'vertex-pipelines@{os.environ[\"VERTEX_PROJECT_ID\"]}.iam.gserviceaccount.com'\n",
+    "os.environ['VERTEX_PIPELINE_ROOT'] = f'gs://{os.environ[\"VERTEX_PROJECT_ID\"]}-pl-root'\n",
+    "os.environ['CONTAINER_IMAGE_REGISTRY'] = f'{os.environ[\"VERTEX_LOCATION\"]}-docker.pkg.dev/{os.environ[\"VERTEX_PROJECT_ID\"]}/vertex-images'"
    ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Using `os` library could suitable. See below:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
+   "outputs": [],
    "source": [
-    "#### Vertex Pipelines Root Bucket\n",
-    "\n",
-    "We need to set the `VERTEX_PIPELINE_ROOT` that is in the Google Cloud project which is used to stage pipeline artifacts."
+    "# 1. Env variables are available in shell commands.\n",
+    "!echo $VERTEX_PROJECT_ID"
    ]
   },
   {
@@ -388,19 +444,32 @@
    },
    "outputs": [],
    "source": [
-    "vertex_pipeline_root=f\"gs://{vertex_project_id}-pl-root\"\n",
-    "\n",
-    "# Set the environment variable\n",
-    "%env VERTEX_PIPELINE_ROOT={vertex_pipeline_root}"
+    "# 2. Env variables available for make commands.\n",
+    "# ! make install\n",
+    "! make compile pipeline=training"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# 3. Env variables can be used in cells using os library.\n",
+    "PROJECT_ID = os.environ[\"VERTEX_PROJECT_ID\"]\n",
+    "TF_BUCKET_URI = f\"{PROJECT_ID}-tfstate\"\n",
+    "print(TF_BUCKET_URI)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
-    "#### Container Image Registry\n",
-    "\n",
-    "We need to set the `CONTAINER_IMAGE_REGISTRY` that is container image repository for training/serving container images."
+    "#### Using dotenv library"
    ]
   },
   {
@@ -411,119 +480,268 @@
    },
    "outputs": [],
    "source": [
-    "container_image_registry=f\"{vertex_location}-docker.pkg.dev/{vertex_project_id}/vertex-images\"\n",
+    "%%writefile .env\n",
+    "\n",
+    "VERTEX_CMEK_IDENTIFIER= # optional\n",
+    "VERTEX_LOCATION=europe-west2\n",
+    "VERTEX_NETWORK= # optional\n",
+    "VERTEX_PROJECT_ID=my-project-id-dot\n",
     "\n",
-    "# Set the environment variable\n",
-    "%env CONTAINER_IMAGE_REGISTRY={container_image_registry}"
+    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
+    "RESOURCE_SUFFIX=default\n",
+    "\n",
+    "# Leave as-is\n",
+    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
+    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
+    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
-    "id": "sBCra4QMA2wR"
+    "tags": []
    },
+   "outputs": [],
    "source": [
-    "### Authenticate your Google Cloud account\n",
+    "from dotenv import load_dotenv\n",
     "\n",
-    "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
+    "load_dotenv()"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
-    "id": "74ccc9e52986"
+    "tags": []
    },
+   "outputs": [],
    "source": [
-    "**1. Vertex AI Workbench**\n",
-    "* Do nothing as you are already authenticated."
+    "# 1. Env variables are available in shell commands.\n",
+    "!echo $VERTEX_PROJECT_ID\n",
+    "!echo $CONTAINER_IMAGE_REGISTRY"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
-    "id": "de775a3773ba"
+    "tags": []
    },
+   "outputs": [],
    "source": [
-    "**2. Local JupyterLab instance, uncomment and run:**"
+    "# 2. Env variables available for make commands.\n",
+    "# ! make install\n",
+    "! make compile pipeline=training"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "254614fa0c46",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# ! gcloud auth login"
+    "# 3. Env variables can be used in cells using os library.\n",
+    "import os\n",
+    "PROJECT_ID = os.environ[\"VERTEX_PROJECT_ID\"]\n",
+    "TF_BUCKET_URI = f\"{PROJECT_ID}-tfstate\"\n",
+    "print(TF_BUCKET_URI)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "ef21552ccea8"
+    "tags": []
    },
    "source": [
-    "**3. Colab, uncomment and run:**"
+    "#### Writing `env.sh`\n",
+    "\n",
+    "This approach has some drawbacks ."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "603adbbf0532"
+    "tags": []
    },
    "outputs": [],
    "source": [
-    "# from google.colab import auth\n",
-    "# auth.authenticate_user()"
+    "%%writefile env.sh\n",
+    "\n",
+    "#!/bin/bash\n",
+    "export VERTEX_CMEK_IDENTIFIER= # optional\n",
+    "export VERTEX_LOCATION=europe-west2\n",
+    "export VERTEX_NETWORK= # optional\n",
+    "export VERTEX_PROJECT_ID=my-project-id-envsh\n",
+    "\n",
+    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
+    "export RESOURCE_SUFFIX=default\n",
+    "\n",
+    "# Leave as-is\n",
+    "export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
+    "export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
+    "export CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images"
    ]
   },
   {
    "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This approach has some issues (see below): 🔴🔴🔴 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
-    "id": "f6b2ccc891ed"
+    "tags": []
    },
+   "outputs": [],
    "source": [
-    "**4. Service account or other**\n",
-    "* See how to grant Cloud Storage permissions to your service account at https://cloud.google.com/storage/docs/gsutil/commands/iam#ch-examples."
+    "# 1. Env variables are not available in shell commands. 🔴"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
-    "id": "zgPO1eR3CYjk"
+    "tags": []
    },
+   "outputs": [],
    "source": [
-    "### Infrastructure deployment using terraform.\n",
-    "\n",
-    "Install Terraform on your local machine. We recommend using [`tfswitch`](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version for you (run `tfswitch` from the [`terraform/envs/dev`](terraform/envs/dev/) directory).\n",
-    "\n",
-    "Now you can deploy the infrastructure using Terraform:"
+    "%%bash\n",
+    "source env.sh"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! echo $VERTEX_PROJECT_ID"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "#### Create tfstate bucket\n",
-    "\n",
-    "Before provisioning our infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the state files for Terraform deployments.\n",
-    "\n",
-    "- *{Note to notebook author: For any user-provided strings that need to be unique (like bucket names or model ID's), append \"-unique\" to the end so proper testing can occur}*"
+    "# To use env variables in a command you need to add %%bash and source env.sh into the cell everytime.\n",
+    "# For example some of the steps in infrastructure deployment would look like:🔴"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "source env.sh\n",
+    "echo $VERTEX_PROJECT_ID"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "source env.sh\n",
+    "gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "source env.sh\n",
+    "terraform -chdir=terraform/envs/dev init -backend-config=\"bucket=${VERTEX_PROJECT_ID}-tfstate\" "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Make commands are working fine since it cointains:\n",
+    "# -include env.sh\n",
+    "# export"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make compile pipeline=training"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "MzGDU7TWdts_",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "tf_state_bucket_uri = f\"gs://{vertex_project_id}-tfstate\"  # @param {type:\"string\"}"
+    "# Env variables are not available for python scripts 🔴\n",
+    "import os\n",
+    "PROJECT_ID = os.environ[\"VERTEX_PROJECT_ID\"]\n",
+    "TF_BUCKET_URI = f\"{PROJECT_ID}-tfstate\"\n",
+    "print(TF_BUCKET_URI)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zgPO1eR3CYjk"
+   },
+   "source": [
+    "## Infrastructure deployment using terraform.\n",
+    "\n",
+    "Please check if you have terraform installed. If not we recommend using [`tfswitch`](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version for you."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Create tfstate bucket\n",
+    "\n",
+    "Before provisioning our infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the state files for Terraform deployments."
    ]
   },
   {
@@ -544,7 +762,7 @@
    },
    "outputs": [],
    "source": [
-    "! gsutil mb -l {vertex_location} -p {vertex_project_id} {tf_state_bucket_uri}"
+    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
    ]
   },
   {
@@ -590,14 +808,14 @@
    },
    "outputs": [],
    "source": [
-    "! terraform -chdir=terraform/envs/dev plan -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\""
+    "! terraform -chdir=terraform/envs/dev plan -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" # -lock=false"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**Terraform Apply** Please check tf plan output to see what infrastructure will be provisioned. If everything looks ok uncomment and run cell below."
+    "**Terraform Apply** Please check tf plan output to see what infrastructure will be provisioned. If everything looks fine uncomment and run cell below."
    ]
   },
   {
@@ -608,7 +826,18 @@
    },
    "outputs": [],
    "source": [
-    "# ! terraform -chdir=terraform/envs/dev apply -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" -auto-approve -lock=false"
+    "! terraform -chdir=terraform/envs/dev apply -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" -auto-approve # -lock=false"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# I've been getting state lock issues 🔴🔴🔴  -lock=false fixes it"
    ]
   },
   {
@@ -693,7 +922,7 @@
     "\n",
     "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
     "\n",
-    "destination_project_id = vertex_project_id\n",
+    "destination_project_id = os.environ[\"VERTEX_PROJECT_ID\"]\n",
     "destination_dataset_id = \"chicago_taxi_trips\"\n",
     "source_project_id = \"bigquery-public-data\"\n",
     "source_dataset_id = \"chicago_taxi_trips\"\n",
@@ -711,7 +940,8 @@
     "    parent=transfer_client.common_project_path(destination_project_id),\n",
     "    transfer_config=transfer_config,\n",
     ")\n",
-    "print(f\"Created transfer config: {transfer_config.name}\")"
+    "TRANSFER_CONFIG=transfer_config.name\n",
+    "print(f\"Created transfer config: {TRANSFER_CONFIG}\")"
    ]
   },
   {
@@ -744,9 +974,9 @@
    "source": [
     "### Running Pipelines\n",
     "\n",
-    "You can run the training pipeline (for example) with:\n",
+    "You can run the training pipeline (for example) by executing cell below.\n",
     "\n",
-    "This will execute the pipeline using the chosen template on Vertex AI, namely it will:\n",
+    "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
     "\n",
     "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
     "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
@@ -794,24 +1024,127 @@
     "id": "TpV-iwP9qw9c"
    },
    "source": [
-    "## 4. Cleaning up\n",
+    "## 3. Cleaning up\n",
     "\n",
     "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
     "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
     "\n",
-    "Otherwise, you can delete the individual resources you created in this tutorial:\n",
+    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Terraform Plan (destroy)**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "sx_vKniMq9ZX",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! terraform -chdir=terraform/envs/dev plan -destroy -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" # -lock=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Terraform Destroy**\n",
     "\n",
-    "{TODO: Include infrastructure cleanup}"
+    "🔴🔴🔴  Cant delete staging and root buckets because contains objects and `force_destroy` is not set to true in our terraform configurations"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "sx_vKniMq9ZX"
+    "tags": []
    },
    "outputs": [],
-   "source": []
+   "source": [
+    "# ! terraform -chdir=terraform/envs/dev destroy -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" -auto-approve # -lock=false  "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "1. Delete data transfer config."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import google.api_core.exceptions\n",
+    "from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "transfer_config_name = TRANSFER_CONFIG\n",
+    "try:\n",
+    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
+    "except google.api_core.exceptions.NotFound:\n",
+    "    print(\"Transfer config not found.\")\n",
+    "else:\n",
+    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "2. Delete BigQuery dataset for the Chicago Taxi data:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "3. Delete BigQuery dataset for data processing during the pipelines:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
+   ]
   }
  ],
  "metadata": {

From c4799f304cf3da2dc9b5bc617644343e34409a01 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Fri, 8 Sep 2023 10:44:11 +0100
Subject: [PATCH 198/238] feat: Typos

---
 examples/pipelines.ipynb | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index 48929d96..ea9e9289 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -33,7 +33,7 @@
     "\n",
     "{TODO: Update the links below.} \n",
     "\n",
-    "{TODO: 🔴 Potentially remove colab and workbench as terraform installation could be difficult?}\n",
+    "{TODO: 🔴🔴🔴 Potentially remove colab and workbench as terraform installation could be difficult?}\n",
     "\n",
     "<table align=\"left\">\n",
     "\n",
@@ -234,7 +234,7 @@
     "id": "58707a750154"
    },
    "source": [
-    "### Colab only: Uncomment the following cell to restart the kernel. 🔴{TODO: Potentially remove colab as terraform installation could be difficult?}"
+    "### Colab only: Uncomment the following cell to restart the kernel. 🔴🔴🔴{TODO: Potentially remove colab as terraform installation could be difficult?}"
    ]
   },
   {
@@ -379,7 +379,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In order to run make commands relevant environment variables need to be set. Please create `env.sh`, and update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)."
+    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)."
    ]
   },
   {
@@ -837,7 +837,7 @@
    },
    "outputs": [],
    "source": [
-    "# I've been getting state lock issues 🔴🔴🔴  -lock=false fixes it"
+    "# I've been getting state lock issues 🔴  -lock=false fixes it"
    ]
   },
   {

From 450a6e05a9d7e524c667f994549e0a9be0576e91 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Mon, 18 Sep 2023 11:45:48 +0100
Subject: [PATCH 199/238] feat: Notebook update, makefile update

---
 Makefile                 |  15 +-
 examples/pipelines.ipynb | 530 +++++++++++++-----------------------
 tutorial.ipynb           | 571 ---------------------------------------
 3 files changed, 198 insertions(+), 918 deletions(-)
 delete mode 100644 tutorial.ipynb

diff --git a/Makefile b/Makefile
index 064500e0..0abfcde0 100644
--- a/Makefile
+++ b/Makefile
@@ -24,15 +24,22 @@ pre-commit: ## Runs the pre-commit checks over entire repo
 	poetry run pre-commit run --all-files
 
 env ?= dev
+AUTO_APPROVE_FLAG :=
 deploy: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
-	@ cd terraform/envs/$(env) && \
+	@if [ "$(auto-approve)" = "true" ]; then \
+		AUTO_APPROVE_FLAG="-auto-approve"; \
+	fi; \
+	cd terraform/envs/$(env) && \
 	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
-	terraform apply -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
+	terraform apply -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}' $$AUTO_APPROVE_FLAG
 
 undeploy: ## DESTROY the Terraform infrastructure in your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
-	@ cd terraform/envs/$(env) && \
+	@if [ "$(auto-approve)" = "true" ]; then \
+		AUTO_APPROVE_FLAG="-auto-approve"; \
+	fi; \
+	cd terraform/envs/$(env) && \
 	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
-	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}'
+	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}' $$AUTO_APPROVE_FLAG
 
 install: ## Set up local environment for Python development on pipelines
 	@cd pipelines && \
diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index ea9e9289..6d5a2785 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -33,8 +33,6 @@
     "\n",
     "{TODO: Update the links below.} \n",
     "\n",
-    "{TODO: 🔴🔴🔴 Potentially remove colab and workbench as terraform installation could be difficult?}\n",
-    "\n",
     "<table align=\"left\">\n",
     "\n",
     "  <td>\n",
@@ -231,26 +229,28 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "58707a750154"
+    "tags": []
    },
    "source": [
-    "### Colab only: Uncomment the following cell to restart the kernel. 🔴🔴🔴{TODO: Potentially remove colab as terraform installation could be difficult?}"
+    "### Terraform"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Check if terrafororm is installed."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "f200f10a1da3",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# Automatically restart kernel after installs so that your environment can access the new packages\n",
-    "# import IPython\n",
-    "\n",
-    "# app = IPython.Application.instance()\n",
-    "# app.kernel.do_shutdown(True)"
+    "! terraform --version"
    ]
   },
   {
@@ -259,62 +259,34 @@
     "tags": []
    },
    "source": [
-    "## Before You Begin"
+    "**If you do not have terraform installed please follow the instructions below.** Depending on your Jupyter environment, you may have to follow different installation methods."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "BF1j6f9HApxa"
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-    "\n",
-    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
+    "tags": []
    },
    "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+    "**1. Vertex AI Workbench**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "oM1iC_MfAts1",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
+    "# "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Authenticate your Google Cloud account {TODO: Potentially remove colab and workbench as terraform installation could be difficult?🔴🔴🔴}\n",
-    "\n",
-    "\n",
-    "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
+    "**2. Local JupyterLab instance**"
    ]
   },
   {
@@ -323,8 +295,7 @@
     "tags": []
    },
    "source": [
-    "**1. Vertex AI Workbench**\n",
-    "* Do nothing as you are already authenticated."
+    "Please follow installation instructions: https://developer.hashicorp.com/terraform/tutorials/aws-get-started/install-cli"
    ]
   },
   {
@@ -333,53 +304,45 @@
     "tags": []
    },
    "source": [
-    "**2. Local JupyterLab instance, uncomment and run:**"
+    "**3. Colab, uncomment and run:**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# ! gcloud auth login"
+    "# %%bash\n",
+    "# curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
+    "# unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
+    "# mv terraform /usr/local/bin > /dev/null\n",
+    "# terraform -version"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "tags": []
+    "id": "58707a750154"
    },
    "source": [
-    "**3. Colab, uncomment and run:**"
+    "### Colab only: Uncomment the following cell to restart the kernel."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "id": "f200f10a1da3",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# from google.colab import auth\n",
-    "# auth.authenticate_user()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Environment Setup {Work in progress}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)."
+    "# Automatically restart kernel after installs so that your environment can access the new packages\n",
+    "# import IPython\n",
+    "\n",
+    "# app = IPython.Application.instance()\n",
+    "# app.kernel.do_shutdown(True)"
    ]
   },
   {
@@ -388,123 +351,81 @@
     "tags": []
    },
    "source": [
-    "#### Using `os` library"
+    "## Before You Begin"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {
-    "tags": []
+    "id": "BF1j6f9HApxa"
    },
-   "outputs": [],
    "source": [
-    "import os\n",
+    "### Set up your Google Cloud project\n",
     "\n",
-    "os.environ['VERTEX_PROJECT_ID'] = 'my-project-id'\n",
-    "os.environ['VERTEX_LOCATION'] = 'europe-west2'\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
     "\n",
-    "os.environ['VERTEX_CMEK_IDENTIFIER'] = ''  # optional\n",
-    "os.environ['VERTEX_NETWORK'] = ''  # optional\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
     "\n",
-    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project.\n",
-    "# Change if working in a team to avoid overwriting resources during development \n",
-    "os.environ['RESOURCE_SUFFIX'] = 'default'\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
     "\n",
-    "# Leave as-is\n",
-    "os.environ['VERTEX_SA_EMAIL'] = f'vertex-pipelines@{os.environ[\"VERTEX_PROJECT_ID\"]}.iam.gserviceaccount.com'\n",
-    "os.environ['VERTEX_PIPELINE_ROOT'] = f'gs://{os.environ[\"VERTEX_PROJECT_ID\"]}-pl-root'\n",
-    "os.environ['CONTAINER_IMAGE_REGISTRY'] = f'{os.environ[\"VERTEX_LOCATION\"]}-docker.pkg.dev/{os.environ[\"VERTEX_PROJECT_ID\"]}/vertex-images'"
+    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Using `os` library could suitable. See below:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# 1. Env variables are available in shell commands.\n",
-    "!echo $VERTEX_PROJECT_ID"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
    "metadata": {
-    "tags": []
+    "id": "WReHDGG5g0XY"
    },
-   "outputs": [],
    "source": [
-    "# 2. Env variables available for make commands.\n",
-    "# ! make install\n",
-    "! make compile pipeline=training"
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "id": "oM1iC_MfAts1",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# 3. Env variables can be used in cells using os library.\n",
-    "PROJECT_ID = os.environ[\"VERTEX_PROJECT_ID\"]\n",
-    "TF_BUCKET_URI = f\"{PROJECT_ID}-tfstate\"\n",
-    "print(TF_BUCKET_URI)"
+    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
+    "# Set the project id\n",
+    "! gcloud config set project {PROJECT_ID}"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "source": [
-    "#### Using dotenv library"
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "\n",
+    "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
    "source": [
-    "%%writefile .env\n",
-    "\n",
-    "VERTEX_CMEK_IDENTIFIER= # optional\n",
-    "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_NETWORK= # optional\n",
-    "VERTEX_PROJECT_ID=my-project-id-dot\n",
-    "\n",
-    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
-    "RESOURCE_SUFFIX=default\n",
-    "\n",
-    "# Leave as-is\n",
-    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
-    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
-    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images"
+    "**1. Vertex AI Workbench**\n",
+    "* Do nothing as you are already authenticated."
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
    "source": [
-    "! pip install python-dotenv"
+    "**2. Local JupyterLab instance, uncomment and run:**"
    ]
   },
   {
@@ -515,22 +436,16 @@
    },
    "outputs": [],
    "source": [
-    "from dotenv import load_dotenv\n",
-    "\n",
-    "load_dotenv()"
+    " # ! gcloud auth login"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
    "source": [
-    "# 1. Env variables are available in shell commands.\n",
-    "!echo $VERTEX_PROJECT_ID\n",
-    "!echo $CONTAINER_IMAGE_REGISTRY"
+    "**3. Colab, uncomment and run:**"
    ]
   },
   {
@@ -541,35 +456,22 @@
    },
    "outputs": [],
    "source": [
-    "# 2. Env variables available for make commands.\n",
-    "# ! make install\n",
-    "! make compile pipeline=training"
+    "# from google.colab import auth\n",
+    "# auth.authenticate_user()"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
-    "# 3. Env variables can be used in cells using os library.\n",
-    "import os\n",
-    "PROJECT_ID = os.environ[\"VERTEX_PROJECT_ID\"]\n",
-    "TF_BUCKET_URI = f\"{PROJECT_ID}-tfstate\"\n",
-    "print(TF_BUCKET_URI)"
+    "### Environment Setup"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "source": [
-    "#### Writing `env.sh`\n",
-    "\n",
-    "This approach has some drawbacks ."
+    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)."
    ]
   },
   {
@@ -580,51 +482,20 @@
    },
    "outputs": [],
    "source": [
-    "%%writefile env.sh\n",
+    "%%writefile .env\n",
     "\n",
-    "#!/bin/bash\n",
-    "export VERTEX_CMEK_IDENTIFIER= # optional\n",
-    "export VERTEX_LOCATION=europe-west2\n",
-    "export VERTEX_NETWORK= # optional\n",
-    "export VERTEX_PROJECT_ID=my-project-id-envsh\n",
+    "VERTEX_CMEK_IDENTIFIER= # optional\n",
+    "VERTEX_LOCATION=europe-west2\n",
+    "VERTEX_NETWORK= # optional\n",
+    "VERTEX_PROJECT_ID=my-project-id\n",
     "\n",
     "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
-    "export RESOURCE_SUFFIX=default\n",
+    "RESOURCE_SUFFIX=default\n",
     "\n",
     "# Leave as-is\n",
-    "export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
-    "export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
-    "export CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This approach has some issues (see below): 🔴🔴🔴 "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# 1. Env variables are not available in shell commands. 🔴"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "source env.sh"
+    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
+    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
+    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images"
    ]
   },
   {
@@ -635,17 +506,7 @@
    },
    "outputs": [],
    "source": [
-    "! echo $VERTEX_PROJECT_ID"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# To use env variables in a command you need to add %%bash and source env.sh into the cell everytime.\n",
-    "# For example some of the steps in infrastructure deployment would look like:🔴"
+    "! pip install python-dotenv"
    ]
   },
   {
@@ -656,57 +517,25 @@
    },
    "outputs": [],
    "source": [
-    "%%bash\n",
-    "source env.sh\n",
-    "echo $VERTEX_PROJECT_ID"
+    "from dotenv import load_dotenv\n",
+    "\n",
+    "load_dotenv()"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {
-    "tags": []
+    "id": "zgPO1eR3CYjk"
    },
-   "outputs": [],
    "source": [
-    "%%bash\n",
-    "source env.sh\n",
-    "gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
+    "## Infrastructure deployment using terraform.\n"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "source env.sh\n",
-    "terraform -chdir=terraform/envs/dev init -backend-config=\"bucket=${VERTEX_PROJECT_ID}-tfstate\" "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Make commands are working fine since it cointains:\n",
-    "# -include env.sh\n",
-    "# export"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
    "source": [
-    "! make compile pipeline=training"
+    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
    ]
   },
   {
@@ -717,22 +546,8 @@
    },
    "outputs": [],
    "source": [
-    "# Env variables are not available for python scripts 🔴\n",
-    "import os\n",
-    "PROJECT_ID = os.environ[\"VERTEX_PROJECT_ID\"]\n",
-    "TF_BUCKET_URI = f\"{PROJECT_ID}-tfstate\"\n",
-    "print(TF_BUCKET_URI)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "zgPO1eR3CYjk"
-   },
-   "source": [
-    "## Infrastructure deployment using terraform.\n",
-    "\n",
-    "Please check if you have terraform installed. If not we recommend using [`tfswitch`](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version for you."
+    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
+    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
    ]
   },
   {
@@ -741,7 +556,7 @@
    "source": [
     "#### Create tfstate bucket\n",
     "\n",
-    "Before provisioning our infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the state files for Terraform deployments."
+    "Before provisioning our infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
    ]
   },
   {
@@ -776,86 +591,76 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Initialize Backend**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [],
-   "source": [
-    "! terraform -chdir=terraform/envs/dev init -backend-config=\"bucket=${VERTEX_PROJECT_ID}-tfstate\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
    "source": [
-    "**Terraform Plan**"
+    "Deploy command will:\n",
+    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
+    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "PyQmSRbKA8r-",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "! terraform -chdir=terraform/envs/dev plan -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" # -lock=false"
+    "! make deploy auto-approve=true"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**Terraform Apply** Please check tf plan output to see what infrastructure will be provisioned. If everything looks fine uncomment and run cell below."
+    "## 2. Example ML Pipelines"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
    "source": [
-    "! terraform -chdir=terraform/envs/dev apply -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" -auto-approve # -lock=false"
+    "To automate, monitor, and govern your ML workflows, you can use [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops). Vertex AI is a powerful platform offered by Google Cloud that empowers organizations to streamline and enhance their Machine Learning (ML) workflows through automation, monitoring, and governance.\n",
+    "\n",
+    "- **Automation**: Vertex AI offers a suite of tools and services designed to automate various aspects of ML development and deployment. This includes automating data preprocessing, model training, hyperparameter tuning, and model deployment. Automation not only saves time but also reduces the potential for human error, making your ML workflows more efficient and reliable.\n",
+    "\n",
+    "- **Monitoring**: Effective monitoring is crucial for maintaining the performance and reliability of ML models in production. Vertex AI provides monitoring capabilities that allow you to track model performance, detect drift in data distributions, and set up alerts for anomalies. This proactive monitoring ensures that your models continue to deliver accurate results as data and business conditions change over time.\n",
+    "\n",
+    "- **Governance**: Managing ML models and data in a secure and compliant manner is essential for businesses, especially those in regulated industries. Vertex AI helps you implement governance policies to control access to data, monitor model usage, and enforce compliance with data privacy regulations. This ensures that your ML operations are in line with legal and ethical standards.\n",
+    "\n",
+    "- **Scalability**: Vertex AI is built on Google Cloud's infrastructure, which means it offers unparalleled scalability. Whether you're dealing with small-scale experiments or large-scale production deployments, Vertex AI can scale to meet your needs, ensuring that your ML workflows can handle increased workloads without performance bottlenecks.\n",
+    "\n",
+    "- **Collaboration**: Collaboration is essential in ML development, and Vertex AI provides features that facilitate collaboration among data scientists, machine learning engineers, and other stakeholders. You can share notebooks, collaborate on model development, and maintain version control of your ML assets.\n",
+    "\n",
+    "- **Model Serving**: Vertex AI makes it easy to deploy ML models as APIs for real-time inference or batch processing. This enables you to integrate your ML models into applications, websites, or other services with ease.\n",
+    "\n",
+    "- **Cost Management**: Cost control is a crucial aspect of any ML project. Vertex AI offers cost management tools and insights to help you optimize your ML workflows and keep your expenses in check.\n",
+    "\n",
+    "By utilizing Vertex AI, you can take advantage of Google Cloud's cutting-edge technology and expertise in machine learning to accelerate your MLOps journey. The platform offers a comprehensive set of tools and services that cover the entire ML lifecycle, from data preparation to model deployment and beyond, making it a valuable resource for organizations looking to harness the power of ML in a scalable, efficient, and secure manner.\n",
+    "\n",
+    "To learn more about MLOps on Vertex AI and how it can transform your ML workflows, you can visit the [official documentation](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops).\n"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {
     "tags": []
    },
-   "outputs": [],
    "source": [
-    "# I've been getting state lock issues 🔴  -lock=false fixes it"
+    "**This repository provides an example ML training and prediction pipelines for XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips).**\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## 2. Example ML Pipelines"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This repository contains example ML training and prediction pipelines for two popular frameworks (XGBoost/sklearn and Tensorflow) using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips). The details of these can be found in the [separate README](pipelines/README.md).\n",
-    "\n",
     "#### Pre-requisites\n",
     "\n",
-    "Before you can run these example pipelines successfully there are a few additional things you will need to deploy (they have not been included in the Terraform code as they are specific to these pipelines)"
+    "Before you can successfully execute the example pipelines, there are a few additional components you need to deploy. These components have not been included in the Terraform code as they are specific to these pipelines."
    ]
   },
   {
@@ -950,9 +755,16 @@
    "source": [
     "### Building the container images\n",
     "\n",
-    "The [model/](/model/) directory contains the code for custom training and serving container images [model/training/train.py](model/training/train.py).\n",
+    "The `model` directory contains the code for custom training and serving container images `model/training/train.py`.\n",
     "\n",
-    "Build the training and serving container images and push them to Artifact Registry."
+    "A custom container is a Docker image that you create to run your training application. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Vertex AI. To learn more you can check out [official documentation](https://cloud.google.com/vertex-ai/docs/training/containers-overview)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To build the training and serving container images and push them to Artifact Registry run the next cell."
    ]
   },
   {
@@ -974,7 +786,7 @@
    "source": [
     "### Running Pipelines\n",
     "\n",
-    "You can run the training pipeline (for example) by executing cell below.\n",
+    "You can run the training pipeline by executing cell below.\n",
     "\n",
     "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
     "\n",
@@ -1000,13 +812,32 @@
     "! make run pipeline=training build=false"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it through the Google Cloud Console UI under Vertex AI/Pipelines."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Training Pipeline**\n",
+    "![Training Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/training_pipeline.png?raw=true)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "**Run Prediction Pipeline** \n",
     "\n",
-    "After successful training run you can try prediction pipeline."
+    "After successful training job, you can try prediction pipeline."
    ]
   },
   {
@@ -1021,24 +852,26 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "TpV-iwP9qw9c"
+    "tags": []
    },
    "source": [
-    "## 3. Cleaning up\n",
-    "\n",
-    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
-    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+    "**Prediction Pipeline**\n",
     "\n",
-    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
+    "![Predictions Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/prediction_pipeline.png?raw=true)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "tags": []
+    "id": "TpV-iwP9qw9c"
    },
    "source": [
-    "**Terraform Plan (destroy)**"
+    "## 3. Cleaning up\n",
+    "\n",
+    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
+    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+    "\n",
+    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
    ]
   },
   {
@@ -1050,7 +883,7 @@
    },
    "outputs": [],
    "source": [
-    "! terraform -chdir=terraform/envs/dev plan -destroy -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" # -lock=false"
+    "! make undeploy auto-approve=true"
    ]
   },
   {
@@ -1059,20 +892,7 @@
     "tags": []
    },
    "source": [
-    "**Terraform Destroy**\n",
-    "\n",
-    "🔴🔴🔴  Cant delete staging and root buckets because contains objects and `force_destroy` is not set to true in our terraform configurations"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# ! terraform -chdir=terraform/envs/dev destroy -var \"project_id=${VERTEX_PROJECT_ID}\" -var \"region=${VERTEX_LOCATION}\" -auto-approve # -lock=false  "
+    "{TODO}🔴🔴🔴  Cant delete staging and root buckets because contains objects and `force_destroy` is not set to true in our terraform configurations"
    ]
   },
   {
@@ -1081,7 +901,9 @@
     "tags": []
    },
    "source": [
-    "1. Delete data transfer config."
+    "1. Delete data transfer config. \n",
+    "\n",
+    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
    ]
   },
   {
@@ -1097,7 +919,7 @@
     "\n",
     "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
     "\n",
-    "transfer_config_name = TRANSFER_CONFIG\n",
+    "transfer_config_name = TRANSFER_CONFIG # Transfer Config Name\n",
     "try:\n",
     "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
     "except google.api_core.exceptions.NotFound:\n",
@@ -1145,6 +967,28 @@
    "source": [
     "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Delete local files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "cd ..\n",
+    "rm -r vertex-pipelines-end-to-end-samples"
+   ]
   }
  ],
  "metadata": {
diff --git a/tutorial.ipynb b/tutorial.ipynb
deleted file mode 100644
index 0b7ba689..00000000
--- a/tutorial.ipynb
+++ /dev/null
@@ -1,571 +0,0 @@
-{
-  "cells": [
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "ur8xi4C7S06n"
-      },
-      "outputs": [],
-      "source": [
-        "# Copyright 2023 Google LLC\n",
-        "#\n",
-        "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-        "# you may not use this file except in compliance with the License.\n",
-        "# You may obtain a copy of the License at\n",
-        "#\n",
-        "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-        "#\n",
-        "# Unless required by applicable law or agreed to in writing, software\n",
-        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-        "# See the License for the specific language governing permissions and\n",
-        "# limitations under the License."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "JAPoU8Sm5E6e"
-      },
-      "source": [
-        "# [TODO] Add your H1 title heading here\n",
-        "\n",
-        "{TODO: Update the links below.} \n",
-        "\n",
-        "<table align=\"left\">\n",
-        "\n",
-        "  <td>\n",
-        "    <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb\">\n",
-        "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
-        "    </a>\n",
-        "  </td>\n",
-        "  <td>\n",
-        "    <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb\">\n",
-        "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
-        "      View on GitHub\n",
-        "    </a>\n",
-        "  </td>\n",
-        "  <td>\n",
-        "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/notebook_template.ipynb\">\n",
-        "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
-        "      Open in Vertex AI Workbench\n",
-        "    </a>\n",
-        "  </td>                                                                                               \n",
-        "</table>"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "24743cf4a1e1"
-      },
-      "source": [
-        "**_NOTE_**: This notebook has been tested in the following environment:\n",
-        "\n",
-        "* Python version = 3.9"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "tvgnzT1CKxrO"
-      },
-      "source": [
-        "## Overview\n",
-        "\n",
-        "{TODO: Include a paragraph or two explaining what this example demonstrates, who should be interested in it, and what you need to know before you get started.}\n",
-        "\n",
-        "Learn more about [web-doc-title](linkback-to-webdoc-page). {TODO: if more than one primary feature, add tag/linkback for each one}"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "d975e698c9a4"
-      },
-      "source": [
-        "### Objective\n",
-        "\n",
-        "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
-        "\n",
-        "This tutorial uses the following Google Cloud ML services and resources:\n",
-        "\n",
-        "- *{TODO: Add high level bullets for the services/resources demonstrated; e.g., Vertex AI Training}*\n",
-        "\n",
-        "\n",
-        "The steps performed include:\n",
-        "\n",
-        "- *{TODO: Add high level bullets for the steps of performed in the notebook}*"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "08d289fa873f"
-      },
-      "source": [
-        "### Dataset\n",
-        "\n",
-        "{TODO: Include a paragraph with Dataset information and where to obtain it.} \n",
-        "\n",
-        "{TODO: Make sure the dataset is accessible to the public. **Googlers**: Add your dataset to the [public samples bucket](http://goto/cloudsamples#sample-storage-bucket) within gs://cloud-samples-data/vertex-ai, if it doesn't already exist there.}"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "aed92deeb4a0"
-      },
-      "source": [
-        "### Costs \n",
-        "\n",
-        "{TODO: Update the list of billable products that your tutorial uses.}\n",
-        "\n",
-        "This tutorial uses billable components of Google Cloud:\n",
-        "\n",
-        "* Vertex AI\n",
-        "* {TODO: BigQuery}\n",
-        "* Cloud Storage\n",
-        "\n",
-        "{TODO: Include links to pricing documentation for each product you listed above.\n",
-        " NOTE: If you use BigQuery or Dataflow, you need to add this to the pricing.\n",
-        "}\n",
-        "\n",
-        "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
-        "{ TODO: [BigQuery pricing](https://cloud.google.com/bigquery/pricing), }\n",
-        "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing), \n",
-        "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
-        "to generate a cost estimate based on your projected usage."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "i7EUnXsZhAGF"
-      },
-      "source": [
-        "## Installation\n",
-        "\n",
-        "Install the following packages required to execute this notebook. \n",
-        "\n",
-        "{TODO: Suggest using the latest major GA version of each package; i.e., --upgrade}"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "2b4ef9b72d43"
-      },
-      "outputs": [],
-      "source": [
-        "# Install the correct Python version\n",
-        "! pyenv install \n",
-        "\n",
-        "# Install poetry #TODO: Fill this section!!\n",
-        "\n",
-        "# configure poetry \n",
-        "! poetry config virtualenvs.prefer-active-python true\n",
-        "\n",
-        "#Install poetry dependencies for ML pipelines\n",
-        "! make install\n",
-        "\n",
-        "# Install pre-commit hooks\n",
-        "! cd pipelines && poetry run pre-commit install\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "58707a750154"
-      },
-      "source": [
-        "### Colab only: Uncomment the following cell to restart the kernel."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "f200f10a1da3"
-      },
-      "outputs": [],
-      "source": [
-        "# # Automatically restart kernel after installs so that your environment can access the new packages\n",
-        "# import IPython\n",
-        "\n",
-        "# app = IPython.Application.instance()\n",
-        "# app.kernel.do_shutdown(True)"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "BF1j6f9HApxa"
-      },
-      "source": [
-        "## 1. Setup\n",
-        "\n",
-        "### Set up your Google Cloud project\n",
-        "\n",
-        "**The following steps are required, regardless of your notebook environment.**\n",
-        "\n",
-        "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-        "\n",
-        "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-        "\n",
-        "3. [Enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com). {TODO: Update the APIs needed for your tutorial. Edit the API names, and update the link to append the API IDs, separating each one with a comma. For example, container.googleapis.com,cloudbuild.googleapis.com}\n",
-        "\n",
-        "4. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "WReHDGG5g0XY"
-      },
-      "source": [
-        "#### Set your project ID\n",
-        "\n",
-        "**If you don't know your project ID**, try the following:\n",
-        "* Run `gcloud config list`.\n",
-        "* Run `gcloud projects list`.\n",
-        "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "oM1iC_MfAts1"
-      },
-      "outputs": [],
-      "source": [
-        "vertex_project_id = \"[your-project-id]\"  # @param {type:\"string\"}\n",
-        "\n",
-        "# Set the project id\n",
-        "! gcloud config set project {vertex_project_id}\n",
-        "\n",
-        "# Set the environment variable\n",
-        "% env VERTEX_PROJECT_ID = {vertex_project_id}"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "region"
-      },
-      "source": [
-        "#### Location\n",
-        "\n",
-        "You can also change the `VERTEX_LOCATION` variable used by Vertex AI. Learn more about [Vertex AI locations](https://cloud.google.com/vertex-ai/docs/general/locations)."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "region"
-      },
-      "outputs": [],
-      "source": [
-        "vertex_location = \"europe-west2\"  # @param {type: \"string\"}\n",
-        "\n",
-        "# Set the environment variable\n",
-        "%env VERTEX_LOCATION={vertex_location}"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "#### Resource suffix\n",
-        "\n",
-        "Specify the `RESOURCE_SUFFIX` (e.g. `<your name>`) to facilitate running concurrent pipelines in the same Google Cloud project. \n",
-        "This is important to change if you are working in a team to avoid overwriting resources during development "
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "resource_suffix=\"default\" # @param {type: \"string\"}\n",
-        "\n",
-        "# Set the environment variable\n",
-        "%env RESOUCE_SUFFIX=resource_suffix"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "#### Vertex pipelines service account\n",
-        "\n",
-        "We need to set the `VERTEX_SA_EMAIL` that is in the Google Cloud project so that this service account can run the pipelines for us."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "vertex_sa_email=f\"vertex-pipelines@{vertex_location}.iam.gserviceaccount.com\" #TODO: vertex_location should be vertex_project_id\n",
-        "\n",
-        "# Set the environment variable\n",
-        "%env VERTEX_SA_EMAIL={vertex_sa_email}"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "sBCra4QMA2wR"
-      },
-      "source": [
-        "### Authenticate your Google Cloud account\n",
-        "\n",
-        "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "74ccc9e52986"
-      },
-      "source": [
-        "**1. Vertex AI Workbench**\n",
-        "* Do nothing as you are already authenticated."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "de775a3773ba"
-      },
-      "source": [
-        "**2. Local JupyterLab instance, uncomment and run:**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "254614fa0c46"
-      },
-      "outputs": [],
-      "source": [
-        "# ! gcloud auth login"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "ef21552ccea8"
-      },
-      "source": [
-        "**3. Colab, uncomment and run:**"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "603adbbf0532"
-      },
-      "outputs": [],
-      "source": [
-        "# from google.colab import auth\n",
-        "# auth.authenticate_user()"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "f6b2ccc891ed"
-      },
-      "source": [
-        "**4. Service account or other**\n",
-        "* See how to grant Cloud Storage permissions to your service account at https://cloud.google.com/storage/docs/gsutil/commands/iam#ch-examples."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "zgPO1eR3CYjk"
-      },
-      "source": [
-        "### Create a Cloud Storage bucket\n",
-        "\n",
-        "Create a storage bucket to store intermediate artifacts such as datasets.\n",
-        "\n",
-        "- *{Note to notebook author: For any user-provided strings that need to be unique (like bucket names or model ID's), append \"-unique\" to the end so proper testing can occur}*"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "MzGDU7TWdts_"
-      },
-      "outputs": [],
-      "source": [
-        "BUCKET_URI = f\"gs://your-bucket-name-{PROJECT_ID}-unique\"  # @param {type:\"string\"}"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "-EcIXiGsCePi"
-      },
-      "source": [
-        "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "NIq7R4HZCfIc"
-      },
-      "outputs": [],
-      "source": [
-        "! gsutil mb -l {REGION} -p {PROJECT_ID} {BUCKET_URI}"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "960505627ddf"
-      },
-      "source": [
-        "### Import libraries"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "PyQmSRbKA8r-"
-      },
-      "outputs": [],
-      "source": [
-        "from google.cloud import aiplatform"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "init_aip:mbsdk,all"
-      },
-      "source": [
-        "### Initialize Vertex AI SDK for Python\n",
-        "\n",
-        "Initialize the Vertex AI SDK for Python for your project."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "init_aip:mbsdk,all"
-      },
-      "outputs": [],
-      "source": [
-        "aiplatform.init(project=PROJECT_ID, location=REGION, staging_bucket=BUCKET_URI)"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## 2. Training Pipeline"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "## 3. Prediction Pipeline"
-      ]
-    },
-    {
-      "attachments": {},
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "TpV-iwP9qw9c"
-      },
-      "source": [
-        "## 4. Cleaning up\n",
-        "\n",
-        "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
-        "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
-        "\n",
-        "Otherwise, you can delete the individual resources you created in this tutorial:\n",
-        "\n",
-        "{TODO: Include commands to delete individual resources below}"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "sx_vKniMq9ZX"
-      },
-      "outputs": [],
-      "source": [
-        "import os\n",
-        "\n",
-        "# Delete endpoint resource\n",
-        "# e.g. `endpoint.delete()`\n",
-        "\n",
-        "# Delete model resource\n",
-        "# e.g. `model.delete()`\n",
-        "\n",
-        "# Delete Cloud Storage objects that were created\n",
-        "delete_bucket = False\n",
-        "if delete_bucket or os.getenv(\"IS_TESTING\"):\n",
-        "    ! gsutil -m rm -r $BUCKET_URI"
-      ]
-    }
-  ],
-  "metadata": {
-    "colab": {
-      "collapsed_sections": [],
-      "name": "notebook_template.ipynb",
-      "toc_visible": true
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "language": "python",
-      "name": "python3"
-    },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "ipython",
-        "version": 3
-      },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
-      "version": "3.11.2"
-    },
-    "vscode": {
-      "interpreter": {
-        "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
-      }
-    }
-  },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}

From ef93fdd5ed44d5a6f81cd65428c784a5c73ffeaa Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Mon, 18 Sep 2023 11:49:14 +0100
Subject: [PATCH 200/238] style: Notebook style

---
 examples/pipelines.ipynb | 21 ++++++++++++++-------
 1 file changed, 14 insertions(+), 7 deletions(-)

diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index 6d5a2785..4d963cec 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -69,7 +69,8 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "tvgnzT1CKxrO"
+    "id": "tvgnzT1CKxrO",
+    "tags": []
    },
    "source": [
     "## Overview\n",
@@ -194,7 +195,8 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "i7EUnXsZhAGF"
+    "id": "i7EUnXsZhAGF",
+    "tags": []
    },
    "source": [
     "## Installation"
@@ -357,7 +359,9 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "BF1j6f9HApxa"
+    "id": "BF1j6f9HApxa",
+    "jp-MarkdownHeadingCollapsed": true,
+    "tags": []
    },
    "source": [
     "### Set up your Google Cloud project\n",
@@ -525,7 +529,8 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "zgPO1eR3CYjk"
+    "id": "zgPO1eR3CYjk",
+    "tags": []
    },
    "source": [
     "## Infrastructure deployment using terraform.\n"
@@ -613,9 +618,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
-    "## 2. Example ML Pipelines"
+    "## Example ML Pipelines"
    ]
   },
   {
@@ -866,7 +873,7 @@
     "id": "TpV-iwP9qw9c"
    },
    "source": [
-    "## 3. Cleaning up\n",
+    "## Cleaning up\n",
     "\n",
     "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
     "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",

From f476171751938c7e9a54a1442218f1d78152d009 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 19 Sep 2023 09:14:12 +0100
Subject: [PATCH 201/238] feat: Terraform for workbench

---
 examples/pipelines.ipynb | 43 ++++++++++++++++++++++++++++++----------
 1 file changed, 32 insertions(+), 11 deletions(-)

diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index 4d963cec..b01ec29d 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -29,7 +29,7 @@
     "id": "JAPoU8Sm5E6e"
    },
    "source": [
-    "# Running Vertex Pipelines using End-to-end Samples repository.\n",
+    "# Running Vertex Pipelines using E2E Samples repository.\n",
     "\n",
     "{TODO: Update the links below.} \n",
     "\n",
@@ -252,7 +252,7 @@
    },
    "outputs": [],
    "source": [
-    "! terraform --version"
+    "! terraform -version"
    ]
   },
   {
@@ -264,13 +264,27 @@
     "**If you do not have terraform installed please follow the instructions below.** Depending on your Jupyter environment, you may have to follow different installation methods."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**1. Local JupyterLab instance**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Please follow installation instructions: https://developer.hashicorp.com/terraform/tutorials/aws-get-started/install-cli"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
     "tags": []
    },
    "source": [
-    "**1. Vertex AI Workbench**"
+    "**2. Vertex AI Workbench, uncomment and run**"
    ]
   },
   {
@@ -281,23 +295,30 @@
    },
    "outputs": [],
    "source": [
-    "# "
+    "# %%bash\n",
+    "# curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
+    "# unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
+    "# mkdir $HOME/bin\n",
+    "# mv terraform $HOME/bin > /dev/null"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {},
+   "outputs": [],
    "source": [
-    "**2. Local JupyterLab instance**"
+    "# import os\n",
+    "# os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], 'bin')"
    ]
   },
   {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
-    "Please follow installation instructions: https://developer.hashicorp.com/terraform/tutorials/aws-get-started/install-cli"
+    "# ! terraform -version"
    ]
   },
   {

From dfa90acd958f431d6da2d2a9a9c55b501c94e548 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Tue, 19 Sep 2023 09:23:15 +0100
Subject: [PATCH 202/238] style: typos

---
 examples/pipelines.ipynb | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index b01ec29d..74a6457d 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -241,7 +241,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Check if terrafororm is installed."
+    "Check if terraform is installed."
    ]
   },
   {
@@ -381,7 +381,6 @@
    "cell_type": "markdown",
    "metadata": {
     "id": "BF1j6f9HApxa",
-    "jp-MarkdownHeadingCollapsed": true,
     "tags": []
    },
    "source": [

From 2d130742c429203977c98e318704ab84de684a53 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 20 Sep 2023 14:14:05 +0100
Subject: [PATCH 203/238] feat: pin pyyaml

---
 components/bigquery-components/poetry.lock    | 619 +++++++++---------
 components/bigquery-components/pyproject.toml |   1 +
 components/vertex-components/poetry.lock      | 255 +++++---
 components/vertex-components/pyproject.toml   |   1 +
 pipelines/poetry.lock                         | 295 +++++----
 pipelines/pyproject.toml                      |   1 +
 6 files changed, 642 insertions(+), 530 deletions(-)

diff --git a/components/bigquery-components/poetry.lock b/components/bigquery-components/poetry.lock
index d2a3ec40..c39c4aac 100644
--- a/components/bigquery-components/poetry.lock
+++ b/components/bigquery-components/poetry.lock
@@ -1,11 +1,12 @@
-# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
 
 [[package]]
 name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
     {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
@@ -13,118 +14,121 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.5.7"
+version = "2023.7.22"
 description = "Python package for providing Mozilla's CA Bundle."
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2023.5.7-py3-none-any.whl", hash = "sha256:c6c2e98f5c7869efca1f8916fed228dd91539f9f1b444c314c06eef02980c716"},
-    {file = "certifi-2023.5.7.tar.gz", hash = "sha256:0f0d56dc5a6ad56fd4ba36484d6cc34451e1c6548c61daad8c320169f91eddc7"},
+    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
+    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
 ]
 
 [[package]]
 name = "charset-normalizer"
-version = "3.1.0"
+version = "3.2.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
-optional = false
-python-versions = ">=3.9.0"
-files = [
-    {file = "charset-normalizer-3.1.0.tar.gz", hash = "sha256:34e0a2f9c370eb95597aae63bf85eb5e96826d81e3dcf88b8886012906f509b5"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e0ac8959c929593fee38da1c2b64ee9778733cdf03c482c9ff1d508b6b593b2b"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d7fc3fca01da18fbabe4625d64bb612b533533ed10045a2ac3dd194bfa656b60"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:04eefcee095f58eaabe6dc3cc2262f3bcd776d2c67005880894f447b3f2cb9c1"},
-    {file = "charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:20064ead0717cf9a73a6d1e779b23d149b53daf971169289ed2ed43a71e8d3b0"},
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+    {file = "charset_normalizer-3.2.0-py3-none-any.whl", hash = "sha256:8e098148dd37b4ce3baca71fb394c81dc5d9c7728c95df695d2dca218edf40e6"},
 ]
 
 [[package]]
 name = "click"
-version = "8.1.3"
+version = "8.1.7"
 description = "Composable command line interface toolkit"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
-    {file = "click-8.1.3-py3-none-any.whl", hash = "sha256:bb4d8133cb15a609f44e8213d9b391b0809795062913b383c62be0ee95b1db48"},
-    {file = "click-8.1.3.tar.gz", hash = "sha256:7682dc8afb30297001674575ea00d1814d808d6a36af415a82bd481d37ba7b8e"},
+    {file = "click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28"},
+    {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "platform_system == \"Windows\""}
-importlib-metadata = {version = "*", markers = "python_version < \"3.8\""}
 
 [[package]]
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -136,6 +140,7 @@ files = [
 name = "docstring-parser"
 version = "0.15"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
+category = "main"
 optional = false
 python-versions = ">=3.6,<4.0"
 files = [
@@ -145,13 +150,14 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.1"
+version = "1.1.3"
 description = "Backport of PEP 654 (exception groups)"
+category = "dev"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.1.1-py3-none-any.whl", hash = "sha256:232c37c63e4f682982c8b6459f33a8981039e5fb8756b2074364e5055c498c9e"},
-    {file = "exceptiongroup-1.1.1.tar.gz", hash = "sha256:d484c3090ba2889ae2928419117447a14daf3c1231d5e30d0aae34f354f01785"},
+    {file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
+    {file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
 ]
 
 [package.extras]
@@ -159,57 +165,59 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "google-api-core"
-version = "2.11.0"
+version = "2.11.1"
 description = "Google API client core library"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.11.0.tar.gz", hash = "sha256:4b9bb5d5a380a0befa0573b302651b8a9a89262c1730e37bf423cec511804c22"},
-    {file = "google_api_core-2.11.0-py3-none-any.whl", hash = "sha256:ce222e27b0de0d7bc63eb043b956996d6dccab14cc3b690aaea91c9cc99dc16e"},
+    {file = "google-api-core-2.11.1.tar.gz", hash = "sha256:25d29e05a0058ed5f19c61c0a78b1b53adea4d9364b464d014fbda941f6d1c9a"},
+    {file = "google_api_core-2.11.1-py3-none-any.whl", hash = "sha256:d92a5a92dc36dd4f4b9ee4e55528a90e432b059f93aee6ad857f9de8cc7ae94a"},
 ]
 
 [package.dependencies]
-google-auth = ">=2.14.1,<3.0dev"
-googleapis-common-protos = ">=1.56.2,<2.0dev"
+google-auth = ">=2.14.1,<3.0.dev0"
+googleapis-common-protos = ">=1.56.2,<2.0.dev0"
 grpcio = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-grpcio-status = {version = ">=1.33.2,<2.0dev", optional = true, markers = "extra == \"grpc\""}
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-requests = ">=2.18.0,<3.0.0dev"
+grpcio-status = {version = ">=1.33.2,<2.0.dev0", optional = true, markers = "extra == \"grpc\""}
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0.dev0"
+requests = ">=2.18.0,<3.0.0.dev0"
 
 [package.extras]
-grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status (>=1.33.2,<2.0dev)", "grpcio-status (>=1.49.1,<2.0dev)"]
-grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
-grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0dev)"]
+grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status (>=1.33.2,<2.0.dev0)", "grpcio-status (>=1.49.1,<2.0.dev0)"]
+grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
+grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.19.0"
+version = "2.23.0"
 description = "Google Authentication Library"
+category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.19.0.tar.gz", hash = "sha256:f39d528077ac540793dd3c22a8706178f157642a67d874db25c640b7fead277e"},
-    {file = "google_auth-2.19.0-py2.py3-none-any.whl", hash = "sha256:be617bfaf77774008e9d177573f782e109188c8a64ae6e744285df5cea3e7df6"},
+    {file = "google-auth-2.23.0.tar.gz", hash = "sha256:753a26312e6f1eaeec20bc6f2644a10926697da93446e1f8e24d6d32d45a922a"},
+    {file = "google_auth-2.23.0-py2.py3-none-any.whl", hash = "sha256:2cec41407bd1e207f5b802638e32bb837df968bb5c05f413d0fa526fac4cf7a7"},
 ]
 
 [package.dependencies]
 cachetools = ">=2.0.0,<6.0"
 pyasn1-modules = ">=0.2.1"
 rsa = ">=3.1.4,<5"
-six = ">=1.9.0"
 urllib3 = "<2.0"
 
 [package.extras]
-aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "requests (>=2.20.0,<3.0.0dev)"]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0.dev0)", "requests (>=2.20.0,<3.0.0.dev0)"]
 enterprise-cert = ["cryptography (==36.0.2)", "pyopenssl (==22.0.0)"]
 pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
-requests = ["requests (>=2.20.0,<3.0.0dev)"]
+requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-bigquery"
 version = "2.30.0"
 description = "Google BigQuery API client library"
+category = "dev"
 optional = false
 python-versions = ">=3.6, <3.11"
 files = [
@@ -239,17 +247,18 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 
 [[package]]
 name = "google-cloud-core"
-version = "2.3.2"
+version = "2.3.3"
 description = "Google Cloud API client core library"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-core-2.3.2.tar.gz", hash = "sha256:b9529ee7047fd8d4bf4a2182de619154240df17fbe60ead399078c1ae152af9a"},
-    {file = "google_cloud_core-2.3.2-py2.py3-none-any.whl", hash = "sha256:8417acf6466be2fa85123441696c4badda48db314c607cf1e5d543fa8bdc22fe"},
+    {file = "google-cloud-core-2.3.3.tar.gz", hash = "sha256:37b80273c8d7eee1ae816b3a20ae43585ea50506cb0e60f3cf5be5f87f1373cb"},
+    {file = "google_cloud_core-2.3.3-py2.py3-none-any.whl", hash = "sha256:fbd11cad3e98a7e5b0343dc07cb1039a5ffd7a5bb96e1f1e27cee4bda4a90863"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.6,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
@@ -257,20 +266,21 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.9.0"
+version = "2.11.0"
 description = "Google Cloud Storage API client library"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-storage-2.9.0.tar.gz", hash = "sha256:9b6ae7b509fc294bdacb84d0f3ea8e20e2c54a8b4bbe39c5707635fec214eff3"},
-    {file = "google_cloud_storage-2.9.0-py2.py3-none-any.whl", hash = "sha256:83a90447f23d5edd045e0037982c270302e3aeb45fc1288d2c2ca713d27bad94"},
+    {file = "google-cloud-storage-2.11.0.tar.gz", hash = "sha256:6fbf62659b83c8f3a0a743af0d661d2046c97c3a5bfb587c4662c4bc68de3e31"},
+    {file = "google_cloud_storage-2.11.0-py2.py3-none-any.whl", hash = "sha256:88cbd7fb3d701c780c4272bc26952db99f25eb283fb4c2208423249f00b5fe53"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 google-cloud-core = ">=2.3.0,<3.0dev"
-google-resumable-media = ">=2.3.2"
+google-resumable-media = ">=2.6.0"
 requests = ">=2.18.0,<3.0.0dev"
 
 [package.extras]
@@ -280,8 +290,9 @@ protobuf = ["protobuf (<5.0.0dev)"]
 name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "google-crc32c-1.5.0.tar.gz", hash = "sha256:89284716bc6a5a415d4eaa11b1726d2d60a0cd12aadf5439828353662ede9dd7"},
     {file = "google_crc32c-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:596d1f98fc70232fcb6590c439f43b350cb762fb5d61ce7b0e9db4539654cc13"},
@@ -358,100 +369,104 @@ testing = ["pytest"]
 
 [[package]]
 name = "google-resumable-media"
-version = "2.5.0"
+version = "2.6.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
+category = "main"
 optional = false
-python-versions = ">= 3.9"
+python-versions = ">= 3.7"
 files = [
-    {file = "google-resumable-media-2.5.0.tar.gz", hash = "sha256:218931e8e2b2a73a58eb354a288e03a0fd5fb1c4583261ac6e4c078666468c93"},
-    {file = "google_resumable_media-2.5.0-py2.py3-none-any.whl", hash = "sha256:da1bd943e2e114a56d85d6848497ebf9be6a14d3db23e9fc57581e7c3e8170ec"},
+    {file = "google-resumable-media-2.6.0.tar.gz", hash = "sha256:972852f6c65f933e15a4a210c2b96930763b47197cdf4aa5f5bea435efb626e7"},
+    {file = "google_resumable_media-2.6.0-py2.py3-none-any.whl", hash = "sha256:fc03d344381970f79eebb632a3c18bb1828593a2dc5572b5f90115ef7d11e81b"},
 ]
 
 [package.dependencies]
 google-crc32c = ">=1.0,<2.0dev"
 
 [package.extras]
-aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)"]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "google-auth (>=1.22.0,<2.0dev)"]
 requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.59.0"
+version = "1.60.0"
 description = "Common protobufs used in Google APIs"
+category = "main"
 optional = false
-python-versions = ">=3.9"
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+    {file = "grpcio-1.58.0-cp39-cp39-win_amd64.whl", hash = "sha256:dcfba7befe3a55dab6fe1eb7fc9359dc0c7f7272b30a70ae0af5d5b063842f28"},
+    {file = "grpcio-1.58.0.tar.gz", hash = "sha256:532410c51ccd851b706d1fbc00a87be0f5312bd6f8e5dbf89d4e99c7f79d7499"},
 ]
 
 [package.extras]
-protobuf = ["grpcio-tools (>=1.54.2)"]
+protobuf = ["grpcio-tools (>=1.58.0)"]
 
 [[package]]
 name = "grpcio-status"
 version = "1.48.2"
 description = "Status proto mapping for gRPC"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -468,6 +483,7 @@ protobuf = ">=3.12.0"
 name = "idna"
 version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
+category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -475,32 +491,13 @@ files = [
     {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
 ]
 
-[[package]]
-name = "importlib-metadata"
-version = "6.6.0"
-description = "Read metadata from Python packages"
-optional = false
-python-versions = ">=3.9"
-files = [
-    {file = "importlib_metadata-6.6.0-py3-none-any.whl", hash = "sha256:43dd286a2cd8995d5eaef7fee2066340423b818ed3fd70adf0bad5f1fac53fed"},
-    {file = "importlib_metadata-6.6.0.tar.gz", hash = "sha256:92501cdf9cc66ebd3e612f1b4f0c0765dfa42f0fa38ffb319b6bd84dd675d705"},
-]
-
-[package.dependencies]
-typing-extensions = {version = ">=3.6.4", markers = "python_version < \"3.8\""}
-zipp = ">=0.5"
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-perf = ["ipython"]
-testing = ["flake8 (<5)", "flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)"]
-
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
+category = "dev"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "iniconfig-2.0.0-py3-none-any.whl", hash = "sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374"},
     {file = "iniconfig-2.0.0.tar.gz", hash = "sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3"},
@@ -508,18 +505,19 @@ files = [
 
 [[package]]
 name = "kfp"
-version = "2.0.1"
+version = "2.2.0"
 description = "Kubeflow Pipelines SDK"
+category = "main"
 optional = false
-python-versions = ">=3.9.0,<3.12.0"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "kfp-2.0.1.tar.gz", hash = "sha256:4a65811778c3a45892d8d11c0f95ba5e410476157ed63cacb1dd82316f60cd4d"},
+    {file = "kfp-2.2.0.tar.gz", hash = "sha256:f4b243e11cc7e6a34dcb3af348b2784ba02f6fa2707b000d215d108bed338518"},
 ]
 
 [package.dependencies]
 click = ">=8.0.0,<9"
 docstring-parser = ">=0.7.3,<1"
-google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.6.1,<3"
 google-cloud-storage = ">=2.2.1,<3"
 kfp-pipeline-spec = "0.2.2"
@@ -529,7 +527,6 @@ protobuf = ">=3.13.0,<4"
 PyYAML = ">=5.3,<7"
 requests-toolbelt = ">=0.8.0,<1"
 tabulate = ">=0.8.6,<1"
-typing-extensions = {version = ">=3.9.4,<5", markers = "python_version < \"3.9\""}
 urllib3 = "<2.0.0"
 
 [package.extras]
@@ -540,8 +537,9 @@ kubernetes = ["kfp-kubernetes (<2)"]
 name = "kfp-pipeline-spec"
 version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
+category = "main"
 optional = false
-python-versions = ">=3.9.0"
+python-versions = ">=3.7.0"
 files = [
     {file = "kfp_pipeline_spec-0.2.2-py3-none-any.whl", hash = "sha256:e83b58ffed3f7ca154d62ab20e14dc9a1a3c9dad589e856dd2b421e226f3b8d0"},
 ]
@@ -551,12 +549,13 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "2.0.0"
+version = "2.0.1"
 description = "Kubeflow Pipelines API"
+category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "kfp-server-api-2.0.0.tar.gz", hash = "sha256:c0462045244a69211bc82a8d6af6602ae8b4f716ee0ac0be5dc34b7ea76c7bd1"},
+    {file = "kfp-server-api-2.0.1.tar.gz", hash = "sha256:4851f414d8f56e0ddd4383ba6de9992debddd2df95e1ecd63b01954c25131abb"},
 ]
 
 [package.dependencies]
@@ -567,13 +566,14 @@ urllib3 = ">=1.15"
 
 [[package]]
 name = "kubernetes"
-version = "25.3.0"
+version = "26.1.0"
 description = "Kubernetes python client"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "kubernetes-25.3.0-py2.py3-none-any.whl", hash = "sha256:eb42333dad0bb5caf4e66460c6a4a1a36f0f057a040f35018f6c05a699baed86"},
-    {file = "kubernetes-25.3.0.tar.gz", hash = "sha256:213befbb4e5aed95f94950c7eed0c2322fc5a2f8f40932e58d28fdd42d90836c"},
+    {file = "kubernetes-26.1.0-py2.py3-none-any.whl", hash = "sha256:e3db6800abf7e36c38d2629b5cb6b74d10988ee0cba6fba45595a7cbe60c0042"},
+    {file = "kubernetes-26.1.0.tar.gz", hash = "sha256:5854b0c508e8d217ca205591384ab58389abdae608576f9c9afc35a3c76a366c"},
 ]
 
 [package.dependencies]
@@ -586,7 +586,7 @@ requests-oauthlib = "*"
 setuptools = ">=21.0.0"
 six = ">=1.9.0"
 urllib3 = ">=1.24.2"
-websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
+websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.0 || >=0.43.0"
 
 [package.extras]
 adal = ["adal (>=1.0.2)"]
@@ -595,6 +595,7 @@ adal = ["adal (>=1.0.2)"]
 name = "oauthlib"
 version = "3.2.2"
 description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -611,8 +612,9 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
+category = "dev"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "packaging-23.1-py3-none-any.whl", hash = "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61"},
     {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
@@ -620,31 +622,30 @@ files = [
 
 [[package]]
 name = "pluggy"
-version = "1.0.0"
+version = "1.3.0"
 description = "plugin and hook calling mechanisms for python"
+category = "dev"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
-    {file = "pluggy-1.0.0-py2.py3-none-any.whl", hash = "sha256:74134bbf457f031a36d68416e1509f34bd5ccc019f0bcc952c7b909d06b37bd3"},
-    {file = "pluggy-1.0.0.tar.gz", hash = "sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159"},
+    {file = "pluggy-1.3.0-py3-none-any.whl", hash = "sha256:d89c696a773f8bd377d18e5ecda92b7a3793cbe66c87060a6fb58c7b6e1061f7"},
+    {file = "pluggy-1.3.0.tar.gz", hash = "sha256:cf61ae8f126ac6f7c451172cf30e3e43d3ca77615509771b3a984a0730651e12"},
 ]
 
-[package.dependencies]
-importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
-
 [package.extras]
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "proto-plus"
-version = "1.22.2"
+version = "1.22.3"
 description = "Beautiful, Pythonic protocol buffers."
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "proto-plus-1.22.2.tar.gz", hash = "sha256:0e8cda3d5a634d9895b75c573c9352c16486cb75deb0e078b5fda34db4243165"},
-    {file = "proto_plus-1.22.2-py3-none-any.whl", hash = "sha256:de34e52d6c9c6fcd704192f09767cb561bb4ee64e70eede20b0834d841f0be4d"},
+    {file = "proto-plus-1.22.3.tar.gz", hash = "sha256:fdcd09713cbd42480740d2fe29c990f7fbd885a67efc328aa8be6ee3e9f76a6b"},
+    {file = "proto_plus-1.22.3-py3-none-any.whl", hash = "sha256:a49cd903bc0b6ab41f76bf65510439d56ca76f868adf0274e738bfdd096894df"},
 ]
 
 [package.dependencies]
@@ -657,8 +658,9 @@ testing = ["google-api-core[grpc] (>=1.31.5)"]
 name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "protobuf-3.20.3-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:f4bd856d702e5b0d96a00ec6b307b0f51c1982c2bf9c0052cf9019e9a544ba99"},
     {file = "protobuf-3.20.3-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl", hash = "sha256:9aae4406ea63d825636cc11ffb34ad3379335803216ee3a856787bcf5ccc751e"},
@@ -688,6 +690,7 @@ files = [
 name = "pyasn1"
 version = "0.5.0"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -699,6 +702,7 @@ files = [
 name = "pyasn1-modules"
 version = "0.3.0"
 description = "A collection of ASN.1-based protocols modules"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -711,31 +715,32 @@ pyasn1 = ">=0.4.6,<0.6.0"
 
 [[package]]
 name = "pytest"
-version = "7.3.1"
+version = "7.4.2"
 description = "pytest: simple powerful testing with Python"
+category = "dev"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
-    {file = "pytest-7.3.1-py3-none-any.whl", hash = "sha256:3799fa815351fea3a5e96ac7e503a96fa51cc9942c3753cda7651b93c1cfa362"},
-    {file = "pytest-7.3.1.tar.gz", hash = "sha256:434afafd78b1d78ed0addf160ad2b77a30d35d4bdf8af234fe621919d9ed15e3"},
+    {file = "pytest-7.4.2-py3-none-any.whl", hash = "sha256:1d881c6124e08ff0a1bb75ba3ec0bfd8b5354a01c194ddd5a0a870a48d99b002"},
+    {file = "pytest-7.4.2.tar.gz", hash = "sha256:a766259cfab564a2ad52cb1aae1b881a75c3eb7e34ca3779697c23ed47c47069"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
 exceptiongroup = {version = ">=1.0.0rc8", markers = "python_version < \"3.11\""}
-importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""}
 iniconfig = "*"
 packaging = "*"
 pluggy = ">=0.12,<2.0"
 tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
-testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "xmlschema"]
+testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "python-dateutil"
 version = "2.8.2"
 description = "Extensions to the standard Python datetime module"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
@@ -748,48 +753,61 @@ six = ">=1.5"
 
 [[package]]
 name = "pyyaml"
-version = "5.4.1"
+version = "6.0.1"
 description = "YAML parser and emitter for Python"
+category = "main"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
+python-versions = ">=3.6"
 files = [
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-    {file = "PyYAML-5.4.1-cp27-cp27m-win_amd64.whl", hash = "sha256:4465124ef1b18d9ace298060f4eccc64b0850899ac4ac53294547536533800c8"},
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+    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"},
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+    {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"},
+    {file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"},
+    {file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
+    {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
 ]
 
 [[package]]
 name = "requests"
 version = "2.31.0"
 description = "Python HTTP for Humans."
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
     {file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
@@ -809,6 +827,7 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 name = "requests-oauthlib"
 version = "1.3.1"
 description = "OAuthlib authentication support for Requests."
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -827,6 +846,7 @@ rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 name = "requests-toolbelt"
 version = "0.10.1"
 description = "A utility belt for advanced users of python-requests"
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -841,6 +861,7 @@ requests = ">=2.0.1,<3.0.0"
 name = "rsa"
 version = "4.9"
 description = "Pure-Python RSA implementation"
+category = "main"
 optional = false
 python-versions = ">=3.6,<4"
 files = [
@@ -853,24 +874,26 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "setuptools"
-version = "67.8.0"
+version = "68.2.2"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 files = [
-    {file = "setuptools-67.8.0-py3-none-any.whl", hash = "sha256:5df61bf30bb10c6f756eb19e7c9f3b473051f48db77fddbe06ff2ca307df9a6f"},
-    {file = "setuptools-67.8.0.tar.gz", hash = "sha256:62642358adc77ffa87233bc4d2354c4b2682d214048f500964dbe760ccedf102"},
+    {file = "setuptools-68.2.2-py3-none-any.whl", hash = "sha256:b454a35605876da60632df1a60f736524eb73cc47bbc9f3f1ef1b644de74fd2a"},
+    {file = "setuptools-68.2.2.tar.gz", hash = "sha256:4ac1475276d2f1c48684874089fefcd83bd7162ddaafb81fac866ba0db282a87"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
-testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.1)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
 name = "six"
 version = "1.16.0"
 description = "Python 2 and 3 compatibility utilities"
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
@@ -882,8 +905,9 @@ files = [
 name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"},
     {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"},
@@ -896,28 +920,19 @@ widechars = ["wcwidth"]
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
+category = "dev"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7"
 files = [
     {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
     {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
 ]
 
-[[package]]
-name = "typing-extensions"
-version = "4.6.2"
-description = "Backported and Experimental Type Hints for Python 3.9+"
-optional = false
-python-versions = ">=3.9"
-files = [
-    {file = "typing_extensions-4.6.2-py3-none-any.whl", hash = "sha256:3a8b36f13dd5fdc5d1b16fe317f5668545de77fa0b8e02006381fd49d731ab98"},
-    {file = "typing_extensions-4.6.2.tar.gz", hash = "sha256:06006244c70ac8ee83fa8282cb188f697b8db25bc8b4df07be1873c43897060c"},
-]
-
 [[package]]
 name = "urllib3"
 version = "1.26.16"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
@@ -932,36 +947,22 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "websocket-client"
-version = "1.5.2"
+version = "1.6.3"
 description = "WebSocket client for Python with low level API options"
+category = "main"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 files = [
-    {file = "websocket-client-1.5.2.tar.gz", hash = "sha256:c7d67c13b928645f259d9b847ab5b57fd2d127213ca41ebd880de1f553b7c23b"},
-    {file = "websocket_client-1.5.2-py3-none-any.whl", hash = "sha256:f8c64e28cd700e7ba1f04350d66422b6833b82a796b525a51e740b8cc8dab4b1"},
+    {file = "websocket-client-1.6.3.tar.gz", hash = "sha256:3aad25d31284266bcfcfd1fd8a743f63282305a364b8d0948a43bd606acc652f"},
+    {file = "websocket_client-1.6.3-py3-none-any.whl", hash = "sha256:6cfc30d051ebabb73a5fa246efdcc14c8fbebbd0330f8984ac3bb6d9edd2ad03"},
 ]
 
 [package.extras]
-docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
+docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
-[[package]]
-name = "zipp"
-version = "3.15.0"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.9"
-files = [
-    {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"},
-    {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"},
-]
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.9)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"]
-
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "6f7ca2171a974f20e9e0c7d38859b0570337711f678f0fed05a9560ce299f0e0"
+content-hash = "22b5fc84eafddbe9d7bd4f3d39f53736433db333da7a8bc4186470ed1b0cfd42"
diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
index 36d55a21..e040ce11 100644
--- a/components/bigquery-components/pyproject.toml
+++ b/components/bigquery-components/pyproject.toml
@@ -13,6 +13,7 @@ classifiers = [
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
 kfp = "^2.0.1"
+pyyaml = "6.0.1"
 
 [tool.poetry.group.dev.dependencies]
 google-cloud-bigquery = "2.30.0"
diff --git a/components/vertex-components/poetry.lock b/components/vertex-components/poetry.lock
index 5368a62b..5152ad6d 100644
--- a/components/vertex-components/poetry.lock
+++ b/components/vertex-components/poetry.lock
@@ -1,9 +1,10 @@
-# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
 
 [[package]]
 name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -15,6 +16,7 @@ files = [
 name = "certifi"
 version = "2023.7.22"
 description = "Python package for providing Mozilla's CA Bundle."
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -26,6 +28,7 @@ files = [
 name = "charset-normalizer"
 version = "3.2.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -108,13 +111,14 @@ files = [
 
 [[package]]
 name = "click"
-version = "8.1.6"
+version = "8.1.7"
 description = "Composable command line interface toolkit"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "click-8.1.6-py3-none-any.whl", hash = "sha256:fa244bb30b3b5ee2cae3da8f55c9e5e0c0e86093306301fb418eb9dc40fbded5"},
-    {file = "click-8.1.6.tar.gz", hash = "sha256:48ee849951919527a045bfe3bf7baa8a959c423134e1a5b98c05c20ba75a1cbd"},
+    {file = "click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28"},
+    {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
 ]
 
 [package.dependencies]
@@ -124,6 +128,7 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -135,6 +140,7 @@ files = [
 name = "docstring-parser"
 version = "0.15"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
+category = "main"
 optional = false
 python-versions = ">=3.6,<4.0"
 files = [
@@ -144,13 +150,14 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.2"
+version = "1.1.3"
 description = "Backport of PEP 654 (exception groups)"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.1.2-py3-none-any.whl", hash = "sha256:e346e69d186172ca7cf029c8c1d16235aa0e04035e5750b4b95039e65204328f"},
-    {file = "exceptiongroup-1.1.2.tar.gz", hash = "sha256:12c3e887d6485d16943a309616de20ae5582633e0a2eda17f4e10fd61c1e8af5"},
+    {file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
+    {file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
 ]
 
 [package.extras]
@@ -160,6 +167,7 @@ test = ["pytest (>=6)"]
 name = "google-api-core"
 version = "2.11.1"
 description = "Google API client core library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -182,20 +190,20 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.22.0"
+version = "2.23.0"
 description = "Google Authentication Library"
+category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.22.0.tar.gz", hash = "sha256:164cba9af4e6e4e40c3a4f90a1a6c12ee56f14c0b4868d1ca91b32826ab334ce"},
-    {file = "google_auth-2.22.0-py2.py3-none-any.whl", hash = "sha256:d61d1b40897407b574da67da1a833bdc10d5a11642566e506565d1b1a46ba873"},
+    {file = "google-auth-2.23.0.tar.gz", hash = "sha256:753a26312e6f1eaeec20bc6f2644a10926697da93446e1f8e24d6d32d45a922a"},
+    {file = "google_auth-2.23.0-py2.py3-none-any.whl", hash = "sha256:2cec41407bd1e207f5b802638e32bb837df968bb5c05f413d0fa526fac4cf7a7"},
 ]
 
 [package.dependencies]
 cachetools = ">=2.0.0,<6.0"
 pyasn1-modules = ">=0.2.1"
 rsa = ">=3.1.4,<5"
-six = ">=1.9.0"
 urllib3 = "<2.0"
 
 [package.extras]
@@ -209,6 +217,7 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 name = "google-cloud-aiplatform"
 version = "1.30.1"
 description = "Vertex AI API client library"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -217,7 +226,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.32.0,<2.0.dev0 || >=2.8.dev0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.32.0,<2.0.0 || >=2.8.0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-bigquery = ">=1.15.0,<4.0.0dev"
 google-cloud-resource-manager = ">=1.3.3,<3.0.0dev"
 google-cloud-storage = ">=1.32.0,<3.0.0dev"
@@ -246,6 +255,7 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 name = "google-cloud-bigquery"
 version = "3.11.4"
 description = "Google BigQuery API client library"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -254,7 +264,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-core = ">=1.6.0,<3.0.0dev"
 google-resumable-media = ">=0.6.0,<3.0dev"
 grpcio = ">=1.47.0,<2.0dev"
@@ -278,6 +288,7 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 name = "google-cloud-core"
 version = "2.3.3"
 description = "Google Cloud API client core library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -286,7 +297,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.6,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
@@ -294,16 +305,17 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "2.1.1"
+version = "2.3.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
+category = "dev"
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "google_cloud_pipeline_components-2.1.1-py3-none-any.whl", hash = "sha256:fdb1621a1db112833a299bfe6353edd2eb7b9195e0d39896491c75e0b6624dcc"},
+    {file = "google_cloud_pipeline_components-2.3.0-py3-none-any.whl", hash = "sha256:bfb6f04598f431577bdf40d3a937646eed16f703d95010379db138d4624be69c"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
 google-cloud-aiplatform = ">=1.14.0,<2"
 kfp = ">=2.0.0b10,<3.0.0"
 
@@ -313,37 +325,39 @@ tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
-version = "1.10.3"
+version = "1.10.4"
 description = "Google Cloud Resource Manager API client library"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-resource-manager-1.10.3.tar.gz", hash = "sha256:f80efcea36f10c5a81889afe93910926e3978b4b1ceeb82f563a2fc863072d14"},
-    {file = "google_cloud_resource_manager-1.10.3-py2.py3-none-any.whl", hash = "sha256:1381a4b0f522248ebe0ebd1289d8822b99c54f4e1fe03924a6e723b2ed93dd7f"},
+    {file = "google-cloud-resource-manager-1.10.4.tar.gz", hash = "sha256:456b25ddda3d4cd27488a72736bbc3af04d713ae2fe3655c01b66a339d28d679"},
+    {file = "google_cloud_resource_manager-1.10.4-py2.py3-none-any.whl", hash = "sha256:2ba56ba8e5280cd425bd63620da48b78da2cd299ece58a71f0f2ce3a32d56f99"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]}
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
 proto-plus = ">=1.22.0,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.10.0"
+version = "2.11.0"
 description = "Google Cloud Storage API client library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-storage-2.10.0.tar.gz", hash = "sha256:934b31ead5f3994e5360f9ff5750982c5b6b11604dc072bc452c25965e076dc7"},
-    {file = "google_cloud_storage-2.10.0-py2.py3-none-any.whl", hash = "sha256:9433cf28801671de1c80434238fb1e7e4a1ba3087470e90f70c928ea77c2b9d7"},
+    {file = "google-cloud-storage-2.11.0.tar.gz", hash = "sha256:6fbf62659b83c8f3a0a743af0d661d2046c97c3a5bfb587c4662c4bc68de3e31"},
+    {file = "google_cloud_storage-2.11.0-py2.py3-none-any.whl", hash = "sha256:88cbd7fb3d701c780c4272bc26952db99f25eb283fb4c2208423249f00b5fe53"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 google-cloud-core = ">=2.3.0,<3.0dev"
-google-resumable-media = ">=2.3.2"
+google-resumable-media = ">=2.6.0"
 requests = ">=2.18.0,<3.0.0dev"
 
 [package.extras]
@@ -353,6 +367,7 @@ protobuf = ["protobuf (<5.0.0dev)"]
 name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -431,26 +446,28 @@ testing = ["pytest"]
 
 [[package]]
 name = "google-resumable-media"
-version = "2.5.0"
+version = "2.6.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
+category = "main"
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "google-resumable-media-2.5.0.tar.gz", hash = "sha256:218931e8e2b2a73a58eb354a288e03a0fd5fb1c4583261ac6e4c078666468c93"},
-    {file = "google_resumable_media-2.5.0-py2.py3-none-any.whl", hash = "sha256:da1bd943e2e114a56d85d6848497ebf9be6a14d3db23e9fc57581e7c3e8170ec"},
+    {file = "google-resumable-media-2.6.0.tar.gz", hash = "sha256:972852f6c65f933e15a4a210c2b96930763b47197cdf4aa5f5bea435efb626e7"},
+    {file = "google_resumable_media-2.6.0-py2.py3-none-any.whl", hash = "sha256:fc03d344381970f79eebb632a3c18bb1828593a2dc5572b5f90115ef7d11e81b"},
 ]
 
 [package.dependencies]
 google-crc32c = ">=1.0,<2.0dev"
 
 [package.extras]
-aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)"]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "google-auth (>=1.22.0,<2.0dev)"]
 requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
 version = "1.60.0"
 description = "Common protobufs used in Google APIs"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -469,6 +486,7 @@ grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 name = "grpc-google-iam-v1"
 version = "0.12.6"
 description = "IAM API client library"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -483,65 +501,67 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 
 [[package]]
 name = "grpcio"
-version = "1.57.0"
+version = "1.58.0"
 description = "HTTP/2-based RPC framework"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.extras]
-protobuf = ["grpcio-tools (>=1.57.0)"]
+protobuf = ["grpcio-tools (>=1.58.0)"]
 
 [[package]]
 name = "grpcio-status"
 version = "1.48.2"
 description = "Status proto mapping for gRPC"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -558,6 +578,7 @@ protobuf = ">=3.12.0"
 name = "idna"
 version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
+category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -569,6 +590,7 @@ files = [
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -578,18 +600,19 @@ files = [
 
 [[package]]
 name = "kfp"
-version = "2.0.1"
+version = "2.2.0"
 description = "Kubeflow Pipelines SDK"
+category = "main"
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "kfp-2.0.1.tar.gz", hash = "sha256:4a65811778c3a45892d8d11c0f95ba5e410476157ed63cacb1dd82316f60cd4d"},
+    {file = "kfp-2.2.0.tar.gz", hash = "sha256:f4b243e11cc7e6a34dcb3af348b2784ba02f6fa2707b000d215d108bed338518"},
 ]
 
 [package.dependencies]
 click = ">=8.0.0,<9"
 docstring-parser = ">=0.7.3,<1"
-google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.6.1,<3"
 google-cloud-storage = ">=2.2.1,<3"
 kfp-pipeline-spec = "0.2.2"
@@ -609,6 +632,7 @@ kubernetes = ["kfp-kubernetes (<2)"]
 name = "kfp-pipeline-spec"
 version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
+category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -620,12 +644,13 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "2.0.0"
+version = "2.0.1"
 description = "Kubeflow Pipelines API"
+category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "kfp-server-api-2.0.0.tar.gz", hash = "sha256:c0462045244a69211bc82a8d6af6602ae8b4f716ee0ac0be5dc34b7ea76c7bd1"},
+    {file = "kfp-server-api-2.0.1.tar.gz", hash = "sha256:4851f414d8f56e0ddd4383ba6de9992debddd2df95e1ecd63b01954c25131abb"},
 ]
 
 [package.dependencies]
@@ -638,6 +663,7 @@ urllib3 = ">=1.15"
 name = "kubernetes"
 version = "26.1.0"
 description = "Kubernetes python client"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -655,7 +681,7 @@ requests-oauthlib = "*"
 setuptools = ">=21.0.0"
 six = ">=1.9.0"
 urllib3 = ">=1.24.2"
-websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
+websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.0 || >=0.43.0"
 
 [package.extras]
 adal = ["adal (>=1.0.2)"]
@@ -664,6 +690,7 @@ adal = ["adal (>=1.0.2)"]
 name = "oauthlib"
 version = "3.2.2"
 description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -680,6 +707,7 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -689,13 +717,14 @@ files = [
 
 [[package]]
 name = "pluggy"
-version = "1.2.0"
+version = "1.3.0"
 description = "plugin and hook calling mechanisms for python"
+category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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-    {file = "pluggy-1.2.0.tar.gz", hash = "sha256:d12f0c4b579b15f5e054301bb226ee85eeeba08ffec228092f8defbaa3a4c4b3"},
+    {file = "pluggy-1.3.0-py3-none-any.whl", hash = "sha256:d89c696a773f8bd377d18e5ecda92b7a3793cbe66c87060a6fb58c7b6e1061f7"},
+    {file = "pluggy-1.3.0.tar.gz", hash = "sha256:cf61ae8f126ac6f7c451172cf30e3e43d3ca77615509771b3a984a0730651e12"},
 ]
 
 [package.extras]
@@ -706,6 +735,7 @@ testing = ["pytest", "pytest-benchmark"]
 name = "proto-plus"
 version = "1.22.3"
 description = "Beautiful, Pythonic protocol buffers."
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -723,6 +753,7 @@ testing = ["google-api-core[grpc] (>=1.31.5)"]
 name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -754,6 +785,7 @@ files = [
 name = "pyasn1"
 version = "0.5.0"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -765,6 +797,7 @@ files = [
 name = "pyasn1-modules"
 version = "0.3.0"
 description = "A collection of ASN.1-based protocols modules"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -777,13 +810,14 @@ pyasn1 = ">=0.4.6,<0.6.0"
 
 [[package]]
 name = "pytest"
-version = "7.4.0"
+version = "7.4.2"
 description = "pytest: simple powerful testing with Python"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "pytest-7.4.0-py3-none-any.whl", hash = "sha256:78bf16451a2eb8c7a2ea98e32dc119fd2aa758f1d5d66dbf0a59d69a3969df32"},
-    {file = "pytest-7.4.0.tar.gz", hash = "sha256:b4bf8c45bd59934ed84001ad51e11b4ee40d40a1229d2c79f9c592b0a3f6bd8a"},
+    {file = "pytest-7.4.2-py3-none-any.whl", hash = "sha256:1d881c6124e08ff0a1bb75ba3ec0bfd8b5354a01c194ddd5a0a870a48d99b002"},
+    {file = "pytest-7.4.2.tar.gz", hash = "sha256:a766259cfab564a2ad52cb1aae1b881a75c3eb7e34ca3779697c23ed47c47069"},
 ]
 
 [package.dependencies]
@@ -801,6 +835,7 @@ testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "no
 name = "python-dateutil"
 version = "2.8.2"
 description = "Extensions to the standard Python datetime module"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
@@ -815,6 +850,7 @@ six = ">=1.5"
 name = "pyyaml"
 version = "6.0.1"
 description = "YAML parser and emitter for Python"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -864,6 +900,7 @@ files = [
 name = "requests"
 version = "2.31.0"
 description = "Python HTTP for Humans."
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -885,6 +922,7 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 name = "requests-oauthlib"
 version = "1.3.1"
 description = "OAuthlib authentication support for Requests."
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -903,6 +941,7 @@ rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 name = "requests-toolbelt"
 version = "0.10.1"
 description = "A utility belt for advanced users of python-requests"
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -917,6 +956,7 @@ requests = ">=2.0.1,<3.0.0"
 name = "rsa"
 version = "4.9"
 description = "Pure-Python RSA implementation"
+category = "main"
 optional = false
 python-versions = ">=3.6,<4"
 files = [
@@ -929,24 +969,26 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "setuptools"
-version = "68.0.0"
+version = "68.2.2"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
+category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "setuptools-68.0.0-py3-none-any.whl", hash = "sha256:11e52c67415a381d10d6b462ced9cfb97066179f0e871399e006c4ab101fc85f"},
-    {file = "setuptools-68.0.0.tar.gz", hash = "sha256:baf1fdb41c6da4cd2eae722e135500da913332ab3f2f5c7d33af9b492acb5235"},
+    {file = "setuptools-68.2.2-py3-none-any.whl", hash = "sha256:b454a35605876da60632df1a60f736524eb73cc47bbc9f3f1ef1b644de74fd2a"},
+    {file = "setuptools-68.2.2.tar.gz", hash = "sha256:4ac1475276d2f1c48684874089fefcd83bd7162ddaafb81fac866ba0db282a87"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
-testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.1)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
 name = "shapely"
 version = "1.8.5.post1"
 description = "Geometric objects, predicates, and operations"
+category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1003,6 +1045,7 @@ vectorized = ["numpy"]
 name = "six"
 version = "1.16.0"
 description = "Python 2 and 3 compatibility utilities"
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
@@ -1014,6 +1057,7 @@ files = [
 name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1028,6 +1072,7 @@ widechars = ["wcwidth"]
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1039,6 +1084,7 @@ files = [
 name = "urllib3"
 version = "1.26.16"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
@@ -1053,21 +1099,22 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "websocket-client"
-version = "1.6.1"
+version = "1.6.3"
 description = "WebSocket client for Python with low level API options"
+category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "websocket-client-1.6.1.tar.gz", hash = "sha256:c951af98631d24f8df89ab1019fc365f2227c0892f12fd150e935607c79dd0dd"},
-    {file = "websocket_client-1.6.1-py3-none-any.whl", hash = "sha256:f1f9f2ad5291f0225a49efad77abf9e700b6fef553900623060dad6e26503b9d"},
+    {file = "websocket-client-1.6.3.tar.gz", hash = "sha256:3aad25d31284266bcfcfd1fd8a743f63282305a364b8d0948a43bd606acc652f"},
+    {file = "websocket_client-1.6.3-py3-none-any.whl", hash = "sha256:6cfc30d051ebabb73a5fa246efdcc14c8fbebbd0330f8984ac3bb6d9edd2ad03"},
 ]
 
 [package.extras]
-docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
+docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "f1eb8e95cdba70c0a5f31de2527e75b4301ba6ab983e367a51a6bf5ef658ceac"
+content-hash = "55cace2bc751bc7493824589863892d3b0336943772b9a6f24131517a8c09701"
diff --git a/components/vertex-components/pyproject.toml b/components/vertex-components/pyproject.toml
index d64b4811..f026a997 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/vertex-components/pyproject.toml
@@ -13,6 +13,7 @@ classifiers = [
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
 kfp = ">=2.0.1,<3.0.0"
+pyyaml = "6.0.1"
 
 [tool.poetry.group.dev.dependencies]
 google-cloud-aiplatform = "1.30.1"
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index 49e3e1f7..9ac7210a 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -1,9 +1,10 @@
-# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
 
 [[package]]
 name = "bigquery-components"
 version = "0.1.0"
 description = "KubeFlow components for BigQuery"
+category = "main"
 optional = false
 python-versions = ">=3.9,<3.11"
 files = []
@@ -20,6 +21,7 @@ url = "../components/bigquery-components"
 name = "cachetools"
 version = "5.3.1"
 description = "Extensible memoizing collections and decorators"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -31,6 +33,7 @@ files = [
 name = "certifi"
 version = "2023.7.22"
 description = "Python package for providing Mozilla's CA Bundle."
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -42,6 +45,7 @@ files = [
 name = "cfgv"
 version = "3.4.0"
 description = "Validate configuration and produce human readable error messages."
+category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -53,6 +57,7 @@ files = [
 name = "charset-normalizer"
 version = "3.2.0"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -135,13 +140,14 @@ files = [
 
 [[package]]
 name = "click"
-version = "8.1.6"
+version = "8.1.7"
 description = "Composable command line interface toolkit"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "click-8.1.6-py3-none-any.whl", hash = "sha256:fa244bb30b3b5ee2cae3da8f55c9e5e0c0e86093306301fb418eb9dc40fbded5"},
-    {file = "click-8.1.6.tar.gz", hash = "sha256:48ee849951919527a045bfe3bf7baa8a959c423134e1a5b98c05c20ba75a1cbd"},
+    {file = "click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28"},
+    {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
 ]
 
 [package.dependencies]
@@ -151,6 +157,7 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -162,6 +169,7 @@ files = [
 name = "coverage"
 version = "7.2.5"
 description = "Code coverage measurement for Python"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -225,6 +233,7 @@ toml = ["tomli"]
 name = "distlib"
 version = "0.3.7"
 description = "Distribution utilities"
+category = "dev"
 optional = false
 python-versions = "*"
 files = [
@@ -236,6 +245,7 @@ files = [
 name = "docstring-parser"
 version = "0.15"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
+category = "main"
 optional = false
 python-versions = ">=3.6,<4.0"
 files = [
@@ -245,13 +255,14 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.2"
+version = "1.1.3"
 description = "Backport of PEP 654 (exception groups)"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.1.2-py3-none-any.whl", hash = "sha256:e346e69d186172ca7cf029c8c1d16235aa0e04035e5750b4b95039e65204328f"},
-    {file = "exceptiongroup-1.1.2.tar.gz", hash = "sha256:12c3e887d6485d16943a309616de20ae5582633e0a2eda17f4e10fd61c1e8af5"},
+    {file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
+    {file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
 ]
 
 [package.extras]
@@ -259,23 +270,26 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "filelock"
-version = "3.12.2"
+version = "3.12.4"
 description = "A platform independent file lock."
+category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "filelock-3.12.2-py3-none-any.whl", hash = "sha256:cbb791cdea2a72f23da6ac5b5269ab0a0d161e9ef0100e653b69049a7706d1ec"},
-    {file = "filelock-3.12.2.tar.gz", hash = "sha256:002740518d8aa59a26b0c76e10fb8c6e15eae825d34b6fdf670333fd7b938d81"},
+    {file = "filelock-3.12.4-py3-none-any.whl", hash = "sha256:08c21d87ded6e2b9da6728c3dff51baf1dcecf973b768ef35bcbc3447edb9ad4"},
+    {file = "filelock-3.12.4.tar.gz", hash = "sha256:2e6f249f1f3654291606e046b09f1fd5eac39b360664c27f5aad072012f8bcbd"},
 ]
 
 [package.extras]
-docs = ["furo (>=2023.5.20)", "sphinx (>=7.0.1)", "sphinx-autodoc-typehints (>=1.23,!=1.23.4)"]
-testing = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "diff-cover (>=7.5)", "pytest (>=7.3.1)", "pytest-cov (>=4.1)", "pytest-mock (>=3.10)", "pytest-timeout (>=2.1)"]
+docs = ["furo (>=2023.7.26)", "sphinx (>=7.1.2)", "sphinx-autodoc-typehints (>=1.24)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3)", "diff-cover (>=7.7)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)", "pytest-timeout (>=2.1)"]
+typing = ["typing-extensions (>=4.7.1)"]
 
 [[package]]
 name = "google-api-core"
 version = "2.11.1"
 description = "Google API client core library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -298,20 +312,20 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.22.0"
+version = "2.23.0"
 description = "Google Authentication Library"
+category = "main"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.22.0.tar.gz", hash = "sha256:164cba9af4e6e4e40c3a4f90a1a6c12ee56f14c0b4868d1ca91b32826ab334ce"},
-    {file = "google_auth-2.22.0-py2.py3-none-any.whl", hash = "sha256:d61d1b40897407b574da67da1a833bdc10d5a11642566e506565d1b1a46ba873"},
+    {file = "google-auth-2.23.0.tar.gz", hash = "sha256:753a26312e6f1eaeec20bc6f2644a10926697da93446e1f8e24d6d32d45a922a"},
+    {file = "google_auth-2.23.0-py2.py3-none-any.whl", hash = "sha256:2cec41407bd1e207f5b802638e32bb837df968bb5c05f413d0fa526fac4cf7a7"},
 ]
 
 [package.dependencies]
 cachetools = ">=2.0.0,<6.0"
 pyasn1-modules = ">=0.2.1"
 rsa = ">=3.1.4,<5"
-six = ">=1.9.0"
 urllib3 = "<2.0"
 
 [package.extras]
@@ -325,6 +339,7 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 name = "google-cloud-aiplatform"
 version = "1.30.1"
 description = "Vertex AI API client library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -333,7 +348,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.32.0,<2.0.dev0 || >=2.8.dev0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.32.0,<2.0.0 || >=2.8.0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-bigquery = ">=1.15.0,<4.0.0dev"
 google-cloud-resource-manager = ">=1.3.3,<3.0.0dev"
 google-cloud-storage = ">=1.32.0,<3.0.0dev"
@@ -362,6 +377,7 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 name = "google-cloud-bigquery"
 version = "3.11.4"
 description = "Google BigQuery API client library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -370,7 +386,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-core = ">=1.6.0,<3.0.0dev"
 google-resumable-media = ">=0.6.0,<3.0dev"
 grpcio = ">=1.47.0,<2.0dev"
@@ -394,6 +410,7 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 name = "google-cloud-core"
 version = "2.3.3"
 description = "Google Cloud API client core library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -402,7 +419,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.6,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
@@ -410,16 +427,17 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "2.1.1"
+version = "2.3.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
+category = "main"
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "google_cloud_pipeline_components-2.1.1-py3-none-any.whl", hash = "sha256:fdb1621a1db112833a299bfe6353edd2eb7b9195e0d39896491c75e0b6624dcc"},
+    {file = "google_cloud_pipeline_components-2.3.0-py3-none-any.whl", hash = "sha256:bfb6f04598f431577bdf40d3a937646eed16f703d95010379db138d4624be69c"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
 google-cloud-aiplatform = ">=1.14.0,<2"
 kfp = ">=2.0.0b10,<3.0.0"
 
@@ -429,37 +447,39 @@ tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
-version = "1.10.3"
+version = "1.10.4"
 description = "Google Cloud Resource Manager API client library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-resource-manager-1.10.3.tar.gz", hash = "sha256:f80efcea36f10c5a81889afe93910926e3978b4b1ceeb82f563a2fc863072d14"},
-    {file = "google_cloud_resource_manager-1.10.3-py2.py3-none-any.whl", hash = "sha256:1381a4b0f522248ebe0ebd1289d8822b99c54f4e1fe03924a6e723b2ed93dd7f"},
+    {file = "google-cloud-resource-manager-1.10.4.tar.gz", hash = "sha256:456b25ddda3d4cd27488a72736bbc3af04d713ae2fe3655c01b66a339d28d679"},
+    {file = "google_cloud_resource_manager-1.10.4-py2.py3-none-any.whl", hash = "sha256:2ba56ba8e5280cd425bd63620da48b78da2cd299ece58a71f0f2ce3a32d56f99"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]}
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
 proto-plus = ">=1.22.0,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.10.0"
+version = "2.11.0"
 description = "Google Cloud Storage API client library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-storage-2.10.0.tar.gz", hash = "sha256:934b31ead5f3994e5360f9ff5750982c5b6b11604dc072bc452c25965e076dc7"},
-    {file = "google_cloud_storage-2.10.0-py2.py3-none-any.whl", hash = "sha256:9433cf28801671de1c80434238fb1e7e4a1ba3087470e90f70c928ea77c2b9d7"},
+    {file = "google-cloud-storage-2.11.0.tar.gz", hash = "sha256:6fbf62659b83c8f3a0a743af0d661d2046c97c3a5bfb587c4662c4bc68de3e31"},
+    {file = "google_cloud_storage-2.11.0-py2.py3-none-any.whl", hash = "sha256:88cbd7fb3d701c780c4272bc26952db99f25eb283fb4c2208423249f00b5fe53"},
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 google-cloud-core = ">=2.3.0,<3.0dev"
-google-resumable-media = ">=2.3.2"
+google-resumable-media = ">=2.6.0"
 requests = ">=2.18.0,<3.0.0dev"
 
 [package.extras]
@@ -469,6 +489,7 @@ protobuf = ["protobuf (<5.0.0dev)"]
 name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -547,26 +568,28 @@ testing = ["pytest"]
 
 [[package]]
 name = "google-resumable-media"
-version = "2.5.0"
+version = "2.6.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
+category = "main"
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "google-resumable-media-2.5.0.tar.gz", hash = "sha256:218931e8e2b2a73a58eb354a288e03a0fd5fb1c4583261ac6e4c078666468c93"},
-    {file = "google_resumable_media-2.5.0-py2.py3-none-any.whl", hash = "sha256:da1bd943e2e114a56d85d6848497ebf9be6a14d3db23e9fc57581e7c3e8170ec"},
+    {file = "google-resumable-media-2.6.0.tar.gz", hash = "sha256:972852f6c65f933e15a4a210c2b96930763b47197cdf4aa5f5bea435efb626e7"},
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 [package.dependencies]
 google-crc32c = ">=1.0,<2.0dev"
 
 [package.extras]
-aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)"]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "google-auth (>=1.22.0,<2.0dev)"]
 requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
 version = "1.60.0"
 description = "Common protobufs used in Google APIs"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -585,6 +608,7 @@ grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 name = "grpc-google-iam-v1"
 version = "0.12.6"
 description = "IAM API client library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -599,65 +623,67 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 
 [[package]]
 name = "grpcio"
-version = "1.57.0"
+version = "1.58.0"
 description = "HTTP/2-based RPC framework"
+category = "main"
 optional = false
 python-versions = ">=3.7"
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+    {file = "grpcio-1.58.0.tar.gz", hash = "sha256:532410c51ccd851b706d1fbc00a87be0f5312bd6f8e5dbf89d4e99c7f79d7499"},
 ]
 
 [package.extras]
-protobuf = ["grpcio-tools (>=1.57.0)"]
+protobuf = ["grpcio-tools (>=1.58.0)"]
 
 [[package]]
 name = "grpcio-status"
 version = "1.48.2"
 description = "Status proto mapping for gRPC"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -672,13 +698,14 @@ protobuf = ">=3.12.0"
 
 [[package]]
 name = "identify"
-version = "2.5.26"
+version = "2.5.29"
 description = "File identification library for Python"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "identify-2.5.26-py2.py3-none-any.whl", hash = "sha256:c22a8ead0d4ca11f1edd6c9418c3220669b3b7533ada0a0ffa6cc0ef85cf9b54"},
-    {file = "identify-2.5.26.tar.gz", hash = "sha256:7243800bce2f58404ed41b7c002e53d4d22bcf3ae1b7900c2d7aefd95394bf7f"},
+    {file = "identify-2.5.29-py2.py3-none-any.whl", hash = "sha256:24437fbf6f4d3fe6efd0eb9d67e24dd9106db99af5ceb27996a5f7895f24bf1b"},
+    {file = "identify-2.5.29.tar.gz", hash = "sha256:d43d52b86b15918c137e3a74fff5224f60385cd0e9c38e99d07c257f02f151a5"},
 ]
 
 [package.extras]
@@ -688,6 +715,7 @@ license = ["ukkonen"]
 name = "idna"
 version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
+category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -699,6 +727,7 @@ files = [
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -710,6 +739,7 @@ files = [
 name = "jinja2"
 version = "3.1.2"
 description = "A very fast and expressive template engine."
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -725,18 +755,19 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "kfp"
-version = "2.0.1"
+version = "2.2.0"
 description = "Kubeflow Pipelines SDK"
+category = "main"
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "kfp-2.0.1.tar.gz", hash = "sha256:4a65811778c3a45892d8d11c0f95ba5e410476157ed63cacb1dd82316f60cd4d"},
+    {file = "kfp-2.2.0.tar.gz", hash = "sha256:f4b243e11cc7e6a34dcb3af348b2784ba02f6fa2707b000d215d108bed338518"},
 ]
 
 [package.dependencies]
 click = ">=8.0.0,<9"
 docstring-parser = ">=0.7.3,<1"
-google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.6.1,<3"
 google-cloud-storage = ">=2.2.1,<3"
 kfp-pipeline-spec = "0.2.2"
@@ -756,6 +787,7 @@ kubernetes = ["kfp-kubernetes (<2)"]
 name = "kfp-pipeline-spec"
 version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
+category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -767,12 +799,13 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "2.0.0"
+version = "2.0.1"
 description = "Kubeflow Pipelines API"
+category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "kfp-server-api-2.0.0.tar.gz", hash = "sha256:c0462045244a69211bc82a8d6af6602ae8b4f716ee0ac0be5dc34b7ea76c7bd1"},
+    {file = "kfp-server-api-2.0.1.tar.gz", hash = "sha256:4851f414d8f56e0ddd4383ba6de9992debddd2df95e1ecd63b01954c25131abb"},
 ]
 
 [package.dependencies]
@@ -785,6 +818,7 @@ urllib3 = ">=1.15"
 name = "kubernetes"
 version = "26.1.0"
 description = "Kubernetes python client"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -802,7 +836,7 @@ requests-oauthlib = "*"
 setuptools = ">=21.0.0"
 six = ">=1.9.0"
 urllib3 = ">=1.24.2"
-websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
+websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.0 || >=0.43.0"
 
 [package.extras]
 adal = ["adal (>=1.0.2)"]
@@ -811,6 +845,7 @@ adal = ["adal (>=1.0.2)"]
 name = "markupsafe"
 version = "2.1.3"
 description = "Safely add untrusted strings to HTML/XML markup."
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -870,6 +905,7 @@ files = [
 name = "nodeenv"
 version = "1.8.0"
 description = "Node.js virtual environment builder"
+category = "dev"
 optional = false
 python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
 files = [
@@ -884,6 +920,7 @@ setuptools = "*"
 name = "oauthlib"
 version = "3.2.2"
 description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -900,6 +937,7 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 name = "packaging"
 version = "23.1"
 description = "Core utilities for Python packages"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -911,6 +949,7 @@ files = [
 name = "platformdirs"
 version = "3.10.0"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -924,13 +963,14 @@ test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-co
 
 [[package]]
 name = "pluggy"
-version = "1.2.0"
+version = "1.3.0"
 description = "plugin and hook calling mechanisms for python"
+category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "pluggy-1.2.0-py3-none-any.whl", hash = "sha256:c2fd55a7d7a3863cba1a013e4e2414658b1d07b6bc57b3919e0c63c9abb99849"},
-    {file = "pluggy-1.2.0.tar.gz", hash = "sha256:d12f0c4b579b15f5e054301bb226ee85eeeba08ffec228092f8defbaa3a4c4b3"},
+    {file = "pluggy-1.3.0-py3-none-any.whl", hash = "sha256:d89c696a773f8bd377d18e5ecda92b7a3793cbe66c87060a6fb58c7b6e1061f7"},
+    {file = "pluggy-1.3.0.tar.gz", hash = "sha256:cf61ae8f126ac6f7c451172cf30e3e43d3ca77615509771b3a984a0730651e12"},
 ]
 
 [package.extras]
@@ -941,6 +981,7 @@ testing = ["pytest", "pytest-benchmark"]
 name = "pre-commit"
 version = "2.21.0"
 description = "A framework for managing and maintaining multi-language pre-commit hooks."
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -959,6 +1000,7 @@ virtualenv = ">=20.10.0"
 name = "proto-plus"
 version = "1.22.3"
 description = "Beautiful, Pythonic protocol buffers."
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -976,6 +1018,7 @@ testing = ["google-api-core[grpc] (>=1.31.5)"]
 name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1007,6 +1050,7 @@ files = [
 name = "pyasn1"
 version = "0.5.0"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -1018,6 +1062,7 @@ files = [
 name = "pyasn1-modules"
 version = "0.3.0"
 description = "A collection of ASN.1-based protocols modules"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -1030,13 +1075,14 @@ pyasn1 = ">=0.4.6,<0.6.0"
 
 [[package]]
 name = "pytest"
-version = "7.4.0"
+version = "7.4.2"
 description = "pytest: simple powerful testing with Python"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "pytest-7.4.0-py3-none-any.whl", hash = "sha256:78bf16451a2eb8c7a2ea98e32dc119fd2aa758f1d5d66dbf0a59d69a3969df32"},
-    {file = "pytest-7.4.0.tar.gz", hash = "sha256:b4bf8c45bd59934ed84001ad51e11b4ee40d40a1229d2c79f9c592b0a3f6bd8a"},
+    {file = "pytest-7.4.2-py3-none-any.whl", hash = "sha256:1d881c6124e08ff0a1bb75ba3ec0bfd8b5354a01c194ddd5a0a870a48d99b002"},
+    {file = "pytest-7.4.2.tar.gz", hash = "sha256:a766259cfab564a2ad52cb1aae1b881a75c3eb7e34ca3779697c23ed47c47069"},
 ]
 
 [package.dependencies]
@@ -1054,6 +1100,7 @@ testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "no
 name = "python-dateutil"
 version = "2.8.2"
 description = "Extensions to the standard Python datetime module"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
@@ -1068,6 +1115,7 @@ six = ">=1.5"
 name = "pyyaml"
 version = "6.0.1"
 description = "YAML parser and emitter for Python"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1117,6 +1165,7 @@ files = [
 name = "requests"
 version = "2.31.0"
 description = "Python HTTP for Humans."
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1138,6 +1187,7 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 name = "requests-oauthlib"
 version = "1.3.1"
 description = "OAuthlib authentication support for Requests."
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -1156,6 +1206,7 @@ rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 name = "requests-toolbelt"
 version = "0.10.1"
 description = "A utility belt for advanced users of python-requests"
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -1170,6 +1221,7 @@ requests = ">=2.0.1,<3.0.0"
 name = "rsa"
 version = "4.9"
 description = "Pure-Python RSA implementation"
+category = "main"
 optional = false
 python-versions = ">=3.6,<4"
 files = [
@@ -1182,24 +1234,26 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "setuptools"
-version = "68.0.0"
+version = "68.2.2"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
+category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "setuptools-68.0.0-py3-none-any.whl", hash = "sha256:11e52c67415a381d10d6b462ced9cfb97066179f0e871399e006c4ab101fc85f"},
-    {file = "setuptools-68.0.0.tar.gz", hash = "sha256:baf1fdb41c6da4cd2eae722e135500da913332ab3f2f5c7d33af9b492acb5235"},
+    {file = "setuptools-68.2.2-py3-none-any.whl", hash = "sha256:b454a35605876da60632df1a60f736524eb73cc47bbc9f3f1ef1b644de74fd2a"},
+    {file = "setuptools-68.2.2.tar.gz", hash = "sha256:4ac1475276d2f1c48684874089fefcd83bd7162ddaafb81fac866ba0db282a87"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (==0.8.3)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
-testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.1)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
 name = "shapely"
 version = "1.8.5.post1"
 description = "Geometric objects, predicates, and operations"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1256,6 +1310,7 @@ vectorized = ["numpy"]
 name = "six"
 version = "1.16.0"
 description = "Python 2 and 3 compatibility utilities"
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
@@ -1267,6 +1322,7 @@ files = [
 name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1281,6 +1337,7 @@ widechars = ["wcwidth"]
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1292,6 +1349,7 @@ files = [
 name = "urllib3"
 version = "1.26.16"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
+category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
@@ -1308,6 +1366,7 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 name = "vertex-components"
 version = "0.1.0"
 description = "KubeFlow components for Vertex AI"
+category = "main"
 optional = false
 python-versions = ">=3.9,<3.11"
 files = []
@@ -1322,13 +1381,14 @@ url = "../components/vertex-components"
 
 [[package]]
 name = "virtualenv"
-version = "20.24.3"
+version = "20.24.5"
 description = "Virtual Python Environment builder"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.24.3-py3-none-any.whl", hash = "sha256:95a6e9398b4967fbcb5fef2acec5efaf9aa4972049d9ae41f95e0972a683fd02"},
-    {file = "virtualenv-20.24.3.tar.gz", hash = "sha256:e5c3b4ce817b0b328af041506a2a299418c98747c4b1e68cb7527e74ced23efc"},
+    {file = "virtualenv-20.24.5-py3-none-any.whl", hash = "sha256:b80039f280f4919c77b30f1c23294ae357c4c8701042086e3fc005963e4e537b"},
+    {file = "virtualenv-20.24.5.tar.gz", hash = "sha256:e8361967f6da6fbdf1426483bfe9fca8287c242ac0bc30429905721cefbff752"},
 ]
 
 [package.dependencies]
@@ -1337,26 +1397,27 @@ filelock = ">=3.12.2,<4"
 platformdirs = ">=3.9.1,<4"
 
 [package.extras]
-docs = ["furo (>=2023.5.20)", "proselint (>=0.13)", "sphinx (>=7.0.1)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [[package]]
 name = "websocket-client"
-version = "1.6.1"
+version = "1.6.3"
 description = "WebSocket client for Python with low level API options"
+category = "main"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "websocket-client-1.6.1.tar.gz", hash = "sha256:c951af98631d24f8df89ab1019fc365f2227c0892f12fd150e935607c79dd0dd"},
-    {file = "websocket_client-1.6.1-py3-none-any.whl", hash = "sha256:f1f9f2ad5291f0225a49efad77abf9e700b6fef553900623060dad6e26503b9d"},
+    {file = "websocket-client-1.6.3.tar.gz", hash = "sha256:3aad25d31284266bcfcfd1fd8a743f63282305a364b8d0948a43bd606acc652f"},
+    {file = "websocket_client-1.6.3-py3-none-any.whl", hash = "sha256:6cfc30d051ebabb73a5fa246efdcc14c8fbebbd0330f8984ac3bb6d9edd2ad03"},
 ]
 
 [package.extras]
-docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"]
+docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "6bb3645ba47001dbf63d97b06f3ab9086d3f444ac3876524dbb0a5f567eebe65"
+content-hash = "e541cdee407ec35712bbca0feaf973239fd9ccc0344cc783329cda5103c83bd8"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 6e533bb2..0daabf3b 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -21,6 +21,7 @@ google-cloud-pipeline-components = "^2.1.0"
 bigquery-components = { path = "../components/bigquery-components", develop = true }
 vertex-components = { path = "../components/vertex-components", develop = true }
 kfp = "^2.0.1"
+pyyaml = "6.0.1"
 
 [tool.poetry.group.dev.dependencies]
 pytest = ">=7.3.1,<8.0.0"

From cb9950208fe38fbdd4ee70ba3af43a8c49b62403 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 21 Sep 2023 10:02:35 +0100
Subject: [PATCH 204/238] feat: makefile

---
 Makefile | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Makefile b/Makefile
index 0abfcde0..b9b71897 100644
--- a/Makefile
+++ b/Makefile
@@ -66,7 +66,7 @@ build: ## Build and push training and/or serving container(s) image using Docker
 		--region=${VERTEX_LOCATION} \
 		--project=${VERTEX_PROJECT_ID} \
 		--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source \
-		--substitutions=_DOCKER_TARGET=${target},_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/${target}:${RESOURCE_SUFFIX} ; \
+		--substitutions=_DOCKER_TARGET=$$target,_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/$$target:${RESOURCE_SUFFIX} ; \
 	done 
 
 

From a73ce26673a34c816aded7f9fa68b0117cdac267 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Mon, 25 Sep 2023 09:49:29 +0100
Subject: [PATCH 205/238] feat: split into colab, workbench, local

---
 examples/pipelines.ipynb           |  226 ++----
 examples/pipelines_colab.ipynb     | 1128 ++++++++++++++++++++++++++++
 examples/pipelines_workbench.ipynb | 1093 +++++++++++++++++++++++++++
 3 files changed, 2269 insertions(+), 178 deletions(-)
 create mode 100644 examples/pipelines_colab.ipynb
 create mode 100644 examples/pipelines_workbench.ipynb

diff --git a/examples/pipelines.ipynb b/examples/pipelines.ipynb
index 74a6457d..8a03b4a3 100644
--- a/examples/pipelines.ipynb
+++ b/examples/pipelines.ipynb
@@ -31,23 +31,22 @@
    "source": [
     "# Running Vertex Pipelines using E2E Samples repository.\n",
     "\n",
-    "{TODO: Update the links below.} \n",
     "\n",
     "<table align=\"left\">\n",
     "\n",
     "  <td>\n",
-    "    <a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb\">\n",
+    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_colab.ipynb\">\n",
     "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a href=\"https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/notebook_template.ipynb\">\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines.ipynb\">\n",
     "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
     "      View on GitHub\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/GoogleCloudPlatform/vertex-ai-samples/main/notebooks/notebook_template.ipynb\">\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_workbench.ipynb\">\n",
     "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
     "      Open in Vertex AI Workbench\n",
     "    </a>\n",
@@ -157,7 +156,8 @@
     "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
     "- Make\n",
     "- [Poetry](https://python-poetry.org)\n",
-    "- [Terraform](https://www.terraform.io) (To install Terraform on your local machine we recommend using [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version.)"
+    "- [Terraform](https://www.terraform.io) (To install Terraform on your local machine we recommend using [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version.)\n",
+    "- [pyenv](https://github.com/pyenv/pyenv)"
    ]
   },
   {
@@ -239,133 +239,25 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Check if terraform is installed."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [],
    "source": [
-    "! terraform -version"
+    "**If you do not have terraform installed please follow the instructions below.**"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**If you do not have terraform installed please follow the instructions below.** Depending on your Jupyter environment, you may have to follow different installation methods."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**1. Local JupyterLab instance**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Please follow installation instructions: https://developer.hashicorp.com/terraform/tutorials/aws-get-started/install-cli"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**2. Vertex AI Workbench, uncomment and run**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# %%bash\n",
-    "# curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
-    "# unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
-    "# mkdir $HOME/bin\n",
-    "# mv terraform $HOME/bin > /dev/null"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# import os\n",
-    "# os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], 'bin')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
    "source": [
-    "# ! terraform -version"
+    "**Local JupyterLab instance**"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**3. Colab, uncomment and run:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# %%bash\n",
-    "# curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
-    "# unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
-    "# mv terraform /usr/local/bin > /dev/null\n",
-    "# terraform -version"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "58707a750154"
-   },
-   "source": [
-    "### Colab only: Uncomment the following cell to restart the kernel."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "f200f10a1da3",
-    "tags": []
-   },
-   "outputs": [],
    "source": [
-    "# Automatically restart kernel after installs so that your environment can access the new packages\n",
-    "# import IPython\n",
-    "\n",
-    "# app = IPython.Application.instance()\n",
-    "# app.kernel.do_shutdown(True)"
+    "Please follow official documentation for installation instructions: https://developer.hashicorp.com/terraform/downloads"
    ]
   },
   {
@@ -418,7 +310,7 @@
    },
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
+    "PROJECT_ID = \"my-project-id\"  # @param {type:\"string\"}\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]
@@ -433,45 +325,6 @@
     "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**1. Vertex AI Workbench**\n",
-    "* Do nothing as you are already authenticated."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**2. Local JupyterLab instance, uncomment and run:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    " # ! gcloud auth login"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**3. Colab, uncomment and run:**"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -480,8 +333,7 @@
    },
    "outputs": [],
    "source": [
-    "# from google.colab import auth\n",
-    "# auth.authenticate_user()"
+    " ! gcloud auth login"
    ]
   },
   {
@@ -495,7 +347,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)."
+    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID` and `VERTEX_LOCATION`)."
    ]
   },
   {
@@ -508,9 +360,7 @@
    "source": [
     "%%writefile .env\n",
     "\n",
-    "VERTEX_CMEK_IDENTIFIER= # optional\n",
     "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_NETWORK= # optional\n",
     "VERTEX_PROJECT_ID=my-project-id\n",
     "\n",
     "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
@@ -519,7 +369,11 @@
     "# Leave as-is\n",
     "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
     "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
-    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images"
+    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
+    "\n",
+    "# Optional\n",
+    "VERTEX_CMEK_IDENTIFIER=\n",
+    "VERTEX_NETWORK="
    ]
   },
   {
@@ -581,7 +435,7 @@
    "source": [
     "#### Create tfstate bucket\n",
     "\n",
-    "Before provisioning our infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
+    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
    ]
   },
   {
@@ -750,6 +604,7 @@
    },
    "outputs": [],
    "source": [
+    "import os\n",
     "from google.cloud import bigquery_datatransfer\n",
     "\n",
     "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
@@ -845,7 +700,7 @@
     "tags": []
    },
    "source": [
-    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it through the Google Cloud Console UI under Vertex AI/Pipelines."
+    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it directly through the Google Cloud Console UI by navigating to Vertex AI and then selecting Pipelines."
    ]
   },
   {
@@ -902,24 +757,23 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "sx_vKniMq9ZX",
-    "tags": []
-   },
-   "outputs": [],
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
-    "! make undeploy auto-approve=true"
+    "**Empty the buckets to enable their deletion:**"
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
+   "outputs": [],
    "source": [
-    "{TODO}🔴🔴🔴  Cant delete staging and root buckets because contains objects and `force_destroy` is not set to true in our terraform configurations"
+    "%%bash\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
    ]
   },
   {
@@ -928,7 +782,7 @@
     "tags": []
    },
    "source": [
-    "1. Delete data transfer config. \n",
+    "**Delete data transfer config:**\n",
     "\n",
     "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
    ]
@@ -961,7 +815,7 @@
     "tags": []
    },
    "source": [
-    "2. Delete BigQuery dataset for the Chicago Taxi data:"
+    "**Delete BigQuery dataset for the Chicago Taxi data:**"
    ]
   },
   {
@@ -981,7 +835,7 @@
     "tags": []
    },
    "source": [
-    "3. Delete BigQuery dataset for data processing during the pipelines:"
+    "**Delete BigQuery dataset for data processing during the pipelines:**"
    ]
   },
   {
@@ -1001,7 +855,7 @@
     "tags": []
    },
    "source": [
-    "Delete local files"
+    "**Delete local files:**"
    ]
   },
   {
@@ -1016,6 +870,22 @@
     "cd ..\n",
     "rm -r vertex-pipelines-end-to-end-samples"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make undeploy auto-approve=true"
+   ]
   }
  ],
  "metadata": {
diff --git a/examples/pipelines_colab.ipynb b/examples/pipelines_colab.ipynb
new file mode 100644
index 00000000..9c98b19a
--- /dev/null
+++ b/examples/pipelines_colab.ipynb
@@ -0,0 +1,1128 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Running Vertex Pipelines using E2E Samples repository.\n",
+    "\n",
+    "\n",
+    "<table align=\"left\">\n",
+    "\n",
+    "  <td>\n",
+    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_colab.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
+    "    </a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
+    "      View on GitHub\n",
+    "    </a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_workbench.ipynb\">\n",
+    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
+    "      Open in Vertex AI Workbench\n",
+    "    </a>\n",
+    "  </td>                                                                                               \n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "24743cf4a1e1"
+   },
+   "source": [
+    "**_NOTE_**: This notebook has been tested in the following environment:\n",
+    "\n",
+    "* Python version = 3.9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tvgnzT1CKxrO",
+    "tags": []
+   },
+   "source": [
+    "## Overview\n",
+    "\n",
+    "This notebook shows you how to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
+    "\n",
+    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d975e698c9a4"
+   },
+   "source": [
+    "### Objective\n",
+    "\n",
+    "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
+    "\n",
+    "This tutorial uses the following Google Cloud services and resources:\n",
+    "\n",
+    "- *`Vertex Pipelines`*\n",
+    "- *`Google Cloud Storage`*\n",
+    "- *`Artifact Registry`*\n",
+    "- *`BigQuery`*\n",
+    "- *`Cloud Build`*\n",
+    "\n",
+    "The steps performed include:\n",
+    "\n",
+    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services.\n",
+    "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "08d289fa873f"
+   },
+   "source": [
+    "### Dataset\n",
+    "\n",
+    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
+    "\n",
+    "\n",
+    "This public dataset is hosted in Google BigQuery."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "aed92deeb4a0"
+   },
+   "source": [
+    "### Costs\n",
+    "\n",
+    "\n",
+    "This tutorial uses billable components of Google Cloud:\n",
+    "\n",
+    "* Vertex AI\n",
+    "* BigQuery\n",
+    "* Cloud Storage\n",
+    "* Cloud Build\n",
+    "* Artifact Registry\n",
+    "\n",
+    "\n",
+    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
+    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
+    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
+    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
+    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
+    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
+    "to generate a cost estimate based on your projected usage."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "YXI8WcMpuyXI",
+    "tags": []
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Poetry](https://python-poetry.org)\n",
+    "- [Terraform](https://www.terraform.io) (To install Terraform on your local machine we recommend using [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version.)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ujfOJ2gHuyXJ",
+    "tags": []
+   },
+   "source": [
+    "## Clone Turbo Templates repository"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "J5YwqQbDuyXJ",
+    "outputId": "9b703837-a177-4956-8c77-2985dea88601",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Clone a Git repository\n",
+    "!git clone -b feat/tutorial_notebook https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples\n",
+    "# !git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rlBC9B_OuyXJ",
+    "outputId": "00a3fd6f-b06d-461d-8a24-a37d0351e095",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "i7EUnXsZhAGF",
+    "tags": []
+   },
+   "source": [
+    "## Installation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "r1hZ7k5guyXJ"
+   },
+   "source": [
+    "Install the packages required for executing this notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "cellView": "form",
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "_5hdfngMuyXJ",
+    "outputId": "1233d17f-8cd2-4185-9b84-3defadc42669"
+   },
+   "outputs": [],
+   "source": [
+    "# @title Prepare notebook.\n",
+    "# @markdown 1. Configure pyenv\n",
+    "!curl https://pyenv.run | bash\n",
+    "\n",
+    "# Add pyenv to PATH\n",
+    "import os\n",
+    "os.environ[\"PATH\"] += \":/root/.pyenv/bin\"\n",
+    "\n",
+    "# Initialize pyenv\n",
+    "!eval \"$(pyenv init -)\"\n",
+    "!eval \"$(pyenv virtualenv-init -)\"\n",
+    "\n",
+    "! pip install poetry\n",
+    "\n",
+    "# @markdown 2. Install the correct Python version\n",
+    "! pyenv install -skip-existing\n",
+    "\n",
+    "# @markdown 3. Configure poetry\n",
+    "! poetry config virtualenvs.prefer-active-python true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "kKr_J0wY6_Pr"
+   },
+   "source": [
+    "#### Install poetry dependencies for ML pipelines."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "hrev7zxh6GCt",
+    "outputId": "68e48bbd-e646-42f1-d315-2557059807f3"
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "make install"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "JuYvvx8yuyXK",
+    "outputId": "12f0622d-0362-4cd9-e333-0df6f7cc01a1"
+   },
+   "outputs": [],
+   "source": [
+    "# @title Installing Terraform by downloading a pre-compiled binary.\n",
+    "# @markdown This cell will:\n",
+    "# @markdown 1. **Download** the appropriate package for your system as a zip archive from the Terraform website.\n",
+    "# @markdown 2. **Unzip** the downloaded package.\n",
+    "# @markdown 3. **Ensure Terraform is on your PATH**.\n",
+    "\n",
+    "%%bash\n",
+    "mkdir temp\n",
+    "cd temp\n",
+    "curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
+    "unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
+    "mv terraform /usr/local/bin > /dev/null\n",
+    "cd ..\n",
+    "rm -r temp\n",
+    "terraform"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "58707a750154"
+   },
+   "source": [
+    "### Colab only: execute the following cell to restart the kernel."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "f200f10a1da3",
+    "outputId": "6c870257-e089-41a3-ed89-c70b311eb7b0",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Automatically restart kernel after installs so that your environment can access the new packages\n",
+    "import IPython\n",
+    "\n",
+    "app = IPython.Application.instance()\n",
+    "app.kernel.do_shutdown(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "D31uhP4V9lTc",
+    "outputId": "1ffe618d-962f-4efc-d1b5-dd82c976733b"
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Gj8s3i90uyXK",
+    "tags": []
+   },
+   "source": [
+    "## Before You Begin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "BF1j6f9HApxa",
+    "tags": []
+   },
+   "source": [
+    "### Set up your Google Cloud project\n",
+    "\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
+    "\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+    "\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
+    "\n",
+    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WReHDGG5g0XY"
+   },
+   "source": [
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "oM1iC_MfAts1",
+    "outputId": "8d1edaa5-d9ea-407e-efea-fbdb9691f60f",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "PROJECT_ID = \"my-project-id\"  # @param {type:\"string\"}\n",
+    "# Set the project id\n",
+    "! gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "PRCfV5duuyXK"
+   },
+   "source": [
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "\n",
+    "Follow the relevant instructions below to authenticate."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "XY-Kz5hmuyXL",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import auth\n",
+    "auth.authenticate_user()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "I5nZH6H5uyXL"
+   },
+   "source": [
+    "### Environment Setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Znu_gBnkuyXL"
+   },
+   "source": [
+    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "dfN37cNEuyXL",
+    "outputId": "4e20a0a9-6551-428a-ab2e-ac22b530b5f1",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%writefile .env\n",
+    "\n",
+    "VERTEX_LOCATION=europe-west2\n",
+    "VERTEX_PROJECT_ID=my-project-id\n",
+    "\n",
+    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
+    "RESOURCE_SUFFIX=default\n",
+    "\n",
+    "# Leave as-is\n",
+    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
+    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
+    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
+    "\n",
+    "# Optional\n",
+    "VERTEX_CMEK_IDENTIFIER=\n",
+    "VERTEX_NETWORK="
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "EC2VyhYvuyXL",
+    "outputId": "ac399c93-78e2-4bc8-c789-32b49809a789",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "E1iwILB7uyXN",
+    "outputId": "efef313e-03b5-4b92-b528-3d92084b39b9",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "\n",
+    "load_dotenv()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zgPO1eR3CYjk",
+    "tags": []
+   },
+   "source": [
+    "## Infrastructure deployment using terraform.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "IMbeEpCuuyXN"
+   },
+   "source": [
+    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "Oqu8hNAluyXN",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
+    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "N0W1RMZluyXN"
+   },
+   "source": [
+    "#### Create tfstate bucket\n",
+    "\n",
+    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "-EcIXiGsCePi"
+   },
+   "source": [
+    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "NIq7R4HZCfIc",
+    "outputId": "c9e11df0-587a-4bb6-92ac-254fc1a78085",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "960505627ddf"
+   },
+   "source": [
+    "### Deploy required infrastructure"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "330YqgzfuyXN",
+    "tags": []
+   },
+   "source": [
+    "Deploy command will:\n",
+    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
+    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "-LPegqLYuyXN",
+    "outputId": "ea4a2b99-d729-4f94-a4a0-67ac883246f0",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "make deploy auto-approve=true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ytXz5BkNuyXN",
+    "tags": []
+   },
+   "source": [
+    "## Example ML Pipelines"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "n2BLhXBpuyXN",
+    "tags": []
+   },
+   "source": [
+    "To automate, monitor, and govern your ML workflows, you can use [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops). Vertex AI is a powerful platform offered by Google Cloud that empowers organizations to streamline and enhance their Machine Learning (ML) workflows through automation, monitoring, and governance.\n",
+    "\n",
+    "- **Automation**: Vertex AI offers a suite of tools and services designed to automate various aspects of ML development and deployment. This includes automating data preprocessing, model training, hyperparameter tuning, and model deployment. Automation not only saves time but also reduces the potential for human error, making your ML workflows more efficient and reliable.\n",
+    "\n",
+    "- **Monitoring**: Effective monitoring is crucial for maintaining the performance and reliability of ML models in production. Vertex AI provides monitoring capabilities that allow you to track model performance, detect drift in data distributions, and set up alerts for anomalies. This proactive monitoring ensures that your models continue to deliver accurate results as data and business conditions change over time.\n",
+    "\n",
+    "- **Governance**: Managing ML models and data in a secure and compliant manner is essential for businesses, especially those in regulated industries. Vertex AI helps you implement governance policies to control access to data, monitor model usage, and enforce compliance with data privacy regulations. This ensures that your ML operations are in line with legal and ethical standards.\n",
+    "\n",
+    "- **Scalability**: Vertex AI is built on Google Cloud's infrastructure, which means it offers unparalleled scalability. Whether you're dealing with small-scale experiments or large-scale production deployments, Vertex AI can scale to meet your needs, ensuring that your ML workflows can handle increased workloads without performance bottlenecks.\n",
+    "\n",
+    "- **Collaboration**: Collaboration is essential in ML development, and Vertex AI provides features that facilitate collaboration among data scientists, machine learning engineers, and other stakeholders. You can share notebooks, collaborate on model development, and maintain version control of your ML assets.\n",
+    "\n",
+    "- **Model Serving**: Vertex AI makes it easy to deploy ML models as APIs for real-time inference or batch processing. This enables you to integrate your ML models into applications, websites, or other services with ease.\n",
+    "\n",
+    "- **Cost Management**: Cost control is a crucial aspect of any ML project. Vertex AI offers cost management tools and insights to help you optimize your ML workflows and keep your expenses in check.\n",
+    "\n",
+    "By utilizing Vertex AI, you can take advantage of Google Cloud's cutting-edge technology and expertise in machine learning to accelerate your MLOps journey. The platform offers a comprehensive set of tools and services that cover the entire ML lifecycle, from data preparation to model deployment and beyond, making it a valuable resource for organizations looking to harness the power of ML in a scalable, efficient, and secure manner.\n",
+    "\n",
+    "To learn more about MLOps on Vertex AI and how it can transform your ML workflows, you can visit the [official documentation](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops).\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Fw_DSPaouyXN",
+    "tags": []
+   },
+   "source": [
+    "**This repository provides an example ML training and prediction pipelines for XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips).**\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "iX4_OKX5uyXN"
+   },
+   "source": [
+    "#### Pre-requisites\n",
+    "\n",
+    "Before you can successfully execute the example pipelines, there are a few additional components you need to deploy. These components have not been included in the Terraform code as they are specific to these pipelines."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "m66vkt7PuyXN"
+   },
+   "source": [
+    "1. Create a new BigQuery dataset for the Chicago Taxi data:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "xBgpwdluuyXN",
+    "outputId": "64044c15-bb91-4b27-973d-1914face2964",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "AQ88x_8xuyXO"
+   },
+   "source": [
+    "2. Create a new BigQuery dataset for data processing during the pipelines:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "sPWQoXP5uyXO",
+    "outputId": "e968f292-6026-43a3-a9a4-637ffa8e5043",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "XTCqhzKOuyXO"
+   },
+   "source": [
+    "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 516
+    },
+    "id": "mr9wTo8-uyXO",
+    "outputId": "1f1aeb1d-869f-41db-8701-b45c1aca81a4"
+   },
+   "outputs": [],
+   "source": [
+    "! pip install google-cloud-bigquery-datatransfer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 877
+    },
+    "id": "EqI6dBIGuyXO",
+    "outputId": "36281530-93bd-43da-cc1f-e72377651eaa",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "destination_project_id = os.environ[\"VERTEX_PROJECT_ID\"]\n",
+    "destination_dataset_id = \"chicago_taxi_trips\"\n",
+    "source_project_id = \"bigquery-public-data\"\n",
+    "source_dataset_id = \"chicago_taxi_trips\"\n",
+    "transfer_config = bigquery_datatransfer.TransferConfig(\n",
+    "    destination_dataset_id=destination_dataset_id,\n",
+    "    display_name=\"Chicago taxi trip mirror\",\n",
+    "    data_source_id=\"cross_region_copy\",\n",
+    "    params={\n",
+    "        \"source_project_id\": source_project_id,\n",
+    "        \"source_dataset_id\": source_dataset_id,\n",
+    "    },\n",
+    "    schedule=\"every 24 hours\",\n",
+    ")\n",
+    "transfer_config = transfer_client.create_transfer_config(\n",
+    "    parent=transfer_client.common_project_path(destination_project_id),\n",
+    "    transfer_config=transfer_config,\n",
+    ")\n",
+    "TRANSFER_CONFIG=transfer_config.name\n",
+    "print(f\"Created transfer config: {TRANSFER_CONFIG}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "xRtAwjcHuyXO"
+   },
+   "source": [
+    "### Building the container images\n",
+    "\n",
+    "The `model` directory contains the code for custom training and serving container images `model/training/train.py`.\n",
+    "\n",
+    "A custom container is a Docker image that you create to run your training application. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Vertex AI. To learn more you can check out [official documentation](https://cloud.google.com/vertex-ai/docs/training/containers-overview)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "hWj89EXmuyXO"
+   },
+   "source": [
+    "To build the training and serving container images and push them to Artifact Registry run the next cell."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "Hu-E6Pn3uyXO",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make build"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "CpJhQCwvuyXO",
+    "tags": []
+   },
+   "source": [
+    "### Running Pipelines\n",
+    "\n",
+    "You can run the training pipeline by executing cell below.\n",
+    "\n",
+    "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
+    "\n",
+    "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
+    "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "rUnltoeDuyXO"
+   },
+   "source": [
+    "**Run Training Pipeline**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "JwXpPsNPuyXO",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make run pipeline=training build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "8a2Rz8tNuyXO",
+    "tags": []
+   },
+   "source": [
+    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it through the Google Cloud Console UI under Vertex AI/Pipelines."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "f1yzYZQSuyXO",
+    "tags": []
+   },
+   "source": [
+    "**Training Pipeline**\n",
+    "![Training Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/training_pipeline.png?raw=true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "Cb1kLnZtuyXO"
+   },
+   "source": [
+    "**Run Prediction Pipeline**\n",
+    "\n",
+    "After successful training job, you can try prediction pipeline."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "8gM-UTYzuyXO"
+   },
+   "outputs": [],
+   "source": [
+    "! make run pipeline=prediction build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "GYeHlnV4uyXO",
+    "tags": []
+   },
+   "source": [
+    "**Prediction Pipeline**\n",
+    "\n",
+    "![Predictions Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/prediction_pipeline.png?raw=true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "TpV-iwP9qw9c"
+   },
+   "source": [
+    "## Cleaning up\n",
+    "\n",
+    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
+    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+    "\n",
+    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "sTCem_rKuyXO"
+   },
+   "source": [
+    "**Empty the buckets to enable their deletion:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "IW1WVh4_uyXO",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "3uXsfDFZuyXP",
+    "tags": []
+   },
+   "source": [
+    "**Delete data transfer config:**\n",
+    "\n",
+    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "L5jdzMZeuyXP",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import google.api_core.exceptions\n",
+    "from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "transfer_config_name = TRANSFER_CONFIG # Transfer Config Name\n",
+    "try:\n",
+    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
+    "except google.api_core.exceptions.NotFound:\n",
+    "    print(\"Transfer config not found.\")\n",
+    "else:\n",
+    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "69WPFNN-uyXP",
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for the Chicago Taxi data:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "KcQ5cguluyXP",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "gSamp3p9uyXP",
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for data processing during the pipelines:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "FRKSZmozuyXP",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "GhYbRJ0NuyXP",
+    "tags": []
+   },
+   "source": [
+    "**Delete local files:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "Msb_7QyLuyXP",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "cd ..\n",
+    "rm -r vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "RKDx-NvyuyXO",
+    "tags": []
+   },
+   "source": [
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "sx_vKniMq9ZX",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make undeploy auto-approve=true"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/examples/pipelines_workbench.ipynb b/examples/pipelines_workbench.ipynb
new file mode 100644
index 00000000..89462d26
--- /dev/null
+++ b/examples/pipelines_workbench.ipynb
@@ -0,0 +1,1093 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c712dfd9-4cf9-49ca-b7c0-f14cfc78d1bd",
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f082fcb1-255f-4445-a20c-66c6dd495728",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Running Vertex Pipelines using E2E Samples repository.\n",
+    "\n",
+    "\n",
+    "<table align=\"left\">\n",
+    "\n",
+    "  <td>\n",
+    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_colab.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
+    "    </a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
+    "      View on GitHub\n",
+    "    </a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_workbench.ipynb\">\n",
+    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
+    "      Open in Vertex AI Workbench\n",
+    "    </a>\n",
+    "  </td>                                                                                               \n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2f814278-15d7-4ab1-9f1f-2c027e99ad6e",
+   "metadata": {
+    "id": "24743cf4a1e1"
+   },
+   "source": [
+    "**_NOTE_**: This notebook has been tested in the following environment:\n",
+    "\n",
+    "* Python version = 3.9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14d2d0de-b29b-4040-bee7-1452af822fca",
+   "metadata": {
+    "id": "tvgnzT1CKxrO",
+    "tags": []
+   },
+   "source": [
+    "## Overview\n",
+    "\n",
+    "This notebook shows you how to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
+    "\n",
+    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b7f815bd-0cc6-47ae-9f71-5cd1817c6a0d",
+   "metadata": {
+    "id": "d975e698c9a4"
+   },
+   "source": [
+    "### Objective\n",
+    "\n",
+    "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
+    "\n",
+    "This tutorial uses the following Google Cloud services and resources:\n",
+    "\n",
+    "- *`Vertex Pipelines`*\n",
+    "- *`Google Cloud Storage`*\n",
+    "- *`Artifact Registry`*\n",
+    "- *`BigQuery`*\n",
+    "- *`Cloud Build`*\n",
+    "\n",
+    "The steps performed include:\n",
+    "\n",
+    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services.\n",
+    "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f8fd9521-9fcc-4961-86e3-d43f3ae15d5e",
+   "metadata": {
+    "id": "08d289fa873f"
+   },
+   "source": [
+    "### Dataset\n",
+    "\n",
+    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
+    "\n",
+    "\n",
+    "This public dataset is hosted in Google BigQuery."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc0248c2-d658-47bc-8ccb-43f39b73700c",
+   "metadata": {
+    "id": "08d289fa873f"
+   },
+   "source": [
+    "### Dataset\n",
+    "\n",
+    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
+    "\n",
+    "\n",
+    "This public dataset is hosted in Google BigQuery."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc563580-630b-46cd-8297-51f8ab620e8a",
+   "metadata": {
+    "id": "08d289fa873f"
+   },
+   "source": [
+    "### Dataset\n",
+    "\n",
+    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
+    "\n",
+    "\n",
+    "This public dataset is hosted in Google BigQuery."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "53231e62-f463-4eb9-a327-3f5537effe80",
+   "metadata": {
+    "id": "aed92deeb4a0"
+   },
+   "source": [
+    "### Costs \n",
+    "\n",
+    "\n",
+    "This tutorial uses billable components of Google Cloud:\n",
+    "\n",
+    "* Vertex AI\n",
+    "* BigQuery\n",
+    "* Cloud Storage\n",
+    "* Cloud Build\n",
+    "* Artifact Registry\n",
+    "\n",
+    "\n",
+    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
+    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
+    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
+    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
+    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
+    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
+    "to generate a cost estimate based on your projected usage."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a66f9fc1-8435-40ef-984d-af5a18e6656e",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Poetry](https://python-poetry.org)\n",
+    "- [Terraform](https://www.terraform.io) (To install Terraform on your local machine we recommend using [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version.)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0ab044e6-d1ce-448d-af88-31b2462fd792",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Clone Turbo Templates repository"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3176102b-059d-483b-ba67-647e78553947",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Clone a Git repository\n",
+    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "514bb16f-5604-4b49-911a-6eff37f07575",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "80b3b918-02da-414c-9ea8-a335bfe60387",
+   "metadata": {
+    "id": "i7EUnXsZhAGF",
+    "tags": []
+   },
+   "source": [
+    "## Installation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "467b87cf-6956-4d9d-b9d9-85ed2efaa195",
+   "metadata": {},
+   "source": [
+    "Install the packages required for executing this notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7f37419b-7a30-44d6-ab16-8e69d952d944",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Install pyenv\n",
+    "!curl https://pyenv.run | bash"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "382725b5-80bf-4b76-ba58-553c7dd071e7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Add pyenv to PATH\n",
+    "import os\n",
+    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.pyenv/bin')\n",
+    "\n",
+    "# Initialize pyenv\n",
+    "!eval \"$(pyenv init -)\"\n",
+    "!eval \"$(pyenv virtualenv-init -)\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b4441b15-24ed-4b41-a434-9e7651c2a5b9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Install poetry\n",
+    "!curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -\n",
+    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.poetry/bin')\n",
+    "!poetry --version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f371b7e1-fea0-40f5-9a2c-7ceacdfbdc37",
+   "metadata": {
+    "id": "2b4ef9b72d43",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Install the correct Python version\n",
+    "! pyenv install -skip-existing\n",
+    "\n",
+    "# configure poetry \n",
+    "! poetry config virtualenvs.prefer-active-python true\n",
+    "\n",
+    "#Install poetry dependencies for ML pipelines\n",
+    "! make install"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6e4a80e2-3169-4c0e-b4df-df7a9f8ec69e",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Terraform"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4371d2cf-523e-4c2a-891d-67e162da3d7c",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Installing Terraform by downloading a pre-compiled binary.**\n",
+    "1. **Download** the appropriate package for your system as a zip archive from the Terraform website.\n",
+    "2. **Unzip** the downloaded package.\n",
+    "3. **Add Terraform to PATH**."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ea4f3ac-f072-482d-aa3d-25e5ba21e3d9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!rm -r $HOME/.bin"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7de12dad-1907-4867-8b0d-bcdc115e815f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!ls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "61201833-4162-4fa8-a555-b83ce99eef59",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "mkdir temp\n",
+    "cd temp\n",
+    "curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
+    "unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
+    "mkdir $HOME/.bin\n",
+    "mv terraform $HOME/.bin > /dev/null\n",
+    "cd ..\n",
+    "rm -r temp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "80366eba-603c-44f0-9069-496ec4499c39",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.bin')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "184e9279-d446-4b29-95be-29cf57eebba7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! terraform -version"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a1571126-c7d3-477a-846a-9a387e7a1aab",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Before You Begin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a13f3a75-a6d2-4d08-8abf-667a597193cf",
+   "metadata": {
+    "id": "BF1j6f9HApxa",
+    "tags": []
+   },
+   "source": [
+    "### Set up your Google Cloud project\n",
+    "\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
+    "\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+    "\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "318a28b1-d443-4348-a3a3-9ea7be7d4a4a",
+   "metadata": {
+    "id": "WReHDGG5g0XY"
+   },
+   "source": [
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cb0d271e-1105-4925-a451-c8b417cc4920",
+   "metadata": {
+    "id": "oM1iC_MfAts1",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "PROJECT_ID = \"my-project-id\"\n",
+    "# Set the project id\n",
+    "! gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "282aa597-f7e4-4fa9-8bb3-eecf95b57d02",
+   "metadata": {},
+   "source": [
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "\n",
+    "You are running the notebook on Vertex AI workbench, therefore, you are already authenticated."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a023663e-f298-462b-9c2a-390ef32c2502",
+   "metadata": {},
+   "source": [
+    "### Environment Setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3f4b1455-bdf0-4d70-a1de-93ace9cea86b",
+   "metadata": {},
+   "source": [
+    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID` and `VERTEX_LOCATION`)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9bc832f9-3b4d-4e4c-8bb5-11bb29364e23",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%writefile .env\n",
+    "\n",
+    "VERTEX_LOCATION=europe-west2\n",
+    "VERTEX_PROJECT_ID=my-project-id\n",
+    "\n",
+    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
+    "RESOURCE_SUFFIX=default\n",
+    "\n",
+    "# Leave as-is\n",
+    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
+    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
+    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
+    "\n",
+    "# Optional\n",
+    "VERTEX_CMEK_IDENTIFIER=\n",
+    "VERTEX_NETWORK="
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "db667536-b4f9-4249-86f1-07d8ac3d6d4c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "303fb592-dabe-4e20-a915-33af32bd7a80",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "\n",
+    "load_dotenv()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ddda6825-4da6-4d1a-8e2f-29717d9a6f04",
+   "metadata": {
+    "id": "zgPO1eR3CYjk",
+    "tags": []
+   },
+   "source": [
+    "## Infrastructure deployment using terraform.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "41c67e53-b246-45c2-bdae-09d2a8c3ad95",
+   "metadata": {},
+   "source": [
+    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a5870230-222b-45bd-97a4-17eb3af6dac5",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
+    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "78418043-e737-48cb-b030-c934835cceb5",
+   "metadata": {},
+   "source": [
+    "#### Create tfstate bucket\n",
+    "\n",
+    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bb7a3f5c-9789-4f27-870c-bd6f38e587e4",
+   "metadata": {
+    "id": "-EcIXiGsCePi"
+   },
+   "source": [
+    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1133567c-b668-44aa-8c6c-77cbd70065fd",
+   "metadata": {
+    "id": "NIq7R4HZCfIc",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a836f098-a37a-4013-9463-4cec11982bac",
+   "metadata": {
+    "id": "960505627ddf"
+   },
+   "source": [
+    "### Deploy required infrastructure"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2668618-4a57-402e-9861-daf95eb27bba",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Deploy command will:\n",
+    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
+    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8329d73d-ba8f-443e-ab65-379a98c6f254",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make deploy auto-approve=true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "adfebbc4-1a15-4bff-a98d-5840ee3be972",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Example ML Pipelines"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cd23f3b5-1e91-4dc1-acb0-9e9b3e06e259",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "To automate, monitor, and govern your ML workflows, you can use [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops). Vertex AI is a powerful platform offered by Google Cloud that empowers organizations to streamline and enhance their Machine Learning (ML) workflows through automation, monitoring, and governance.\n",
+    "\n",
+    "- **Automation**: Vertex AI offers a suite of tools and services designed to automate various aspects of ML development and deployment. This includes automating data preprocessing, model training, hyperparameter tuning, and model deployment. Automation not only saves time but also reduces the potential for human error, making your ML workflows more efficient and reliable.\n",
+    "\n",
+    "- **Monitoring**: Effective monitoring is crucial for maintaining the performance and reliability of ML models in production. Vertex AI provides monitoring capabilities that allow you to track model performance, detect drift in data distributions, and set up alerts for anomalies. This proactive monitoring ensures that your models continue to deliver accurate results as data and business conditions change over time.\n",
+    "\n",
+    "- **Governance**: Managing ML models and data in a secure and compliant manner is essential for businesses, especially those in regulated industries. Vertex AI helps you implement governance policies to control access to data, monitor model usage, and enforce compliance with data privacy regulations. This ensures that your ML operations are in line with legal and ethical standards.\n",
+    "\n",
+    "- **Scalability**: Vertex AI is built on Google Cloud's infrastructure, which means it offers unparalleled scalability. Whether you're dealing with small-scale experiments or large-scale production deployments, Vertex AI can scale to meet your needs, ensuring that your ML workflows can handle increased workloads without performance bottlenecks.\n",
+    "\n",
+    "- **Collaboration**: Collaboration is essential in ML development, and Vertex AI provides features that facilitate collaboration among data scientists, machine learning engineers, and other stakeholders. You can share notebooks, collaborate on model development, and maintain version control of your ML assets.\n",
+    "\n",
+    "- **Model Serving**: Vertex AI makes it easy to deploy ML models as APIs for real-time inference or batch processing. This enables you to integrate your ML models into applications, websites, or other services with ease.\n",
+    "\n",
+    "- **Cost Management**: Cost control is a crucial aspect of any ML project. Vertex AI offers cost management tools and insights to help you optimize your ML workflows and keep your expenses in check.\n",
+    "\n",
+    "By utilizing Vertex AI, you can take advantage of Google Cloud's cutting-edge technology and expertise in machine learning to accelerate your MLOps journey. The platform offers a comprehensive set of tools and services that cover the entire ML lifecycle, from data preparation to model deployment and beyond, making it a valuable resource for organizations looking to harness the power of ML in a scalable, efficient, and secure manner.\n",
+    "\n",
+    "To learn more about MLOps on Vertex AI and how it can transform your ML workflows, you can visit the [official documentation](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops).\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2ccf23b8-cce4-44bf-8b4e-1140bf7a8d95",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**This repository provides an example ML training and prediction pipelines for XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips).**\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aea16c5d-fada-4920-9ef7-efad814afe26",
+   "metadata": {},
+   "source": [
+    "#### Pre-requisites\n",
+    "\n",
+    "Before you can successfully execute the example pipelines, there are a few additional components you need to deploy. These components have not been included in the Terraform code as they are specific to these pipelines."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "72cdb72e-ecc8-4134-b4d6-e808eddf80a7",
+   "metadata": {},
+   "source": [
+    "1. Create a new BigQuery dataset for the Chicago Taxi data:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2e24884b-e16b-4f5f-bec1-9b7c901130cf",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d0b11e95-a8b4-4c4b-8f90-d040a97253dd",
+   "metadata": {},
+   "source": [
+    "2. Create a new BigQuery dataset for data processing during the pipelines:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6fee2b6d-44dd-4371-9fd5-76a95dd33d74",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "18a8c603-6d36-4d70-b0b4-25b71f9d9b6b",
+   "metadata": {},
+   "source": [
+    "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c0aeced0-25a4-4d65-ba16-695a2c257c19",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install google-cloud-bigquery-datatransfer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "66a2dcba-2ee4-44a4-9709-25c95cff7786",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "destination_project_id = os.environ[\"VERTEX_PROJECT_ID\"]\n",
+    "destination_dataset_id = \"chicago_taxi_trips\"\n",
+    "source_project_id = \"bigquery-public-data\"\n",
+    "source_dataset_id = \"chicago_taxi_trips\"\n",
+    "transfer_config = bigquery_datatransfer.TransferConfig(\n",
+    "    destination_dataset_id=destination_dataset_id,\n",
+    "    display_name=\"Chicago taxi trip mirror\",\n",
+    "    data_source_id=\"cross_region_copy\",\n",
+    "    params={\n",
+    "        \"source_project_id\": source_project_id,\n",
+    "        \"source_dataset_id\": source_dataset_id,\n",
+    "    },\n",
+    "    schedule=\"every 24 hours\",\n",
+    ")\n",
+    "transfer_config = transfer_client.create_transfer_config(\n",
+    "    parent=transfer_client.common_project_path(destination_project_id),\n",
+    "    transfer_config=transfer_config,\n",
+    ")\n",
+    "TRANSFER_CONFIG=transfer_config.name\n",
+    "print(f\"Created transfer config: {TRANSFER_CONFIG}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2c6b6b48-9861-40a3-a999-d73aeac674be",
+   "metadata": {},
+   "source": [
+    "### Building the container images\n",
+    "\n",
+    "The `model` directory contains the code for custom training and serving container images `model/training/train.py`.\n",
+    "\n",
+    "A custom container is a Docker image that you create to run your training application. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Vertex AI. To learn more you can check out [official documentation](https://cloud.google.com/vertex-ai/docs/training/containers-overview)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "905ad09c-d4c0-40cf-bfaa-621bd8c8e2c9",
+   "metadata": {},
+   "source": [
+    "To build the training and serving container images and push them to Artifact Registry run the next cell."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9bd43278-9809-4673-b1ad-4eaed2446f21",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make build"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4248cc3d-660f-409e-9395-7f700a123e18",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Running Pipelines\n",
+    "\n",
+    "You can run the training pipeline by executing cell below.\n",
+    "\n",
+    "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
+    "\n",
+    "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
+    "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "db38a19e-bd11-4311-85f4-f8714d3743a6",
+   "metadata": {},
+   "source": [
+    "**Run Training Pipeline**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "99de7032-b9c9-4ad4-b750-89ac9e9a0cdf",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make run pipeline=training build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4a351524-923e-4f94-bc5f-2e8363473f8e",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it through the Google Cloud Console UI under Vertex AI/Pipelines."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "627acd39-f46f-43ff-8d19-e7cd18ef7547",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Training Pipeline**\n",
+    "![Training Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/training_pipeline.png?raw=true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e8b196f6-0c99-402c-816e-aa94ad17f987",
+   "metadata": {},
+   "source": [
+    "**Run Prediction Pipeline** \n",
+    "\n",
+    "After successful training job, you can try prediction pipeline."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "56d8595e-b1a3-4b23-9e76-bf7ba34fc443",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make run pipeline=prediction build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c9372260-6c12-4d01-bfd9-15640e39fe67",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Prediction Pipeline**\n",
+    "\n",
+    "![Predictions Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/prediction_pipeline.png?raw=true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "84cf85b5-add4-4df1-a635-b7f513407343",
+   "metadata": {
+    "id": "TpV-iwP9qw9c"
+   },
+   "source": [
+    "## Cleaning up\n",
+    "\n",
+    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
+    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+    "\n",
+    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "04cd62bf-aa69-474a-8765-d32c59ef53da",
+   "metadata": {},
+   "source": [
+    "**Empty the buckets to enable their deletion:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9f37f2ce-b9ad-465a-a6fc-ea279a22b95a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "291ef684-bbaa-4949-99f2-ff55a86baf70",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete data transfer config:**\n",
+    "\n",
+    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7eaf1057-14a0-4135-b871-9cf703b08b1c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import google.api_core.exceptions\n",
+    "from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "transfer_config_name = TRANSFER_CONFIG # Transfer Config Name\n",
+    "try:\n",
+    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
+    "except google.api_core.exceptions.NotFound:\n",
+    "    print(\"Transfer config not found.\")\n",
+    "else:\n",
+    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e79792bb-31e0-4427-a9fc-951b8a9b8968",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for the Chicago Taxi data:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6bb5d0f9-1498-4314-a0ad-f6aacb044a3b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c2d4cf02-1d43-4e70-b411-d9660635c2f0",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for data processing during the pipelines:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5b7dfd7a-29b8-4b23-9893-b2a1bd05aac9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc67063a-337a-4517-9bd0-15f07d5bc5ee",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete local files:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6d0aec50-4b7c-407c-b73f-825c40e3758b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "cd ..\n",
+    "rm -r vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4aeb5933-65e7-46a4-a228-ac927510c117",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7c938e96-1139-4d84-abd8-a2fc5c10c35b",
+   "metadata": {
+    "id": "sx_vKniMq9ZX",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make undeploy auto-approve=true"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From d1403ff2524bd88e8811cdbfd082da430160583a Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Mon, 25 Sep 2023 09:50:32 +0100
Subject: [PATCH 206/238] feat: update

---
 examples/pipelines_colab.ipynb | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/examples/pipelines_colab.ipynb b/examples/pipelines_colab.ipynb
index 9c98b19a..3ca2f293 100644
--- a/examples/pipelines_colab.ipynb
+++ b/examples/pipelines_colab.ipynb
@@ -184,8 +184,7 @@
    "outputs": [],
    "source": [
     "# Clone a Git repository\n",
-    "!git clone -b feat/tutorial_notebook https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples\n",
-    "# !git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
    ]
   },
   {
@@ -1101,7 +1100,7 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -1115,11 +1114,11 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.10.5"
   },
   "vscode": {
    "interpreter": {
-    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
    }
   }
  },

From bb58845cbbf2ad30d95ecdfa27050b0c29884c50 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Mon, 25 Sep 2023 11:36:59 +0100
Subject: [PATCH 207/238] feat: terraform disable dependent services

---
 terraform/modules/vertex_deployment/main.tf      | 9 +++++----
 terraform/modules/vertex_deployment/variables.tf | 6 +++++-
 2 files changed, 10 insertions(+), 5 deletions(-)

diff --git a/terraform/modules/vertex_deployment/main.tf b/terraform/modules/vertex_deployment/main.tf
index 66a3b4b9..3b58bae5 100644
--- a/terraform/modules/vertex_deployment/main.tf
+++ b/terraform/modules/vertex_deployment/main.tf
@@ -16,10 +16,11 @@
 
 ## Google Cloud APIs to enable ##
 resource "google_project_service" "gcp_services" {
-  for_each           = toset(var.gcp_service_list)
-  project            = var.project_id
-  service            = each.key
-  disable_on_destroy = var.disable_services_on_destroy
+  for_each                   = toset(var.gcp_service_list)
+  project                    = var.project_id
+  service                    = each.key
+  disable_on_destroy         = var.disable_services_on_destroy
+  disable_dependent_services = var.disable_dependent_services
 }
 
 ## Service Accounts ##
diff --git a/terraform/modules/vertex_deployment/variables.tf b/terraform/modules/vertex_deployment/variables.tf
index 93d81205..074d66ec 100644
--- a/terraform/modules/vertex_deployment/variables.tf
+++ b/terraform/modules/vertex_deployment/variables.tf
@@ -51,7 +51,11 @@ variable "disable_services_on_destroy" {
   type        = bool
   default     = true
 }
-
+variable "disable_dependent_services" {
+  description = "If true, services that are enabled and which depend on this service should also be disabled when this service is destroyed. If false or unset, an error will be generated if any enabled services depend on this service when destroying it."
+  type        = bool
+  default     = true
+}
 variable "cloudfunction_region" {
   description = "Google Cloud region to use for the Cloud Function (and CF staging bucket). Defaults to the same as var.region"
   type        = string

From 8989336e3a1d577557b576249cee0127ec8b6160 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 27 Sep 2023 15:22:40 +0100
Subject: [PATCH 208/238] feat: Changing notebook directory, splitting into 3
 notebooks

---
 .../local/01_infrastructure_setup.ipynb       | 480 +++++++++++++
 docs/notebooks/local/02_run_pipelines.ipynb   | 661 ++++++++++++++++++
 .../local/03_infrastructure_cleanup.ipynb     | 419 +++++++++++
 .../notebooks/local}/pipelines.ipynb          |   2 +-
 .../notebooks}/pipelines_colab.ipynb          |   4 +-
 .../notebooks}/pipelines_workbench.ipynb      |   0
 6 files changed, 1563 insertions(+), 3 deletions(-)
 create mode 100644 docs/notebooks/local/01_infrastructure_setup.ipynb
 create mode 100644 docs/notebooks/local/02_run_pipelines.ipynb
 create mode 100644 docs/notebooks/local/03_infrastructure_cleanup.ipynb
 rename {examples => docs/notebooks/local}/pipelines.ipynb (99%)
 rename {examples => docs/notebooks}/pipelines_colab.ipynb (99%)
 rename {examples => docs/notebooks}/pipelines_workbench.ipynb (100%)

diff --git a/docs/notebooks/local/01_infrastructure_setup.ipynb b/docs/notebooks/local/01_infrastructure_setup.ipynb
new file mode 100644
index 00000000..5fe6cf87
--- /dev/null
+++ b/docs/notebooks/local/01_infrastructure_setup.ipynb
@@ -0,0 +1,480 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Running Vertex Pipelines using E2E Samples repository - Infrastructure setup.\n",
+    "\n",
+    "\n",
+    "<table align=\"left\">\n",
+    "\n",
+    "  <td>\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/01_infrastructure_setup.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
+    "      View on GitHub\n",
+    "    </a>\n",
+    "  </td>                                                                                         \n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "24743cf4a1e1"
+   },
+   "source": [
+    "**_NOTE_**: This notebook has been tested in the following environment:\n",
+    "\n",
+    "* Python version = 3.9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tvgnzT1CKxrO",
+    "tags": []
+   },
+   "source": [
+    "## Overview\n",
+    "\n",
+    "This notebook shows you how to setup infrastructure to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
+    "\n",
+    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d975e698c9a4"
+   },
+   "source": [
+    "### Objective\n",
+    "\n",
+    "In this tutorial, you learn how to set up the cloud infrastructure, in order to launch your first training and predicition pipeline:\n",
+    "\n",
+    "This tutorial uses the following Google Cloud services and resources:\n",
+    "\n",
+    "- *`Vertex Pipelines`*\n",
+    "- *`Google Cloud Storage`*\n",
+    "- *`Artifact Registry`*\n",
+    "- *`BigQuery`*\n",
+    "- *`Cloud Build`*\n",
+    "\n",
+    "The steps performed include:\n",
+    "\n",
+    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "aed92deeb4a0"
+   },
+   "source": [
+    "### Costs \n",
+    "\n",
+    "\n",
+    "This tutorial uses billable components of Google Cloud:\n",
+    "\n",
+    "* Vertex AI\n",
+    "* BigQuery\n",
+    "* Cloud Storage\n",
+    "* Cloud Build\n",
+    "* Artifact Registry\n",
+    "\n",
+    "\n",
+    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
+    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
+    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
+    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
+    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
+    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
+    "to generate a cost estimate based on your projected usage."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Terraform](https://www.terraform.io)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Clone Turbo Templates repository"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Clone a Git repository\n",
+    "# !git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples\n",
+    "!git clone -b feat/tutorial_notebook https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Infrastructure"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):\n",
+    "\n",
+    "- `cloudfunction` - deploys a (Pub/Sub-triggered) Cloud Function from local source code\n",
+    "- `scheduled_pipelines` - deploys Cloud Scheduler jobs that will trigger Vertex Pipeline runs (via the above Cloud Function)\n",
+    "- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, Artifact Registry repos, service accounts, and IAM permissions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Terraform Installation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**If you do not have terraform installed please please refer to the official documentation for detailed installation instructions: https://developer.hashicorp.com/terraform/downloads**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Before You Begin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "BF1j6f9HApxa",
+    "tags": []
+   },
+   "source": [
+    "### Set up your Google Cloud project\n",
+    "\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
+    "\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+    "\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
+    "\n",
+    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WReHDGG5g0XY"
+   },
+   "source": [
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "oM1iC_MfAts1",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "PROJECT_ID = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "# Set the project id\n",
+    "! gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "\n",
+    "As you're running a Jupyter environment locally, you'll need to authenticate manually. Please follow the instructions provided below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    " ! gcloud auth login"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Environment Setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to run `make` commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID` and `VERTEX_LOCATION`)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%writefile .env\n",
+    "\n",
+    "VERTEX_LOCATION=europe-west2\n",
+    "VERTEX_PROJECT_ID=dt-donatas-sandbox-dev\n",
+    "\n",
+    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
+    "RESOURCE_SUFFIX=default\n",
+    "\n",
+    "# Leave as-is\n",
+    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
+    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
+    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
+    "\n",
+    "# Optional\n",
+    "VERTEX_CMEK_IDENTIFIER=\n",
+    "VERTEX_NETWORK="
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "load_dotenv()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zgPO1eR3CYjk",
+    "tags": []
+   },
+   "source": [
+    "## Infrastructure deployment using terraform.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
+    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Create tfstate bucket\n",
+    "\n",
+    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "-EcIXiGsCePi"
+   },
+   "source": [
+    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "NIq7R4HZCfIc",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "960505627ddf"
+   },
+   "source": [
+    "### Deploy required infrastructure"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Deploy command will:\n",
+    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
+    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make deploy auto-approve=true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Congratulations on successfully deploying the infrastructure required to run ML pipelines!"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/notebooks/local/02_run_pipelines.ipynb b/docs/notebooks/local/02_run_pipelines.ipynb
new file mode 100644
index 00000000..38ad35bd
--- /dev/null
+++ b/docs/notebooks/local/02_run_pipelines.ipynb
@@ -0,0 +1,661 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Running Vertex Pipelines using E2E Samples repository - Triggering Pipelines.\n",
+    "\n",
+    "\n",
+    "<table align=\"left\">\n",
+    "\n",
+    "  <td>\n",
+    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_colab.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
+    "    </a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
+    "      View on GitHub\n",
+    "    </a>\n",
+    "  </td>\n",
+    "  <td>\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_workbench.ipynb\">\n",
+    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
+    "      Open in Vertex AI Workbench\n",
+    "    </a>\n",
+    "  </td>                                                                                               \n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "24743cf4a1e1"
+   },
+   "source": [
+    "**_NOTE_**: This notebook has been tested in the following environment:\n",
+    "\n",
+    "* Python version = 3.9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tvgnzT1CKxrO",
+    "tags": []
+   },
+   "source": [
+    "## Overview\n",
+    "\n",
+    "This notebook shows you how to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
+    "\n",
+    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d975e698c9a4"
+   },
+   "source": [
+    "### Objective\n",
+    "\n",
+    "In this tutorial, you learn how to launch your first training and predicition pipeline, and analyse the results:\n",
+    "\n",
+    "This tutorial uses the following Google Cloud services and resources:\n",
+    "\n",
+    "- *`Vertex Pipelines`*\n",
+    "- *`Google Cloud Storage`*\n",
+    "- *`Artifact Registry`*\n",
+    "- *`BigQuery`*\n",
+    "- *`Cloud Build`*\n",
+    "\n",
+    "The steps performed include:\n",
+    "\n",
+    "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "08d289fa873f"
+   },
+   "source": [
+    "### Dataset\n",
+    "\n",
+    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
+    "\n",
+    "\n",
+    "This public dataset is hosted in Google BigQuery."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "aed92deeb4a0"
+   },
+   "source": [
+    "### Costs \n",
+    "\n",
+    "\n",
+    "This tutorial uses billable components of Google Cloud:\n",
+    "\n",
+    "* Vertex AI\n",
+    "* BigQuery\n",
+    "* Cloud Storage\n",
+    "* Cloud Build\n",
+    "* Artifact Registry\n",
+    "\n",
+    "\n",
+    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
+    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
+    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
+    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
+    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
+    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
+    "to generate a cost estimate based on your projected usage."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Poetry](https://python-poetry.org)\n",
+    "- [pyenv](https://github.com/pyenv/pyenv)\n",
+    "- Infrastructure deployed ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Change working directory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "i7EUnXsZhAGF",
+    "tags": []
+   },
+   "source": [
+    "## Installation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Install the packages required for executing this notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "2b4ef9b72d43",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Install the correct Python version\n",
+    "! pyenv install -skip-existing\n",
+    "\n",
+    "# configure poetry \n",
+    "! poetry config virtualenvs.prefer-active-python true\n",
+    "\n",
+    "#Install poetry dependencies for ML pipelines\n",
+    "! make install"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Terraform"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**If you do not have terraform installed please follow the instructions below.**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Local JupyterLab instance**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Please follow official documentation for installation instructions: https://developer.hashicorp.com/terraform/downloads"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Before You Begin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "BF1j6f9HApxa",
+    "tags": []
+   },
+   "source": [
+    "### Set up your Google Cloud project\n",
+    "\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
+    "\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+    "\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
+    "\n",
+    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WReHDGG5g0XY"
+   },
+   "source": [
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "oM1iC_MfAts1",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "PROJECT_ID = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "# Set the project id\n",
+    "! gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "\n",
+    "As you're running a Jupyter environment locally, you'll need to authenticate manually. Please follow the instructions provided below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    " ! gcloud auth login"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Environment Setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to run make commands relevant environment variables need to be set. You can re-use `.env` file defined in [01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ! pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "load_dotenv()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Example ML Pipelines"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "To automate, monitor, and govern your ML workflows, you can use [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops). Vertex AI is a powerful platform offered by Google Cloud that empowers organizations to streamline and enhance their Machine Learning (ML) workflows through automation, monitoring, and governance.\n",
+    "\n",
+    "- **Automation**: Vertex AI offers a suite of tools and services designed to automate various aspects of ML development and deployment. This includes automating data preprocessing, model training, hyperparameter tuning, and model deployment. Automation not only saves time but also reduces the potential for human error, making your ML workflows more efficient and reliable.\n",
+    "\n",
+    "- **Monitoring**: Effective monitoring is crucial for maintaining the performance and reliability of ML models in production. Vertex AI provides monitoring capabilities that allow you to track model performance, detect drift in data distributions, and set up alerts for anomalies. This proactive monitoring ensures that your models continue to deliver accurate results as data and business conditions change over time.\n",
+    "\n",
+    "- **Governance**: Managing ML models and data in a secure and compliant manner is essential for businesses, especially those in regulated industries. Vertex AI helps you implement governance policies to control access to data, monitor model usage, and enforce compliance with data privacy regulations. This ensures that your ML operations are in line with legal and ethical standards.\n",
+    "\n",
+    "- **Scalability**: Vertex AI is built on Google Cloud's infrastructure, which means it offers unparalleled scalability. Whether you're dealing with small-scale experiments or large-scale production deployments, Vertex AI can scale to meet your needs, ensuring that your ML workflows can handle increased workloads without performance bottlenecks.\n",
+    "\n",
+    "- **Collaboration**: Collaboration is essential in ML development, and Vertex AI provides features that facilitate collaboration among data scientists, machine learning engineers, and other stakeholders. You can share notebooks, collaborate on model development, and maintain version control of your ML assets.\n",
+    "\n",
+    "- **Model Serving**: Vertex AI makes it easy to deploy ML models as APIs for real-time inference or batch processing. This enables you to integrate your ML models into applications, websites, or other services with ease.\n",
+    "\n",
+    "- **Cost Management**: Cost control is a crucial aspect of any ML project. Vertex AI offers cost management tools and insights to help you optimize your ML workflows and keep your expenses in check.\n",
+    "\n",
+    "By utilizing Vertex AI, you can take advantage of Google Cloud's cutting-edge technology and expertise in machine learning to accelerate your MLOps journey. The platform offers a comprehensive set of tools and services that cover the entire ML lifecycle, from data preparation to model deployment and beyond, making it a valuable resource for organizations looking to harness the power of ML in a scalable, efficient, and secure manner.\n",
+    "\n",
+    "To learn more about MLOps on Vertex AI and how it can transform your ML workflows, you can visit the [official documentation](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops).\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**This repository provides an example ML training and prediction pipelines for XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips).**\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Pre-requisites\n",
+    "\n",
+    "Before you can successfully execute the example pipelines, there are a few additional components you need to deploy. These components have not been included in the Terraform code as they are specific to these pipelines."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "1. Create a new BigQuery dataset for the Chicago Taxi data:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "2. Create a new BigQuery dataset for data processing during the pipelines:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install google-cloud-bigquery-datatransfer"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "destination_project_id = os.environ[\"VERTEX_PROJECT_ID\"]\n",
+    "destination_dataset_id = \"chicago_taxi_trips\"\n",
+    "source_project_id = \"bigquery-public-data\"\n",
+    "source_dataset_id = \"chicago_taxi_trips\"\n",
+    "transfer_config = bigquery_datatransfer.TransferConfig(\n",
+    "    destination_dataset_id=destination_dataset_id,\n",
+    "    display_name=\"Chicago taxi trip mirror\",\n",
+    "    data_source_id=\"cross_region_copy\",\n",
+    "    params={\n",
+    "        \"source_project_id\": source_project_id,\n",
+    "        \"source_dataset_id\": source_dataset_id,\n",
+    "    },\n",
+    "    schedule=\"every 24 hours\",\n",
+    ")\n",
+    "transfer_config = transfer_client.create_transfer_config(\n",
+    "    parent=transfer_client.common_project_path(destination_project_id),\n",
+    "    transfer_config=transfer_config,\n",
+    ")\n",
+    "TRANSFER_CONFIG=transfer_config.name\n",
+    "print(f\"Created transfer config: {TRANSFER_CONFIG}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Building the container images\n",
+    "\n",
+    "The `model` directory contains the code for custom training and serving container images `model/training/train.py`.\n",
+    "\n",
+    "A custom container is a Docker image that you create to run your training application. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Vertex AI. To learn more you can check out [official documentation](https://cloud.google.com/vertex-ai/docs/training/containers-overview)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To build the training and serving container images and push them to Artifact Registry run the next cell."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make build"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Running Pipelines\n",
+    "\n",
+    "You can run the training pipeline by executing cell below.\n",
+    "\n",
+    "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
+    "\n",
+    "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
+    "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Run Training Pipeline**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make run pipeline=training build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it directly through the Google Cloud Console UI by navigating to Vertex AI and then selecting Pipelines."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Training Pipeline**\n",
+    "![Training Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/training_pipeline.png?raw=true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Run Prediction Pipeline** \n",
+    "\n",
+    "After successful training job, you can try prediction pipeline."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make run pipeline=prediction build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Prediction Pipeline**\n",
+    "\n",
+    "![Predictions Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/prediction_pipeline.png?raw=true)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Congratulations on successfully running your first ML pipelines!"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/notebooks/local/03_infrastructure_cleanup.ipynb b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
new file mode 100644
index 00000000..ed8ba8e2
--- /dev/null
+++ b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
@@ -0,0 +1,419 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Running Vertex Pipelines using E2E Samples repository - Infrastructure Cleanup\n",
+    "\n",
+    "\n",
+    "<table align=\"left\">\n",
+    "  <td>\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/03_infrastructure_cleanup.ipynb\">\n",
+    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
+    "      View on GitHub\n",
+    "    </a>\n",
+    "  </td>                                                                            \n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "24743cf4a1e1"
+   },
+   "source": [
+    "**_NOTE_**: This notebook has been tested in the following environment:\n",
+    "\n",
+    "* Python version = 3.9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tvgnzT1CKxrO",
+    "tags": []
+   },
+   "source": [
+    "## Overview\n",
+    "\n",
+    "This notebook shows you how to destroy infrastructure which was created in ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d975e698c9a4"
+   },
+   "source": [
+    "### Objective\n",
+    "\n",
+    "In this tutorial, you learn how to destroy infrastructure using terraform.\n",
+    "\n",
+    "The steps performed include:\n",
+    "\n",
+    "* Destroy infrastructure using Terraform."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Terraform](https://www.terraform.io)\n",
+    "- Infrastructure deployed ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Change working directory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Before You Begin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "BF1j6f9HApxa",
+    "tags": []
+   },
+   "source": [
+    "### Set up your Google Cloud project\n",
+    "\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
+    "\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+    "\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
+    "\n",
+    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WReHDGG5g0XY"
+   },
+   "source": [
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "oM1iC_MfAts1",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "PROJECT_ID = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "# Set the project id\n",
+    "! gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "\n",
+    "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    " ! gcloud auth login"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Environment Setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to run make commands relevant environment variables need to be set. You can re-use `.env` file defined in [01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ! pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "load_dotenv()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "TpV-iwP9qw9c"
+   },
+   "source": [
+    "## Cleaning up\n",
+    "\n",
+    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
+    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+    "\n",
+    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Empty the buckets to enable their deletion:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete data transfer config:**\n",
+    "\n",
+    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import google.api_core.exceptions\n",
+    "from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "transfer_config_name = \"my-transfer-config\" # Transfer Config Resource Name (projects/{project_number}/locations/{location}/transferConfigs/{transfer_config_id)\n",
+    "try:\n",
+    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
+    "except google.api_core.exceptions.NotFound:\n",
+    "    print(\"Transfer config not found.\")\n",
+    "else:\n",
+    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for the Chicago Taxi data:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for data processing during the pipelines:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete local files:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "cd ..\n",
+    "rm -r vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make undeploy auto-approve=true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Congratulations on successfully destroyed your infrastructure!"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/examples/pipelines.ipynb b/docs/notebooks/local/pipelines.ipynb
similarity index 99%
rename from examples/pipelines.ipynb
rename to docs/notebooks/local/pipelines.ipynb
index 8a03b4a3..cf64e203 100644
--- a/examples/pipelines.ipynb
+++ b/docs/notebooks/local/pipelines.ipynb
@@ -361,7 +361,7 @@
     "%%writefile .env\n",
     "\n",
     "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_PROJECT_ID=my-project-id\n",
+    "VERTEX_PROJECT_ID=dt-donatas-sandbox-dev\n",
     "\n",
     "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
     "RESOURCE_SUFFIX=default\n",
diff --git a/examples/pipelines_colab.ipynb b/docs/notebooks/pipelines_colab.ipynb
similarity index 99%
rename from examples/pipelines_colab.ipynb
rename to docs/notebooks/pipelines_colab.ipynb
index 3ca2f293..438246b6 100644
--- a/examples/pipelines_colab.ipynb
+++ b/docs/notebooks/pipelines_colab.ipynb
@@ -1100,7 +1100,7 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -1114,7 +1114,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.9.6"
   },
   "vscode": {
    "interpreter": {
diff --git a/examples/pipelines_workbench.ipynb b/docs/notebooks/pipelines_workbench.ipynb
similarity index 100%
rename from examples/pipelines_workbench.ipynb
rename to docs/notebooks/pipelines_workbench.ipynb

From 158202509eade9cf3b6f93f513b41e95e064c7a2 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Wed, 27 Sep 2023 15:24:10 +0100
Subject: [PATCH 209/238] feat: Changing project_id

---
 docs/notebooks/local/01_infrastructure_setup.ipynb   | 4 ++--
 docs/notebooks/local/02_run_pipelines.ipynb          | 2 +-
 docs/notebooks/local/03_infrastructure_cleanup.ipynb | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/docs/notebooks/local/01_infrastructure_setup.ipynb b/docs/notebooks/local/01_infrastructure_setup.ipynb
index 5fe6cf87..b40ccaf1 100644
--- a/docs/notebooks/local/01_infrastructure_setup.ipynb
+++ b/docs/notebooks/local/01_infrastructure_setup.ipynb
@@ -250,7 +250,7 @@
    },
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "PROJECT_ID = \"[my-project-id]\"\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]
@@ -301,7 +301,7 @@
     "%%writefile .env\n",
     "\n",
     "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_PROJECT_ID=dt-donatas-sandbox-dev\n",
+    "VERTEX_PROJECT_ID=my-project-id\n",
     "\n",
     "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
     "RESOURCE_SUFFIX=default\n",
diff --git a/docs/notebooks/local/02_run_pipelines.ipynb b/docs/notebooks/local/02_run_pipelines.ipynb
index 38ad35bd..4eb86cd4 100644
--- a/docs/notebooks/local/02_run_pipelines.ipynb
+++ b/docs/notebooks/local/02_run_pipelines.ipynb
@@ -297,7 +297,7 @@
    },
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]
diff --git a/docs/notebooks/local/03_infrastructure_cleanup.ipynb b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
index ed8ba8e2..5c7c7959 100644
--- a/docs/notebooks/local/03_infrastructure_cleanup.ipynb
+++ b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
@@ -164,7 +164,7 @@
    },
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]

From b5da3c1a1f090cbdb0c820d9fff524ed0eb2173f Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 28 Sep 2023 10:09:32 +0100
Subject: [PATCH 210/238] feat: Small updates to notebooks (local)

---
 .../local/01_infrastructure_setup.ipynb       |  3 +-
 .../local/03_infrastructure_cleanup.ipynb     | 30 ++++++++---------
 docs/notebooks/local/pipelines.ipynb          | 32 +++++++++----------
 3 files changed, 32 insertions(+), 33 deletions(-)

diff --git a/docs/notebooks/local/01_infrastructure_setup.ipynb b/docs/notebooks/local/01_infrastructure_setup.ipynb
index b40ccaf1..33c9fa02 100644
--- a/docs/notebooks/local/01_infrastructure_setup.ipynb
+++ b/docs/notebooks/local/01_infrastructure_setup.ipynb
@@ -149,8 +149,7 @@
    "outputs": [],
    "source": [
     "# Clone a Git repository\n",
-    "# !git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples\n",
-    "!git clone -b feat/tutorial_notebook https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
    ]
   },
   {
diff --git a/docs/notebooks/local/03_infrastructure_cleanup.ipynb b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
index 5c7c7959..e0f938ae 100644
--- a/docs/notebooks/local/03_infrastructure_cleanup.ipynb
+++ b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
@@ -164,7 +164,7 @@
    },
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
+    "PROJECT_ID = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]
@@ -341,40 +341,40 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "source": [
-    "**Delete local files:**"
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "%%bash\n",
-    "cd ..\n",
-    "rm -r vertex-pipelines-end-to-end-samples"
+    "! make undeploy auto-approve=true"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
-    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+    "**Delete local files:**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "! make undeploy auto-approve=true"
+    "%%bash\n",
+    "cd ..\n",
+    "rm -r vertex-pipelines-end-to-end-samples"
    ]
   },
   {
diff --git a/docs/notebooks/local/pipelines.ipynb b/docs/notebooks/local/pipelines.ipynb
index cf64e203..bbc89339 100644
--- a/docs/notebooks/local/pipelines.ipynb
+++ b/docs/notebooks/local/pipelines.ipynb
@@ -310,7 +310,7 @@
    },
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"my-project-id\"  # @param {type:\"string\"}\n",
+    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]
@@ -361,7 +361,7 @@
     "%%writefile .env\n",
     "\n",
     "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_PROJECT_ID=dt-donatas-sandbox-dev\n",
+    "VERTEX_PROJECT_ID=my-project-id\n",
     "\n",
     "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
     "RESOURCE_SUFFIX=default\n",
@@ -851,40 +851,40 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "source": [
-    "**Delete local files:**"
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "%%bash\n",
-    "cd ..\n",
-    "rm -r vertex-pipelines-end-to-end-samples"
+    "! make undeploy auto-approve=true"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
-    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+    "**Delete local files:**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
-    "! make undeploy auto-approve=true"
+    "%%bash\n",
+    "cd ..\n",
+    "rm -r vertex-pipelines-end-to-end-samples"
    ]
   }
  ],

From 0a6972cc867c40a31339abf99710910a6ff09ac0 Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 28 Sep 2023 14:05:22 +0100
Subject: [PATCH 211/238] feat: Adding workbench notebook

---
 .../local/01_infrastructure_setup.ipynb       |  16 +-
 docs/notebooks/local/02_run_pipelines.ipynb   |  61 +-
 .../local/03_infrastructure_cleanup.ipynb     |  29 +-
 docs/notebooks/local/pipelines.ipynb          |  18 +-
 .../workbench/01_infrastructure_setup.ipynb   | 498 ++++++++++++++
 .../02_run_pipelines.ipynb}                   | 616 ++----------------
 .../workbench/03_infrastructure_cleanup.ipynb | 411 ++++++++++++
 .../{ => workbench}/pipelines_workbench.ipynb | 147 +----
 8 files changed, 1005 insertions(+), 791 deletions(-)
 create mode 100644 docs/notebooks/workbench/01_infrastructure_setup.ipynb
 rename docs/notebooks/{pipelines_colab.ipynb => workbench/02_run_pipelines.ipynb} (53%)
 create mode 100644 docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
 rename docs/notebooks/{ => workbench}/pipelines_workbench.ipynb (90%)

diff --git a/docs/notebooks/local/01_infrastructure_setup.ipynb b/docs/notebooks/local/01_infrastructure_setup.ipynb
index 33c9fa02..030ccad8 100644
--- a/docs/notebooks/local/01_infrastructure_setup.ipynb
+++ b/docs/notebooks/local/01_infrastructure_setup.ipynb
@@ -26,7 +26,8 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "JAPoU8Sm5E6e"
+    "id": "JAPoU8Sm5E6e",
+    "tags": []
    },
    "source": [
     "# Running Vertex Pipelines using E2E Samples repository - Infrastructure setup.\n",
@@ -43,17 +44,6 @@
     "</table>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "24743cf4a1e1"
-   },
-   "source": [
-    "**_NOTE_**: This notebook has been tested in the following environment:\n",
-    "\n",
-    "* Python version = 3.9"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -272,7 +262,7 @@
    },
    "outputs": [],
    "source": [
-    " ! gcloud auth login"
+    "! gcloud auth login"
    ]
   },
   {
diff --git a/docs/notebooks/local/02_run_pipelines.ipynb b/docs/notebooks/local/02_run_pipelines.ipynb
index 4eb86cd4..006d99a5 100644
--- a/docs/notebooks/local/02_run_pipelines.ipynb
+++ b/docs/notebooks/local/02_run_pipelines.ipynb
@@ -33,38 +33,15 @@
     "\n",
     "\n",
     "<table align=\"left\">\n",
-    "\n",
-    "  <td>\n",
-    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_colab.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
-    "    </a>\n",
-    "  </td>\n",
     "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines.ipynb\">\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/03_run_pipelines.ipynb\">\n",
     "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
     "      View on GitHub\n",
     "    </a>\n",
-    "  </td>\n",
-    "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_workbench.ipynb\">\n",
-    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
-    "      Open in Vertex AI Workbench\n",
-    "    </a>\n",
-    "  </td>                                                                                               \n",
+    "  </td>                                                                            \n",
     "</table>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "24743cf4a1e1"
-   },
-   "source": [
-    "**_NOTE_**: This notebook has been tested in the following environment:\n",
-    "\n",
-    "* Python version = 3.9"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -215,38 +192,6 @@
     "! make install"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Terraform"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**If you do not have terraform installed please follow the instructions below.**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Local JupyterLab instance**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Please follow official documentation for installation instructions: https://developer.hashicorp.com/terraform/downloads"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -320,7 +265,7 @@
    },
    "outputs": [],
    "source": [
-    " ! gcloud auth login"
+    "! gcloud auth login"
    ]
   },
   {
diff --git a/docs/notebooks/local/03_infrastructure_cleanup.ipynb b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
index e0f938ae..0163cf0e 100644
--- a/docs/notebooks/local/03_infrastructure_cleanup.ipynb
+++ b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
@@ -42,17 +42,6 @@
     "</table>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "24743cf4a1e1"
-   },
-   "source": [
-    "**_NOTE_**: This notebook has been tested in the following environment:\n",
-    "\n",
-    "* Python version = 3.9"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -158,13 +147,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "id": "oM1iC_MfAts1",
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"dt-donatas-sandbox-dev\"  # @param {type:\"string\"}\n",
+    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]
@@ -187,7 +173,7 @@
    },
    "outputs": [],
    "source": [
-    " ! gcloud auth login"
+    "! gcloud auth login"
    ]
   },
   {
@@ -378,10 +364,11 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Congratulations on successfully destroyed your infrastructure!"
+    "### Congratulations on successfully destroying your infrastructure!"
    ]
   }
  ],
@@ -392,7 +379,7 @@
    "toc_visible": true
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -406,11 +393,11 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.10.5"
   },
   "vscode": {
    "interpreter": {
-    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
    }
   }
  },
diff --git a/docs/notebooks/local/pipelines.ipynb b/docs/notebooks/local/pipelines.ipynb
index bbc89339..04eeccb2 100644
--- a/docs/notebooks/local/pipelines.ipynb
+++ b/docs/notebooks/local/pipelines.ipynb
@@ -24,6 +24,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "id": "JAPoU8Sm5E6e"
@@ -35,18 +36,18 @@
     "<table align=\"left\">\n",
     "\n",
     "  <td>\n",
-    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_colab.ipynb\">\n",
+    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/local//pipelines_colab.ipynb\">\n",
     "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines.ipynb\">\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/local/pipelines.ipynb\">\n",
     "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
     "      View on GitHub\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_workbench.ipynb\">\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/local/pipelines_workbench.ipynb\">\n",
     "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
     "      Open in Vertex AI Workbench\n",
     "    </a>\n",
@@ -54,17 +55,6 @@
     "</table>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "24743cf4a1e1"
-   },
-   "source": [
-    "**_NOTE_**: This notebook has been tested in the following environment:\n",
-    "\n",
-    "* Python version = 3.9"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/docs/notebooks/workbench/01_infrastructure_setup.ipynb b/docs/notebooks/workbench/01_infrastructure_setup.ipynb
new file mode 100644
index 00000000..2e6829a4
--- /dev/null
+++ b/docs/notebooks/workbench/01_infrastructure_setup.ipynb
@@ -0,0 +1,498 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Running Vertex Pipelines using E2E Samples repository - Infrastructure setup.\n",
+    "\n",
+    "\n",
+    "<table align=\"left\">\n",
+    "\n",
+    "  <td>\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/01_infrastructure_setup.ipynb\">\n",
+    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
+    "      Open in Vertex AI Workbench\n",
+    "    </a>\n",
+    "  </td>                                                                                               \n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tvgnzT1CKxrO",
+    "tags": []
+   },
+   "source": [
+    "## Overview\n",
+    "\n",
+    "This notebook shows you how to setup infrastructure to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
+    "\n",
+    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d975e698c9a4"
+   },
+   "source": [
+    "### Objective\n",
+    "\n",
+    "In this tutorial, you learn how to set up the cloud infrastructure, in order to launch your first training and predicition pipeline:\n",
+    "\n",
+    "This tutorial uses the following Google Cloud services and resources:\n",
+    "\n",
+    "- *`Vertex Pipelines`*\n",
+    "- *`Google Cloud Storage`*\n",
+    "- *`Artifact Registry`*\n",
+    "- *`BigQuery`*\n",
+    "- *`Cloud Build`*\n",
+    "\n",
+    "The steps performed include:\n",
+    "\n",
+    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "aed92deeb4a0"
+   },
+   "source": [
+    "### Costs \n",
+    "\n",
+    "\n",
+    "This tutorial uses billable components of Google Cloud:\n",
+    "\n",
+    "* Vertex AI\n",
+    "* BigQuery\n",
+    "* Cloud Storage\n",
+    "* Cloud Build\n",
+    "* Artifact Registry\n",
+    "\n",
+    "\n",
+    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
+    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
+    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
+    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
+    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
+    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
+    "to generate a cost estimate based on your projected usage."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Terraform](https://www.terraform.io)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Clone Turbo Templates repository"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Clone a Git repository\n",
+    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Infrastructure"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):\n",
+    "\n",
+    "- `cloudfunction` - deploys a (Pub/Sub-triggered) Cloud Function from local source code\n",
+    "- `scheduled_pipelines` - deploys Cloud Scheduler jobs that will trigger Vertex Pipeline runs (via the above Cloud Function)\n",
+    "- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, Artifact Registry repos, service accounts, and IAM permissions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Terraform Installation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Installing Terraform by downloading a pre-compiled binary.**\n",
+    "1. **Download** the appropriate package for your system as a zip archive from the Terraform website.\n",
+    "2. **Unzip** the downloaded package.\n",
+    "3. **Add Terraform to PATH**."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "mkdir temp\n",
+    "cd temp\n",
+    "curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
+    "unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
+    "mkdir $HOME/.bin\n",
+    "mv terraform $HOME/.bin > /dev/null\n",
+    "cd ..\n",
+    "rm -r temp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.bin')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! terraform -version"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Before You Begin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "BF1j6f9HApxa",
+    "tags": []
+   },
+   "source": [
+    "### Set up your Google Cloud project\n",
+    "\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
+    "\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+    "\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
+    "\n",
+    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WReHDGG5g0XY"
+   },
+   "source": [
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "oM1iC_MfAts1",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "PROJECT_ID = \"[my-project-id]\"\n",
+    "# Set the project id\n",
+    "! gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "\n",
+    "As you're running a Jupyter environment on workbench, you are already authenticated."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Environment Setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to run `make` commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID` and `VERTEX_LOCATION`)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%writefile .env\n",
+    "\n",
+    "VERTEX_LOCATION=europe-west2\n",
+    "VERTEX_PROJECT_ID=my-project-id\n",
+    "\n",
+    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
+    "RESOURCE_SUFFIX=default\n",
+    "\n",
+    "# Leave as-is\n",
+    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
+    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
+    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
+    "\n",
+    "# Optional\n",
+    "VERTEX_CMEK_IDENTIFIER=\n",
+    "VERTEX_NETWORK="
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "load_dotenv()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zgPO1eR3CYjk",
+    "tags": []
+   },
+   "source": [
+    "## Infrastructure deployment using terraform.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
+    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Create tfstate bucket\n",
+    "\n",
+    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "-EcIXiGsCePi"
+   },
+   "source": [
+    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "NIq7R4HZCfIc",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "960505627ddf"
+   },
+   "source": [
+    "### Deploy required infrastructure"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "Deploy command will:\n",
+    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
+    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make deploy auto-approve=true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Congratulations on successfully deploying the infrastructure required to run ML pipelines!"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python (Local)",
+   "language": "python",
+   "name": "local-base"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/notebooks/pipelines_colab.ipynb b/docs/notebooks/workbench/02_run_pipelines.ipynb
similarity index 53%
rename from docs/notebooks/pipelines_colab.ipynb
rename to docs/notebooks/workbench/02_run_pipelines.ipynb
index 438246b6..2f54d840 100644
--- a/docs/notebooks/pipelines_colab.ipynb
+++ b/docs/notebooks/workbench/02_run_pipelines.ipynb
@@ -29,24 +29,13 @@
     "id": "JAPoU8Sm5E6e"
    },
    "source": [
-    "# Running Vertex Pipelines using E2E Samples repository.\n",
+    "# Running Vertex Pipelines using E2E Samples repository - Triggering Pipelines.\n",
     "\n",
     "\n",
     "<table align=\"left\">\n",
     "\n",
     "  <td>\n",
-    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_colab.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
-    "    </a>\n",
-    "  </td>\n",
-    "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
-    "      View on GitHub\n",
-    "    </a>\n",
-    "  </td>\n",
-    "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_workbench.ipynb\">\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/02_run_pipelines.ipynb\">\n",
     "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
     "      Open in Vertex AI Workbench\n",
     "    </a>\n",
@@ -54,17 +43,6 @@
     "</table>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "24743cf4a1e1"
-   },
-   "source": [
-    "**_NOTE_**: This notebook has been tested in the following environment:\n",
-    "\n",
-    "* Python version = 3.9"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -87,7 +65,7 @@
    "source": [
     "### Objective\n",
     "\n",
-    "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
+    "In this tutorial, you learn how to launch your first training and predicition pipeline, and analyse the results:\n",
     "\n",
     "This tutorial uses the following Google Cloud services and resources:\n",
     "\n",
@@ -99,7 +77,6 @@
     "\n",
     "The steps performed include:\n",
     "\n",
-    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services.\n",
     "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
    ]
   },
@@ -123,7 +100,7 @@
     "id": "aed92deeb4a0"
    },
    "source": [
-    "### Costs\n",
+    "### Costs \n",
     "\n",
     "\n",
     "This tutorial uses billable components of Google Cloud:\n",
@@ -147,7 +124,6 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "YXI8WcMpuyXI",
     "tags": []
    },
    "source": [
@@ -157,45 +133,23 @@
     "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
     "- Make\n",
     "- [Poetry](https://python-poetry.org)\n",
-    "- [Terraform](https://www.terraform.io) (To install Terraform on your local machine we recommend using [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version.)"
+    "- [pyenv](https://github.com/pyenv/pyenv)\n",
+    "- Infrastructure deployed ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "ujfOJ2gHuyXJ",
-    "tags": []
-   },
-   "source": [
-    "## Clone Turbo Templates repository"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "J5YwqQbDuyXJ",
-    "outputId": "9b703837-a177-4956-8c77-2985dea88601",
     "tags": []
    },
-   "outputs": [],
    "source": [
-    "# Clone a Git repository\n",
-    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+    "## Change working directory"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "rlBC9B_OuyXJ",
-    "outputId": "00a3fd6f-b06d-461d-8a24-a37d0351e095",
     "tags": []
    },
    "outputs": [],
@@ -215,9 +169,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "r1hZ7k5guyXJ"
-   },
+   "metadata": {},
    "source": [
     "Install the packages required for executing this notebook."
    ]
@@ -225,140 +177,32 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "cellView": "form",
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "_5hdfngMuyXJ",
-    "outputId": "1233d17f-8cd2-4185-9b84-3defadc42669"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# @title Prepare notebook.\n",
-    "# @markdown 1. Configure pyenv\n",
-    "!curl https://pyenv.run | bash\n",
-    "\n",
-    "# Add pyenv to PATH\n",
+    "# Install poetry\n",
     "import os\n",
-    "os.environ[\"PATH\"] += \":/root/.pyenv/bin\"\n",
-    "\n",
-    "# Initialize pyenv\n",
-    "!eval \"$(pyenv init -)\"\n",
-    "!eval \"$(pyenv virtualenv-init -)\"\n",
-    "\n",
-    "! pip install poetry\n",
-    "\n",
-    "# @markdown 2. Install the correct Python version\n",
-    "! pyenv install -skip-existing\n",
-    "\n",
-    "# @markdown 3. Configure poetry\n",
-    "! poetry config virtualenvs.prefer-active-python true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "kKr_J0wY6_Pr"
-   },
-   "source": [
-    "#### Install poetry dependencies for ML pipelines."
+    "!curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -\n",
+    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.poetry/bin')\n",
+    "!poetry --version"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "hrev7zxh6GCt",
-    "outputId": "68e48bbd-e646-42f1-d315-2557059807f3"
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "make install"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/",
-     "height": 1000
-    },
-    "id": "JuYvvx8yuyXK",
-    "outputId": "12f0622d-0362-4cd9-e333-0df6f7cc01a1"
-   },
-   "outputs": [],
-   "source": [
-    "# @title Installing Terraform by downloading a pre-compiled binary.\n",
-    "# @markdown This cell will:\n",
-    "# @markdown 1. **Download** the appropriate package for your system as a zip archive from the Terraform website.\n",
-    "# @markdown 2. **Unzip** the downloaded package.\n",
-    "# @markdown 3. **Ensure Terraform is on your PATH**.\n",
-    "\n",
-    "%%bash\n",
-    "mkdir temp\n",
-    "cd temp\n",
-    "curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
-    "unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
-    "mv terraform /usr/local/bin > /dev/null\n",
-    "cd ..\n",
-    "rm -r temp\n",
-    "terraform"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "58707a750154"
-   },
-   "source": [
-    "### Colab only: execute the following cell to restart the kernel."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "f200f10a1da3",
-    "outputId": "6c870257-e089-41a3-ed89-c70b311eb7b0",
+    "id": "2b4ef9b72d43",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "# Automatically restart kernel after installs so that your environment can access the new packages\n",
-    "import IPython\n",
-    "\n",
-    "app = IPython.Application.instance()\n",
-    "app.kernel.do_shutdown(True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "D31uhP4V9lTc",
-    "outputId": "1ffe618d-962f-4efc-d1b5-dd82c976733b"
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
+    "#Install poetry dependencies for ML pipelines\n",
+    "! make install"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "Gj8s3i90uyXK",
     "tags": []
    },
    "source": [
@@ -401,105 +245,51 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
     "id": "oM1iC_MfAts1",
-    "outputId": "8d1edaa5-d9ea-407e-efea-fbdb9691f60f",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "PROJECT_ID = \"my-project-id\"  # @param {type:\"string\"}\n",
+    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "PRCfV5duuyXK"
-   },
+   "metadata": {},
    "source": [
     "### Authenticate your Google Cloud account\n",
     "\n",
     "\n",
-    "Follow the relevant instructions below to authenticate."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "XY-Kz5hmuyXL",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from google.colab import auth\n",
-    "auth.authenticate_user()"
+    "As you're running a Jupyter environment on workbench, you are already authenticated."
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "I5nZH6H5uyXL"
-   },
+   "metadata": {},
    "source": [
     "### Environment Setup"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "Znu_gBnkuyXL"
-   },
+   "metadata": {},
    "source": [
-    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)."
+    "In order to run make commands relevant environment variables need to be set. You can re-use `.env` file defined in [01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb)."
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "dfN37cNEuyXL",
-    "outputId": "4e20a0a9-6551-428a-ab2e-ac22b530b5f1",
-    "tags": []
-   },
-   "outputs": [],
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
-    "%%writefile .env\n",
-    "\n",
-    "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_PROJECT_ID=my-project-id\n",
-    "\n",
-    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
-    "RESOURCE_SUFFIX=default\n",
-    "\n",
-    "# Leave as-is\n",
-    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
-    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
-    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
-    "\n",
-    "# Optional\n",
-    "VERTEX_CMEK_IDENTIFIER=\n",
-    "VERTEX_NETWORK="
+    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "EC2VyhYvuyXL",
-    "outputId": "ac399c93-78e2-4bc8-c789-32b49809a789",
-    "tags": []
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "! pip install python-dotenv"
@@ -509,131 +299,17 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "E1iwILB7uyXN",
-    "outputId": "efef313e-03b5-4b92-b528-3d92084b39b9",
     "tags": []
    },
    "outputs": [],
    "source": [
     "from dotenv import load_dotenv\n",
-    "\n",
     "load_dotenv()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "zgPO1eR3CYjk",
-    "tags": []
-   },
-   "source": [
-    "## Infrastructure deployment using terraform.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "IMbeEpCuuyXN"
-   },
-   "source": [
-    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "Oqu8hNAluyXN",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
-    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "N0W1RMZluyXN"
-   },
-   "source": [
-    "#### Create tfstate bucket\n",
-    "\n",
-    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "-EcIXiGsCePi"
-   },
-   "source": [
-    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "NIq7R4HZCfIc",
-    "outputId": "c9e11df0-587a-4bb6-92ac-254fc1a78085",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "960505627ddf"
-   },
-   "source": [
-    "### Deploy required infrastructure"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "330YqgzfuyXN",
-    "tags": []
-   },
-   "source": [
-    "Deploy command will:\n",
-    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
-    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/",
-     "height": 1000
-    },
-    "id": "-LPegqLYuyXN",
-    "outputId": "ea4a2b99-d729-4f94-a4a0-67ac883246f0",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "make deploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "ytXz5BkNuyXN",
     "tags": []
    },
    "source": [
@@ -643,7 +319,6 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "n2BLhXBpuyXN",
     "tags": []
    },
    "source": [
@@ -671,7 +346,6 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "Fw_DSPaouyXN",
     "tags": []
    },
    "source": [
@@ -680,9 +354,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "iX4_OKX5uyXN"
-   },
+   "metadata": {},
    "source": [
     "#### Pre-requisites\n",
     "\n",
@@ -691,9 +363,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "m66vkt7PuyXN"
-   },
+   "metadata": {},
    "source": [
     "1. Create a new BigQuery dataset for the Chicago Taxi data:"
    ]
@@ -702,11 +372,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "xBgpwdluuyXN",
-    "outputId": "64044c15-bb91-4b27-973d-1914face2964",
     "tags": []
    },
    "outputs": [],
@@ -716,9 +381,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "AQ88x_8xuyXO"
-   },
+   "metadata": {},
    "source": [
     "2. Create a new BigQuery dataset for data processing during the pipelines:"
    ]
@@ -727,11 +390,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "sPWQoXP5uyXO",
-    "outputId": "e968f292-6026-43a3-a9a4-637ffa8e5043",
     "tags": []
    },
    "outputs": [],
@@ -741,9 +399,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "XTCqhzKOuyXO"
-   },
+   "metadata": {},
    "source": [
     "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
    ]
@@ -751,14 +407,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/",
-     "height": 516
-    },
-    "id": "mr9wTo8-uyXO",
-    "outputId": "1f1aeb1d-869f-41db-8701-b45c1aca81a4"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "! pip install google-cloud-bigquery-datatransfer"
@@ -768,12 +417,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/",
-     "height": 877
-    },
-    "id": "EqI6dBIGuyXO",
-    "outputId": "36281530-93bd-43da-cc1f-e72377651eaa",
     "tags": []
    },
    "outputs": [],
@@ -807,9 +450,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "xRtAwjcHuyXO"
-   },
+   "metadata": {},
    "source": [
     "### Building the container images\n",
     "\n",
@@ -820,9 +461,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "hWj89EXmuyXO"
-   },
+   "metadata": {},
    "source": [
     "To build the training and serving container images and push them to Artifact Registry run the next cell."
    ]
@@ -831,7 +470,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "Hu-E6Pn3uyXO",
     "tags": []
    },
    "outputs": [],
@@ -842,7 +480,6 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "CpJhQCwvuyXO",
     "tags": []
    },
    "source": [
@@ -858,9 +495,7 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "rUnltoeDuyXO"
-   },
+   "metadata": {},
    "source": [
     "**Run Training Pipeline**"
    ]
@@ -869,7 +504,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "JwXpPsNPuyXO",
     "tags": []
    },
    "outputs": [],
@@ -880,17 +514,15 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "8a2Rz8tNuyXO",
     "tags": []
    },
    "source": [
-    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it through the Google Cloud Console UI under Vertex AI/Pipelines."
+    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it directly through the Google Cloud Console UI by navigating to Vertex AI and then selecting Pipelines."
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "f1yzYZQSuyXO",
     "tags": []
    },
    "source": [
@@ -900,11 +532,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "Cb1kLnZtuyXO"
-   },
+   "metadata": {},
    "source": [
-    "**Run Prediction Pipeline**\n",
+    "**Run Prediction Pipeline** \n",
     "\n",
     "After successful training job, you can try prediction pipeline."
    ]
@@ -912,9 +542,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "id": "8gM-UTYzuyXO"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "! make run pipeline=prediction build=false"
@@ -923,7 +551,6 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "GYeHlnV4uyXO",
     "tags": []
    },
    "source": [
@@ -935,174 +562,23 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "id": "TpV-iwP9qw9c"
-   },
-   "source": [
-    "## Cleaning up\n",
-    "\n",
-    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
-    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
-    "\n",
-    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "sTCem_rKuyXO"
-   },
-   "source": [
-    "**Empty the buckets to enable their deletion:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "IW1WVh4_uyXO",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "3uXsfDFZuyXP",
     "tags": []
    },
    "source": [
-    "**Delete data transfer config:**\n",
-    "\n",
-    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "L5jdzMZeuyXP",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import google.api_core.exceptions\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "transfer_config_name = TRANSFER_CONFIG # Transfer Config Name\n",
-    "try:\n",
-    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
-    "except google.api_core.exceptions.NotFound:\n",
-    "    print(\"Transfer config not found.\")\n",
-    "else:\n",
-    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "69WPFNN-uyXP",
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for the Chicago Taxi data:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "KcQ5cguluyXP",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "gSamp3p9uyXP",
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for data processing during the pipelines:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "FRKSZmozuyXP",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "GhYbRJ0NuyXP",
-    "tags": []
-   },
-   "source": [
-    "**Delete local files:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "Msb_7QyLuyXP",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "cd ..\n",
-    "rm -r vertex-pipelines-end-to-end-samples"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "RKDx-NvyuyXO",
-    "tags": []
-   },
-   "source": [
-    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "sx_vKniMq9ZX",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make undeploy auto-approve=true"
+    "### Congratulations on successfully running your first ML pipelines!"
    ]
   }
  ],
  "metadata": {
   "colab": {
-   "provenance": []
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python (Local)",
    "language": "python",
-   "name": "python3"
+   "name": "local-base"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1114,11 +590,11 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {
-    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
    }
   }
  },
diff --git a/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb b/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
new file mode 100644
index 00000000..b5c38598
--- /dev/null
+++ b/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
@@ -0,0 +1,411 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Running Vertex Pipelines using E2E Samples repository - Infrastructure Cleanup\n",
+    "\n",
+    "\n",
+    "<table align=\"left\">\n",
+    "\n",
+    "  <td>\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb\">\n",
+    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
+    "      Open in Vertex AI Workbench\n",
+    "    </a>\n",
+    "  </td>                                                                                               \n",
+    "</table>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "24743cf4a1e1"
+   },
+   "source": [
+    "**_NOTE_**: This notebook has been tested in the following environment:\n",
+    "\n",
+    "* Python version = 3.9"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "tvgnzT1CKxrO",
+    "tags": []
+   },
+   "source": [
+    "## Overview\n",
+    "\n",
+    "This notebook shows you how to destroy infrastructure which was created in ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "d975e698c9a4"
+   },
+   "source": [
+    "### Objective\n",
+    "\n",
+    "In this tutorial, you learn how to destroy infrastructure using terraform.\n",
+    "\n",
+    "The steps performed include:\n",
+    "\n",
+    "* Destroy infrastructure using Terraform."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Prerequisites\n",
+    "\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Terraform](https://www.terraform.io)\n",
+    "- Infrastructure deployed ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Change working directory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Before You Begin"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "BF1j6f9HApxa",
+    "tags": []
+   },
+   "source": [
+    "### Set up your Google Cloud project\n",
+    "\n",
+    "**The following steps are required, regardless of your notebook environment.**\n",
+    "\n",
+    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
+    "\n",
+    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
+    "\n",
+    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "WReHDGG5g0XY"
+   },
+   "source": [
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "oM1iC_MfAts1",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
+    "# Set the project id\n",
+    "! gcloud config set project {PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Authenticate your Google Cloud account\n",
+    "\n",
+    "\n",
+    "As you're running a Jupyter environment on workbench, you are already authenticated."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Environment Setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In order to run make commands relevant environment variables need to be set. You can re-use `.env` file defined in [01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "load_dotenv()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "TpV-iwP9qw9c"
+   },
+   "source": [
+    "## Cleaning up\n",
+    "\n",
+    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
+    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+    "\n",
+    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Empty the buckets to enable their deletion:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete data transfer config:**\n",
+    "\n",
+    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import google.api_core.exceptions\n",
+    "from google.cloud import bigquery_datatransfer\n",
+    "\n",
+    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
+    "\n",
+    "transfer_config_name = \"my-transfer-config\" # Transfer Config Resource Name (projects/{project_number}/locations/{location}/transferConfigs/{transfer_config_id)\n",
+    "try:\n",
+    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
+    "except google.api_core.exceptions.NotFound:\n",
+    "    print(\"Transfer config not found.\")\n",
+    "else:\n",
+    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for the Chicago Taxi data:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for data processing during the pipelines:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.bin')\n",
+    "! make undeploy auto-approve=true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete local files:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "cd ..\n",
+    "rm -r vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Congratulations on successfully destroyed your infrastructure!"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python (Local)",
+   "language": "python",
+   "name": "local-base"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/notebooks/pipelines_workbench.ipynb b/docs/notebooks/workbench/pipelines_workbench.ipynb
similarity index 90%
rename from docs/notebooks/pipelines_workbench.ipynb
rename to docs/notebooks/workbench/pipelines_workbench.ipynb
index 89462d26..9eb4e1ab 100644
--- a/docs/notebooks/pipelines_workbench.ipynb
+++ b/docs/notebooks/workbench/pipelines_workbench.ipynb
@@ -37,18 +37,18 @@
     "<table align=\"left\">\n",
     "\n",
     "  <td>\n",
-    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_colab.ipynb\">\n",
+    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/pipelines_colab.ipynb\">\n",
     "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines.ipynb\">\n",
+    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/pipelines.ipynb\">\n",
     "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
     "      View on GitHub\n",
     "    </a>\n",
     "  </td>\n",
     "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/examples/pipelines_workbench.ipynb\">\n",
+    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/pipelines_workbench.ipynb\">\n",
     "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
     "      Open in Vertex AI Workbench\n",
     "    </a>\n",
@@ -56,18 +56,6 @@
     "</table>"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "2f814278-15d7-4ab1-9f1f-2c027e99ad6e",
-   "metadata": {
-    "id": "24743cf4a1e1"
-   },
-   "source": [
-    "**_NOTE_**: This notebook has been tested in the following environment:\n",
-    "\n",
-    "* Python version = 3.9"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "14d2d0de-b29b-4040-bee7-1452af822fca",
@@ -123,36 +111,6 @@
     "This public dataset is hosted in Google BigQuery."
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "dc0248c2-d658-47bc-8ccb-43f39b73700c",
-   "metadata": {
-    "id": "08d289fa873f"
-   },
-   "source": [
-    "### Dataset\n",
-    "\n",
-    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
-    "\n",
-    "\n",
-    "This public dataset is hosted in Google BigQuery."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cc563580-630b-46cd-8297-51f8ab620e8a",
-   "metadata": {
-    "id": "08d289fa873f"
-   },
-   "source": [
-    "### Dataset\n",
-    "\n",
-    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
-    "\n",
-    "\n",
-    "This public dataset is hosted in Google BigQuery."
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "53231e62-f463-4eb9-a327-3f5537effe80",
@@ -251,33 +209,6 @@
     "Install the packages required for executing this notebook."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7f37419b-7a30-44d6-ab16-8e69d952d944",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Install pyenv\n",
-    "!curl https://pyenv.run | bash"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "382725b5-80bf-4b76-ba58-553c7dd071e7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Add pyenv to PATH\n",
-    "import os\n",
-    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.pyenv/bin')\n",
-    "\n",
-    "# Initialize pyenv\n",
-    "!eval \"$(pyenv init -)\"\n",
-    "!eval \"$(pyenv virtualenv-init -)\""
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -286,6 +217,7 @@
    "outputs": [],
    "source": [
     "# Install poetry\n",
+    "import os\n",
     "!curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -\n",
     "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.poetry/bin')\n",
     "!poetry --version"
@@ -301,12 +233,6 @@
    },
    "outputs": [],
    "source": [
-    "# Install the correct Python version\n",
-    "! pyenv install -skip-existing\n",
-    "\n",
-    "# configure poetry \n",
-    "! poetry config virtualenvs.prefer-active-python true\n",
-    "\n",
     "#Install poetry dependencies for ML pipelines\n",
     "! make install"
    ]
@@ -334,26 +260,6 @@
     "3. **Add Terraform to PATH**."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2ea4f3ac-f072-482d-aa3d-25e5ba21e3d9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!rm -r $HOME/.bin"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7de12dad-1907-4867-8b0d-bcdc115e815f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!ls"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -445,9 +351,20 @@
     "id": "oM1iC_MfAts1",
     "tags": []
    },
-   "outputs": [],
-   "source": [
-    "PROJECT_ID = \"my-project-id\"\n",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1;33mWARNING:\u001b[0m You do not appear to have access to project [[my-project-id]] or it does not exist.\n",
+      "Are you sure you wish to set property [core/project] to [my-project-id]?\n",
+      "\n",
+      "Do you want to continue (Y/n)?  "
+     ]
+    }
+   ],
+   "source": [
+    "PROJECT_ID = \"[my-project-id]\"\n",
     "# Set the project id\n",
     "! gcloud config set project {PROJECT_ID}"
    ]
@@ -1023,57 +940,57 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cc67063a-337a-4517-9bd0-15f07d5bc5ee",
+   "id": "4aeb5933-65e7-46a4-a228-ac927510c117",
    "metadata": {
     "tags": []
    },
    "source": [
-    "**Delete local files:**"
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6d0aec50-4b7c-407c-b73f-825c40e3758b",
+   "id": "7c938e96-1139-4d84-abd8-a2fc5c10c35b",
    "metadata": {
+    "id": "sx_vKniMq9ZX",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "%%bash\n",
-    "cd ..\n",
-    "rm -r vertex-pipelines-end-to-end-samples"
+    "! make undeploy auto-approve=true"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "4aeb5933-65e7-46a4-a228-ac927510c117",
+   "id": "cc67063a-337a-4517-9bd0-15f07d5bc5ee",
    "metadata": {
     "tags": []
    },
    "source": [
-    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+    "**Delete local files:**"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7c938e96-1139-4d84-abd8-a2fc5c10c35b",
+   "id": "6d0aec50-4b7c-407c-b73f-825c40e3758b",
    "metadata": {
-    "id": "sx_vKniMq9ZX",
     "tags": []
    },
    "outputs": [],
    "source": [
-    "! make undeploy auto-approve=true"
+    "%%bash\n",
+    "cd ..\n",
+    "rm -r vertex-pipelines-end-to-end-samples"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "PySpark (Local)",
    "language": "python",
-   "name": "python3"
+   "name": "local-pyspark"
   },
   "language_info": {
    "codemirror_mode": {
@@ -1085,7 +1002,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

From fb80ecc742cee548c73ab06d3f3c1e8ecfe9964e Mon Sep 17 00:00:00 2001
From: Donatas M <125287387+donatas-dt@users.noreply.github.com>
Date: Thu, 28 Sep 2023 14:09:51 +0100
Subject: [PATCH 212/238] fix: Typo

---
 .../workbench/03_infrastructure_cleanup.ipynb         | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb b/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
index b5c38598..06ea8fb6 100644
--- a/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
+++ b/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
@@ -370,10 +370,11 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Congratulations on successfully destroyed your infrastructure!"
+    "### Congratulations on successfully destroying your infrastructure!"
    ]
   }
  ],
@@ -384,9 +385,9 @@
    "toc_visible": true
   },
   "kernelspec": {
-   "display_name": "Python (Local)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "local-base"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -398,11 +399,11 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.5"
   },
   "vscode": {
    "interpreter": {
-    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
    }
   }
  },

From 4138241825b5a3e069fc8c99a3a5dea8dfb67da9 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Tue, 7 Nov 2023 13:58:47 +0100
Subject: [PATCH 213/238] Simplify docs and notebooks

---
 Makefile                                      |   41 +-
 README.md                                     |  228 +--
 .../{bigquery-components => }/.python-version |    0
 components/bigquery-components/README.md      |   25 -
 components/bigquery-components/poetry.lock    |  968 -----------
 components/bigquery-components/pyproject.toml |   42 -
 .../src/bigquery_components/__init__.py       |    7 -
 .../bigquery-components/tests/conftest.py     |   50 -
 .../bigquery-components/tests/test_dummy.py   |    2 -
 .../{vertex-components => }/poetry.lock       |  576 +++----
 .../{vertex-components => }/pyproject.toml    |   10 +-
 .../components}/__init__.py                   |    2 +
 .../components/extract_table.py}              |    2 +-
 .../components}/lookup_model.py               |    0
 .../components}/model_batch_predict.py        |    0
 .../components}/upload_model.py               |    0
 .../{vertex-components => }/tests/conftest.py |    0
 .../test_extract_table.py}                    |    8 +-
 .../tests/test_lookup_model.py                |    4 +-
 .../tests/test_model_batch_predict.py         |    4 +-
 .../tests/test_upload_model.py                |    4 +-
 components/vertex-components/.python-version  |    1 -
 components/vertex-components/README.md        |   25 -
 cloudbuild/README.md => docs/AUTOMATION.md    |    0
 components/README.md => docs/COMPONENTS.md    |   10 +
 docs/{TESTING_SETUP.md => CONTRIBUTION.md}    |    0
 docs/INFRASTRUCTURE.md                        |   43 +
 pipelines/README.md => docs/PIPELINES.md      |   49 +-
 docs/notebooks/01_infrastructure_setup.ipynb  |  289 ++++
 docs/notebooks/02_run_pipelines.ipynb         |  254 +++
 .../notebooks/03_infrastructure_cleanup.ipynb |  199 +++
 .../local/01_infrastructure_setup.ipynb       |  469 ------
 docs/notebooks/local/02_run_pipelines.ipynb   |  606 -------
 .../local/03_infrastructure_cleanup.ipynb     |  406 -----
 docs/notebooks/local/pipelines.ipynb          |  912 -----------
 docs/notebooks/scripts/install_poetry.sh      |    6 +
 docs/notebooks/scripts/install_terraform.sh   |    9 +
 .../workbench/01_infrastructure_setup.ipynb   |  498 ------
 .../workbench/02_run_pipelines.ipynb          |  603 -------
 .../workbench/03_infrastructure_cleanup.ipynb |  412 -----
 .../workbench/pipelines_workbench.ipynb       | 1010 ------------
 env.sh.example                                |    6 +-
 pipelines/poetry.lock                         | 1423 -----------------
 pipelines/pyproject.toml                      |    7 +-
 .../src/pipelines/prediction/pipeline.py      |    2 +-
 pipelines/src/pipelines/training/pipeline.py  |    9 +-
 46 files changed, 1261 insertions(+), 7960 deletions(-)
 rename components/{bigquery-components => }/.python-version (100%)
 delete mode 100644 components/bigquery-components/README.md
 delete mode 100644 components/bigquery-components/poetry.lock
 delete mode 100644 components/bigquery-components/pyproject.toml
 delete mode 100644 components/bigquery-components/src/bigquery_components/__init__.py
 delete mode 100644 components/bigquery-components/tests/conftest.py
 delete mode 100644 components/bigquery-components/tests/test_dummy.py
 rename components/{vertex-components => }/poetry.lock (52%)
 rename components/{vertex-components => }/pyproject.toml (78%)
 rename components/{vertex-components/src/vertex_components => src/components}/__init__.py (79%)
 rename components/{bigquery-components/src/bigquery_components/extract_bq_to_dataset.py => src/components/extract_table.py} (99%)
 rename components/{vertex-components/src/vertex_components => src/components}/lookup_model.py (100%)
 rename components/{vertex-components/src/vertex_components => src/components}/model_batch_predict.py (100%)
 rename components/{vertex-components/src/vertex_components => src/components}/upload_model.py (100%)
 rename components/{vertex-components => }/tests/conftest.py (100%)
 rename components/{bigquery-components/tests/test_extract_bq_to_dataset.py => tests/test_extract_table.py} (89%)
 rename components/{vertex-components => }/tests/test_lookup_model.py (97%)
 rename components/{vertex-components => }/tests/test_model_batch_predict.py (96%)
 rename components/{vertex-components => }/tests/test_upload_model.py (99%)
 delete mode 100644 components/vertex-components/.python-version
 delete mode 100644 components/vertex-components/README.md
 rename cloudbuild/README.md => docs/AUTOMATION.md (100%)
 rename components/README.md => docs/COMPONENTS.md (77%)
 rename docs/{TESTING_SETUP.md => CONTRIBUTION.md} (100%)
 create mode 100644 docs/INFRASTRUCTURE.md
 rename pipelines/README.md => docs/PIPELINES.md (77%)
 create mode 100644 docs/notebooks/01_infrastructure_setup.ipynb
 create mode 100644 docs/notebooks/02_run_pipelines.ipynb
 create mode 100644 docs/notebooks/03_infrastructure_cleanup.ipynb
 delete mode 100644 docs/notebooks/local/01_infrastructure_setup.ipynb
 delete mode 100644 docs/notebooks/local/02_run_pipelines.ipynb
 delete mode 100644 docs/notebooks/local/03_infrastructure_cleanup.ipynb
 delete mode 100644 docs/notebooks/local/pipelines.ipynb
 create mode 100644 docs/notebooks/scripts/install_poetry.sh
 create mode 100644 docs/notebooks/scripts/install_terraform.sh
 delete mode 100644 docs/notebooks/workbench/01_infrastructure_setup.ipynb
 delete mode 100644 docs/notebooks/workbench/02_run_pipelines.ipynb
 delete mode 100644 docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
 delete mode 100644 docs/notebooks/workbench/pipelines_workbench.ipynb
 delete mode 100644 pipelines/poetry.lock

diff --git a/Makefile b/Makefile
index b9b71897..eeda7282 100644
--- a/Makefile
+++ b/Makefile
@@ -44,14 +44,8 @@ undeploy: ## DESTROY the Terraform infrastructure in your project. Requires VERT
 install: ## Set up local environment for Python development on pipelines
 	@cd pipelines && \
 	poetry install --with dev && \
-	cd .. && \
-	for component_group in components/*/ ; do \
-		echo "Setup for $$component_group" && \
-		cd "$$component_group" && \
-		poetry install --with dev && \
-		cd ../.. ;\
-	done ; \
-
+	cd ../components && \
+	poetry install --with dev
 
 compile: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
 	@cd pipelines/src && \
@@ -89,20 +83,17 @@ run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|pre
 	cd pipelines/src && \
 	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline} --wait=${wait}
 
-test: ## Run unit tests for a specific component group or for all component groups and the pipeline trigger code. Optionally specify GROUP=<component group e.g. vertex-components>
-	@if [ -n "${GROUP}" ]; then \
-		echo "Test components under components/${GROUP}" && \
-		cd components/${GROUP} && \
-		poetry run pytest ; \
-	else \
-		echo "Testing scripts" && \
-		cd pipelines && \
-		poetry run python -m pytest tests/utils &&\
-		cd .. && \
-		for i in components/*/ ; do \
-			echo "Test components under $$i" && \
-			cd "$$i" && \
-			poetry run pytest && \
-			cd ../.. ;\
-		done ; \
-	fi
+components ?= true
+test: ## Run unit tests. Specify components=<true|false> to test scripts and optionally components
+	@if [ $(components) = "true" ]; then \
+		echo "Testing components" && \
+		cd components && \
+		poetry run pytest && \
+		cd .. ;  \
+	elif [ $(components) != "false" ]; then \
+		echo "ValueError: components must be either true or false" ; \
+		exit ; \
+	fi && \
+	echo "Testing scripts" && \
+	cd pipelines && \
+	poetry run python -m pytest tests/utils
diff --git a/README.md b/README.md
index f2f7e556..e046568f 100644
--- a/README.md
+++ b/README.md
@@ -21,13 +21,17 @@ _AKA "Vertex AI Turbo Templates"_
 ## Introduction
 
 This repository provides a reference implementation of [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/) for creating a production-ready MLOps solution on Google Cloud.
-You can take this repository as a starting point you own ML use cases. The implementation includes:
+You can take this repository as a starting point you own ML use cases. 
+The implementation includes:
 
-* Infrastructure-as-Code using Terraform for a typical dev/test/prod setup of Vertex AI and other relevant services
-* ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case (using the [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset))
-* Reusable KFP components that can be used in ML pipelines
-* CI/CD using Google Cloud Build for linting, testing, and deploying ML pipelines
-* Developer scripts (Makefile, Python scripts etc)
+* **Infrastructure-as-Code** using Terraform for a typical dev/test/prod setup of Vertex AI and other relevant services
+* **ML training and prediction pipelines** using the Kubeflow Pipelines
+* **Reusable Kubeflow components** that can be used in common ML pipelines
+* **CI/CD** using Google Cloud Build for linting, testing, and deploying ML pipelines
+* **Developer scripts** (Makefile, Python scripts etc.)
+
+**Get started today by following [this step-by-step notebook tutorial](docs/notebooks)! 🚀**
+In this three-part notebook series you'll deploy a Google Cloud project and run production-ready ML pipelines using Vertex AI without writing a single line of code.
 
 ## Cloud Architecture
 
@@ -42,219 +46,113 @@ There are four different Google Cloud projects in use
 * `prod` - production environment
 * `admin` - separate Google Cloud project for setting up CI/CD in Cloud Build (since the CI/CD pipelines operate across the different environments)
 
-Vertex Pipelines are scheduled using Google Cloud Scheduler. Cloud Scheduler emits a Pub/Sub message that triggers a Cloud Function, which in turn triggers the Vertex Pipeline to run. _In future, this will be replaced with the Vertex Pipelines Scheduler (once there is a Terraform resource for it)._
-
-## Infrastructure
-
-The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):
-
-- `cloudfunction` - deploys a (Pub/Sub-triggered) Cloud Function from local source code
-- `scheduled_pipelines` - deploys Cloud Scheduler jobs that will trigger Vertex Pipeline runs (via the above Cloud Function)
-- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, Artifact Registry repos, service accounts, and IAM permissions.
+Vertex Pipelines are scheduled using Google Cloud Scheduler. 
+Cloud Scheduler emits a Pub/Sub message that triggers a Cloud Function, which in turn triggers the Vertex Pipeline to run. 
+_In future, this will be replaced with the Vertex Pipelines Scheduler (once there is a Terraform resource for it)._
 
-There is a Terraform configuration for each environment (dev/test/prod) under [`terraform/envs`](terraform/envs/).
+## Setup
 
-How to deploy this infrastructure is covered in a [later section](#deploying-infrastructure).
-
-## Developer setup
-
-### Prerequisites
+**Prerequisites:**
 
+- [Terraform](https://www.terraform.io/) for managing cloud infrastructure
+- [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate Terraform version (recommended) 
 - [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions
+- [Poetry](https://python-poetry.org/) for managing Python dependencies
 - [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)
 - Make
+- Cloned repo
 
-### Local setup
-
-1. Clone the repository locally (or create a new repo from this template)
-1. Install the correct Python version: `pyenv install`
-1. Install poetry - follow the instructions in the [poetry documentation](https://python-poetry.org/docs/#installation)
-1. Configure poetry to use the Python version from pyenv: `poetry config virtualenvs.prefer-active-python true`
-1. Install poetry dependencies for ML pipelines: `make install`
-1. Install pre-commit hooks: `cd pipelines && poetry run pre-commit install`
-1. Copy `env.sh.example` to `env.sh`, and update the environment variables in `env.sh` for your dev environment (particularly `VERTEX_PROJECT_ID`, `VERTEX_LOCATION` and `RESOURCE_SUFFIX`)
-1. Authenticate to Google Cloud
-    1. `gcloud auth login`
-    1. `gcloud auth application-default login`
-
-### Deploying infrastructure
-
-You will need four Google Cloud projects:
-
-- dev
-- test
-- prod
-- admin
+**Deploy infrastructure:**
 
+You will need four Google Cloud projects dev, test, prod, and admin.
 The Cloud Build pipelines will run in the _admin_ project, and deploy resources into the dev/test/prod projects.
-
 Before your CI/CD pipelines can deploy the infrastructure, you will need to set up a Terraform state bucket for each environment:
 
 ```bash
-gsutil mb -l <GCP region e.g. europe-west2> -p <DEV PROJECT ID> --pap=enforced gs://<DEV PROJECT ID>-tfstate && gsutil ubla set on gs://<DEV PROJECT ID>-tfstate
-
-gsutil mb -l <GCP region e.g. europe-west2> -p <TEST PROJECT ID> --pap=enforced gs://<TEST PROJECT ID>-tfstate && gsutil ubla set on gs://<TEST PROJECT ID>-tfstate
-
-gsutil mb -l <GCP region e.g. europe-west2> -p <PROD PROJECT ID> --pap=enforced gs://<PROD PROJECT ID>-tfstate && gsutil ubla set on gs://<PROD PROJECT ID>-tfstate
+export DEV_PROJECT_ID=my-dev-gcp-project
+export DEV_LOCATION=europe-west2
+gsutil mb -l DEV_LOCATION -p DEV_PROJECT_ID --pap=enforced gs://DEV_PROJECT_ID-tfstate && \
+  gsutil ubla set on gs://DEV_PROJECT_ID-tfstate
 ```
 
-You will also need to manually enable the Cloud Resource Manager and Service Usage APs for your _admin_ project:
+Enable APIs in admin project:
 
 ```bash
-gcloud services enable cloudresourcemanager.googleapis.com --project=<ADMIN PROJECT ID>
-gcloud services enable serviceusage.googleapis.com --project=<ADMIN PROJECT ID>
+export ADMIN_PROJECT_ID=my-admin-gcp-project
+gcloud services enable cloudresourcemanager.googleapis.com serviceusage.googleapis.com --project=ADMIN_PROJECT_ID
 ```
 
-Install Terraform on your local machine. We recommend using [`tfswitch`](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version for you (run `tfswitch` from the [`terraform/envs/dev`](terraform/envs/dev/) directory).
-
-Now you can deploy the infrastructure using Terraform:
-
 ```bash
 make deploy env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
-make deploy env=test VERTEX_PROJECT_ID=<TEST PROJECT ID>
-make deploy env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
 ```
 
-#### Optional - Tearing down infrastructure
+More details about infrastructure is explained in [this README](docs/PIPELINES.md).
+It describes the scheduling of pipelines and how to tear down infrastructure.
 
-To tear down the infrastructure you have created with Terraform, run these commands:
+**Install dependencies:**
 
 ```bash
-make undeploy env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
-make undeploy env=test VERTEX_PROJECT_ID=<TEST PROJECT ID>
-make undeploy env=prod VERTEX_PROJECT_ID=<PROD PROJECT ID>
+pyenv install -skip-existing                          # install Python
+poetry config virtualenvs.prefer-active-python true   # configure Poetry
+make install                                          # install Python dependencies
+cd pipelines && poetry run pre-commit install         # install pre-commit hooks
+cp env.sh.example env.sh
 ```
 
-### Example ML pipelines
+Update the environment variables for your dev environment in `env.sh`.
 
-This repository contains example ML training and prediction pipelines for scikit-learn/XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips). The details of these can be found in the [separate README](pipelines/README.md).
+**Authenticate to Google Cloud:**
 
-#### Pre-requisites
-
-Before you can run these example pipelines successfully there are a few additional things you will need to deploy into each environment (they have not been included in the Terraform code as they are specific to these Chicago Taxi pipelines)
-
-1. Create a new BigQuery dataset for the Chicago Taxi data:
-
-```
-bq --location=${VERTEX_LOCATION} mk --dataset "${VERTEX_PROJECT_ID}:chicago_taxi_trips"
-```
-
-2. Create a new BigQuery dataset for data processing during the pipelines:
-
-```
-bq --location=${VERTEX_LOCATION} mk --dataset "${VERTEX_PROJECT_ID}:preprocessing"
-```
-
-3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project
-
-```
-bq mk --transfer_config \
-  --project_id=${VERTEX_PROJECT_ID} \
-  --data_source="cross_region_copy" \
-  --target_dataset="chicago_taxi_trips" \
-  --display_name="Chicago taxi trip mirror" \
-  --params='{"source_dataset_id":"'"chicago_taxi_trips"'","source_project_id":"'"bigquery-public-data"'"}'
+```bash
+gcloud auth login
+gcloud auth application-default login
 ```
 
-### Building the container images
+## Run
 
-The [model/](/model/) directory contains the code for custom training and serving container images, including the model training script at [model/training/train.py](model/training/train.py). You can modify this to suit your own use case.
+This repository contains example ML training and prediction pipelines which are explained in [this README](docs/PIPELINES.md).
 
+**Build containers:** The [model/](/model/) directory contains the code for custom training and serving container images, including the model training script at [model/training/train.py](model/training/train.py). 
+You can modify this to suit your own use case.
 Build the training and serving container images and push them to Artifact Registry with:
 
 ```bash
-make build
+make build [ targets=training serving ]
 ```
 
-Optionally specify the `target` variable to only build one of the images. For example, to build only the serving image:
+Optionally specify the `targets` variable to only build one of the images.
 
-```bash
-make build target=serving
-```
+**Execute pipelines:** Vertex AI Pipelines uses KubeFlow to orchestrate your training steps, as such you'll need to:
 
-### Running Pipelines
+1. Compile the pipeline
+1. Build dependent Docker containers
+1. Run the pipeline in Vertex AI
 
-You can run the training pipeline (for example) with:
+Execute the following command to run through steps 1-3:
 
 ```bash
-make run pipeline=training [ wait=<true|false> ]
+make run pipeline=training [ wait=<true|false> ] [ build=<true|false> ] [ compile=<true|false> ]
 ```
 
-This will execute the pipeline using the chosen template on Vertex AI, namely it will:
-
-1. Compile the pipeline using the Kubeflow Pipelines SDK
-1. Trigger the pipeline with the help of `pipelines/trigger/main.py`
-1. (optional) Wait for pipeline to finish before returning if `wait` is set to `true` (default is false)
-
-#### Pipeline input parameters
-
-The ML pipelines have input parameters. As you can see in the pipeline definition files (`pipelines/src/pipelines/<training|prediction>/pipeline.py`), they have default values, and some of these default values are derived from environment variables (which in turn are defined in `env.sh`).
+The make run command has the following true/false flags:
 
-When triggering ad hoc runs in your dev/sandbox environment, or when running the E2E tests in CI, these default values are used. For the test and production deployments, the pipeline parameters are defined in the Terraform code for the Cloud Scheduler jobs (`terraform/envs/<dev|test|prod>/scheduled_jobs.auto.tfvars`) - see the section on [Scheduling pipelines](#scheduling-pipelines).
+- `build` - re-build containers for training & serving code (limit by setting targets=training to build only one of the containers)
+- `compile` - re-compile the pipeline to YAML
+- `wait` - run the pipeline (a-)sync
 
-## Testing
+## Test
 
 Unit tests are performed using [pytest](https://docs.pytest.org).
-The unit tests for custom KFP components are run on each pull request. To run them on your local machine:
+The unit tests are run on each pull request. 
+To run them locally you can execute the following command and optionally enable or disable testing of components:
 
 ```
-make test
+make test [ components=<true|false> ]
 ```
 
-Alternatively, only test one of the component groups by running:
-```
-make test GROUP=vertex-components
-```
-
-There are also unit tests for the utility scripts in [pipelines/src/pipelines/utils](/pipelines/src/pipelines/utils/). To run them on your local machine:
-
-```
-make test
-```
-
-## Customize pipelines
-
-### Adding a new pipeline
-
-This repository contains a training and a (batch) prediction pipeline. To add another ML pipeline (e.g. for continuous evaluation), create a new directory under the `pipelines/src/pipelines` directory. Within your new pipeline folder, create a `pipeline.py` file - this is where you should provide your pipeline definition using the KFP DSL (in a function named `pipeline`).
-
-Alternatively, you can just copy and paste the `training` or `prediction` directory.
-
-See below for an example folder structure:
-
-```
-vertex-pipelines-end-to-end-samples
-|
-├── pipelines
-│   ├── src
-│   │   ├── pipelines
-│   │   │   ├── new_pipeline
-│   │   │   │   ├── pipeline.py
-│   │   │   │   └── queries
-│   │   │   │       └── my_query.sql
-```
-
-Make sure that you give the ML pipeline a unique name in the `@pipeline` decorator.
-
-To run your pipeline, use `make run` as before (optionally adding parameter to wait until pipeline is finished before returning - defaults to false):
-
-```bash
-make run pipeline=your_new_pipeline [ wait=<true|false> ]
-```
-
-Some of the scripts e.g. CI/CD pipelines assume only a training and prediction pipeline. You will need to adapt these to add in the compile, run and upload steps for your new pipeline in [cloudbuild/pr-checks.yaml](/cloudbuild/pr-checks.yaml), [cloudbuild/e2e-test.yaml](/cloudbuild/e2e-test.yaml) and [cloudbuild/release.yaml](/cloudbuild/release.yaml).
-
-### Scheduling pipelines
-
-Terraform is used to deploy Cloud Scheduler jobs that trigger the Vertex Pipeline runs. This is done by the CI/CD pipelines (see section below on CI/CD).
-
-To schedule pipelines into an environment, you will need to provide the `cloud_schedulers_config` variable to the Terraform configuration for the relevant environment. You can find an example of this configuration in [`terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example`](terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example). Copy this example file into the relevant directory for your environment (e.g. `terraform/envs/dev` for the dev environment) and remove the `.example` suffix. Adjust the configuration file as appropriate.
-
-## CI/CD
-
-For details on setting up CI/CD, see the [CI/CD README](/cloudbuild/README.md).
+## Automation
 
-For details on setting up CI/CD for the template codebase itself (instead of for your own ML use case), follow the guide [here](/docs/TESTING_SETUP.md).
+For details on setting up CI/CD, see [this README](/docs/AUTOMATION.md).
 
 ## Putting it all together
 
diff --git a/components/bigquery-components/.python-version b/components/.python-version
similarity index 100%
rename from components/bigquery-components/.python-version
rename to components/.python-version
diff --git a/components/bigquery-components/README.md b/components/bigquery-components/README.md
deleted file mode 100644
index 2fce84dd..00000000
--- a/components/bigquery-components/README.md
+++ /dev/null
@@ -1,25 +0,0 @@
-<!-- 
-Copyright 2022 Google LLC
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    https://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
- -->
-
-# BigQuery Components
-
-A python package which provides common BigQuery components for interacting with BigQuery.
-Currently, the following components are implemented:
-
-- `bq_query_to_table`: Execute a SQL query and persist results in a table.
-- `extract_bq_to_dataset`: Export a table to a KubeFlow dataset on Cloud Storage.
-
-These components either augment, extend, or add new functionalities that aren't found in [Google Cloud Pipeline Components list](https://cloud.google.com/vertex-ai/docs/pipelines/gcpc-list).
diff --git a/components/bigquery-components/poetry.lock b/components/bigquery-components/poetry.lock
deleted file mode 100644
index c39c4aac..00000000
--- a/components/bigquery-components/poetry.lock
+++ /dev/null
@@ -1,968 +0,0 @@
-# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
-
-[[package]]
-name = "cachetools"
-version = "5.3.1"
-description = "Extensible memoizing collections and decorators"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
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-    {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
-]
-
-[[package]]
-name = "certifi"
-version = "2023.7.22"
-description = "Python package for providing Mozilla's CA Bundle."
-category = "main"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
-    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
-]
-
-[[package]]
-name = "charset-normalizer"
-version = "3.2.0"
-description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
-category = "main"
-optional = false
-python-versions = ">=3.7.0"
-files = [
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-files = [
-    {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
-    {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
-]
-
-[[package]]
-name = "urllib3"
-version = "1.26.16"
-description = "HTTP library with thread-safe connection pooling, file post, and more."
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
-files = [
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-]
-
-[package.extras]
-brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
-secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
-socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
-
-[[package]]
-name = "websocket-client"
-version = "1.6.3"
-description = "WebSocket client for Python with low level API options"
-category = "main"
-optional = false
-python-versions = ">=3.8"
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-]
-
-[package.extras]
-docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
-optional = ["python-socks", "wsaccel"]
-test = ["websockets"]
-
-[metadata]
-lock-version = "2.0"
-python-versions = ">=3.9,<3.11"
-content-hash = "22b5fc84eafddbe9d7bd4f3d39f53736433db333da7a8bc4186470ed1b0cfd42"
diff --git a/components/bigquery-components/pyproject.toml b/components/bigquery-components/pyproject.toml
deleted file mode 100644
index e040ce11..00000000
--- a/components/bigquery-components/pyproject.toml
+++ /dev/null
@@ -1,42 +0,0 @@
-[tool.poetry]
-name = "bigquery-components"
-version = "0.1.0"
-authors = ["Example User <user@example.com>"]
-description = "KubeFlow components for BigQuery"
-readme = "README.md"
-classifiers = [
-    "Development Status :: 3 - Alpha",
-    "Intended Audience :: Developers",
-    "Programming Language :: Python :: 3.9",
-]
-
-[tool.poetry.dependencies]
-python = ">=3.9,<3.11"
-kfp = "^2.0.1"
-pyyaml = "6.0.1"
-
-[tool.poetry.group.dev.dependencies]
-google-cloud-bigquery = "2.30.0"
-pytest = ">=7.3.1,<8.0.0"
-
-[build-system]
-requires = ["poetry-core>=1.0.0"]
-build-backend = "poetry.core.masonry.api"
-
-[tool.flake8]
-max-line-length = 88
-per-file-ignores = [
-    "E203",
-    "F841"
-]
-ignore = [
-    "E203",
-    "F841",
-]
-
-[tool.pytest.ini_options]
-pythonpath = [
-  "src"
-]
-testpaths = "tests"
-junit_family = "xunit2"
diff --git a/components/bigquery-components/src/bigquery_components/__init__.py b/components/bigquery-components/src/bigquery_components/__init__.py
deleted file mode 100644
index e979abab..00000000
--- a/components/bigquery-components/src/bigquery_components/__init__.py
+++ /dev/null
@@ -1,7 +0,0 @@
-from .extract_bq_to_dataset import extract_bq_to_dataset
-
-
-__version__ = "0.0.1"
-__all__ = [
-    "extract_bq_to_dataset",
-]
diff --git a/components/bigquery-components/tests/conftest.py b/components/bigquery-components/tests/conftest.py
deleted file mode 100644
index 898c2590..00000000
--- a/components/bigquery-components/tests/conftest.py
+++ /dev/null
@@ -1,50 +0,0 @@
-# Copyright 2022 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import pytest
-import kfp.v2.dsl
-
-
-@pytest.fixture(autouse=True)
-def mock_kfp_artifact(monkeypatch):
-    """
-    This fixture runs once after all tests are collected. It mocks the Artifact object
-    (and thus any derived classes such as Dataset, Model, etc.) to return the URI as
-    the path.
-
-    Unit tests set the URI of artifacts, however, KFP components use Artifact.path to
-    retrieve paths to files. If a URI doesn't start with gs:// or minio:// or s3://,
-    the path with be None. This behaviour is avoided by mocking the Artifact._get_path
-    method.
-
-    Args:
-        monkeypatch: Used to patch the decorator `@component` in `kfp.v2.dsl`.
-            This prevents KFP from changing the Python functions when applying
-            pytests.
-
-    Returns:
-        None
-
-    """
-
-    def _get_path(self):
-        """
-        Returns:
-            str: The URI path of the Artifact
-        """
-        # simply return the URI
-        return self.uri
-
-    # mock the _get_path method of Artifact which is used by the property path
-    monkeypatch.setattr(kfp.v2.dsl.Artifact, "_get_path", _get_path)
diff --git a/components/bigquery-components/tests/test_dummy.py b/components/bigquery-components/tests/test_dummy.py
deleted file mode 100644
index 10cf3ad0..00000000
--- a/components/bigquery-components/tests/test_dummy.py
+++ /dev/null
@@ -1,2 +0,0 @@
-def test_dummy():
-    pass
diff --git a/components/vertex-components/poetry.lock b/components/poetry.lock
similarity index 52%
rename from components/vertex-components/poetry.lock
rename to components/poetry.lock
index 5152ad6d..57851f68 100644
--- a/components/vertex-components/poetry.lock
+++ b/components/poetry.lock
@@ -1,22 +1,20 @@
-# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
 
 [[package]]
 name = "cachetools"
-version = "5.3.1"
+version = "5.3.2"
 description = "Extensible memoizing collections and decorators"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
-    {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
+    {file = "cachetools-5.3.2-py3-none-any.whl", hash = "sha256:861f35a13a451f94e301ce2bec7cac63e881232ccce7ed67fab9b5df4d3beaa1"},
+    {file = "cachetools-5.3.2.tar.gz", hash = "sha256:086ee420196f7b2ab9ca2db2520aca326318b68fe5ba8bc4d49cca91add450f2"},
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 [[package]]
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 version = "2023.7.22"
 description = "Python package for providing Mozilla's CA Bundle."
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
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+    {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:d0eccceffcb53201b5bfebb52600a5fb483a20b61da9dbc885f8b103cbe7598c"},
+    {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:9f96df6923e21816da7e0ad3fd47dd8f94b2a5ce594e00677c0013018b813458"},
+    {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:7f04c839ed0b6b98b1a7501a002144b76c18fb1c1850c8b98d458ac269e26ed2"},
+    {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:34d1c8da1e78d2e001f363791c98a272bb734000fcef47a491c1e3b0505657a8"},
+    {file = "charset_normalizer-3.3.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:ff8fa367d09b717b2a17a052544193ad76cd49979c805768879cb63d9ca50561"},
+    {file = "charset_normalizer-3.3.2-cp39-cp39-win32.whl", hash = "sha256:aed38f6e4fb3f5d6bf81bfa990a07806be9d83cf7bacef998ab1a9bd660a581f"},
+    {file = "charset_normalizer-3.3.2-cp39-cp39-win_amd64.whl", hash = "sha256:b01b88d45a6fcb69667cd6d2f7a9aeb4bf53760d7fc536bf679ec94fe9f3ff3d"},
+    {file = "charset_normalizer-3.3.2-py3-none-any.whl", hash = "sha256:3e4d1f6587322d2788836a99c69062fbb091331ec940e02d12d179c1d53e25fc"},
 ]
 
 [[package]]
 name = "click"
 version = "8.1.7"
 description = "Composable command line interface toolkit"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -128,7 +139,6 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -140,7 +150,6 @@ files = [
 name = "docstring-parser"
 version = "0.15"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
-category = "main"
 optional = false
 python-versions = ">=3.6,<4.0"
 files = [
@@ -152,7 +161,6 @@ files = [
 name = "exceptiongroup"
 version = "1.1.3"
 description = "Backport of PEP 654 (exception groups)"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -165,14 +173,13 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "google-api-core"
-version = "2.11.1"
+version = "2.12.0"
 description = "Google API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.11.1.tar.gz", hash = "sha256:25d29e05a0058ed5f19c61c0a78b1b53adea4d9364b464d014fbda941f6d1c9a"},
-    {file = "google_api_core-2.11.1-py3-none-any.whl", hash = "sha256:d92a5a92dc36dd4f4b9ee4e55528a90e432b059f93aee6ad857f9de8cc7ae94a"},
+    {file = "google-api-core-2.12.0.tar.gz", hash = "sha256:c22e01b1e3c4dcd90998494879612c38d0a3411d1f7b679eb89e2abe3ce1f553"},
+    {file = "google_api_core-2.12.0-py3-none-any.whl", hash = "sha256:ec6054f7d64ad13b41e43d96f735acbd763b0f3b695dabaa2d579673f6a6e160"},
 ]
 
 [package.dependencies]
@@ -190,21 +197,19 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.23.0"
+version = "2.23.4"
 description = "Google Authentication Library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.23.0.tar.gz", hash = "sha256:753a26312e6f1eaeec20bc6f2644a10926697da93446e1f8e24d6d32d45a922a"},
-    {file = "google_auth-2.23.0-py2.py3-none-any.whl", hash = "sha256:2cec41407bd1e207f5b802638e32bb837df968bb5c05f413d0fa526fac4cf7a7"},
+    {file = "google-auth-2.23.4.tar.gz", hash = "sha256:79905d6b1652187def79d491d6e23d0cbb3a21d3c7ba0dbaa9c8a01906b13ff3"},
+    {file = "google_auth-2.23.4-py2.py3-none-any.whl", hash = "sha256:d4bbc92fe4b8bfd2f3e8d88e5ba7085935da208ee38a134fc280e7ce682a05f2"},
 ]
 
 [package.dependencies]
 cachetools = ">=2.0.0,<6.0"
 pyasn1-modules = ">=0.2.1"
 rsa = ">=3.1.4,<5"
-urllib3 = "<2.0"
 
 [package.extras]
 aiohttp = ["aiohttp (>=3.6.2,<4.0.0.dev0)", "requests (>=2.20.0,<3.0.0.dev0)"]
@@ -215,56 +220,56 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.30.1"
+version = "1.36.0"
 description = "Vertex AI API client library"
-category = "dev"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "google-cloud-aiplatform-1.30.1.tar.gz", hash = "sha256:7552a6b2e66d7a9ff3c4b2bb95b0e9c182e7475dfb35d6347e9299f78779135a"},
-    {file = "google_cloud_aiplatform-1.30.1-py2.py3-none-any.whl", hash = "sha256:ab1bbd4cf83cf583b7dea7e53421ad076f18b63e93cb22fb53c03176d5aa9258"},
+    {file = "google-cloud-aiplatform-1.36.0.tar.gz", hash = "sha256:c35eb179fa3107c262024a63bb4a3dc1887678424a0b9f49f0da3f5179896186"},
+    {file = "google_cloud_aiplatform-1.36.0-py2.py3-none-any.whl", hash = "sha256:06adb1605208a9bdbadd8c4deeaeb6511a7f59220ef606e2d95ccc1da705ebda"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.32.0,<2.0.0 || >=2.8.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.32.0,<2.0.dev0 || >=2.8.dev0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-bigquery = ">=1.15.0,<4.0.0dev"
 google-cloud-resource-manager = ">=1.3.3,<3.0.0dev"
 google-cloud-storage = ">=1.32.0,<3.0.0dev"
 packaging = ">=14.3"
 proto-plus = ">=1.22.0,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
-shapely = "<2.0.0"
+shapely = "<3.0.0dev"
 
 [package.extras]
 autologging = ["mlflow (>=1.27.0,<=2.1.1)"]
 cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
-datasets = ["pyarrow (>=3.0.0,<8.0dev)"]
+datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)"]
 endpoint = ["requests (>=2.28.1)"]
-full = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pyyaml (>=5.3,<7)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
+full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.103.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (==0.0.11)", "google-vizier (==0.0.4)", "google-vizier (>=0.0.14)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (==5.3.1)", "ray[default] (>=2.4,<2.5)", "ray[default] (>=2.5,<2.5.1)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
 lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"]
 metadata = ["numpy (>=1.15.0)", "pandas (>=1.0.0)"]
-pipelines = ["pyyaml (>=5.3,<7)"]
-prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<0.76.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"]
+pipelines = ["pyyaml (==5.3.1)"]
+prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<0.103.1)", "httpx (>=0.23.0,<0.25.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"]
+preview = ["cloudpickle (<3.0)", "google-cloud-logging (<4.0)"]
 private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"]
+ray = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "pandas (>=1.0.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "ray[default] (>=2.4,<2.5)", "ray[default] (>=2.5,<2.5.1)"]
 tensorboard = ["tensorflow (>=2.3.0,<3.0.0dev)"]
-testing = ["docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.76.0)", "google-cloud-bigquery-storage", "google-vizier (==0.0.4)", "grpcio-testing", "ipython", "kfp", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3,<7)", "requests (>=2.28.1)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
-vizier = ["google-vizier (==0.0.4)"]
+testing = ["bigframes", "cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.103.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (==0.0.11)", "google-vizier (==0.0.4)", "google-vizier (>=0.0.14)", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "ipython", "kfp", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyfakefs", "pytest-asyncio", "pytest-xdist", "pyyaml (==5.3.1)", "ray[default] (>=2.4,<2.5)", "ray[default] (>=2.5,<2.5.1)", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<=2.12.0)", "tensorflow (>=2.4.0,<3.0.0dev)", "torch (>=2.0.0,<2.1.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost", "xgboost-ray"]
+vizier = ["google-vizier (==0.0.11)", "google-vizier (==0.0.4)", "google-vizier (>=0.0.14)", "google-vizier (>=0.1.6)"]
 xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "3.11.4"
+version = "3.13.0"
 description = "Google BigQuery API client library"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-bigquery-3.11.4.tar.gz", hash = "sha256:697df117241a2283bcbb93b21e10badc14e51c9a90800d2a7e1a3e1c7d842974"},
-    {file = "google_cloud_bigquery-3.11.4-py2.py3-none-any.whl", hash = "sha256:5fa7897743a0ed949ade25a0942fc9e7557d8fce307c6f8a76d1b604cf27f1b1"},
+    {file = "google-cloud-bigquery-3.13.0.tar.gz", hash = "sha256:794ccfc93ccb0e0ad689442f896f9c82de56da0fe18a195531bb37096c2657d6"},
+    {file = "google_cloud_bigquery-3.13.0-py2.py3-none-any.whl", hash = "sha256:eda3dbcff676e17962c54e5224e415b55e4f6833a5c896c6c8902b69e7dba4b4"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
 google-cloud-core = ">=1.6.0,<3.0.0dev"
 google-resumable-media = ">=0.6.0,<3.0dev"
 grpcio = ">=1.47.0,<2.0dev"
@@ -275,9 +280,9 @@ python-dateutil = ">=2.7.2,<3.0dev"
 requests = ">=2.21.0,<3.0.0dev"
 
 [package.extras]
-all = ["Shapely (>=1.8.4,<2.0dev)", "db-dtypes (>=0.3.0,<2.0.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)", "ipywidgets (>=7.7.0)", "opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)", "tqdm (>=4.7.4,<5.0.0dev)"]
+all = ["Shapely (>=1.8.4,<3.0.0dev)", "db-dtypes (>=0.3.0,<2.0.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)", "ipywidgets (>=7.7.0)", "opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)", "tqdm (>=4.7.4,<5.0.0dev)"]
 bqstorage = ["google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "pyarrow (>=3.0.0)"]
-geopandas = ["Shapely (>=1.8.4,<2.0dev)", "geopandas (>=0.9.0,<1.0dev)"]
+geopandas = ["Shapely (>=1.8.4,<3.0.0dev)", "geopandas (>=0.9.0,<1.0dev)"]
 ipython = ["ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)"]
 ipywidgets = ["ipykernel (>=6.0.0)", "ipywidgets (>=7.7.0)"]
 opentelemetry = ["opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)"]
@@ -288,7 +293,6 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 name = "google-cloud-core"
 version = "2.3.3"
 description = "Google Cloud API client core library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -297,7 +301,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.6,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
@@ -307,7 +311,6 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)"]
 name = "google-cloud-pipeline-components"
 version = "2.3.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
-category = "dev"
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
@@ -315,7 +318,7 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-cloud-aiplatform = ">=1.14.0,<2"
 kfp = ">=2.0.0b10,<3.0.0"
 
@@ -327,7 +330,6 @@ tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 name = "google-cloud-resource-manager"
 version = "1.10.4"
 description = "Google Cloud Resource Manager API client library"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -336,27 +338,27 @@ files = [
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
 proto-plus = ">=1.22.0,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.11.0"
+version = "2.13.0"
 description = "Google Cloud Storage API client library"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
-google-auth = ">=1.25.0,<3.0dev"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-auth = ">=2.23.3,<3.0dev"
 google-cloud-core = ">=2.3.0,<3.0dev"
+google-crc32c = ">=1.0,<2.0dev"
 google-resumable-media = ">=2.6.0"
 requests = ">=2.18.0,<3.0.0dev"
 
@@ -367,7 +369,6 @@ protobuf = ["protobuf (<5.0.0dev)"]
 name = "google-crc32c"
 version = "1.5.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -448,7 +449,6 @@ testing = ["pytest"]
 name = "google-resumable-media"
 version = "2.6.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
-category = "main"
 optional = false
 python-versions = ">= 3.7"
 files = [
@@ -465,14 +465,13 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.60.0"
+version = "1.61.0"
 description = "Common protobufs used in Google APIs"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -486,7 +485,6 @@ grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 name = "grpc-google-iam-v1"
 version = "0.12.6"
 description = "IAM API client library"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -501,67 +499,74 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 
 [[package]]
 name = "grpcio"
-version = "1.58.0"
+version = "1.59.2"
 description = "HTTP/2-based RPC framework"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
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+    {file = "grpcio-1.59.2-cp39-cp39-win32.whl", hash = "sha256:686e975a5d16602dc0982c7c703948d17184bd1397e16c8ee03511ecb8c4cdda"},
+    {file = "grpcio-1.59.2-cp39-cp39-win_amd64.whl", hash = "sha256:242adc47725b9a499ee77c6a2e36688fa6c96484611f33b1be4c57ab075a92dd"},
+    {file = "grpcio-1.59.2.tar.gz", hash = "sha256:d8f9cd4ad1be90b0cf350a2f04a38a36e44a026cac1e036ac593dc48efe91d52"},
 ]
 
 [package.extras]
-protobuf = ["grpcio-tools (>=1.58.0)"]
+protobuf = ["grpcio-tools (>=1.59.2)"]
 
 [[package]]
 name = "grpcio-status"
 version = "1.48.2"
 description = "Status proto mapping for gRPC"
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -578,7 +583,6 @@ protobuf = ">=3.12.0"
 name = "idna"
 version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
-category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -590,7 +594,6 @@ files = [
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -600,19 +603,18 @@ files = [
 
 [[package]]
 name = "kfp"
-version = "2.2.0"
+version = "2.4.0"
 description = "Kubeflow Pipelines SDK"
-category = "main"
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "kfp-2.2.0.tar.gz", hash = "sha256:f4b243e11cc7e6a34dcb3af348b2784ba02f6fa2707b000d215d108bed338518"},
+    {file = "kfp-2.4.0.tar.gz", hash = "sha256:44c25ce80b948629bf0fb0815b49d8d97039a825597a4378078bbaa0610aef69"},
 ]
 
 [package.dependencies]
 click = ">=8.0.0,<9"
 docstring-parser = ">=0.7.3,<1"
-google-api-core = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.6.1,<3"
 google-cloud-storage = ">=2.2.1,<3"
 kfp-pipeline-spec = "0.2.2"
@@ -632,7 +634,6 @@ kubernetes = ["kfp-kubernetes (<2)"]
 name = "kfp-pipeline-spec"
 version = "0.2.2"
 description = "Kubeflow Pipelines pipeline spec"
-category = "main"
 optional = false
 python-versions = ">=3.7.0"
 files = [
@@ -644,13 +645,12 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "2.0.1"
+version = "2.0.3"
 description = "Kubeflow Pipelines API"
-category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "kfp-server-api-2.0.1.tar.gz", hash = "sha256:4851f414d8f56e0ddd4383ba6de9992debddd2df95e1ecd63b01954c25131abb"},
+    {file = "kfp-server-api-2.0.3.tar.gz", hash = "sha256:89701d5882f80f7a0445b76de173a1d9ad6dc17b10854a9d9901f18e121e78e2"},
 ]
 
 [package.dependencies]
@@ -663,7 +663,6 @@ urllib3 = ">=1.15"
 name = "kubernetes"
 version = "26.1.0"
 description = "Kubernetes python client"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -681,16 +680,56 @@ requests-oauthlib = "*"
 setuptools = ">=21.0.0"
 six = ">=1.9.0"
 urllib3 = ">=1.24.2"
-websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.0 || >=0.43.0"
+websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
 
 [package.extras]
 adal = ["adal (>=1.0.2)"]
 
+[[package]]
+name = "numpy"
+version = "1.26.1"
+description = "Fundamental package for array computing in Python"
+optional = false
+python-versions = "<3.13,>=3.9"
+files = [
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+    {file = "numpy-1.26.1-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:6965888d65d2848e8768824ca8288db0a81263c1efccec881cb35a0d805fcd2f"},
+    {file = "numpy-1.26.1.tar.gz", hash = "sha256:c8c6c72d4a9f831f328efb1312642a1cafafaa88981d9ab76368d50d07d93cbe"},
+]
+
 [[package]]
 name = "oauthlib"
 version = "3.2.2"
 description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -705,21 +744,19 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 
 [[package]]
 name = "packaging"
-version = "23.1"
+version = "23.2"
 description = "Core utilities for Python packages"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "packaging-23.1-py3-none-any.whl", hash = "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61"},
-    {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
+    {file = "packaging-23.2-py3-none-any.whl", hash = "sha256:8c491190033a9af7e1d931d0b5dacc2ef47509b34dd0de67ed209b5203fc88c7"},
+    {file = "packaging-23.2.tar.gz", hash = "sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5"},
 ]
 
 [[package]]
 name = "pluggy"
 version = "1.3.0"
 description = "plugin and hook calling mechanisms for python"
-category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -735,7 +772,6 @@ testing = ["pytest", "pytest-benchmark"]
 name = "proto-plus"
 version = "1.22.3"
 description = "Beautiful, Pythonic protocol buffers."
-category = "dev"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -753,7 +789,6 @@ testing = ["google-api-core[grpc] (>=1.31.5)"]
 name = "protobuf"
 version = "3.20.3"
 description = "Protocol Buffers"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -785,7 +820,6 @@ files = [
 name = "pyasn1"
 version = "0.5.0"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -797,7 +831,6 @@ files = [
 name = "pyasn1-modules"
 version = "0.3.0"
 description = "A collection of ASN.1-based protocols modules"
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
@@ -810,14 +843,13 @@ pyasn1 = ">=0.4.6,<0.6.0"
 
 [[package]]
 name = "pytest"
-version = "7.4.2"
+version = "7.4.3"
 description = "pytest: simple powerful testing with Python"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "pytest-7.4.2-py3-none-any.whl", hash = "sha256:1d881c6124e08ff0a1bb75ba3ec0bfd8b5354a01c194ddd5a0a870a48d99b002"},
-    {file = "pytest-7.4.2.tar.gz", hash = "sha256:a766259cfab564a2ad52cb1aae1b881a75c3eb7e34ca3779697c23ed47c47069"},
+    {file = "pytest-7.4.3-py3-none-any.whl", hash = "sha256:0d009c083ea859a71b76adf7c1d502e4bc170b80a8ef002da5806527b9591fac"},
+    {file = "pytest-7.4.3.tar.gz", hash = "sha256:d989d136982de4e3b29dabcc838ad581c64e8ed52c11fbe86ddebd9da0818cd5"},
 ]
 
 [package.dependencies]
@@ -835,7 +867,6 @@ testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "no
 name = "python-dateutil"
 version = "2.8.2"
 description = "Extensions to the standard Python datetime module"
-category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
@@ -850,7 +881,6 @@ six = ">=1.5"
 name = "pyyaml"
 version = "6.0.1"
 description = "YAML parser and emitter for Python"
-category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -900,7 +930,6 @@ files = [
 name = "requests"
 version = "2.31.0"
 description = "Python HTTP for Humans."
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -922,7 +951,6 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 name = "requests-oauthlib"
 version = "1.3.1"
 description = "OAuthlib authentication support for Requests."
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
@@ -941,7 +969,6 @@ rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 name = "requests-toolbelt"
 version = "0.10.1"
 description = "A utility belt for advanced users of python-requests"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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 name = "rsa"
 version = "4.9"
 description = "Pure-Python RSA implementation"
-category = "main"
 optional = false
 python-versions = ">=3.6,<4"
 files = [
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 name = "setuptools"
 version = "68.2.2"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
-category = "main"
 optional = false
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 ]
 
+[package.dependencies]
+numpy = ">=1.14"
+
 [package.extras]
-all = ["numpy", "pytest", "pytest-cov"]
+docs = ["matplotlib", "numpydoc (==1.1.*)", "sphinx", "sphinx-book-theme", "sphinx-remove-toctrees"]
 test = ["pytest", "pytest-cov"]
-vectorized = ["numpy"]
 
 [[package]]
 name = "six"
 version = "1.16.0"
 description = "Python 2 and 3 compatibility utilities"
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 files = [
@@ -1057,7 +1081,6 @@ files = [
 name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
-category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1072,7 +1095,6 @@ widechars = ["wcwidth"]
 name = "tomli"
 version = "2.0.1"
 description = "A lil' TOML parser"
-category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1082,31 +1104,29 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "1.26.16"
+version = "1.26.18"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
-category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
 files = [
-    {file = "urllib3-1.26.16-py2.py3-none-any.whl", hash = "sha256:8d36afa7616d8ab714608411b4a3b13e58f463aee519024578e062e141dce20f"},
-    {file = "urllib3-1.26.16.tar.gz", hash = "sha256:8f135f6502756bde6b2a9b28989df5fbe87c9970cecaa69041edcce7f0589b14"},
+    {file = "urllib3-1.26.18-py2.py3-none-any.whl", hash = "sha256:34b97092d7e0a3a8cf7cd10e386f401b3737364026c45e622aa02903dffe0f07"},
+    {file = "urllib3-1.26.18.tar.gz", hash = "sha256:f8ecc1bba5667413457c529ab955bf8c67b45db799d159066261719e328580a0"},
 ]
 
 [package.extras]
-brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
+brotli = ["brotli (==1.0.9)", "brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
 secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
 socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "websocket-client"
-version = "1.6.3"
+version = "1.6.4"
 description = "WebSocket client for Python with low level API options"
-category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "websocket-client-1.6.3.tar.gz", hash = "sha256:3aad25d31284266bcfcfd1fd8a743f63282305a364b8d0948a43bd606acc652f"},
-    {file = "websocket_client-1.6.3-py3-none-any.whl", hash = "sha256:6cfc30d051ebabb73a5fa246efdcc14c8fbebbd0330f8984ac3bb6d9edd2ad03"},
+    {file = "websocket-client-1.6.4.tar.gz", hash = "sha256:b3324019b3c28572086c4a319f91d1dcd44e6e11cd340232978c684a7650d0df"},
+    {file = "websocket_client-1.6.4-py3-none-any.whl", hash = "sha256:084072e0a7f5f347ef2ac3d8698a5e0b4ffbfcab607628cadabc650fc9a83a24"},
 ]
 
 [package.extras]
@@ -1117,4 +1137,4 @@ test = ["websockets"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "55cace2bc751bc7493824589863892d3b0336943772b9a6f24131517a8c09701"
+content-hash = "ba3460b4c978535d1cddd62e9530c1997537e408cd4df6375bc913b62b717aa2"
diff --git a/components/vertex-components/pyproject.toml b/components/pyproject.toml
similarity index 78%
rename from components/vertex-components/pyproject.toml
rename to components/pyproject.toml
index f026a997..b5b546ce 100644
--- a/components/vertex-components/pyproject.toml
+++ b/components/pyproject.toml
@@ -1,9 +1,8 @@
 [tool.poetry]
-name = "vertex-components"
+name = "components"
 version = "0.1.0"
 authors = ["Example User <user@example.com>"]
-description = "KubeFlow components for Vertex AI"
-readme = "README.md"
+description = "KubeFlow components for Google Cloud"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
@@ -16,9 +15,10 @@ kfp = ">=2.0.1,<3.0.0"
 pyyaml = "6.0.1"
 
 [tool.poetry.group.dev.dependencies]
-google-cloud-aiplatform = "1.30.1"
+google-cloud-aiplatform = ">=1.30.1"
+google-cloud-bigquery = ">=2.30.0"
+google-cloud-pipeline-components = "^2.1.0"
 pytest = ">=7.3.1,<8.0.0"
-google-cloud-pipeline-components = "^2.0.0"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
diff --git a/components/vertex-components/src/vertex_components/__init__.py b/components/src/components/__init__.py
similarity index 79%
rename from components/vertex-components/src/vertex_components/__init__.py
rename to components/src/components/__init__.py
index 3e112c57..22a41762 100644
--- a/components/vertex-components/src/vertex_components/__init__.py
+++ b/components/src/components/__init__.py
@@ -1,3 +1,4 @@
+from .extract_table import extract_table
 from .lookup_model import lookup_model
 from .model_batch_predict import model_batch_predict
 from .upload_model import upload_model
@@ -5,6 +6,7 @@
 
 __version__ = "0.0.1"
 __all__ = [
+    "extract_table",
     "lookup_model",
     "model_batch_predict",
     "upload_model",
diff --git a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py b/components/src/components/extract_table.py
similarity index 99%
rename from components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
rename to components/src/components/extract_table.py
index 7039b022..ddbc5de6 100644
--- a/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py
+++ b/components/src/components/extract_table.py
@@ -19,7 +19,7 @@
     base_image="python:3.9",
     packages_to_install=["google-cloud-bigquery==2.30.0"],
 )
-def extract_bq_to_dataset(
+def extract_table(
     bq_client_project_id: str,
     source_project_id: str,
     dataset_id: str,
diff --git a/components/vertex-components/src/vertex_components/lookup_model.py b/components/src/components/lookup_model.py
similarity index 100%
rename from components/vertex-components/src/vertex_components/lookup_model.py
rename to components/src/components/lookup_model.py
diff --git a/components/vertex-components/src/vertex_components/model_batch_predict.py b/components/src/components/model_batch_predict.py
similarity index 100%
rename from components/vertex-components/src/vertex_components/model_batch_predict.py
rename to components/src/components/model_batch_predict.py
diff --git a/components/vertex-components/src/vertex_components/upload_model.py b/components/src/components/upload_model.py
similarity index 100%
rename from components/vertex-components/src/vertex_components/upload_model.py
rename to components/src/components/upload_model.py
diff --git a/components/vertex-components/tests/conftest.py b/components/tests/conftest.py
similarity index 100%
rename from components/vertex-components/tests/conftest.py
rename to components/tests/conftest.py
diff --git a/components/bigquery-components/tests/test_extract_bq_to_dataset.py b/components/tests/test_extract_table.py
similarity index 89%
rename from components/bigquery-components/tests/test_extract_bq_to_dataset.py
rename to components/tests/test_extract_table.py
index dec9f1eb..ad4f80a3 100644
--- a/components/bigquery-components/tests/test_extract_bq_to_dataset.py
+++ b/components/tests/test_extract_table.py
@@ -2,15 +2,15 @@
 from kfp.dsl import Dataset
 from unittest import mock
 
-import bigquery_components
+import components
 
-extract_bq_to_dataset = bigquery_components.extract_bq_to_dataset.python_func
+extract_bq_to_dataset = components.extract_table.python_func
 
 
 @mock.patch("google.cloud.bigquery.client.Client")
 @mock.patch("google.cloud.bigquery.table.Table")
 @mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
-def test_extract_bq_to_dataset(mock_job_config, mock_table, mock_client, tmpdir):
+def test_extract_table(mock_job_config, mock_table, mock_client, tmpdir):
     """
     Checks that the extract_bq_to_dataset is called correctly
     """
@@ -40,7 +40,7 @@ def test_extract_bq_to_dataset(mock_job_config, mock_table, mock_client, tmpdir)
 @mock.patch("google.cloud.bigquery.table.Table")
 @mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
 @mock.patch("pathlib.Path.exists")
-def test_extract_bq_to_dataset_skip_existing(
+def test_extract_table_skip_existing(
     mock_path_exists, mock_job_config, mock_table, mock_client, tmpdir
 ):
     """
diff --git a/components/vertex-components/tests/test_lookup_model.py b/components/tests/test_lookup_model.py
similarity index 97%
rename from components/vertex-components/tests/test_lookup_model.py
rename to components/tests/test_lookup_model.py
index 5e0b2e4c..17a6b4ad 100644
--- a/components/vertex-components/tests/test_lookup_model.py
+++ b/components/tests/test_lookup_model.py
@@ -16,9 +16,9 @@
 from unittest import mock
 import pytest
 
-import vertex_components
+import components
 
-lookup_model = vertex_components.lookup_model.python_func
+lookup_model = components.lookup_model.python_func
 
 
 @mock.patch("google.cloud.aiplatform.Model")
diff --git a/components/vertex-components/tests/test_model_batch_predict.py b/components/tests/test_model_batch_predict.py
similarity index 96%
rename from components/vertex-components/tests/test_model_batch_predict.py
rename to components/tests/test_model_batch_predict.py
index 8131794d..26cafe2b 100644
--- a/components/vertex-components/tests/test_model_batch_predict.py
+++ b/components/tests/test_model_batch_predict.py
@@ -18,9 +18,9 @@
 from google.cloud.aiplatform_v1beta1.types.job_state import JobState
 
 
-import vertex_components
+import components
 
-model_batch_predict = vertex_components.model_batch_predict.python_func
+model_batch_predict = components.model_batch_predict.python_func
 
 
 SKEW_THRESHOLD = {"defaultSkewThreshold": {"value": 0.001}}
diff --git a/components/vertex-components/tests/test_upload_model.py b/components/tests/test_upload_model.py
similarity index 99%
rename from components/vertex-components/tests/test_upload_model.py
rename to components/tests/test_upload_model.py
index a9ef4258..704e6c05 100644
--- a/components/vertex-components/tests/test_upload_model.py
+++ b/components/tests/test_upload_model.py
@@ -19,9 +19,9 @@
 from google.cloud.aiplatform_v1 import ModelEvaluation
 from google_cloud_pipeline_components.types.artifact_types import VertexModel
 
-import vertex_components
+import components
 
-upload_model = vertex_components.upload_model.python_func
+upload_model = components.upload_model.python_func
 
 
 @mock.patch("google.cloud.aiplatform_v1.ModelServiceClient")
diff --git a/components/vertex-components/.python-version b/components/vertex-components/.python-version
deleted file mode 100644
index 9f3d4c17..00000000
--- a/components/vertex-components/.python-version
+++ /dev/null
@@ -1 +0,0 @@
-3.9.16
diff --git a/components/vertex-components/README.md b/components/vertex-components/README.md
deleted file mode 100644
index 8252c9f0..00000000
--- a/components/vertex-components/README.md
+++ /dev/null
@@ -1,25 +0,0 @@
-<!-- 
-Copyright 2022 Google LLC
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    https://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
- -->
-
-# Vertex Components
-
-A Python package which provides common KubeFlow components for interacting with Vertex AI.
-Currently, the following components are implemented:
-
-- `upload_model`: Uploads a new model version to the Vertex Model Registry, importing a model evaluation, and updating the "default" tag on the model if the new version (challenger) is superior to the previous (champion) model.
-- `model_batch_predict`: Run a [Batch Prediction Job](https://cloud.google.com/ai-platform/prediction/docs/batch-predict).
-
-These components either augment, extend, or add new functionalities that aren't found in [Google Cloud Pipeline Components list](https://cloud.google.com/vertex-ai/docs/pipelines/gcpc-list).
diff --git a/cloudbuild/README.md b/docs/AUTOMATION.md
similarity index 100%
rename from cloudbuild/README.md
rename to docs/AUTOMATION.md
diff --git a/components/README.md b/docs/COMPONENTS.md
similarity index 77%
rename from components/README.md
rename to docs/COMPONENTS.md
index f601b9bf..e2009442 100644
--- a/components/README.md
+++ b/docs/COMPONENTS.md
@@ -2,6 +2,16 @@
 
 This directory contains multiple Python packages that are used to define pipeline components with the Kubeflow Pipelines SDK. Each subdirectory is a package with its own set of Python dependencies. Components with the same Python dependencies can reside in the same package, but components with different Python dependencies should be split into different Python packages.
 
+A Python package which provides common KubeFlow components for interacting with Google Cloud.
+The following components are implemented:
+
+- `extract_table`: Extract a table from BigQuery to Cloud Storage.
+- `lookup_model`: Look up a mode in the Vertex AI Model Registry given a name (and version optionally).
+- `upload_model`: Uploads a new model version to the Vertex Model Registry, importing a model evaluation, and updating the "default" tag on the model if the new version (challenger) is superior to the previous (champion) model.
+- `model_batch_predict`: Run a [Batch Prediction Job](https://cloud.google.com/ai-platform/prediction/docs/batch-predict).
+
+These components either augment, extend, or add new functionalities that aren't found in [Google Cloud Pipeline Components list](https://cloud.google.com/vertex-ai/docs/pipelines/gcpc-list).
+
 ## Creating a new pipeline components package
 
 To create a new set of components (with different Python dependencies), copy one of the existing subdirectories and rename the different files and directories as appropriate (e.g. `vertex-components` -> `my-new-components`). You will also need to update any references in the Python files themselves, as well as `poetry.lock` and `pyproject.toml`.
diff --git a/docs/TESTING_SETUP.md b/docs/CONTRIBUTION.md
similarity index 100%
rename from docs/TESTING_SETUP.md
rename to docs/CONTRIBUTION.md
diff --git a/docs/INFRASTRUCTURE.md b/docs/INFRASTRUCTURE.md
new file mode 100644
index 00000000..cf2e02c7
--- /dev/null
+++ b/docs/INFRASTRUCTURE.md
@@ -0,0 +1,43 @@
+<!-- 
+Copyright 2022 Google LLC
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    https://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+ -->
+# Infrastructure
+
+We recommend using [`tfswitch`](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version for you (run `tfswitch` from the [`terraform/envs/dev`](terraform/envs/dev/) directory).
+
+The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):
+
+- `cloudfunction` - deploys a (Pub/Sub-triggered) Cloud Function from local source code
+- `scheduled_pipelines` - deploys Cloud Scheduler jobs that will trigger Vertex Pipeline runs (via the above Cloud Function)
+- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, Artifact Registry repos, service accounts, and IAM permissions.
+
+There is a Terraform configuration for each environment (dev/test/prod) under [`terraform/envs`](terraform/envs/).
+
+## Schedule pipelines
+
+Terraform is used to deploy Cloud Scheduler jobs that trigger the Vertex Pipeline runs. This is done by the CI/CD pipelines (see section below on CI/CD).
+
+To schedule pipelines into an environment, you will need to provide the `cloud_schedulers_config` variable to the Terraform configuration for the relevant environment. 
+You can find an example of this configuration in [`terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example`](terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example). 
+Copy this example file into the relevant directory for your environment (e.g. `terraform/envs/dev` for the dev environment) and remove the `.example` suffix. 
+Adjust the configuration file as appropriate.
+
+## Tear down infrastructure
+
+To tear down the infrastructure you have created with Terraform, run these commands:
+
+```bash
+make undeploy env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
+```
diff --git a/pipelines/README.md b/docs/PIPELINES.md
similarity index 77%
rename from pipelines/README.md
rename to docs/PIPELINES.md
index dccf64be..cfd9b27a 100644
--- a/pipelines/README.md
+++ b/docs/PIPELINES.md
@@ -17,6 +17,47 @@ limitations under the License.
 
 There are two ML pipelines defined in this repository: a training pipeline (located in [pipelines/src/pipelines/training/pipeline.py](/pipelines/src/pipelines/training/pipeline.py)) and a batch prediction pipeline (located in [pipelines/src/pipelines/prediction/pipeline.py](/pipelines/src/pipelines/prediction/pipeline.py)).
 
+## Pipeline input parameters
+
+The ML pipelines have input parameters. 
+As you can see in the pipeline definition files (`pipelines/src/pipelines/<training|prediction>/pipeline.py`), they have default values, and some of these default values are derived from environment variables (which in turn are defined in `env.sh`).
+
+When triggering ad hoc runs in your dev/sandbox environment, or when running the E2E tests in CI, these default values are used. 
+For the test and production deployments, the pipeline parameters are defined in the Terraform code for the Cloud Scheduler jobs (`terraform/envs/<dev|test|prod>/scheduled_jobs.auto.tfvars`) - see the section on [Scheduling pipelines](#scheduling-pipelines).
+
+## Customize pipelines
+
+### Adding a new pipeline
+
+This repository contains a training and a (batch) prediction pipeline. To add another ML pipeline (e.g. for continuous evaluation), create a new directory under the `pipelines/src/pipelines` directory. Within your new pipeline folder, create a `pipeline.py` file - this is where you should provide your pipeline definition using the KFP DSL (in a function named `pipeline`).
+
+Alternatively, you can just copy and paste the `training` or `prediction` directory.
+
+See below for an example folder structure:
+
+```
+vertex-pipelines-end-to-end-samples
+|
+├── pipelines
+│   ├── src
+│   │   ├── pipelines
+│   │   │   ├── new_pipeline
+│   │   │   │   ├── pipeline.py
+│   │   │   │   └── queries
+│   │   │   │       └── my_query.sql
+```
+
+Make sure that you give the ML pipeline a unique name in the `@pipeline` decorator.
+
+To run your pipeline, use `make run` as before (optionally adding parameter to wait until pipeline is finished before returning - defaults to false):
+
+```bash
+make run pipeline=your_new_pipeline [ wait=<true|false> ]
+```
+
+Some of the scripts e.g. CI/CD pipelines assume only a training and prediction pipeline. You will need to adapt these to add in the compile, run and upload steps for your new pipeline in [cloudbuild/pr-checks.yaml](/cloudbuild/pr-checks.yaml), [cloudbuild/e2e-test.yaml](/cloudbuild/e2e-test.yaml) and [cloudbuild/release.yaml](/cloudbuild/release.yaml).
+
+
 ## Training pipeline
 
 A screenshot of the completed ML pipeline is shown below.
@@ -43,7 +84,7 @@ Once the data has been split into three tables (for train/test/validation split)
 
 (Alternatively, you could choose to omit this step, leave the data in BigQuery and consume the data directly from BigQuery for your training step).
 
-This step is performed using a custom KFP component located in [components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py](/components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py).
+This step is performed using a custom KFP component located in [components/bigquery-components/src/bigquery_components/extract_bq_to_dataset.py](/vertex_components/extract_bq_to_dataset.py).
 
 ### Training step
 
@@ -62,7 +103,7 @@ The model is evaluated and metrics are saved as a JSON file. In the Vertex pipel
 ### Upload model step
 
 The upload model step uploads the model to the Vertex model registry. This step uses a custom KFP component that can be 
-found in [components/vertex-components/src/vertex_components/upload_model.py](/components/vertex-components/src/vertex_components/upload_model.py). It does the following:
+found in [components/vertex-components/src/vertex_components/upload_model.py](//vertex_components/upload_model.py). It does the following:
 
 1. Checks if there is an existing "champion" model with the same name in the Vertex Model Registry
 1. If there is, fetch its latest model evaluation and compare it with the model evaluation of the newly trained "challenger" model
@@ -96,11 +137,11 @@ The `preprocessing` step in the pipeline uses this string (`preprocessing_query`
 
 ### Lookup model
 
-This step looks up the "champion" model from the Vertex Model Registry. It uses a custom KFP component that can be found in [components/vertex-components/src/vertex_components/lookup_model.py](/components/vertex-components/src/vertex_components/lookup_model.py). It uses the Vertex AI Python SDK to list models with a given model name and retrieve the model version that uses the `default` alias, indicating that it is the "champion" model.
+This step looks up the "champion" model from the Vertex Model Registry. It uses a custom KFP component that can be found in [components/vertex-components/src/vertex_components/lookup_model.py](//vertex_components/lookup_model.py). It uses the Vertex AI Python SDK to list models with a given model name and retrieve the model version that uses the `default` alias, indicating that it is the "champion" model.
 
 ### Batch Prediction
 
-This step submits a Vertex Batch Prediction job that generates predictions from the BigQuery table from the ingestion/preprocessing step. It uses a custom KFP component that can be found in [components/vertex-components/src/vertex_components/model_batch_predict.py](/components/vertex-components/src/vertex_components/model_batch_predict.py). It uses Vertex Model Monitoring for batch prediction to monitor the data for drift.
+This step submits a Vertex Batch Prediction job that generates predictions from the BigQuery table from the ingestion/preprocessing step. It uses a custom KFP component that can be found in [components/vertex-components/src/vertex_components/model_batch_predict.py](//vertex_components/model_batch_predict.py). It uses Vertex Model Monitoring for batch prediction to monitor the data for drift.
 
 ## Pipeline input parameters
 
diff --git a/docs/notebooks/01_infrastructure_setup.ipynb b/docs/notebooks/01_infrastructure_setup.ipynb
new file mode 100644
index 00000000..8a31cb43
--- /dev/null
+++ b/docs/notebooks/01_infrastructure_setup.ipynb
@@ -0,0 +1,289 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e",
+    "tags": []
+   },
+   "source": [
+    "# Getting Started with Vertex AI Turbo Templates\n",
+    "\n",
+    "This notebook sets up infrastructure to run production-ready pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
+    "\n",
+    "1. **[Infrastructure Setup](./02_run_pipelines.ipynb) - this notebook**\n",
+    "1. [Run Pipelines](./02_run_pipelines.ipynb)\n",
+    "1. [Infrastructure Clean Up](./02_run_pipelines.ipynb)\n",
+    "\n",
+    "\n",
+    "**Prerequisites:**\n",
+    "\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Terraform](https://www.terraform.io)\n",
+    "\n",
+    "**For Vertex AI Workbench users**: Uncomment and execute the following cell install Terraform."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ! bash ./scripts/install_terraform.sh"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Authenticate\n",
+    "\n",
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "VERTEX_PROJECT_ID = \"dt-turbo-templates-dev\"\n",
+    "! gcloud auth login\n",
+    "! gcloud config set project {VERTEX_PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Clone Code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Configure your code by setting the variables:\n",
+    "- `VERTEX_PROJECT_ID` - as set above\n",
+    "- `VERTEX_LOCATION` - location of the cloud project\n",
+    "- `RESOURCE_SUFFIX` - suffix (e.g. `<your name>`) to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%writefile .env.sh\n",
+    "#!/bin/bash\n",
+    "VERTEX_PROJECT_ID=my-project-id\n",
+    "VERTEX_LOCATION=europe-west2\n",
+    "RESOURCE_SUFFIX=default"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For most use cases you won't need to change the following variables unless you've modified the Terraform code."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%writefile -a .env.sh\n",
+    "# Optional\n",
+    "VERTEX_CMEK_IDENTIFIER=\n",
+    "VERTEX_NETWORK=\n",
+    "# Leave as-is\n",
+    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
+    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
+    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! source .env.sh && echo $VERTEX_PROJECT_ID"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "zgPO1eR3CYjk",
+    "tags": []
+   },
+   "source": [
+    "## Deploy Infrastructure\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):\n",
+    "\n",
+    "- `cloudfunction` - deploys a (Pub/Sub-triggered) Cloud Function from local source code\n",
+    "- `scheduled_pipelines` - deploys Cloud Scheduler jobs that will trigger Vertex Pipeline runs (via the above Cloud Function)\n",
+    "- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, Artifact Registry repos, service accounts, and IAM permissions."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Enable APIs**:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! gcloud services enable cloudresourcemanager.googleapis.com serviceusage.googleapis.com"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Create Cloud Storage bucket:**\n",
+    "\n",
+    "Store the [Terraform state files](https://developer.hashicorp.com/terraform/language/state/remote) in the bucket `[project-id]-tfstate`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "NIq7R4HZCfIc",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! source .env.sh && gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Deploy:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! make deploy auto-approve=true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You've successfully deployed a `dev` environment! 🎉 \n",
+    "Continue with [this notebook](./02_run_pipelines.ipynb) to run your first Vertex AI Pipelines in the deployed project.\n",
+    "\n",
+    "**Note:** If you'd like to deploy separate cloud environments as shown below, try out `make deploy env=dev` where you can replace `dev` with `test` or `prod`."
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/notebooks/02_run_pipelines.ipynb b/docs/notebooks/02_run_pipelines.ipynb
new file mode 100644
index 00000000..02843e4b
--- /dev/null
+++ b/docs/notebooks/02_run_pipelines.ipynb
@@ -0,0 +1,254 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Getting Started with Vertex AI Turbo Templates\n",
+    "\n",
+    "This notebook sets up infrastructure to run production-ready pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
+    "\n",
+    "1. [Infrastructure Setup](./02_run_pipelines.ipynb)\n",
+    "1. **[Run Pipelines](./02_run_pipelines.ipynb) - this notebook**\n",
+    "1. [Infrastructure Clean Up](./02_run_pipelines.ipynb)\n",
+    "\n",
+    "\n",
+    "**Prerequisites:**\n",
+    "\n",
+    "- Deployed `dev` project\n",
+    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Poetry](https://python-poetry.org)\n",
+    "- [pyenv](https://github.com/pyenv/pyenv)\n",
+    "\n",
+    "**For Vertex AI Workbench users**: Uncomment and execute the following cell install Poetry."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# ! bash ./scripts/install_poetry.sh"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Authenticate\n",
+    "\n",
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "VERTEX_PROJECT_ID = \"dt-turbo-templates-dev\"\n",
+    "! gcloud auth login\n",
+    "! gcloud config set project {VERTEX_PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "i7EUnXsZhAGF",
+    "tags": []
+   },
+   "source": [
+    "## Install Dependencies\n",
+    "\n",
+    "Install Python and Poetry dependencies:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "2b4ef9b72d43",
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! pyenv install -skip-existing\n",
+    "! poetry config virtualenvs.prefer-active-python true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `Makefile` installs virtual Python environments for the Vertex AI Pipelines and components within using Poetry:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make install"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Run Training Pipeline\n",
+    "\n",
+    "Vertex AI Pipelines uses KubeFlow to orchestrate your training steps, as such you'll need to:\n",
+    "\n",
+    "1. Compile the pipeline\n",
+    "1. Build dependent Docker containers\n",
+    "1. Run the pipeline in Vertex AI\n",
+    "\n",
+    "The already templated training pipeline will execute a pipeline similar to the image below in Vertex AI:\n",
+    "\n",
+    "![Training Pipeline](../images/training_pipeline.png)\n",
+    "\n",
+    "Don't worry about executing steps 1-3 manually (and each time you run your pipeline!), simply run the following command:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make run pipeline=training wait=true"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "While the pipeline executes, here's a more detailed explanation of what's happening:\n",
+    "\n",
+    "**1. Compile the pipeline:** By using the KubeFlow SDK, you've compiled the training pipeline in `pipelines/training` to YAML.\n",
+    "\n",
+    "**2. Build dependent Docker containers:** In `model` you can maintain your training (and serving) code which is containerised and pushed to [Artifact Registry](https://cloud.google.com/artifact-registry). \n",
+    "In this way, your training pipeline can execute your training code in the `Train model` pipeline step.\n",
+    "\n",
+    "**3. Run the pipeline in Vertex AI:** By using the Vertex AI Python SDK and the pipeline YAML file, you execute your training pipeline."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Run Prediction Pipeline\n",
+    "\n",
+    "After successful training job, run the prediction pipeline which will look similar to:\n",
+    "\n",
+    "<img src=\"../images/prediction_pipeline.png\" alt=\"image\" width=\"500\" height=\"auto\">"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make run pipeline=prediction build=false"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Note:** The `make run` command has the following true/false flags:\n",
+    "\n",
+    "- `build` - re-build containers for training & serving code (limit by setting `targets=training` to build only one of the containers)\n",
+    "- `compile` - re-compile the pipeline to YAML\n",
+    "- `wait` - run the pipeline (a-)sync"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "You've successfully raun your first training and prediction pipeline in Vertex AI! 🎉\n",
+    "Continue with [this notebook](./03_infrastructure_cleanup.ipynb) to run clean up the infrastructure."
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/notebooks/03_infrastructure_cleanup.ipynb b/docs/notebooks/03_infrastructure_cleanup.ipynb
new file mode 100644
index 00000000..b3d674b1
--- /dev/null
+++ b/docs/notebooks/03_infrastructure_cleanup.ipynb
@@ -0,0 +1,199 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JAPoU8Sm5E6e"
+   },
+   "source": [
+    "# Getting Started with Vertex AI Turbo Templates\n",
+    "\n",
+    "This notebook sets up infrastructure to run production-ready pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
+    "\n",
+    "1. [Infrastructure Setup](./02_run_pipelines.ipynb)\n",
+    "1. [Run Pipelines](./02_run_pipelines.ipynb)\n",
+    "1. **[Infrastructure Clean Up](./02_run_pipelines.ipynb) - this notebook**\n",
+    "\n",
+    "\n",
+    "**Prerequisites:**\n",
+    "\n",
+    "- Deployed `dev` project\n",
+    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
+    "- Make\n",
+    "- [Terraform](https://www.terraform.io)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Authenticate\n",
+    "\n",
+    "#### Set your project ID\n",
+    "\n",
+    "**If you don't know your project ID**, try the following:\n",
+    "* Run `gcloud config list`.\n",
+    "* Run `gcloud projects list`.\n",
+    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "VERTEX_PROJECT_ID = \"dt-turbo-templates-dev\"\n",
+    "! gcloud auth login\n",
+    "! gcloud config set project {VERTEX_PROJECT_ID}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "TpV-iwP9qw9c"
+   },
+   "source": [
+    "## Clean Up Infrastructure\n",
+    "\n",
+    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
+    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
+    "\n",
+    "Otherwise, you can delete the individual resources you created in this tutorial:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%cd vertex-pipelines-end-to-end-samples/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Empty the buckets to enable their deletion:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
+    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "**Delete BigQuery dataset for data processing during the pipelines:**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make undeploy auto-approve=true"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You've successfully cleaned your dev environment! 🎉 \n",
+    "This is the end of the three-part notebook series.\n",
+    "\n",
+    "**Now it's time to adapt the template to your own use case.** \n",
+    "You can start by updating the training and serving code in `model` folder. "
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/notebooks/local/01_infrastructure_setup.ipynb b/docs/notebooks/local/01_infrastructure_setup.ipynb
deleted file mode 100644
index 030ccad8..00000000
--- a/docs/notebooks/local/01_infrastructure_setup.ipynb
+++ /dev/null
@@ -1,469 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "ur8xi4C7S06n"
-   },
-   "outputs": [],
-   "source": [
-    "# Copyright 2023 Google LLC\n",
-    "#\n",
-    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-    "# you may not use this file except in compliance with the License.\n",
-    "# You may obtain a copy of the License at\n",
-    "#\n",
-    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-    "#\n",
-    "# Unless required by applicable law or agreed to in writing, software\n",
-    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-    "# See the License for the specific language governing permissions and\n",
-    "# limitations under the License."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "JAPoU8Sm5E6e",
-    "tags": []
-   },
-   "source": [
-    "# Running Vertex Pipelines using E2E Samples repository - Infrastructure setup.\n",
-    "\n",
-    "\n",
-    "<table align=\"left\">\n",
-    "\n",
-    "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/01_infrastructure_setup.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
-    "      View on GitHub\n",
-    "    </a>\n",
-    "  </td>                                                                                         \n",
-    "</table>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "tvgnzT1CKxrO",
-    "tags": []
-   },
-   "source": [
-    "## Overview\n",
-    "\n",
-    "This notebook shows you how to setup infrastructure to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
-    "\n",
-    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "d975e698c9a4"
-   },
-   "source": [
-    "### Objective\n",
-    "\n",
-    "In this tutorial, you learn how to set up the cloud infrastructure, in order to launch your first training and predicition pipeline:\n",
-    "\n",
-    "This tutorial uses the following Google Cloud services and resources:\n",
-    "\n",
-    "- *`Vertex Pipelines`*\n",
-    "- *`Google Cloud Storage`*\n",
-    "- *`Artifact Registry`*\n",
-    "- *`BigQuery`*\n",
-    "- *`Cloud Build`*\n",
-    "\n",
-    "The steps performed include:\n",
-    "\n",
-    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "aed92deeb4a0"
-   },
-   "source": [
-    "### Costs \n",
-    "\n",
-    "\n",
-    "This tutorial uses billable components of Google Cloud:\n",
-    "\n",
-    "* Vertex AI\n",
-    "* BigQuery\n",
-    "* Cloud Storage\n",
-    "* Cloud Build\n",
-    "* Artifact Registry\n",
-    "\n",
-    "\n",
-    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
-    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
-    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
-    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
-    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
-    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
-    "to generate a cost estimate based on your projected usage."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Prerequisites\n",
-    "\n",
-    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
-    "- Make\n",
-    "- [Terraform](https://www.terraform.io)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Clone Turbo Templates repository"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Clone a Git repository\n",
-    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Infrastructure"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):\n",
-    "\n",
-    "- `cloudfunction` - deploys a (Pub/Sub-triggered) Cloud Function from local source code\n",
-    "- `scheduled_pipelines` - deploys Cloud Scheduler jobs that will trigger Vertex Pipeline runs (via the above Cloud Function)\n",
-    "- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, Artifact Registry repos, service accounts, and IAM permissions."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Terraform Installation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**If you do not have terraform installed please please refer to the official documentation for detailed installation instructions: https://developer.hashicorp.com/terraform/downloads**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Before You Begin"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "BF1j6f9HApxa",
-    "tags": []
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-    "\n",
-    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
-   },
-   "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "oM1iC_MfAts1",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "PROJECT_ID = \"[my-project-id]\"\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Authenticate your Google Cloud account\n",
-    "\n",
-    "\n",
-    "As you're running a Jupyter environment locally, you'll need to authenticate manually. Please follow the instructions provided below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud auth login"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to run `make` commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID` and `VERTEX_LOCATION`)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%writefile .env\n",
-    "\n",
-    "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_PROJECT_ID=my-project-id\n",
-    "\n",
-    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
-    "RESOURCE_SUFFIX=default\n",
-    "\n",
-    "# Leave as-is\n",
-    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
-    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
-    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
-    "\n",
-    "# Optional\n",
-    "VERTEX_CMEK_IDENTIFIER=\n",
-    "VERTEX_NETWORK="
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from dotenv import load_dotenv\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "zgPO1eR3CYjk",
-    "tags": []
-   },
-   "source": [
-    "## Infrastructure deployment using terraform.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
-    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Create tfstate bucket\n",
-    "\n",
-    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "-EcIXiGsCePi"
-   },
-   "source": [
-    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "NIq7R4HZCfIc",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "960505627ddf"
-   },
-   "source": [
-    "### Deploy required infrastructure"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "Deploy command will:\n",
-    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
-    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make deploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Congratulations on successfully deploying the infrastructure required to run ML pipelines!"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "collapsed_sections": [],
-   "name": "notebook_template.ipynb",
-   "toc_visible": true
-  },
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.6"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/docs/notebooks/local/02_run_pipelines.ipynb b/docs/notebooks/local/02_run_pipelines.ipynb
deleted file mode 100644
index 006d99a5..00000000
--- a/docs/notebooks/local/02_run_pipelines.ipynb
+++ /dev/null
@@ -1,606 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "ur8xi4C7S06n"
-   },
-   "outputs": [],
-   "source": [
-    "# Copyright 2023 Google LLC\n",
-    "#\n",
-    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-    "# you may not use this file except in compliance with the License.\n",
-    "# You may obtain a copy of the License at\n",
-    "#\n",
-    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-    "#\n",
-    "# Unless required by applicable law or agreed to in writing, software\n",
-    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-    "# See the License for the specific language governing permissions and\n",
-    "# limitations under the License."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "JAPoU8Sm5E6e"
-   },
-   "source": [
-    "# Running Vertex Pipelines using E2E Samples repository - Triggering Pipelines.\n",
-    "\n",
-    "\n",
-    "<table align=\"left\">\n",
-    "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/03_run_pipelines.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
-    "      View on GitHub\n",
-    "    </a>\n",
-    "  </td>                                                                            \n",
-    "</table>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "tvgnzT1CKxrO",
-    "tags": []
-   },
-   "source": [
-    "## Overview\n",
-    "\n",
-    "This notebook shows you how to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
-    "\n",
-    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "d975e698c9a4"
-   },
-   "source": [
-    "### Objective\n",
-    "\n",
-    "In this tutorial, you learn how to launch your first training and predicition pipeline, and analyse the results:\n",
-    "\n",
-    "This tutorial uses the following Google Cloud services and resources:\n",
-    "\n",
-    "- *`Vertex Pipelines`*\n",
-    "- *`Google Cloud Storage`*\n",
-    "- *`Artifact Registry`*\n",
-    "- *`BigQuery`*\n",
-    "- *`Cloud Build`*\n",
-    "\n",
-    "The steps performed include:\n",
-    "\n",
-    "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "08d289fa873f"
-   },
-   "source": [
-    "### Dataset\n",
-    "\n",
-    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
-    "\n",
-    "\n",
-    "This public dataset is hosted in Google BigQuery."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "aed92deeb4a0"
-   },
-   "source": [
-    "### Costs \n",
-    "\n",
-    "\n",
-    "This tutorial uses billable components of Google Cloud:\n",
-    "\n",
-    "* Vertex AI\n",
-    "* BigQuery\n",
-    "* Cloud Storage\n",
-    "* Cloud Build\n",
-    "* Artifact Registry\n",
-    "\n",
-    "\n",
-    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
-    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
-    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
-    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
-    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
-    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
-    "to generate a cost estimate based on your projected usage."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Prerequisites\n",
-    "\n",
-    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
-    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
-    "- Make\n",
-    "- [Poetry](https://python-poetry.org)\n",
-    "- [pyenv](https://github.com/pyenv/pyenv)\n",
-    "- Infrastructure deployed ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Change working directory"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "i7EUnXsZhAGF",
-    "tags": []
-   },
-   "source": [
-    "## Installation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Install the packages required for executing this notebook."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "2b4ef9b72d43",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Install the correct Python version\n",
-    "! pyenv install -skip-existing\n",
-    "\n",
-    "# configure poetry \n",
-    "! poetry config virtualenvs.prefer-active-python true\n",
-    "\n",
-    "#Install poetry dependencies for ML pipelines\n",
-    "! make install"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Before You Begin"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "BF1j6f9HApxa",
-    "tags": []
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-    "\n",
-    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
-   },
-   "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "oM1iC_MfAts1",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Authenticate your Google Cloud account\n",
-    "\n",
-    "\n",
-    "As you're running a Jupyter environment locally, you'll need to authenticate manually. Please follow the instructions provided below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud auth login"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to run make commands relevant environment variables need to be set. You can re-use `.env` file defined in [01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# ! pip install python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from dotenv import load_dotenv\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Example ML Pipelines"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "To automate, monitor, and govern your ML workflows, you can use [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops). Vertex AI is a powerful platform offered by Google Cloud that empowers organizations to streamline and enhance their Machine Learning (ML) workflows through automation, monitoring, and governance.\n",
-    "\n",
-    "- **Automation**: Vertex AI offers a suite of tools and services designed to automate various aspects of ML development and deployment. This includes automating data preprocessing, model training, hyperparameter tuning, and model deployment. Automation not only saves time but also reduces the potential for human error, making your ML workflows more efficient and reliable.\n",
-    "\n",
-    "- **Monitoring**: Effective monitoring is crucial for maintaining the performance and reliability of ML models in production. Vertex AI provides monitoring capabilities that allow you to track model performance, detect drift in data distributions, and set up alerts for anomalies. This proactive monitoring ensures that your models continue to deliver accurate results as data and business conditions change over time.\n",
-    "\n",
-    "- **Governance**: Managing ML models and data in a secure and compliant manner is essential for businesses, especially those in regulated industries. Vertex AI helps you implement governance policies to control access to data, monitor model usage, and enforce compliance with data privacy regulations. This ensures that your ML operations are in line with legal and ethical standards.\n",
-    "\n",
-    "- **Scalability**: Vertex AI is built on Google Cloud's infrastructure, which means it offers unparalleled scalability. Whether you're dealing with small-scale experiments or large-scale production deployments, Vertex AI can scale to meet your needs, ensuring that your ML workflows can handle increased workloads without performance bottlenecks.\n",
-    "\n",
-    "- **Collaboration**: Collaboration is essential in ML development, and Vertex AI provides features that facilitate collaboration among data scientists, machine learning engineers, and other stakeholders. You can share notebooks, collaborate on model development, and maintain version control of your ML assets.\n",
-    "\n",
-    "- **Model Serving**: Vertex AI makes it easy to deploy ML models as APIs for real-time inference or batch processing. This enables you to integrate your ML models into applications, websites, or other services with ease.\n",
-    "\n",
-    "- **Cost Management**: Cost control is a crucial aspect of any ML project. Vertex AI offers cost management tools and insights to help you optimize your ML workflows and keep your expenses in check.\n",
-    "\n",
-    "By utilizing Vertex AI, you can take advantage of Google Cloud's cutting-edge technology and expertise in machine learning to accelerate your MLOps journey. The platform offers a comprehensive set of tools and services that cover the entire ML lifecycle, from data preparation to model deployment and beyond, making it a valuable resource for organizations looking to harness the power of ML in a scalable, efficient, and secure manner.\n",
-    "\n",
-    "To learn more about MLOps on Vertex AI and how it can transform your ML workflows, you can visit the [official documentation](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops).\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**This repository provides an example ML training and prediction pipelines for XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips).**\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Pre-requisites\n",
-    "\n",
-    "Before you can successfully execute the example pipelines, there are a few additional components you need to deploy. These components have not been included in the Terraform code as they are specific to these pipelines."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "1. Create a new BigQuery dataset for the Chicago Taxi data:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "2. Create a new BigQuery dataset for data processing during the pipelines:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install google-cloud-bigquery-datatransfer"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "destination_project_id = os.environ[\"VERTEX_PROJECT_ID\"]\n",
-    "destination_dataset_id = \"chicago_taxi_trips\"\n",
-    "source_project_id = \"bigquery-public-data\"\n",
-    "source_dataset_id = \"chicago_taxi_trips\"\n",
-    "transfer_config = bigquery_datatransfer.TransferConfig(\n",
-    "    destination_dataset_id=destination_dataset_id,\n",
-    "    display_name=\"Chicago taxi trip mirror\",\n",
-    "    data_source_id=\"cross_region_copy\",\n",
-    "    params={\n",
-    "        \"source_project_id\": source_project_id,\n",
-    "        \"source_dataset_id\": source_dataset_id,\n",
-    "    },\n",
-    "    schedule=\"every 24 hours\",\n",
-    ")\n",
-    "transfer_config = transfer_client.create_transfer_config(\n",
-    "    parent=transfer_client.common_project_path(destination_project_id),\n",
-    "    transfer_config=transfer_config,\n",
-    ")\n",
-    "TRANSFER_CONFIG=transfer_config.name\n",
-    "print(f\"Created transfer config: {TRANSFER_CONFIG}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Building the container images\n",
-    "\n",
-    "The `model` directory contains the code for custom training and serving container images `model/training/train.py`.\n",
-    "\n",
-    "A custom container is a Docker image that you create to run your training application. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Vertex AI. To learn more you can check out [official documentation](https://cloud.google.com/vertex-ai/docs/training/containers-overview)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To build the training and serving container images and push them to Artifact Registry run the next cell."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make build"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Running Pipelines\n",
-    "\n",
-    "You can run the training pipeline by executing cell below.\n",
-    "\n",
-    "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
-    "\n",
-    "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
-    "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Run Training Pipeline**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make run pipeline=training build=false"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it directly through the Google Cloud Console UI by navigating to Vertex AI and then selecting Pipelines."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Training Pipeline**\n",
-    "![Training Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/training_pipeline.png?raw=true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Run Prediction Pipeline** \n",
-    "\n",
-    "After successful training job, you can try prediction pipeline."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! make run pipeline=prediction build=false"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Prediction Pipeline**\n",
-    "\n",
-    "![Predictions Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/prediction_pipeline.png?raw=true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Congratulations on successfully running your first ML pipelines!"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "collapsed_sections": [],
-   "name": "notebook_template.ipynb",
-   "toc_visible": true
-  },
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.6"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/docs/notebooks/local/03_infrastructure_cleanup.ipynb b/docs/notebooks/local/03_infrastructure_cleanup.ipynb
deleted file mode 100644
index 0163cf0e..00000000
--- a/docs/notebooks/local/03_infrastructure_cleanup.ipynb
+++ /dev/null
@@ -1,406 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "ur8xi4C7S06n"
-   },
-   "outputs": [],
-   "source": [
-    "# Copyright 2023 Google LLC\n",
-    "#\n",
-    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-    "# you may not use this file except in compliance with the License.\n",
-    "# You may obtain a copy of the License at\n",
-    "#\n",
-    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-    "#\n",
-    "# Unless required by applicable law or agreed to in writing, software\n",
-    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-    "# See the License for the specific language governing permissions and\n",
-    "# limitations under the License."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "JAPoU8Sm5E6e"
-   },
-   "source": [
-    "# Running Vertex Pipelines using E2E Samples repository - Infrastructure Cleanup\n",
-    "\n",
-    "\n",
-    "<table align=\"left\">\n",
-    "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/03_infrastructure_cleanup.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
-    "      View on GitHub\n",
-    "    </a>\n",
-    "  </td>                                                                            \n",
-    "</table>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "tvgnzT1CKxrO",
-    "tags": []
-   },
-   "source": [
-    "## Overview\n",
-    "\n",
-    "This notebook shows you how to destroy infrastructure which was created in ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "d975e698c9a4"
-   },
-   "source": [
-    "### Objective\n",
-    "\n",
-    "In this tutorial, you learn how to destroy infrastructure using terraform.\n",
-    "\n",
-    "The steps performed include:\n",
-    "\n",
-    "* Destroy infrastructure using Terraform."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Prerequisites\n",
-    "\n",
-    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
-    "- Make\n",
-    "- [Terraform](https://www.terraform.io)\n",
-    "- Infrastructure deployed ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Change working directory"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Before You Begin"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "BF1j6f9HApxa",
-    "tags": []
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-    "\n",
-    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
-   },
-   "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Authenticate your Google Cloud account\n",
-    "\n",
-    "\n",
-    "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud auth login"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to run make commands relevant environment variables need to be set. You can re-use `.env` file defined in [01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# ! pip install python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from dotenv import load_dotenv\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "TpV-iwP9qw9c"
-   },
-   "source": [
-    "## Cleaning up\n",
-    "\n",
-    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
-    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
-    "\n",
-    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Empty the buckets to enable their deletion:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete data transfer config:**\n",
-    "\n",
-    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import google.api_core.exceptions\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "transfer_config_name = \"my-transfer-config\" # Transfer Config Resource Name (projects/{project_number}/locations/{location}/transferConfigs/{transfer_config_id)\n",
-    "try:\n",
-    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
-    "except google.api_core.exceptions.NotFound:\n",
-    "    print(\"Transfer config not found.\")\n",
-    "else:\n",
-    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for the Chicago Taxi data:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for data processing during the pipelines:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! make undeploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete local files:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "cd ..\n",
-    "rm -r vertex-pipelines-end-to-end-samples"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Congratulations on successfully destroying your infrastructure!"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "collapsed_sections": [],
-   "name": "notebook_template.ipynb",
-   "toc_visible": true
-  },
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.5"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/docs/notebooks/local/pipelines.ipynb b/docs/notebooks/local/pipelines.ipynb
deleted file mode 100644
index 04eeccb2..00000000
--- a/docs/notebooks/local/pipelines.ipynb
+++ /dev/null
@@ -1,912 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "ur8xi4C7S06n"
-   },
-   "outputs": [],
-   "source": [
-    "# Copyright 2023 Google LLC\n",
-    "#\n",
-    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-    "# you may not use this file except in compliance with the License.\n",
-    "# You may obtain a copy of the License at\n",
-    "#\n",
-    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-    "#\n",
-    "# Unless required by applicable law or agreed to in writing, software\n",
-    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-    "# See the License for the specific language governing permissions and\n",
-    "# limitations under the License."
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "JAPoU8Sm5E6e"
-   },
-   "source": [
-    "# Running Vertex Pipelines using E2E Samples repository.\n",
-    "\n",
-    "\n",
-    "<table align=\"left\">\n",
-    "\n",
-    "  <td>\n",
-    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/local//pipelines_colab.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
-    "    </a>\n",
-    "  </td>\n",
-    "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/local/pipelines.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
-    "      View on GitHub\n",
-    "    </a>\n",
-    "  </td>\n",
-    "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/local/pipelines_workbench.ipynb\">\n",
-    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
-    "      Open in Vertex AI Workbench\n",
-    "    </a>\n",
-    "  </td>                                                                                               \n",
-    "</table>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "tvgnzT1CKxrO",
-    "tags": []
-   },
-   "source": [
-    "## Overview\n",
-    "\n",
-    "This notebook shows you how to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
-    "\n",
-    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "d975e698c9a4"
-   },
-   "source": [
-    "### Objective\n",
-    "\n",
-    "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
-    "\n",
-    "This tutorial uses the following Google Cloud services and resources:\n",
-    "\n",
-    "- *`Vertex Pipelines`*\n",
-    "- *`Google Cloud Storage`*\n",
-    "- *`Artifact Registry`*\n",
-    "- *`BigQuery`*\n",
-    "- *`Cloud Build`*\n",
-    "\n",
-    "The steps performed include:\n",
-    "\n",
-    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services.\n",
-    "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "08d289fa873f"
-   },
-   "source": [
-    "### Dataset\n",
-    "\n",
-    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
-    "\n",
-    "\n",
-    "This public dataset is hosted in Google BigQuery."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "aed92deeb4a0"
-   },
-   "source": [
-    "### Costs \n",
-    "\n",
-    "\n",
-    "This tutorial uses billable components of Google Cloud:\n",
-    "\n",
-    "* Vertex AI\n",
-    "* BigQuery\n",
-    "* Cloud Storage\n",
-    "* Cloud Build\n",
-    "* Artifact Registry\n",
-    "\n",
-    "\n",
-    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
-    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
-    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
-    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
-    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
-    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
-    "to generate a cost estimate based on your projected usage."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Prerequisites\n",
-    "\n",
-    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
-    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
-    "- Make\n",
-    "- [Poetry](https://python-poetry.org)\n",
-    "- [Terraform](https://www.terraform.io) (To install Terraform on your local machine we recommend using [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version.)\n",
-    "- [pyenv](https://github.com/pyenv/pyenv)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Clone Turbo Templates repository"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Clone a Git repository\n",
-    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "i7EUnXsZhAGF",
-    "tags": []
-   },
-   "source": [
-    "## Installation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Install the packages required for executing this notebook."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "2b4ef9b72d43",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Install the correct Python version\n",
-    "! pyenv install -skip-existing\n",
-    "\n",
-    "# configure poetry \n",
-    "! poetry config virtualenvs.prefer-active-python true\n",
-    "\n",
-    "#Install poetry dependencies for ML pipelines\n",
-    "! make install"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Terraform"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**If you do not have terraform installed please follow the instructions below.**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Local JupyterLab instance**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Please follow official documentation for installation instructions: https://developer.hashicorp.com/terraform/downloads"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Before You Begin"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "BF1j6f9HApxa",
-    "tags": []
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-    "\n",
-    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
-   },
-   "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "oM1iC_MfAts1",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Authenticate your Google Cloud account\n",
-    "\n",
-    "\n",
-    "Depending on your Jupyter environment, you may have to manually authenticate. Follow the relevant instructions below."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    " ! gcloud auth login"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID` and `VERTEX_LOCATION`)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%writefile .env\n",
-    "\n",
-    "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_PROJECT_ID=my-project-id\n",
-    "\n",
-    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
-    "RESOURCE_SUFFIX=default\n",
-    "\n",
-    "# Leave as-is\n",
-    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
-    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
-    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
-    "\n",
-    "# Optional\n",
-    "VERTEX_CMEK_IDENTIFIER=\n",
-    "VERTEX_NETWORK="
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! pip install python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from dotenv import load_dotenv\n",
-    "\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "zgPO1eR3CYjk",
-    "tags": []
-   },
-   "source": [
-    "## Infrastructure deployment using terraform.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
-    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Create tfstate bucket\n",
-    "\n",
-    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "-EcIXiGsCePi"
-   },
-   "source": [
-    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "NIq7R4HZCfIc",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "960505627ddf"
-   },
-   "source": [
-    "### Deploy required infrastructure"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "Deploy command will:\n",
-    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
-    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make deploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Example ML Pipelines"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "To automate, monitor, and govern your ML workflows, you can use [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops). Vertex AI is a powerful platform offered by Google Cloud that empowers organizations to streamline and enhance their Machine Learning (ML) workflows through automation, monitoring, and governance.\n",
-    "\n",
-    "- **Automation**: Vertex AI offers a suite of tools and services designed to automate various aspects of ML development and deployment. This includes automating data preprocessing, model training, hyperparameter tuning, and model deployment. Automation not only saves time but also reduces the potential for human error, making your ML workflows more efficient and reliable.\n",
-    "\n",
-    "- **Monitoring**: Effective monitoring is crucial for maintaining the performance and reliability of ML models in production. Vertex AI provides monitoring capabilities that allow you to track model performance, detect drift in data distributions, and set up alerts for anomalies. This proactive monitoring ensures that your models continue to deliver accurate results as data and business conditions change over time.\n",
-    "\n",
-    "- **Governance**: Managing ML models and data in a secure and compliant manner is essential for businesses, especially those in regulated industries. Vertex AI helps you implement governance policies to control access to data, monitor model usage, and enforce compliance with data privacy regulations. This ensures that your ML operations are in line with legal and ethical standards.\n",
-    "\n",
-    "- **Scalability**: Vertex AI is built on Google Cloud's infrastructure, which means it offers unparalleled scalability. Whether you're dealing with small-scale experiments or large-scale production deployments, Vertex AI can scale to meet your needs, ensuring that your ML workflows can handle increased workloads without performance bottlenecks.\n",
-    "\n",
-    "- **Collaboration**: Collaboration is essential in ML development, and Vertex AI provides features that facilitate collaboration among data scientists, machine learning engineers, and other stakeholders. You can share notebooks, collaborate on model development, and maintain version control of your ML assets.\n",
-    "\n",
-    "- **Model Serving**: Vertex AI makes it easy to deploy ML models as APIs for real-time inference or batch processing. This enables you to integrate your ML models into applications, websites, or other services with ease.\n",
-    "\n",
-    "- **Cost Management**: Cost control is a crucial aspect of any ML project. Vertex AI offers cost management tools and insights to help you optimize your ML workflows and keep your expenses in check.\n",
-    "\n",
-    "By utilizing Vertex AI, you can take advantage of Google Cloud's cutting-edge technology and expertise in machine learning to accelerate your MLOps journey. The platform offers a comprehensive set of tools and services that cover the entire ML lifecycle, from data preparation to model deployment and beyond, making it a valuable resource for organizations looking to harness the power of ML in a scalable, efficient, and secure manner.\n",
-    "\n",
-    "To learn more about MLOps on Vertex AI and how it can transform your ML workflows, you can visit the [official documentation](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops).\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**This repository provides an example ML training and prediction pipelines for XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips).**\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Pre-requisites\n",
-    "\n",
-    "Before you can successfully execute the example pipelines, there are a few additional components you need to deploy. These components have not been included in the Terraform code as they are specific to these pipelines."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "1. Create a new BigQuery dataset for the Chicago Taxi data:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "2. Create a new BigQuery dataset for data processing during the pipelines:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install google-cloud-bigquery-datatransfer"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "destination_project_id = os.environ[\"VERTEX_PROJECT_ID\"]\n",
-    "destination_dataset_id = \"chicago_taxi_trips\"\n",
-    "source_project_id = \"bigquery-public-data\"\n",
-    "source_dataset_id = \"chicago_taxi_trips\"\n",
-    "transfer_config = bigquery_datatransfer.TransferConfig(\n",
-    "    destination_dataset_id=destination_dataset_id,\n",
-    "    display_name=\"Chicago taxi trip mirror\",\n",
-    "    data_source_id=\"cross_region_copy\",\n",
-    "    params={\n",
-    "        \"source_project_id\": source_project_id,\n",
-    "        \"source_dataset_id\": source_dataset_id,\n",
-    "    },\n",
-    "    schedule=\"every 24 hours\",\n",
-    ")\n",
-    "transfer_config = transfer_client.create_transfer_config(\n",
-    "    parent=transfer_client.common_project_path(destination_project_id),\n",
-    "    transfer_config=transfer_config,\n",
-    ")\n",
-    "TRANSFER_CONFIG=transfer_config.name\n",
-    "print(f\"Created transfer config: {TRANSFER_CONFIG}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Building the container images\n",
-    "\n",
-    "The `model` directory contains the code for custom training and serving container images `model/training/train.py`.\n",
-    "\n",
-    "A custom container is a Docker image that you create to run your training application. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Vertex AI. To learn more you can check out [official documentation](https://cloud.google.com/vertex-ai/docs/training/containers-overview)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To build the training and serving container images and push them to Artifact Registry run the next cell."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make build"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Running Pipelines\n",
-    "\n",
-    "You can run the training pipeline by executing cell below.\n",
-    "\n",
-    "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
-    "\n",
-    "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
-    "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Run Training Pipeline**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make run pipeline=training build=false"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it directly through the Google Cloud Console UI by navigating to Vertex AI and then selecting Pipelines."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Training Pipeline**\n",
-    "![Training Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/training_pipeline.png?raw=true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Run Prediction Pipeline** \n",
-    "\n",
-    "After successful training job, you can try prediction pipeline."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! make run pipeline=prediction build=false"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Prediction Pipeline**\n",
-    "\n",
-    "![Predictions Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/prediction_pipeline.png?raw=true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "TpV-iwP9qw9c"
-   },
-   "source": [
-    "## Cleaning up\n",
-    "\n",
-    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
-    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
-    "\n",
-    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Empty the buckets to enable their deletion:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete data transfer config:**\n",
-    "\n",
-    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import google.api_core.exceptions\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "transfer_config_name = TRANSFER_CONFIG # Transfer Config Name\n",
-    "try:\n",
-    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
-    "except google.api_core.exceptions.NotFound:\n",
-    "    print(\"Transfer config not found.\")\n",
-    "else:\n",
-    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for the Chicago Taxi data:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for data processing during the pipelines:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! make undeploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete local files:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "cd ..\n",
-    "rm -r vertex-pipelines-end-to-end-samples"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "collapsed_sections": [],
-   "name": "notebook_template.ipynb",
-   "toc_visible": true
-  },
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.6"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/docs/notebooks/scripts/install_poetry.sh b/docs/notebooks/scripts/install_poetry.sh
new file mode 100644
index 00000000..ef9e0252
--- /dev/null
+++ b/docs/notebooks/scripts/install_poetry.sh
@@ -0,0 +1,6 @@
+#!/bin/bash
+# install poetry
+curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -
+# add poetry to PATH
+echo "export PATH=$HOME/.poetry/bin:PATH" >> $HOME/.bashrc
+poetry --version
diff --git a/docs/notebooks/scripts/install_terraform.sh b/docs/notebooks/scripts/install_terraform.sh
new file mode 100644
index 00000000..eba5fb8e
--- /dev/null
+++ b/docs/notebooks/scripts/install_terraform.sh
@@ -0,0 +1,9 @@
+#!/bin/bash
+# create temporary folder
+mkdir tmp && cd tmp || exit
+# download terraform and unzip
+curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip && unzip terraform.zip > /dev/null
+# move binaries to ~/.bin
+mkdir $HOME/.bin && mv terraform $HOME/.bin > /dev/null
+# clean up temporary folder
+cd .. && rm -r tmp || exit
diff --git a/docs/notebooks/workbench/01_infrastructure_setup.ipynb b/docs/notebooks/workbench/01_infrastructure_setup.ipynb
deleted file mode 100644
index 2e6829a4..00000000
--- a/docs/notebooks/workbench/01_infrastructure_setup.ipynb
+++ /dev/null
@@ -1,498 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "ur8xi4C7S06n"
-   },
-   "outputs": [],
-   "source": [
-    "# Copyright 2023 Google LLC\n",
-    "#\n",
-    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-    "# you may not use this file except in compliance with the License.\n",
-    "# You may obtain a copy of the License at\n",
-    "#\n",
-    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-    "#\n",
-    "# Unless required by applicable law or agreed to in writing, software\n",
-    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-    "# See the License for the specific language governing permissions and\n",
-    "# limitations under the License."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "JAPoU8Sm5E6e"
-   },
-   "source": [
-    "# Running Vertex Pipelines using E2E Samples repository - Infrastructure setup.\n",
-    "\n",
-    "\n",
-    "<table align=\"left\">\n",
-    "\n",
-    "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/01_infrastructure_setup.ipynb\">\n",
-    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
-    "      Open in Vertex AI Workbench\n",
-    "    </a>\n",
-    "  </td>                                                                                               \n",
-    "</table>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "tvgnzT1CKxrO",
-    "tags": []
-   },
-   "source": [
-    "## Overview\n",
-    "\n",
-    "This notebook shows you how to setup infrastructure to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
-    "\n",
-    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "d975e698c9a4"
-   },
-   "source": [
-    "### Objective\n",
-    "\n",
-    "In this tutorial, you learn how to set up the cloud infrastructure, in order to launch your first training and predicition pipeline:\n",
-    "\n",
-    "This tutorial uses the following Google Cloud services and resources:\n",
-    "\n",
-    "- *`Vertex Pipelines`*\n",
-    "- *`Google Cloud Storage`*\n",
-    "- *`Artifact Registry`*\n",
-    "- *`BigQuery`*\n",
-    "- *`Cloud Build`*\n",
-    "\n",
-    "The steps performed include:\n",
-    "\n",
-    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "aed92deeb4a0"
-   },
-   "source": [
-    "### Costs \n",
-    "\n",
-    "\n",
-    "This tutorial uses billable components of Google Cloud:\n",
-    "\n",
-    "* Vertex AI\n",
-    "* BigQuery\n",
-    "* Cloud Storage\n",
-    "* Cloud Build\n",
-    "* Artifact Registry\n",
-    "\n",
-    "\n",
-    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
-    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
-    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
-    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
-    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
-    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
-    "to generate a cost estimate based on your projected usage."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Prerequisites\n",
-    "\n",
-    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
-    "- Make\n",
-    "- [Terraform](https://www.terraform.io)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Clone Turbo Templates repository"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Clone a Git repository\n",
-    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Infrastructure"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The cloud infrastructure is managed using Terraform and is defined in the [`terraform`](terraform) directory. There are three Terraform modules defined in [`terraform/modules`](terraform/modules):\n",
-    "\n",
-    "- `cloudfunction` - deploys a (Pub/Sub-triggered) Cloud Function from local source code\n",
-    "- `scheduled_pipelines` - deploys Cloud Scheduler jobs that will trigger Vertex Pipeline runs (via the above Cloud Function)\n",
-    "- `vertex_deployment` - deploys Cloud infrastructure required for running Vertex Pipelines, including enabling APIs, creating buckets, Artifact Registry repos, service accounts, and IAM permissions."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Terraform Installation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Installing Terraform by downloading a pre-compiled binary.**\n",
-    "1. **Download** the appropriate package for your system as a zip archive from the Terraform website.\n",
-    "2. **Unzip** the downloaded package.\n",
-    "3. **Add Terraform to PATH**."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "mkdir temp\n",
-    "cd temp\n",
-    "curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
-    "unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
-    "mkdir $HOME/.bin\n",
-    "mv terraform $HOME/.bin > /dev/null\n",
-    "cd ..\n",
-    "rm -r temp"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.bin')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! terraform -version"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Before You Begin"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "BF1j6f9HApxa",
-    "tags": []
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-    "\n",
-    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
-   },
-   "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "oM1iC_MfAts1",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "PROJECT_ID = \"[my-project-id]\"\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Authenticate your Google Cloud account\n",
-    "\n",
-    "\n",
-    "As you're running a Jupyter environment on workbench, you are already authenticated."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to run `make` commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID` and `VERTEX_LOCATION`)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%writefile .env\n",
-    "\n",
-    "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_PROJECT_ID=my-project-id\n",
-    "\n",
-    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
-    "RESOURCE_SUFFIX=default\n",
-    "\n",
-    "# Leave as-is\n",
-    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
-    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
-    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
-    "\n",
-    "# Optional\n",
-    "VERTEX_CMEK_IDENTIFIER=\n",
-    "VERTEX_NETWORK="
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from dotenv import load_dotenv\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "zgPO1eR3CYjk",
-    "tags": []
-   },
-   "source": [
-    "## Infrastructure deployment using terraform.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
-    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Create tfstate bucket\n",
-    "\n",
-    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "-EcIXiGsCePi"
-   },
-   "source": [
-    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "NIq7R4HZCfIc",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "960505627ddf"
-   },
-   "source": [
-    "### Deploy required infrastructure"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "Deploy command will:\n",
-    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
-    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make deploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Congratulations on successfully deploying the infrastructure required to run ML pipelines!"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "collapsed_sections": [],
-   "name": "notebook_template.ipynb",
-   "toc_visible": true
-  },
-  "kernelspec": {
-   "display_name": "Python (Local)",
-   "language": "python",
-   "name": "local-base"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/docs/notebooks/workbench/02_run_pipelines.ipynb b/docs/notebooks/workbench/02_run_pipelines.ipynb
deleted file mode 100644
index 2f54d840..00000000
--- a/docs/notebooks/workbench/02_run_pipelines.ipynb
+++ /dev/null
@@ -1,603 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "ur8xi4C7S06n"
-   },
-   "outputs": [],
-   "source": [
-    "# Copyright 2023 Google LLC\n",
-    "#\n",
-    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-    "# you may not use this file except in compliance with the License.\n",
-    "# You may obtain a copy of the License at\n",
-    "#\n",
-    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-    "#\n",
-    "# Unless required by applicable law or agreed to in writing, software\n",
-    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-    "# See the License for the specific language governing permissions and\n",
-    "# limitations under the License."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "JAPoU8Sm5E6e"
-   },
-   "source": [
-    "# Running Vertex Pipelines using E2E Samples repository - Triggering Pipelines.\n",
-    "\n",
-    "\n",
-    "<table align=\"left\">\n",
-    "\n",
-    "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/02_run_pipelines.ipynb\">\n",
-    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
-    "      Open in Vertex AI Workbench\n",
-    "    </a>\n",
-    "  </td>                                                                                               \n",
-    "</table>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "tvgnzT1CKxrO",
-    "tags": []
-   },
-   "source": [
-    "## Overview\n",
-    "\n",
-    "This notebook shows you how to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
-    "\n",
-    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "d975e698c9a4"
-   },
-   "source": [
-    "### Objective\n",
-    "\n",
-    "In this tutorial, you learn how to launch your first training and predicition pipeline, and analyse the results:\n",
-    "\n",
-    "This tutorial uses the following Google Cloud services and resources:\n",
-    "\n",
-    "- *`Vertex Pipelines`*\n",
-    "- *`Google Cloud Storage`*\n",
-    "- *`Artifact Registry`*\n",
-    "- *`BigQuery`*\n",
-    "- *`Cloud Build`*\n",
-    "\n",
-    "The steps performed include:\n",
-    "\n",
-    "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "08d289fa873f"
-   },
-   "source": [
-    "### Dataset\n",
-    "\n",
-    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
-    "\n",
-    "\n",
-    "This public dataset is hosted in Google BigQuery."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "aed92deeb4a0"
-   },
-   "source": [
-    "### Costs \n",
-    "\n",
-    "\n",
-    "This tutorial uses billable components of Google Cloud:\n",
-    "\n",
-    "* Vertex AI\n",
-    "* BigQuery\n",
-    "* Cloud Storage\n",
-    "* Cloud Build\n",
-    "* Artifact Registry\n",
-    "\n",
-    "\n",
-    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
-    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
-    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
-    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
-    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
-    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
-    "to generate a cost estimate based on your projected usage."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Prerequisites\n",
-    "\n",
-    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
-    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
-    "- Make\n",
-    "- [Poetry](https://python-poetry.org)\n",
-    "- [pyenv](https://github.com/pyenv/pyenv)\n",
-    "- Infrastructure deployed ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Change working directory"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "i7EUnXsZhAGF",
-    "tags": []
-   },
-   "source": [
-    "## Installation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Install the packages required for executing this notebook."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Install poetry\n",
-    "import os\n",
-    "!curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -\n",
-    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.poetry/bin')\n",
-    "!poetry --version"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "2b4ef9b72d43",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "#Install poetry dependencies for ML pipelines\n",
-    "! make install"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Before You Begin"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "BF1j6f9HApxa",
-    "tags": []
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-    "\n",
-    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
-   },
-   "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "oM1iC_MfAts1",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Authenticate your Google Cloud account\n",
-    "\n",
-    "\n",
-    "As you're running a Jupyter environment on workbench, you are already authenticated."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to run make commands relevant environment variables need to be set. You can re-use `.env` file defined in [01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from dotenv import load_dotenv\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Example ML Pipelines"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "To automate, monitor, and govern your ML workflows, you can use [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops). Vertex AI is a powerful platform offered by Google Cloud that empowers organizations to streamline and enhance their Machine Learning (ML) workflows through automation, monitoring, and governance.\n",
-    "\n",
-    "- **Automation**: Vertex AI offers a suite of tools and services designed to automate various aspects of ML development and deployment. This includes automating data preprocessing, model training, hyperparameter tuning, and model deployment. Automation not only saves time but also reduces the potential for human error, making your ML workflows more efficient and reliable.\n",
-    "\n",
-    "- **Monitoring**: Effective monitoring is crucial for maintaining the performance and reliability of ML models in production. Vertex AI provides monitoring capabilities that allow you to track model performance, detect drift in data distributions, and set up alerts for anomalies. This proactive monitoring ensures that your models continue to deliver accurate results as data and business conditions change over time.\n",
-    "\n",
-    "- **Governance**: Managing ML models and data in a secure and compliant manner is essential for businesses, especially those in regulated industries. Vertex AI helps you implement governance policies to control access to data, monitor model usage, and enforce compliance with data privacy regulations. This ensures that your ML operations are in line with legal and ethical standards.\n",
-    "\n",
-    "- **Scalability**: Vertex AI is built on Google Cloud's infrastructure, which means it offers unparalleled scalability. Whether you're dealing with small-scale experiments or large-scale production deployments, Vertex AI can scale to meet your needs, ensuring that your ML workflows can handle increased workloads without performance bottlenecks.\n",
-    "\n",
-    "- **Collaboration**: Collaboration is essential in ML development, and Vertex AI provides features that facilitate collaboration among data scientists, machine learning engineers, and other stakeholders. You can share notebooks, collaborate on model development, and maintain version control of your ML assets.\n",
-    "\n",
-    "- **Model Serving**: Vertex AI makes it easy to deploy ML models as APIs for real-time inference or batch processing. This enables you to integrate your ML models into applications, websites, or other services with ease.\n",
-    "\n",
-    "- **Cost Management**: Cost control is a crucial aspect of any ML project. Vertex AI offers cost management tools and insights to help you optimize your ML workflows and keep your expenses in check.\n",
-    "\n",
-    "By utilizing Vertex AI, you can take advantage of Google Cloud's cutting-edge technology and expertise in machine learning to accelerate your MLOps journey. The platform offers a comprehensive set of tools and services that cover the entire ML lifecycle, from data preparation to model deployment and beyond, making it a valuable resource for organizations looking to harness the power of ML in a scalable, efficient, and secure manner.\n",
-    "\n",
-    "To learn more about MLOps on Vertex AI and how it can transform your ML workflows, you can visit the [official documentation](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops).\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**This repository provides an example ML training and prediction pipelines for XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips).**\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### Pre-requisites\n",
-    "\n",
-    "Before you can successfully execute the example pipelines, there are a few additional components you need to deploy. These components have not been included in the Terraform code as they are specific to these pipelines."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "1. Create a new BigQuery dataset for the Chicago Taxi data:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "2. Create a new BigQuery dataset for data processing during the pipelines:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install google-cloud-bigquery-datatransfer"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "destination_project_id = os.environ[\"VERTEX_PROJECT_ID\"]\n",
-    "destination_dataset_id = \"chicago_taxi_trips\"\n",
-    "source_project_id = \"bigquery-public-data\"\n",
-    "source_dataset_id = \"chicago_taxi_trips\"\n",
-    "transfer_config = bigquery_datatransfer.TransferConfig(\n",
-    "    destination_dataset_id=destination_dataset_id,\n",
-    "    display_name=\"Chicago taxi trip mirror\",\n",
-    "    data_source_id=\"cross_region_copy\",\n",
-    "    params={\n",
-    "        \"source_project_id\": source_project_id,\n",
-    "        \"source_dataset_id\": source_dataset_id,\n",
-    "    },\n",
-    "    schedule=\"every 24 hours\",\n",
-    ")\n",
-    "transfer_config = transfer_client.create_transfer_config(\n",
-    "    parent=transfer_client.common_project_path(destination_project_id),\n",
-    "    transfer_config=transfer_config,\n",
-    ")\n",
-    "TRANSFER_CONFIG=transfer_config.name\n",
-    "print(f\"Created transfer config: {TRANSFER_CONFIG}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Building the container images\n",
-    "\n",
-    "The `model` directory contains the code for custom training and serving container images `model/training/train.py`.\n",
-    "\n",
-    "A custom container is a Docker image that you create to run your training application. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Vertex AI. To learn more you can check out [official documentation](https://cloud.google.com/vertex-ai/docs/training/containers-overview)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To build the training and serving container images and push them to Artifact Registry run the next cell."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make build"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Running Pipelines\n",
-    "\n",
-    "You can run the training pipeline by executing cell below.\n",
-    "\n",
-    "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
-    "\n",
-    "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
-    "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Run Training Pipeline**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make run pipeline=training build=false"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it directly through the Google Cloud Console UI by navigating to Vertex AI and then selecting Pipelines."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Training Pipeline**\n",
-    "![Training Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/training_pipeline.png?raw=true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Run Prediction Pipeline** \n",
-    "\n",
-    "After successful training job, you can try prediction pipeline."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! make run pipeline=prediction build=false"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Prediction Pipeline**\n",
-    "\n",
-    "![Predictions Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/prediction_pipeline.png?raw=true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Congratulations on successfully running your first ML pipelines!"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "collapsed_sections": [],
-   "name": "notebook_template.ipynb",
-   "toc_visible": true
-  },
-  "kernelspec": {
-   "display_name": "Python (Local)",
-   "language": "python",
-   "name": "local-base"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb b/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
deleted file mode 100644
index 06ea8fb6..00000000
--- a/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb
+++ /dev/null
@@ -1,412 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "ur8xi4C7S06n"
-   },
-   "outputs": [],
-   "source": [
-    "# Copyright 2023 Google LLC\n",
-    "#\n",
-    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-    "# you may not use this file except in compliance with the License.\n",
-    "# You may obtain a copy of the License at\n",
-    "#\n",
-    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-    "#\n",
-    "# Unless required by applicable law or agreed to in writing, software\n",
-    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-    "# See the License for the specific language governing permissions and\n",
-    "# limitations under the License."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "JAPoU8Sm5E6e"
-   },
-   "source": [
-    "# Running Vertex Pipelines using E2E Samples repository - Infrastructure Cleanup\n",
-    "\n",
-    "\n",
-    "<table align=\"left\">\n",
-    "\n",
-    "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/03_infrastructure_cleanup.ipynb\">\n",
-    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
-    "      Open in Vertex AI Workbench\n",
-    "    </a>\n",
-    "  </td>                                                                                               \n",
-    "</table>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "24743cf4a1e1"
-   },
-   "source": [
-    "**_NOTE_**: This notebook has been tested in the following environment:\n",
-    "\n",
-    "* Python version = 3.9"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "tvgnzT1CKxrO",
-    "tags": []
-   },
-   "source": [
-    "## Overview\n",
-    "\n",
-    "This notebook shows you how to destroy infrastructure which was created in ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "d975e698c9a4"
-   },
-   "source": [
-    "### Objective\n",
-    "\n",
-    "In this tutorial, you learn how to destroy infrastructure using terraform.\n",
-    "\n",
-    "The steps performed include:\n",
-    "\n",
-    "* Destroy infrastructure using Terraform."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Prerequisites\n",
-    "\n",
-    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
-    "- Make\n",
-    "- [Terraform](https://www.terraform.io)\n",
-    "- Infrastructure deployed ([01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb))."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Change working directory"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Before You Begin"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "BF1j6f9HApxa",
-    "tags": []
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project).\n",
-    "\n",
-    "3. If you are running this notebook locally, you need to install the [Cloud SDK](https://cloud.google.com/sdk)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
-   },
-   "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "oM1iC_MfAts1",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "PROJECT_ID = \"[my-project-id]\"  # @param {type:\"string\"}\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Authenticate your Google Cloud account\n",
-    "\n",
-    "\n",
-    "As you're running a Jupyter environment on workbench, you are already authenticated."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In order to run make commands relevant environment variables need to be set. You can re-use `.env` file defined in [01_infrastructure_setup.ipynb](01_infrastructure_setup.ipynb)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Load environment variables using [Python-dotenv](https://pypi.org/project/python-dotenv/)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from dotenv import load_dotenv\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "TpV-iwP9qw9c"
-   },
-   "source": [
-    "## Cleaning up\n",
-    "\n",
-    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
-    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
-    "\n",
-    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Empty the buckets to enable their deletion:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete data transfer config:**\n",
-    "\n",
-    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import google.api_core.exceptions\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "transfer_config_name = \"my-transfer-config\" # Transfer Config Resource Name (projects/{project_number}/locations/{location}/transferConfigs/{transfer_config_id)\n",
-    "try:\n",
-    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
-    "except google.api_core.exceptions.NotFound:\n",
-    "    print(\"Transfer config not found.\")\n",
-    "else:\n",
-    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for the Chicago Taxi data:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for data processing during the pipelines:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.bin')\n",
-    "! make undeploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete local files:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "cd ..\n",
-    "rm -r vertex-pipelines-end-to-end-samples"
-   ]
-  },
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Congratulations on successfully destroying your infrastructure!"
-   ]
-  }
- ],
- "metadata": {
-  "colab": {
-   "collapsed_sections": [],
-   "name": "notebook_template.ipynb",
-   "toc_visible": true
-  },
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.5"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "fd2d2b37aae7c0649f55b7e5d509b0b6c853821eea0be4d0f279f57c5531e1e5"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/docs/notebooks/workbench/pipelines_workbench.ipynb b/docs/notebooks/workbench/pipelines_workbench.ipynb
deleted file mode 100644
index 9eb4e1ab..00000000
--- a/docs/notebooks/workbench/pipelines_workbench.ipynb
+++ /dev/null
@@ -1,1010 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c712dfd9-4cf9-49ca-b7c0-f14cfc78d1bd",
-   "metadata": {
-    "id": "ur8xi4C7S06n"
-   },
-   "outputs": [],
-   "source": [
-    "# Copyright 2023 Google LLC\n",
-    "#\n",
-    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
-    "# you may not use this file except in compliance with the License.\n",
-    "# You may obtain a copy of the License at\n",
-    "#\n",
-    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
-    "#\n",
-    "# Unless required by applicable law or agreed to in writing, software\n",
-    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
-    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
-    "# See the License for the specific language governing permissions and\n",
-    "# limitations under the License."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f082fcb1-255f-4445-a20c-66c6dd495728",
-   "metadata": {
-    "id": "JAPoU8Sm5E6e"
-   },
-   "source": [
-    "# Running Vertex Pipelines using E2E Samples repository.\n",
-    "\n",
-    "\n",
-    "<table align=\"left\">\n",
-    "\n",
-    "  <td>\n",
-    "    <a href=\"https://colab.research.google.com/github/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/pipelines_colab.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/colab-logo-32px.png\" alt=\"Colab logo\"> Run in Colab\n",
-    "    </a>\n",
-    "  </td>\n",
-    "  <td>\n",
-    "    <a href=\"https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/pipelines.ipynb\">\n",
-    "      <img src=\"https://cloud.google.com/ml-engine/images/github-logo-32px.png\" alt=\"GitHub logo\">\n",
-    "      View on GitHub\n",
-    "    </a>\n",
-    "  </td>\n",
-    "  <td>\n",
-    "    <a href=\"https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https://raw.githubusercontent.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/notebooks/workbench/pipelines_workbench.ipynb\">\n",
-    "      <img src=\"https://lh3.googleusercontent.com/UiNooY4LUgW_oTvpsNhPpQzsstV5W8F7rYgxgGBD85cWJoLmrOzhVs_ksK_vgx40SHs7jCqkTkCk=e14-rj-sc0xffffff-h130-w32\" alt=\"Vertex AI logo\">\n",
-    "      Open in Vertex AI Workbench\n",
-    "    </a>\n",
-    "  </td>                                                                                               \n",
-    "</table>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "14d2d0de-b29b-4040-bee7-1452af822fca",
-   "metadata": {
-    "id": "tvgnzT1CKxrO",
-    "tags": []
-   },
-   "source": [
-    "## Overview\n",
-    "\n",
-    "This notebook shows you how to run production ready pipelines on Google Cloud using Datatonic's Vertex Pipelines End-to-end Samples repository.\n",
-    "\n",
-    "Learn more about [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/introduction)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b7f815bd-0cc6-47ae-9f71-5cd1817c6a0d",
-   "metadata": {
-    "id": "d975e698c9a4"
-   },
-   "source": [
-    "### Objective\n",
-    "\n",
-    "In this tutorial, you learn how to set up the repo, launch your first training and predicition pipeline, and analyse the results:\n",
-    "\n",
-    "This tutorial uses the following Google Cloud services and resources:\n",
-    "\n",
-    "- *`Vertex Pipelines`*\n",
-    "- *`Google Cloud Storage`*\n",
-    "- *`Artifact Registry`*\n",
-    "- *`BigQuery`*\n",
-    "- *`Cloud Build`*\n",
-    "\n",
-    "The steps performed include:\n",
-    "\n",
-    "* Deploy infrastructure using Terraform for a typical setup of Vertex AI and other relevant services.\n",
-    "* Run ML training and batch prediction pipelines using the Kubeflow Pipelines SDK for an example use case."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f8fd9521-9fcc-4961-86e3-d43f3ae15d5e",
-   "metadata": {
-    "id": "08d289fa873f"
-   },
-   "source": [
-    "### Dataset\n",
-    "\n",
-    "Example ML training and predictions pipelines for scikit-learn/XGBoost will use the popular [Chicago Taxi Trips Dataset](https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=chicago_taxi_trips&page=dataset). The dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency.\n",
-    "\n",
-    "\n",
-    "This public dataset is hosted in Google BigQuery."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "53231e62-f463-4eb9-a327-3f5537effe80",
-   "metadata": {
-    "id": "aed92deeb4a0"
-   },
-   "source": [
-    "### Costs \n",
-    "\n",
-    "\n",
-    "This tutorial uses billable components of Google Cloud:\n",
-    "\n",
-    "* Vertex AI\n",
-    "* BigQuery\n",
-    "* Cloud Storage\n",
-    "* Cloud Build\n",
-    "* Artifact Registry\n",
-    "\n",
-    "\n",
-    "Learn about [Vertex AI pricing](https://cloud.google.com/vertex-ai/pricing),\n",
-    "[BigQuery pricing](https://cloud.google.com/bigquery/pricing),\n",
-    "and [Cloud Storage pricing](https://cloud.google.com/storage/pricing),\n",
-    "and [Cloud Build pricing](https://cloud.google.com/build/pricing),\n",
-    "and [Artifact Registry](https://cloud.google.com/artifact-registry/pricing),\n",
-    "and use the [Pricing Calculator](https://cloud.google.com/products/calculator/)\n",
-    "to generate a cost estimate based on your projected usage."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a66f9fc1-8435-40ef-984d-af5a18e6656e",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Prerequisites\n",
-    "\n",
-    "- [Pyenv](https://github.com/pyenv/pyenv#installation) for managing Python versions\n",
-    "- [Google Cloud SDK (gcloud)](https://cloud.google.com/sdk/docs/quickstart)\n",
-    "- Make\n",
-    "- [Poetry](https://python-poetry.org)\n",
-    "- [Terraform](https://www.terraform.io) (To install Terraform on your local machine we recommend using [tfswitch](https://tfswitch.warrensbox.com/) to automatically choose and download an appropriate version.)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0ab044e6-d1ce-448d-af88-31b2462fd792",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Clone Turbo Templates repository"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "3176102b-059d-483b-ba67-647e78553947",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "# Clone a Git repository\n",
-    "!git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "514bb16f-5604-4b49-911a-6eff37f07575",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%cd vertex-pipelines-end-to-end-samples/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "80b3b918-02da-414c-9ea8-a335bfe60387",
-   "metadata": {
-    "id": "i7EUnXsZhAGF",
-    "tags": []
-   },
-   "source": [
-    "## Installation"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "467b87cf-6956-4d9d-b9d9-85ed2efaa195",
-   "metadata": {},
-   "source": [
-    "Install the packages required for executing this notebook."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b4441b15-24ed-4b41-a434-9e7651c2a5b9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Install poetry\n",
-    "import os\n",
-    "!curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -\n",
-    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.poetry/bin')\n",
-    "!poetry --version"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f371b7e1-fea0-40f5-9a2c-7ceacdfbdc37",
-   "metadata": {
-    "id": "2b4ef9b72d43",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "#Install poetry dependencies for ML pipelines\n",
-    "! make install"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "6e4a80e2-3169-4c0e-b4df-df7a9f8ec69e",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Terraform"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4371d2cf-523e-4c2a-891d-67e162da3d7c",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Installing Terraform by downloading a pre-compiled binary.**\n",
-    "1. **Download** the appropriate package for your system as a zip archive from the Terraform website.\n",
-    "2. **Unzip** the downloaded package.\n",
-    "3. **Add Terraform to PATH**."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "61201833-4162-4fa8-a555-b83ce99eef59",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "mkdir temp\n",
-    "cd temp\n",
-    "curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip\n",
-    "unzip terraform.zip > /dev/null && rm -f terraform.zip > /dev/null\n",
-    "mkdir $HOME/.bin\n",
-    "mv terraform $HOME/.bin > /dev/null\n",
-    "cd ..\n",
-    "rm -r temp"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "80366eba-603c-44f0-9069-496ec4499c39",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "os.environ['PATH'] += os.pathsep + os.path.join(os.environ['HOME'], '.bin')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "184e9279-d446-4b29-95be-29cf57eebba7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! terraform -version"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a1571126-c7d3-477a-846a-9a387e7a1aab",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Before You Begin"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a13f3a75-a6d2-4d08-8abf-667a597193cf",
-   "metadata": {
-    "id": "BF1j6f9HApxa",
-    "tags": []
-   },
-   "source": [
-    "### Set up your Google Cloud project\n",
-    "\n",
-    "**The following steps are required, regardless of your notebook environment.**\n",
-    "\n",
-    "1. [Select or create a Google Cloud project](https://console.cloud.google.com/cloud-resource-manager). When you first create an account, you get a $300 free credit towards your compute/storage costs.\n",
-    "\n",
-    "2. [Make sure that billing is enabled for your project](https://cloud.google.com/billing/docs/how-to/modify-project)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "318a28b1-d443-4348-a3a3-9ea7be7d4a4a",
-   "metadata": {
-    "id": "WReHDGG5g0XY"
-   },
-   "source": [
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cb0d271e-1105-4925-a451-c8b417cc4920",
-   "metadata": {
-    "id": "oM1iC_MfAts1",
-    "tags": []
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001b[1;33mWARNING:\u001b[0m You do not appear to have access to project [[my-project-id]] or it does not exist.\n",
-      "Are you sure you wish to set property [core/project] to [my-project-id]?\n",
-      "\n",
-      "Do you want to continue (Y/n)?  "
-     ]
-    }
-   ],
-   "source": [
-    "PROJECT_ID = \"[my-project-id]\"\n",
-    "# Set the project id\n",
-    "! gcloud config set project {PROJECT_ID}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "282aa597-f7e4-4fa9-8bb3-eecf95b57d02",
-   "metadata": {},
-   "source": [
-    "### Authenticate your Google Cloud account\n",
-    "\n",
-    "\n",
-    "You are running the notebook on Vertex AI workbench, therefore, you are already authenticated."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a023663e-f298-462b-9c2a-390ef32c2502",
-   "metadata": {},
-   "source": [
-    "### Environment Setup"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3f4b1455-bdf0-4d70-a1de-93ace9cea86b",
-   "metadata": {},
-   "source": [
-    "In order to run make commands relevant environment variables need to be set. Please update the environment variables for your dev environment (particularly `VERTEX_PROJECT_ID` and `VERTEX_LOCATION`)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9bc832f9-3b4d-4e4c-8bb5-11bb29364e23",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%writefile .env\n",
-    "\n",
-    "VERTEX_LOCATION=europe-west2\n",
-    "VERTEX_PROJECT_ID=my-project-id\n",
-    "\n",
-    "# Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development \n",
-    "RESOURCE_SUFFIX=default\n",
-    "\n",
-    "# Leave as-is\n",
-    "VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com\n",
-    "VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root\n",
-    "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images\n",
-    "\n",
-    "# Optional\n",
-    "VERTEX_CMEK_IDENTIFIER=\n",
-    "VERTEX_NETWORK="
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "db667536-b4f9-4249-86f1-07d8ac3d6d4c",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! pip install python-dotenv"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "303fb592-dabe-4e20-a915-33af32bd7a80",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "from dotenv import load_dotenv\n",
-    "\n",
-    "load_dotenv()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ddda6825-4da6-4d1a-8e2f-29717d9a6f04",
-   "metadata": {
-    "id": "zgPO1eR3CYjk",
-    "tags": []
-   },
-   "source": [
-    "## Infrastructure deployment using terraform.\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "41c67e53-b246-45c2-bdae-09d2a8c3ad95",
-   "metadata": {},
-   "source": [
-    "#### Enable the Cloud Resource Manager and Service Usage APs for your project."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a5870230-222b-45bd-97a4-17eb3af6dac5",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gcloud services enable cloudresourcemanager.googleapis.com --project=$VERTEX_PROJECT_ID\n",
-    "! gcloud services enable serviceusage.googleapis.com --project=$VERTEX_PROJECT_ID"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "78418043-e737-48cb-b030-c934835cceb5",
-   "metadata": {},
-   "source": [
-    "#### Create tfstate bucket\n",
-    "\n",
-    "Before provisioning your infrastructure we need to create Google Cloud Storage (GCS) bucket that will be used to store the [state files](https://developer.hashicorp.com/terraform/language/state/remote) remotely for Terraform deployments."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "bb7a3f5c-9789-4f27-870c-bd6f38e587e4",
-   "metadata": {
-    "id": "-EcIXiGsCePi"
-   },
-   "source": [
-    "**Only if your bucket doesn't already exist**: Run the following cell to create your Cloud Storage bucket."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "1133567c-b668-44aa-8c6c-77cbd70065fd",
-   "metadata": {
-    "id": "NIq7R4HZCfIc",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a836f098-a37a-4013-9463-4cec11982bac",
-   "metadata": {
-    "id": "960505627ddf"
-   },
-   "source": [
-    "### Deploy required infrastructure"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d2668618-4a57-402e-9861-daf95eb27bba",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "Deploy command will:\n",
-    "1. Prepare a Terraform working directory by downloading any necessary provider plugins and initialize the backend configuration.\n",
-    "1. Create infrastructure resources defined in Terraform configuration (terraform/envs/dev)."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8329d73d-ba8f-443e-ab65-379a98c6f254",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make deploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "adfebbc4-1a15-4bff-a98d-5840ee3be972",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "## Example ML Pipelines"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cd23f3b5-1e91-4dc1-acb0-9e9b3e06e259",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "To automate, monitor, and govern your ML workflows, you can use [Vertex AI](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops). Vertex AI is a powerful platform offered by Google Cloud that empowers organizations to streamline and enhance their Machine Learning (ML) workflows through automation, monitoring, and governance.\n",
-    "\n",
-    "- **Automation**: Vertex AI offers a suite of tools and services designed to automate various aspects of ML development and deployment. This includes automating data preprocessing, model training, hyperparameter tuning, and model deployment. Automation not only saves time but also reduces the potential for human error, making your ML workflows more efficient and reliable.\n",
-    "\n",
-    "- **Monitoring**: Effective monitoring is crucial for maintaining the performance and reliability of ML models in production. Vertex AI provides monitoring capabilities that allow you to track model performance, detect drift in data distributions, and set up alerts for anomalies. This proactive monitoring ensures that your models continue to deliver accurate results as data and business conditions change over time.\n",
-    "\n",
-    "- **Governance**: Managing ML models and data in a secure and compliant manner is essential for businesses, especially those in regulated industries. Vertex AI helps you implement governance policies to control access to data, monitor model usage, and enforce compliance with data privacy regulations. This ensures that your ML operations are in line with legal and ethical standards.\n",
-    "\n",
-    "- **Scalability**: Vertex AI is built on Google Cloud's infrastructure, which means it offers unparalleled scalability. Whether you're dealing with small-scale experiments or large-scale production deployments, Vertex AI can scale to meet your needs, ensuring that your ML workflows can handle increased workloads without performance bottlenecks.\n",
-    "\n",
-    "- **Collaboration**: Collaboration is essential in ML development, and Vertex AI provides features that facilitate collaboration among data scientists, machine learning engineers, and other stakeholders. You can share notebooks, collaborate on model development, and maintain version control of your ML assets.\n",
-    "\n",
-    "- **Model Serving**: Vertex AI makes it easy to deploy ML models as APIs for real-time inference or batch processing. This enables you to integrate your ML models into applications, websites, or other services with ease.\n",
-    "\n",
-    "- **Cost Management**: Cost control is a crucial aspect of any ML project. Vertex AI offers cost management tools and insights to help you optimize your ML workflows and keep your expenses in check.\n",
-    "\n",
-    "By utilizing Vertex AI, you can take advantage of Google Cloud's cutting-edge technology and expertise in machine learning to accelerate your MLOps journey. The platform offers a comprehensive set of tools and services that cover the entire ML lifecycle, from data preparation to model deployment and beyond, making it a valuable resource for organizations looking to harness the power of ML in a scalable, efficient, and secure manner.\n",
-    "\n",
-    "To learn more about MLOps on Vertex AI and how it can transform your ML workflows, you can visit the [official documentation](https://cloud.google.com/vertex-ai/docs/start/introduction-mlops).\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2ccf23b8-cce4-44bf-8b4e-1140bf7a8d95",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**This repository provides an example ML training and prediction pipelines for XGBoost using the popular [Chicago Taxi Dataset](https://console.cloud.google.com/marketplace/details/city-of-chicago-public-data/chicago-taxi-trips).**\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "aea16c5d-fada-4920-9ef7-efad814afe26",
-   "metadata": {},
-   "source": [
-    "#### Pre-requisites\n",
-    "\n",
-    "Before you can successfully execute the example pipelines, there are a few additional components you need to deploy. These components have not been included in the Terraform code as they are specific to these pipelines."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "72cdb72e-ecc8-4134-b4d6-e808eddf80a7",
-   "metadata": {},
-   "source": [
-    "1. Create a new BigQuery dataset for the Chicago Taxi data:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2e24884b-e16b-4f5f-bec1-9b7c901130cf",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "d0b11e95-a8b4-4c4b-8f90-d040a97253dd",
-   "metadata": {},
-   "source": [
-    "2. Create a new BigQuery dataset for data processing during the pipelines:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6fee2b6d-44dd-4371-9fd5-76a95dd33d74",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} mk --dataset \"${VERTEX_PROJECT_ID}:preprocessing\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "18a8c603-6d36-4d70-b0b4-25b71f9d9b6b",
-   "metadata": {},
-   "source": [
-    "3. Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c0aeced0-25a4-4d65-ba16-695a2c257c19",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! pip install google-cloud-bigquery-datatransfer"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "66a2dcba-2ee4-44a4-9709-25c95cff7786",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "destination_project_id = os.environ[\"VERTEX_PROJECT_ID\"]\n",
-    "destination_dataset_id = \"chicago_taxi_trips\"\n",
-    "source_project_id = \"bigquery-public-data\"\n",
-    "source_dataset_id = \"chicago_taxi_trips\"\n",
-    "transfer_config = bigquery_datatransfer.TransferConfig(\n",
-    "    destination_dataset_id=destination_dataset_id,\n",
-    "    display_name=\"Chicago taxi trip mirror\",\n",
-    "    data_source_id=\"cross_region_copy\",\n",
-    "    params={\n",
-    "        \"source_project_id\": source_project_id,\n",
-    "        \"source_dataset_id\": source_dataset_id,\n",
-    "    },\n",
-    "    schedule=\"every 24 hours\",\n",
-    ")\n",
-    "transfer_config = transfer_client.create_transfer_config(\n",
-    "    parent=transfer_client.common_project_path(destination_project_id),\n",
-    "    transfer_config=transfer_config,\n",
-    ")\n",
-    "TRANSFER_CONFIG=transfer_config.name\n",
-    "print(f\"Created transfer config: {TRANSFER_CONFIG}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2c6b6b48-9861-40a3-a999-d73aeac674be",
-   "metadata": {},
-   "source": [
-    "### Building the container images\n",
-    "\n",
-    "The `model` directory contains the code for custom training and serving container images `model/training/train.py`.\n",
-    "\n",
-    "A custom container is a Docker image that you create to run your training application. By running your machine learning (ML) training job in a custom container, you can use ML frameworks, non-ML dependencies, libraries, and binaries that are not otherwise supported on Vertex AI. To learn more you can check out [official documentation](https://cloud.google.com/vertex-ai/docs/training/containers-overview)."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "905ad09c-d4c0-40cf-bfaa-621bd8c8e2c9",
-   "metadata": {},
-   "source": [
-    "To build the training and serving container images and push them to Artifact Registry run the next cell."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9bd43278-9809-4673-b1ad-4eaed2446f21",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make build"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4248cc3d-660f-409e-9395-7f700a123e18",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "### Running Pipelines\n",
-    "\n",
-    "You can run the training pipeline by executing cell below.\n",
-    "\n",
-    "This will start the pipeline using the chosen template on Vertex AI, namely it will:\n",
-    "\n",
-    "1. Compile the pipeline using the Kubeflow Pipelines SDK\n",
-    "1. Trigger the pipeline with the help of `pipelines/trigger/main.py`"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "db38a19e-bd11-4311-85f4-f8714d3743a6",
-   "metadata": {},
-   "source": [
-    "**Run Training Pipeline**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "99de7032-b9c9-4ad4-b750-89ac9e9a0cdf",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make run pipeline=training build=false"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4a351524-923e-4f94-bc5f-2e8363473f8e",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "After executing the command, a link will appear, leading you to the Vertex AI platform, where you can monitor your pipeline job. Alternatively, you can access it through the Google Cloud Console UI under Vertex AI/Pipelines."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "627acd39-f46f-43ff-8d19-e7cd18ef7547",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Training Pipeline**\n",
-    "![Training Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/training_pipeline.png?raw=true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e8b196f6-0c99-402c-816e-aa94ad17f987",
-   "metadata": {},
-   "source": [
-    "**Run Prediction Pipeline** \n",
-    "\n",
-    "After successful training job, you can try prediction pipeline."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "56d8595e-b1a3-4b23-9e76-bf7ba34fc443",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! make run pipeline=prediction build=false"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c9372260-6c12-4d01-bfd9-15640e39fe67",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Prediction Pipeline**\n",
-    "\n",
-    "![Predictions Pipeline](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/blob/develop/docs/images/prediction_pipeline.png?raw=true)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "84cf85b5-add4-4df1-a635-b7f513407343",
-   "metadata": {
-    "id": "TpV-iwP9qw9c"
-   },
-   "source": [
-    "## Cleaning up\n",
-    "\n",
-    "To clean up all Google Cloud resources used in this project, you can [delete the Google Cloud\n",
-    "project](https://cloud.google.com/resource-manager/docs/creating-managing-projects#shutting_down_projects) you used for the tutorial.\n",
-    "\n",
-    "Otherwise, you can delete the individual resources you created in this tutorial:\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "04cd62bf-aa69-474a-8765-d32c59ef53da",
-   "metadata": {},
-   "source": [
-    "**Empty the buckets to enable their deletion:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9f37f2ce-b9ad-465a-a6fc-ea279a22b95a",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-staging/**\n",
-    "gsutil rm -a gs://${VERTEX_PROJECT_ID}-pl-root/**"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "291ef684-bbaa-4949-99f2-ff55a86baf70",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete data transfer config:**\n",
-    "\n",
-    "*If transfer config name was not set automatically you can find it via Google Cloud Console UI (BigQuery/Data Transfers)*."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7eaf1057-14a0-4135-b871-9cf703b08b1c",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "import google.api_core.exceptions\n",
-    "from google.cloud import bigquery_datatransfer\n",
-    "\n",
-    "transfer_client = bigquery_datatransfer.DataTransferServiceClient()\n",
-    "\n",
-    "transfer_config_name = TRANSFER_CONFIG # Transfer Config Name\n",
-    "try:\n",
-    "    transfer_client.delete_transfer_config(name=transfer_config_name)\n",
-    "except google.api_core.exceptions.NotFound:\n",
-    "    print(\"Transfer config not found.\")\n",
-    "else:\n",
-    "    print(f\"Deleted transfer config: {transfer_config_name}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e79792bb-31e0-4427-a9fc-951b8a9b8968",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for the Chicago Taxi data:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6bb5d0f9-1498-4314-a0ad-f6aacb044a3b",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:chicago_taxi_trips\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c2d4cf02-1d43-4e70-b411-d9660635c2f0",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete BigQuery dataset for data processing during the pipelines:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5b7dfd7a-29b8-4b23-9893-b2a1bd05aac9",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4aeb5933-65e7-46a4-a228-ac927510c117",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Destroy infrastructure by executing undeploy command (terraform destroy):**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "7c938e96-1139-4d84-abd8-a2fc5c10c35b",
-   "metadata": {
-    "id": "sx_vKniMq9ZX",
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "! make undeploy auto-approve=true"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "cc67063a-337a-4517-9bd0-15f07d5bc5ee",
-   "metadata": {
-    "tags": []
-   },
-   "source": [
-    "**Delete local files:**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6d0aec50-4b7c-407c-b73f-825c40e3758b",
-   "metadata": {
-    "tags": []
-   },
-   "outputs": [],
-   "source": [
-    "%%bash\n",
-    "cd ..\n",
-    "rm -r vertex-pipelines-end-to-end-samples"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "PySpark (Local)",
-   "language": "python",
-   "name": "local-pyspark"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.12"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/env.sh.example b/env.sh.example
index 63152c5c..029c3089 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -13,10 +13,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-export VERTEX_CMEK_IDENTIFIER= # optional
-export VERTEX_LOCATION=europe-west2
-export VERTEX_NETWORK= # optional
 export VERTEX_PROJECT_ID=my-gcp-project
+export VERTEX_LOCATION=europe-west2
+export VERTEX_NETWORK=
+export VERTEX_CMEK_IDENTIFIER=
 
 # Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development 
 export RESOURCE_SUFFIX=default
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
deleted file mode 100644
index 9ac7210a..00000000
--- a/pipelines/poetry.lock
+++ /dev/null
@@ -1,1423 +0,0 @@
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-
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-    {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
-]
-
-[[package]]
-name = "tabulate"
-version = "0.9.0"
-description = "Pretty-print tabular data"
-category = "main"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"},
-    {file = "tabulate-0.9.0.tar.gz", hash = "sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c"},
-]
-
-[package.extras]
-widechars = ["wcwidth"]
-
-[[package]]
-name = "tomli"
-version = "2.0.1"
-description = "A lil' TOML parser"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
-    {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
-]
-
-[[package]]
-name = "urllib3"
-version = "1.26.16"
-description = "HTTP library with thread-safe connection pooling, file post, and more."
-category = "main"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
-files = [
-    {file = "urllib3-1.26.16-py2.py3-none-any.whl", hash = "sha256:8d36afa7616d8ab714608411b4a3b13e58f463aee519024578e062e141dce20f"},
-    {file = "urllib3-1.26.16.tar.gz", hash = "sha256:8f135f6502756bde6b2a9b28989df5fbe87c9970cecaa69041edcce7f0589b14"},
-]
-
-[package.extras]
-brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
-secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
-socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
-
-[[package]]
-name = "vertex-components"
-version = "0.1.0"
-description = "KubeFlow components for Vertex AI"
-category = "main"
-optional = false
-python-versions = ">=3.9,<3.11"
-files = []
-develop = true
-
-[package.dependencies]
-kfp = ">=2.0.1,<3.0.0"
-
-[package.source]
-type = "directory"
-url = "../components/vertex-components"
-
-[[package]]
-name = "virtualenv"
-version = "20.24.5"
-description = "Virtual Python Environment builder"
-category = "dev"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "virtualenv-20.24.5-py3-none-any.whl", hash = "sha256:b80039f280f4919c77b30f1c23294ae357c4c8701042086e3fc005963e4e537b"},
-    {file = "virtualenv-20.24.5.tar.gz", hash = "sha256:e8361967f6da6fbdf1426483bfe9fca8287c242ac0bc30429905721cefbff752"},
-]
-
-[package.dependencies]
-distlib = ">=0.3.7,<1"
-filelock = ">=3.12.2,<4"
-platformdirs = ">=3.9.1,<4"
-
-[package.extras]
-docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
-test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
-
-[[package]]
-name = "websocket-client"
-version = "1.6.3"
-description = "WebSocket client for Python with low level API options"
-category = "main"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "websocket-client-1.6.3.tar.gz", hash = "sha256:3aad25d31284266bcfcfd1fd8a743f63282305a364b8d0948a43bd606acc652f"},
-    {file = "websocket_client-1.6.3-py3-none-any.whl", hash = "sha256:6cfc30d051ebabb73a5fa246efdcc14c8fbebbd0330f8984ac3bb6d9edd2ad03"},
-]
-
-[package.extras]
-docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
-optional = ["python-socks", "wsaccel"]
-test = ["websockets"]
-
-[metadata]
-lock-version = "2.0"
-python-versions = ">=3.9,<3.11"
-content-hash = "e541cdee407ec35712bbca0feaf973239fd9ccc0344cc783329cda5103c83bd8"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 0daabf3b..7a6f0d92 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -3,7 +3,6 @@ name = "pipelines"
 version = "0.1.0"
 authors = ["Example User <user@example.com>"]
 description = "Vertex AI Pipelines end-to-end sample"
-readme = "README.md"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Developers",
@@ -16,12 +15,12 @@ packages = [
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
 Jinja2 = ">=3.0.1,<4.0.0"
-google-cloud-aiplatform = "1.30.1"
+google-cloud-aiplatform = ">=1.30.1"
 google-cloud-pipeline-components = "^2.1.0"
-bigquery-components = { path = "../components/bigquery-components", develop = true }
-vertex-components = { path = "../components/vertex-components", develop = true }
+components = { path = "../components", develop = true }
 kfp = "^2.0.1"
 pyyaml = "6.0.1"
+jupyter = "^1.0.0"
 
 [tool.poetry.group.dev.dependencies]
 pytest = ">=7.3.1,<8.0.0"
diff --git a/pipelines/src/pipelines/prediction/pipeline.py b/pipelines/src/pipelines/prediction/pipeline.py
index a97713a2..e75b78d1 100644
--- a/pipelines/src/pipelines/prediction/pipeline.py
+++ b/pipelines/src/pipelines/prediction/pipeline.py
@@ -19,7 +19,7 @@
 from kfp import dsl
 
 from pipelines import generate_query
-from vertex_components import lookup_model, model_batch_predict
+from components import lookup_model, model_batch_predict
 
 
 @dsl.pipeline(name="xgboost-prediction-pipeline")
diff --git a/pipelines/src/pipelines/training/pipeline.py b/pipelines/src/pipelines/training/pipeline.py
index be5861f3..fff03e2a 100644
--- a/pipelines/src/pipelines/training/pipeline.py
+++ b/pipelines/src/pipelines/training/pipeline.py
@@ -19,8 +19,7 @@
 from kfp import dsl
 from kfp.dsl import Dataset, Input, Metrics, Model, Output, OutputPath
 from pipelines import generate_query
-from bigquery_components import extract_bq_to_dataset
-from vertex_components import upload_model
+from components import extract_table, upload_model
 
 CONTAINER_IMAGE_REGISTRY = os.environ["CONTAINER_IMAGE_REGISTRY"]
 RESOURCE_SUFFIX = os.environ.get("RESOURCE_SUFFIX", "default")
@@ -155,7 +154,7 @@ def pipeline(
     # data extraction to gcs
 
     train_dataset = (
-        extract_bq_to_dataset(
+        extract_table(
             bq_client_project_id=project_id,
             source_project_id=project_id,
             dataset_id=dataset_id,
@@ -167,7 +166,7 @@ def pipeline(
         .set_caching_options(False)
     ).outputs["dataset"]
     valid_dataset = (
-        extract_bq_to_dataset(
+        extract_table(
             bq_client_project_id=project_id,
             source_project_id=project_id,
             dataset_id=dataset_id,
@@ -179,7 +178,7 @@ def pipeline(
         .set_caching_options(False)
     ).outputs["dataset"]
     test_dataset = (
-        extract_bq_to_dataset(
+        extract_table(
             bq_client_project_id=project_id,
             source_project_id=project_id,
             dataset_id=dataset_id,

From 99e681b7b0f8122b6dce6431f46149f9e94376d5 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Tue, 7 Nov 2023 14:03:13 +0100
Subject: [PATCH 214/238] Add poetry.lock

---
 pipelines/poetry.lock | 3153 +++++++++++++++++++++++++++++++++++++++++
 1 file changed, 3153 insertions(+)
 create mode 100644 pipelines/poetry.lock

diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
new file mode 100644
index 00000000..de28886b
--- /dev/null
+++ b/pipelines/poetry.lock
@@ -0,0 +1,3153 @@
+# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
+
+[[package]]
+name = "anyio"
+version = "4.0.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "anyio-4.0.0-py3-none-any.whl", hash = "sha256:cfdb2b588b9fc25ede96d8db56ed50848b0b649dca3dd1df0b11f683bb9e0b5f"},
+    {file = "anyio-4.0.0.tar.gz", hash = "sha256:f7ed51751b2c2add651e5747c891b47e26d2a21be5d32d9311dfe9692f3e5d7a"},
+]
+
+[package.dependencies]
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
+idna = ">=2.8"
+sniffio = ">=1.1"
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.22)"]
+
+[[package]]
+name = "appnope"
+version = "0.1.3"
+description = "Disable App Nap on macOS >= 10.9"
+optional = false
+python-versions = "*"
+files = [
+    {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"},
+    {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
+]
+
+[[package]]
+name = "argon2-cffi"
+version = "23.1.0"
+description = "Argon2 for Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "argon2_cffi-23.1.0-py3-none-any.whl", hash = "sha256:c670642b78ba29641818ab2e68bd4e6a78ba53b7eff7b4c3815ae16abf91c7ea"},
+    {file = "argon2_cffi-23.1.0.tar.gz", hash = "sha256:879c3e79a2729ce768ebb7d36d4609e3a78a4ca2ec3a9f12286ca057e3d0db08"},
+]
+
+[package.dependencies]
+argon2-cffi-bindings = "*"
+
+[package.extras]
+dev = ["argon2-cffi[tests,typing]", "tox (>4)"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-copybutton", "sphinx-notfound-page"]
+tests = ["hypothesis", "pytest"]
+typing = ["mypy"]
+
+[[package]]
+name = "argon2-cffi-bindings"
+version = "21.2.0"
+description = "Low-level CFFI bindings for Argon2"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "argon2-cffi-bindings-21.2.0.tar.gz", hash = "sha256:bb89ceffa6c791807d1305ceb77dbfacc5aa499891d2c55661c6459651fc39e3"},
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+[package.extras]
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+tests = ["pytest"]
+
+[[package]]
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+version = "1.3.0"
+description = "Better dates & times for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
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+test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"]
+
+[[package]]
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+version = "2.4.1"
+description = "Annotate AST trees with source code positions"
+optional = false
+python-versions = "*"
+files = [
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+
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+
+[[package]]
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+version = "23.1.0"
+description = "Classes Without Boilerplate"
+optional = false
+python-versions = ">=3.7"
+files = [
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+dev = ["attrs[docs,tests]", "pre-commit"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
+tests = ["attrs[tests-no-zope]", "zope-interface"]
+tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+
+[[package]]
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+version = "2.13.1"
+description = "Internationalization utilities"
+optional = false
+python-versions = ">=3.7"
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+
+[[package]]
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+version = "1.26.18"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
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+brotli = ["brotli (==1.0.9)", "brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
+secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
+socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
+
+[[package]]
+name = "virtualenv"
+version = "20.24.6"
+description = "Virtual Python Environment builder"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "virtualenv-20.24.6-py3-none-any.whl", hash = "sha256:520d056652454c5098a00c0f073611ccbea4c79089331f60bf9d7ba247bb7381"},
+    {file = "virtualenv-20.24.6.tar.gz", hash = "sha256:02ece4f56fbf939dbbc33c0715159951d6bf14aaf5457b092e4548e1382455af"},
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+[package.dependencies]
+distlib = ">=0.3.7,<1"
+filelock = ">=3.12.2,<4"
+platformdirs = ">=3.9.1,<4"
+
+[package.extras]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
+
+[[package]]
+name = "wcwidth"
+version = "0.2.9"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = "*"
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+version = "1.13"
+description = "A library for working with the color formats defined by HTML and CSS."
+optional = false
+python-versions = ">=3.7"
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+tests = ["pytest", "pytest-cov"]
+
+[[package]]
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+description = "Character encoding aliases for legacy web content"
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+version = "3.17.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
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+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.9,<3.11"
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From f6c969ca36fe66620c9df8a9cb795c80fe75aa03 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Tue, 7 Nov 2023 15:33:08 +0100
Subject: [PATCH 215/238] Update licenses

---
 README.md                                        |  7 +++++--
 components/src/components/__init__.py            | 14 ++++++++++++++
 components/src/components/extract_table.py       | 10 +++++-----
 components/src/components/lookup_model.py        | 10 +++++-----
 components/src/components/model_batch_predict.py | 10 +++++-----
 components/tests/conftest.py                     |  2 +-
 components/tests/test_extract_table.py           | 14 ++++++++++++++
 components/tests/test_lookup_model.py            |  2 +-
 components/tests/test_model_batch_predict.py     |  3 ++-
 components/tests/test_upload_model.py            |  1 +
 pipelines/src/pipelines/__init__.py              |  2 +-
 pipelines/src/pipelines/prediction/pipeline.py   |  2 +-
 pipelines/src/pipelines/training/pipeline.py     |  2 +-
 pipelines/src/pipelines/utils/upload_pipeline.py |  1 +
 pipelines/tests/__init__.py                      |  2 +-
 pipelines/tests/conftest.py                      |  2 +-
 16 files changed, 59 insertions(+), 25 deletions(-)

diff --git a/README.md b/README.md
index e046568f..32b543ca 100644
--- a/README.md
+++ b/README.md
@@ -86,7 +86,7 @@ gcloud services enable cloudresourcemanager.googleapis.com serviceusage.googleap
 make deploy env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
 ```
 
-More details about infrastructure is explained in [this README](docs/PIPELINES.md).
+More details about infrastructure is explained in [this README](docs/INFRASTRUCTURE.md).
 It describes the scheduling of pipelines and how to tear down infrastructure.
 
 **Install dependencies:**
@@ -134,7 +134,7 @@ Execute the following command to run through steps 1-3:
 make run pipeline=training [ wait=<true|false> ] [ build=<true|false> ] [ compile=<true|false> ]
 ```
 
-The make run command has the following true/false flags:
+The command has the following true/false flags:
 
 - `build` - re-build containers for training & serving code (limit by setting targets=training to build only one of the containers)
 - `compile` - re-compile the pipeline to YAML
@@ -157,3 +157,6 @@ For details on setting up CI/CD, see [this README](/docs/AUTOMATION.md).
 ## Putting it all together
 
 For a full walkthrough of the journey from changing the ML pipeline code to having it scheduled and running in production, please see the guide [here](docs/PRODUCTION.md).
+
+We value your contribution, see [this guide](docs/CONTRIBUTION.md) for contributing to this project.
+
diff --git a/components/src/components/__init__.py b/components/src/components/__init__.py
index 22a41762..9313d29a 100644
--- a/components/src/components/__init__.py
+++ b/components/src/components/__init__.py
@@ -1,3 +1,17 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 from .extract_table import extract_table
 from .lookup_model import lookup_model
 from .model_batch_predict import model_batch_predict
diff --git a/components/src/components/extract_table.py b/components/src/components/extract_table.py
index ddbc5de6..496e5377 100644
--- a/components/src/components/extract_table.py
+++ b/components/src/components/extract_table.py
@@ -1,11 +1,11 @@
-# Copyright 2022 Google LLC
-
+# Copyright 2023 Google LLC
+#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
 # Unless required by applicable law or agreed to in writing, software
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
diff --git a/components/src/components/lookup_model.py b/components/src/components/lookup_model.py
index e41c3ed8..813208a7 100644
--- a/components/src/components/lookup_model.py
+++ b/components/src/components/lookup_model.py
@@ -1,11 +1,11 @@
-# Copyright 2022 Google LLC
-
+# Copyright 2023 Google LLC
+#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
 # Unless required by applicable law or agreed to in writing, software
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
diff --git a/components/src/components/model_batch_predict.py b/components/src/components/model_batch_predict.py
index 08370ac5..da5b6b14 100644
--- a/components/src/components/model_batch_predict.py
+++ b/components/src/components/model_batch_predict.py
@@ -1,11 +1,11 @@
-# Copyright 2022 Google LLC
-
+# Copyright 2023 Google LLC
+#
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
-
-#     https://www.apache.org/licenses/LICENSE-2.0
-
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
 # Unless required by applicable law or agreed to in writing, software
 # distributed under the License is distributed on an "AS IS" BASIS,
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
diff --git a/components/tests/conftest.py b/components/tests/conftest.py
index f689a9b9..89cdc9ba 100644
--- a/components/tests/conftest.py
+++ b/components/tests/conftest.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/components/tests/test_extract_table.py b/components/tests/test_extract_table.py
index ad4f80a3..2db07695 100644
--- a/components/tests/test_extract_table.py
+++ b/components/tests/test_extract_table.py
@@ -1,3 +1,17 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
 import google.cloud.bigquery  # noqa
 from kfp.dsl import Dataset
 from unittest import mock
diff --git a/components/tests/test_lookup_model.py b/components/tests/test_lookup_model.py
index 17a6b4ad..a7868b66 100644
--- a/components/tests/test_lookup_model.py
+++ b/components/tests/test_lookup_model.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/components/tests/test_model_batch_predict.py b/components/tests/test_model_batch_predict.py
index 26cafe2b..ad4c427a 100644
--- a/components/tests/test_model_batch_predict.py
+++ b/components/tests/test_model_batch_predict.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+
 import json
 import pytest
 from unittest import mock
diff --git a/components/tests/test_upload_model.py b/components/tests/test_upload_model.py
index 704e6c05..cb35b4e8 100644
--- a/components/tests/test_upload_model.py
+++ b/components/tests/test_upload_model.py
@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+
 import json
 import logging
 from unittest import mock
diff --git a/pipelines/src/pipelines/__init__.py b/pipelines/src/pipelines/__init__.py
index 113da917..33ac7fee 100644
--- a/pipelines/src/pipelines/__init__.py
+++ b/pipelines/src/pipelines/__init__.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/pipelines/src/pipelines/prediction/pipeline.py b/pipelines/src/pipelines/prediction/pipeline.py
index e75b78d1..dd63d727 100644
--- a/pipelines/src/pipelines/prediction/pipeline.py
+++ b/pipelines/src/pipelines/prediction/pipeline.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/pipelines/src/pipelines/training/pipeline.py b/pipelines/src/pipelines/training/pipeline.py
index fff03e2a..dd73e910 100644
--- a/pipelines/src/pipelines/training/pipeline.py
+++ b/pipelines/src/pipelines/training/pipeline.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/pipelines/src/pipelines/utils/upload_pipeline.py b/pipelines/src/pipelines/utils/upload_pipeline.py
index 358d66de..35cc7d53 100644
--- a/pipelines/src/pipelines/utils/upload_pipeline.py
+++ b/pipelines/src/pipelines/utils/upload_pipeline.py
@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+
 import argparse
 from typing import List
 from kfp.registry import RegistryClient
diff --git a/pipelines/tests/__init__.py b/pipelines/tests/__init__.py
index 6d6d1266..7ba50f93 100644
--- a/pipelines/tests/__init__.py
+++ b/pipelines/tests/__init__.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/pipelines/tests/conftest.py b/pipelines/tests/conftest.py
index 4d1ece88..8083a83c 100644
--- a/pipelines/tests/conftest.py
+++ b/pipelines/tests/conftest.py
@@ -1,4 +1,4 @@
-# Copyright 2022 Google LLC
+# Copyright 2023 Google LLC
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

From 6f19ee40437e50e4b8058c483a221717f20c8802 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Tue, 7 Nov 2023 15:37:41 +0100
Subject: [PATCH 216/238] Update README.md

---
 README.md | 1 -
 1 file changed, 1 deletion(-)

diff --git a/README.md b/README.md
index 32b543ca..fbecd4ef 100644
--- a/README.md
+++ b/README.md
@@ -159,4 +159,3 @@ For details on setting up CI/CD, see [this README](/docs/AUTOMATION.md).
 For a full walkthrough of the journey from changing the ML pipeline code to having it scheduled and running in production, please see the guide [here](docs/PRODUCTION.md).
 
 We value your contribution, see [this guide](docs/CONTRIBUTION.md) for contributing to this project.
-

From ba515e7b02ef8f98480fcbdc4da4b3270782aab1 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Tue, 7 Nov 2023 15:43:11 +0100
Subject: [PATCH 217/238] Update docs and remove pre-commit from PR checks

---
 cloudbuild/pr-checks.yaml | 1 -
 docs/AUTOMATION.md        | 4 +++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/cloudbuild/pr-checks.yaml b/cloudbuild/pr-checks.yaml
index 085a1324..a11710ff 100644
--- a/cloudbuild/pr-checks.yaml
+++ b/cloudbuild/pr-checks.yaml
@@ -27,7 +27,6 @@ steps:
         make install && \
         git init && \
         git add . && \
-        make pre-commit && \
         make compile pipeline=training && \
         make compile pipeline=prediction && \
         make test
diff --git a/docs/AUTOMATION.md b/docs/AUTOMATION.md
index e3a5bedd..5094b4a7 100644
--- a/docs/AUTOMATION.md
+++ b/docs/AUTOMATION.md
@@ -48,7 +48,9 @@ Your Cloud Build pipelines will need a service account to use. Create a new serv
 
 ### On Pull Request to `main` / `master` branch
 
-Set up a trigger for the `pr-checks.yaml` pipeline.
+Set up a trigger for the `pr-checks.yaml` pipeline. 
+We recommend to add `make pre-commit` (which is already part of the `Makefile`), to keep your ML use case code clean.
+By default pull requests don't execute pre-commit hooks to improve the ease of use for new users of the template.
 
 Set up a trigger for the `e2e-test.yaml` pipeline, and provide substitution values for the following variables:
 

From 7fdb1848e2930c1d30f18ece5427c4fac71c1848 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Tue, 7 Nov 2023 15:50:08 +0100
Subject: [PATCH 218/238] Update notebooks

---
 docs/notebooks/01_infrastructure_setup.ipynb   | 9 ---------
 docs/notebooks/02_run_pipelines.ipynb          | 2 +-
 docs/notebooks/03_infrastructure_cleanup.ipynb | 2 +-
 3 files changed, 2 insertions(+), 11 deletions(-)

diff --git a/docs/notebooks/01_infrastructure_setup.ipynb b/docs/notebooks/01_infrastructure_setup.ipynb
index 8a31cb43..736a5e58 100644
--- a/docs/notebooks/01_infrastructure_setup.ipynb
+++ b/docs/notebooks/01_infrastructure_setup.ipynb
@@ -155,15 +155,6 @@
     "CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "! source .env.sh && echo $VERTEX_PROJECT_ID"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
diff --git a/docs/notebooks/02_run_pipelines.ipynb b/docs/notebooks/02_run_pipelines.ipynb
index 02843e4b..7f20a290 100644
--- a/docs/notebooks/02_run_pipelines.ipynb
+++ b/docs/notebooks/02_run_pipelines.ipynb
@@ -79,7 +79,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "VERTEX_PROJECT_ID = \"dt-turbo-templates-dev\"\n",
+    "VERTEX_PROJECT_ID = \"my-project-id\"\n",
     "! gcloud auth login\n",
     "! gcloud config set project {VERTEX_PROJECT_ID}"
    ]
diff --git a/docs/notebooks/03_infrastructure_cleanup.ipynb b/docs/notebooks/03_infrastructure_cleanup.ipynb
index b3d674b1..5068407c 100644
--- a/docs/notebooks/03_infrastructure_cleanup.ipynb
+++ b/docs/notebooks/03_infrastructure_cleanup.ipynb
@@ -68,7 +68,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "VERTEX_PROJECT_ID = \"dt-turbo-templates-dev\"\n",
+    "VERTEX_PROJECT_ID = \"my-project-id\"\n",
     "! gcloud auth login\n",
     "! gcloud config set project {VERTEX_PROJECT_ID}"
    ]

From 51fad4bbe1e8ea972e4950aaa2bb8e5b7cf53773 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Wed, 8 Nov 2023 12:06:35 +0100
Subject: [PATCH 219/238] Fix spelling in notebooks

---
 docs/notebooks/01_infrastructure_setup.ipynb | 2 +-
 docs/notebooks/02_run_pipelines.ipynb        | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/notebooks/01_infrastructure_setup.ipynb b/docs/notebooks/01_infrastructure_setup.ipynb
index 736a5e58..1aedd663 100644
--- a/docs/notebooks/01_infrastructure_setup.ipynb
+++ b/docs/notebooks/01_infrastructure_setup.ipynb
@@ -77,7 +77,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "VERTEX_PROJECT_ID = \"dt-turbo-templates-dev\"\n",
+    "VERTEX_PROJECT_ID = \"my-project-id\"\n",
     "! gcloud auth login\n",
     "! gcloud config set project {VERTEX_PROJECT_ID}"
    ]
diff --git a/docs/notebooks/02_run_pipelines.ipynb b/docs/notebooks/02_run_pipelines.ipynb
index 7f20a290..89fd64fc 100644
--- a/docs/notebooks/02_run_pipelines.ipynb
+++ b/docs/notebooks/02_run_pipelines.ipynb
@@ -215,7 +215,7 @@
     "tags": []
    },
    "source": [
-    "You've successfully raun your first training and prediction pipeline in Vertex AI! 🎉\n",
+    "You've successfully run your first training and prediction pipeline in Vertex AI! 🎉\n",
     "Continue with [this notebook](./03_infrastructure_cleanup.ipynb) to run clean up the infrastructure."
    ]
   }

From 19ab4f03d2264c57b1cfa5e42faa9ab4cc08316f Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Thu, 9 Nov 2023 14:03:13 +0100
Subject: [PATCH 220/238] Fix spelling in notebooks

---
 docs/notebooks/01_infrastructure_setup.ipynb   | 4 ++--
 docs/notebooks/02_run_pipelines.ipynb          | 2 +-
 docs/notebooks/03_infrastructure_cleanup.ipynb | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/docs/notebooks/01_infrastructure_setup.ipynb b/docs/notebooks/01_infrastructure_setup.ipynb
index 1aedd663..47766570 100644
--- a/docs/notebooks/01_infrastructure_setup.ipynb
+++ b/docs/notebooks/01_infrastructure_setup.ipynb
@@ -32,7 +32,7 @@
    "source": [
     "# Getting Started with Vertex AI Turbo Templates\n",
     "\n",
-    "This notebook sets up infrastructure to run production-ready pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
+    "This notebook sets up infrastructure to run production-ready pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupyter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
     "\n",
     "1. **[Infrastructure Setup](./02_run_pipelines.ipynb) - this notebook**\n",
     "1. [Run Pipelines](./02_run_pipelines.ipynb)\n",
@@ -45,7 +45,7 @@
     "- Make\n",
     "- [Terraform](https://www.terraform.io)\n",
     "\n",
-    "**For Vertex AI Workbench users**: Uncomment and execute the following cell install Terraform."
+    "**For Vertex AI Workbench users**: Uncomment and execute the following cell to install Terraform."
    ]
   },
   {
diff --git a/docs/notebooks/02_run_pipelines.ipynb b/docs/notebooks/02_run_pipelines.ipynb
index 89fd64fc..c3e71964 100644
--- a/docs/notebooks/02_run_pipelines.ipynb
+++ b/docs/notebooks/02_run_pipelines.ipynb
@@ -31,7 +31,7 @@
    "source": [
     "# Getting Started with Vertex AI Turbo Templates\n",
     "\n",
-    "This notebook sets up infrastructure to run production-ready pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
+    "In this notebook you'll run your first production-ready training and prediction pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupyter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
     "\n",
     "1. [Infrastructure Setup](./02_run_pipelines.ipynb)\n",
     "1. **[Run Pipelines](./02_run_pipelines.ipynb) - this notebook**\n",
diff --git a/docs/notebooks/03_infrastructure_cleanup.ipynb b/docs/notebooks/03_infrastructure_cleanup.ipynb
index 5068407c..f3f5d776 100644
--- a/docs/notebooks/03_infrastructure_cleanup.ipynb
+++ b/docs/notebooks/03_infrastructure_cleanup.ipynb
@@ -31,7 +31,7 @@
    "source": [
     "# Getting Started with Vertex AI Turbo Templates\n",
     "\n",
-    "This notebook sets up infrastructure to run production-ready pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
+    "This notebook cleans up any infrastructure used run production-ready pipelines on Google Cloud. Follow this three-part notebook series to get started in a local Jupter notebook or in [Vertex AI Workbench](https://cloud.google.com/vertex-ai-notebooks):\n",
     "\n",
     "1. [Infrastructure Setup](./02_run_pipelines.ipynb)\n",
     "1. [Run Pipelines](./02_run_pipelines.ipynb)\n",

From 6978293daf1542ea41331b0a89023b0d609b69b6 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Thu, 9 Nov 2023 14:05:26 +0100
Subject: [PATCH 221/238] Fix spelling in notebooks

---
 docs/notebooks/02_run_pipelines.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/notebooks/02_run_pipelines.ipynb b/docs/notebooks/02_run_pipelines.ipynb
index c3e71964..5cb70550 100644
--- a/docs/notebooks/02_run_pipelines.ipynb
+++ b/docs/notebooks/02_run_pipelines.ipynb
@@ -182,7 +182,7 @@
    "source": [
     "## Run Prediction Pipeline\n",
     "\n",
-    "After successful training job, run the prediction pipeline which will look similar to:\n",
+    "After running a successful training pipeline job, run the prediction pipeline which will look similar to:\n",
     "\n",
     "<img src=\"../images/prediction_pipeline.png\" alt=\"image\" width=\"500\" height=\"auto\">"
    ]

From 317b288adcfdbef805b659943665b431b5c938cd Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Thu, 9 Nov 2023 17:34:20 +0100
Subject: [PATCH 222/238] Make repo cloning optional in notebooks

---
 docs/notebooks/01_infrastructure_setup.ipynb | 13 +++++++++++--
 1 file changed, 11 insertions(+), 2 deletions(-)

diff --git a/docs/notebooks/01_infrastructure_setup.ipynb b/docs/notebooks/01_infrastructure_setup.ipynb
index 47766570..dd7b2a06 100644
--- a/docs/notebooks/01_infrastructure_setup.ipynb
+++ b/docs/notebooks/01_infrastructure_setup.ipynb
@@ -86,7 +86,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Clone Code"
+    "## Clone Code\n",
+    "\n",
+    "**If you haven't cloned the template, yet:** Uncomment and execute the following cell to clone the code."
    ]
   },
   {
@@ -95,7 +97,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "! git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+    "#! git clone -b develop https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Switch to the folder in which the template code is cloned to:"
    ]
   },
   {

From 40c9d24c9879c82764d4163bd5779b3084fa8553 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Mon, 13 Nov 2023 18:14:07 +0100
Subject: [PATCH 223/238] Add hparam notebook

---
 docs/images/hparam_tuning.png                 | Bin 0 -> 48040 bytes
 .../extras/01_hyperparameter_tuning.ipynb     | 433 ++++++++++++++++++
 2 files changed, 433 insertions(+)
 create mode 100644 docs/images/hparam_tuning.png
 create mode 100644 docs/notebooks/extras/01_hyperparameter_tuning.ipynb

diff --git a/docs/images/hparam_tuning.png b/docs/images/hparam_tuning.png
new file mode 100644
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diff --git a/docs/notebooks/extras/01_hyperparameter_tuning.ipynb b/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
new file mode 100644
index 00000000..7b3789f8
--- /dev/null
+++ b/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
@@ -0,0 +1,433 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ur8xi4C7S06n"
+   },
+   "outputs": [],
+   "source": [
+    "# Copyright 2023 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     https://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hyperparameter Tuning with Vertex AI Turbo Templates\n",
+    "\n",
+    "This notebook guides you through production-ready pipelines on Google Cloud with hyperparameter tuning enabled. \n",
+    "If you're new to the Vertex AI Turbo Template, start with the [three-part notebook series](../01_infrastructure_setup.ipynb) first. \n",
+    "\n",
+    "**Prerequisites:**\n",
+    "\n",
+    "- deployed cloud project\n",
+    "- cloned template\n",
+    "- `env.sh` configured\n",
+    "- Python dependencies installed\n",
+    "\n",
+    "Let's change into the root of the repository:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%cd ../../"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Model training\n",
+    "\n",
+    "**Update Python dependencies:** Add the following line to `model/pyproject.toml` to install (cloudml-hypertune)[https://github.com/GoogleCloudPlatform/cloudml-hypertune] as part of your model training code:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! cd model && poetry add cloudml-hypertune"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Extend training code:** Add hyperparameters which require tuning to the expected command-line arguments `model/training/train.py`.\n",
+    "In this example we're adding the `learning_rate` hyperparamter:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "parser.add_argument(\n",
+    "    \"--learning_rate\", type=float, default=0.3, help=\"Learning rate (default: 0.3)\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Report evaluation metric:** Don't forget to report the primary evaluation metric `rootMeanSquaredError` once the model is trained and evaluated:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import hypertune\n",
+    "\n",
+    "hpt = hypertune.HyperTune()\n",
+    "hpt.report_hyperparameter_tuning_metric(\n",
+    "    hyperparameter_metric_tag=\"rootMeanSquaredError\",\n",
+    "    metric_value=hp_metric,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Training pipeline"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Add Python imports:** Add the `HyperparameterTuningJobRunOp` to your training pipeline in `pipelines/src/pipelines/training.py`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from google_cloud_pipeline_components.v1.hyperparameter_tuning_job import HyperparameterTuningJobRunOp as hpt_job_op\n",
+    "from google.cloud.aiplatform import hyperparameter_tuning as hpt\n",
+    "from google_cloud_pipeline_components.v1 import hyperparameter_tuning_job as hpt_job"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Before adapting the training pipeline, we'll need to implement three new components:\n",
+    "\n",
+    "- **get_worker_pool_specs:** Generate a specification for worker pools as a necessary input for performing hyperparameter tuning.\n",
+    "- **hpt_job_op:** This runs the actual job. This components doesn't need to be implemented as it's already provided by [Google Cloud Pipeline Components](https://cloud.google.com/vertex-ai/docs/pipelines/components-introduction).\n",
+    "- **get_trials:** Retrieve all trials and their evaluation metrics after a successful hyperparameter tuning job. \n",
+    "- **get_best_trial:** Get the best trial from all trials. This allows to understand which hyperparameters have led to the best model and also to retrieve the trained model artifact.\n",
+    "\n",
+    "Your updated training pipeline will look similar to this Vertex AI pipeline once implemented:\n",
+    "\n",
+    "<p align=\"center\">\n",
+    "    <img src=\"../../images/hparam_tuning.png\" alt=\"image\" width=\"250\" height=\"auto\">\n",
+    "</p>\n",
+    "\n",
+    "Now add the following components to your training pipeline code:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@dsl.component(base_image=\"python:3.9\")\n",
+    "def get_worker_pool_specs(\n",
+    "    input_data: Input[Dataset],\n",
+    "    arguments: dict,\n",
+    ") -> list:\n",
+    "    \"\"\"\n",
+    "    Generate a specification for worker pools to perform hyperparameter tuning.\n",
+    "\n",
+    "    Args:\n",
+    "        input_data (Input[Dataset]): Input data for training\n",
+    "        hparams (dict): Hyperparameters\n",
+    "\n",
+    "    Returns:\n",
+    "        list: A list of worker pool specifications, each specifying the machine type,\n",
+    "        Docker image, and command arguments for a worker pool.\n",
+    "\n",
+    "    \"\"\"\n",
+    "\n",
+    "    COMMAND = [\"python\"]\n",
+    "    ARGS = [\n",
+    "        \"-m\", \"training\",\n",
+    "        \"--input_path\", input_data.path,\n",
+    "    ]\n",
+    "    for key, value in arguments.items():\n",
+    "        ARGS.extend([\"--\" + str(key), str(value)])\n",
+    "\n",
+    "    return [{\n",
+    "        \"machine_spec\": {\n",
+    "            \"machine_type\": \"n1-standard-4\",\n",
+    "        },\n",
+    "        \"replica_count\": 1,\n",
+    "        \"container_spec\": {\n",
+    "            \"image_uri\": TRAINING_IMAGE,\n",
+    "            \"command\": COMMAND,\n",
+    "            \"args\": ARGS,\n",
+    "        },\n",
+    "    }]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@dsl.component(\n",
+    "    packages_to_install=[\n",
+    "        \"google-cloud-aiplatform\",\n",
+    "        \"google-cloud-pipeline-components\",\n",
+    "        \"protobuf\",\n",
+    "    ],\n",
+    "    base_image=\"python:3.9\",\n",
+    ")\n",
+    "def get_trials(gcp_resources: str) -> list:\n",
+    "    \"\"\"Retrieve all trials after a successful hyperparameters tuning job.\n",
+    "\n",
+    "    Args:\n",
+    "        gcp_resources (str): Proto tracking the hyperparameter tuning job.\n",
+    "\n",
+    "    Returns:\n",
+    "        List of strings representing the intermediate JSON representation of the\n",
+    "        trials from the hyperparameter tuning job.\n",
+    "    \"\"\"\n",
+    "    from google.cloud import aiplatform\n",
+    "    from google_cloud_pipeline_components.proto.gcp_resources_pb2 import GcpResources\n",
+    "    from google.protobuf.json_format import Parse\n",
+    "    from google.cloud.aiplatform_v1.types import study\n",
+    "\n",
+    "    api_endpoint_suffix = \"-aiplatform.googleapis.com\"\n",
+    "    gcp_resources_proto = Parse(gcp_resources, GcpResources())\n",
+    "    gcp_resources_split = gcp_resources_proto.resources[0].resource_uri.partition(\n",
+    "        \"projects\"\n",
+    "    )\n",
+    "    resource_name = gcp_resources_split[1] + gcp_resources_split[2]\n",
+    "    prefix_str = gcp_resources_split[0]\n",
+    "    prefix_str = prefix_str[: prefix_str.find(api_endpoint_suffix)]\n",
+    "    api_endpoint = prefix_str[(prefix_str.rfind(\"//\") + 2) :] + api_endpoint_suffix\n",
+    "\n",
+    "    client_options = {\"api_endpoint\": api_endpoint}\n",
+    "    job_client = aiplatform.gapic.JobServiceClient(client_options=client_options)\n",
+    "    response = job_client.get_hyperparameter_tuning_job(name=resource_name)\n",
+    "\n",
+    "    return [study.Trial.to_json(trial) for trial in response.trials]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@dsl.component(packages_to_install=[\"google-cloud-aiplatform\"], base_image=\"python:3.9\")\n",
+    "def get_best_trial(trials: list, study_spec_metrics: list) -> str:\n",
+    "    \"\"\"Retrieves the best trial from the trials.\n",
+    "\n",
+    "    Args:\n",
+    "        trials (list): Required. List representing the intermediate\n",
+    "          JSON representation of the trials from the hyperparameter tuning job.\n",
+    "        study_spec_metrics (list): Required. List serialized from dictionary\n",
+    "          representing the metrics to optimize.\n",
+    "          The dictionary key is the metric_id, which is reported by your training\n",
+    "          job, and the dictionary value is the optimization goal of the metric\n",
+    "          ('minimize' or 'maximize'). example:\n",
+    "          metrics = hyperparameter_tuning_job.serialize_metrics(\n",
+    "              {'loss': 'minimize', 'accuracy': 'maximize'})\n",
+    "\n",
+    "    Returns:\n",
+    "        String representing the intermediate JSON representation of the best\n",
+    "        trial from the list of trials.\n",
+    "\n",
+    "    Raises:\n",
+    "        RuntimeError: If there are multiple metrics.\n",
+    "    \"\"\"\n",
+    "    from google.cloud.aiplatform_v1.types import study\n",
+    "\n",
+    "    if len(study_spec_metrics) > 1:\n",
+    "        raise RuntimeError(\n",
+    "            \"Unable to determine best parameters for multi-objective\"\n",
+    "            \" hyperparameter tuning.\"\n",
+    "        )\n",
+    "    trials_list = [study.Trial.from_json(trial) for trial in trials]\n",
+    "    best_trial = None\n",
+    "    goal = study_spec_metrics[0][\"goal\"]\n",
+    "    best_fn = None\n",
+    "    if goal == study.StudySpec.MetricSpec.GoalType.MAXIMIZE:\n",
+    "        best_fn = max\n",
+    "    elif goal == study.StudySpec.MetricSpec.GoalType.MINIMIZE:\n",
+    "        best_fn = min\n",
+    "    best_trial = best_fn(\n",
+    "        trials_list, key=lambda trial: trial.final_measurement.metrics[0].value\n",
+    "    )\n",
+    "\n",
+    "    return study.Trial.to_json(best_trial)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Training pipeline:** In the  define new variables and use the just implemented components by replacing the initial `train` component:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@dsl.pipeline(name=\"...\")\n",
+    "def pipeline():\n",
+    "\n",
+    "    # ...\n",
+    "\n",
+    "    # define static arguments which will be used for all tuning jobs\n",
+    "    # `learning_rate` is excluded as we'll optimise this hyperparameter\n",
+    "    static_arguments = dict(\n",
+    "        n_estimators=200,\n",
+    "        label=label,\n",
+    "        # ...\n",
+    "    )\n",
+    "    # the metric(s) we want to optimise for\n",
+    "    metrics = hpt_job.serialize_metrics({\"rootMeanSquaredError\": \"minimize\"})\n",
+    "    \n",
+    "    # prepare your data ...\n",
+    "    \n",
+    "    data_op = # ...\n",
+    "    \n",
+    "    # now use the new components ...\n",
+    "    \n",
+    "    specs_op = get_worker_pool_specs(\n",
+    "        input_data=data_op.outputs[\"data\"],\n",
+    "        arguments=training_arguments,\n",
+    "    )\n",
+    "    \n",
+    "    tuning_op = hpt_job_op(\n",
+    "        display_name=\"tuning-job\",\n",
+    "        project=project,\n",
+    "        location=location,\n",
+    "        worker_pool_specs=specs_op.output,\n",
+    "        \n",
+    "        # TODO: adjust to your use case\n",
+    "        base_output_directory=\"...\", # e.g. a folder in your pipeline bucket root\n",
+    "        max_trial_count=3,           # e.g. run up to 3x trials\n",
+    "        parallel_trial_count=3,      # e.g. run all of them in parallel\n",
+    "        study_spec_algorithm=\"ALGORITHM_UNSPECIFIED\",\n",
+    "        study_spec_measurement_selection_type=\"BEST_MEASUREMENT\",\n",
+    "        study_spec_metrics=metrics,\n",
+    "        \n",
+    "        # TODO: specify the hyperparameters to be tuned\n",
+    "        study_spec_parameters=hpt_job.serialize_parameters({\n",
+    "            \"learning_rate\": hpt.DoubleParameterSpec(min=0.001, max=1, scale=\"log\"),\n",
+    "        }),\n",
+    "    )\n",
+    "    \n",
+    "    trials_op = get_trials(gcp_resources=tuning_op.outputs[\"gcp_resources\"])\n",
+    "    \n",
+    "    best_trial_op = get_best_trial(\n",
+    "        trials=trials_op.output, \n",
+    "        study_spec_metrics=metrics,\n",
+    "    )\n",
+    "    \n",
+    "    # TODO: upload the model with the best trial ..."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Run pipeline\n",
+    "\n",
+    "Vertex AI Pipelines uses KubeFlow to orchestrate your training steps, as such you'll need to:\n",
+    "\n",
+    "1. Compile the pipeline\n",
+    "2. Re-build the training container (as we've update the dependencies and code)\n",
+    "3. Run the pipeline in Vertex AI\n",
+    "\n",
+    "Don't worry about executing steps 1-3 manually (and each time you run your pipeline!), simply run the following command:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! make run pipeline=training build=true targets=training"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You've successfully updated your training pipeline to support hyperparameter tuning! 🎉 \n",
+    "\n",
+    "Continue by reading more about [hyperparameter tuning in Vertex AI](https://cloud.google.com/vertex-ai/docs/training/hyperparameter-tuning-overview) or by improving your new training pipeline by uploading the model with the best evaluation result."
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "collapsed_sections": [],
+   "name": "notebook_template.ipynb",
+   "toc_visible": true
+  },
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "bb5c7b0035bb37e2e2e56e6840dfdd8f7fa070884ae8e041fbcae450545b1006"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

From 5c7b75afacd9443a97ce9ad684b4af4e0e3dccce Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Mon, 13 Nov 2023 18:21:39 +0100
Subject: [PATCH 224/238] Minor improvements to notebook

---
 .../extras/01_hyperparameter_tuning.ipynb       | 17 +++++++++++++++--
 1 file changed, 15 insertions(+), 2 deletions(-)

diff --git a/docs/notebooks/extras/01_hyperparameter_tuning.ipynb b/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
index 7b3789f8..c04db9da 100644
--- a/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
+++ b/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
@@ -29,7 +29,7 @@
    "source": [
     "# Hyperparameter Tuning with Vertex AI Turbo Templates\n",
     "\n",
-    "This notebook guides you through production-ready pipelines on Google Cloud with hyperparameter tuning enabled. \n",
+    "This notebook guides you through production-ready pipelines on Google Cloud and how to enable hyperparameter tuning in your training pipeline. \n",
     "If you're new to the Vertex AI Turbo Template, start with the [three-part notebook series](../01_infrastructure_setup.ipynb) first. \n",
     "\n",
     "**Prerequisites:**\n",
@@ -57,6 +57,12 @@
    "source": [
     "## Model training\n",
     "\n",
+    "Start by updating the model training code and it's dependencies by:\n",
+    "\n",
+    "- updating your Python dependencies\n",
+    "- extending your training code\n",
+    "- reporting evaluation metrics for each training trial\n",
+    "\n",
     "**Update Python dependencies:** Add the following line to `model/pyproject.toml` to install (cloudml-hypertune)[https://github.com/GoogleCloudPlatform/cloudml-hypertune] as part of your model training code:"
    ]
   },
@@ -114,7 +120,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Training pipeline"
+    "## Training pipeline\n",
+    "\n",
+    "Since your training code is updated now, let's navigate to the training pipeline and start adapting to train multiple models concurrently with different hyperparameters while optimising your primary evaluation metric. \n",
+    "This is done by:\n",
+    "\n",
+    "- adding new Python imports\n",
+    "- implementing new pipeline components\n",
+    "- replacing the training operation with a new set of component operations"
    ]
   },
   {

From 7a28ae2e87a226a038445cac5dd91bc59ef752e7 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Mon, 13 Nov 2023 18:25:43 +0100
Subject: [PATCH 225/238] Minor improvements to notebook

---
 .../notebooks/extras/01_hyperparameter_tuning.ipynb | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/docs/notebooks/extras/01_hyperparameter_tuning.ipynb b/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
index c04db9da..a19170f0 100644
--- a/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
+++ b/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
@@ -63,7 +63,7 @@
     "- extending your training code\n",
     "- reporting evaluation metrics for each training trial\n",
     "\n",
-    "**Update Python dependencies:** Add the following line to `model/pyproject.toml` to install (cloudml-hypertune)[https://github.com/GoogleCloudPlatform/cloudml-hypertune] as part of your model training code:"
+    "**Update Python dependencies:** Add the following line to `model/pyproject.toml` to install [cloudml-hypertune](https://github.com/GoogleCloudPlatform/cloudml-hypertune) as part of your model training code:"
    ]
   },
   {
@@ -79,8 +79,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**Extend training code:** Add hyperparameters which require tuning to the expected command-line arguments `model/training/train.py`.\n",
-    "In this example we're adding the `learning_rate` hyperparamter:"
+    "**Extend training code:** Add hyperparameters which require tuning to the expected command-line arguments in `model/training/train.py`.\n",
+    "In this example we're adding the `learning_rate` hyperparameter:"
    ]
   },
   {
@@ -112,7 +112,7 @@
     "hpt = hypertune.HyperTune()\n",
     "hpt.report_hyperparameter_tuning_metric(\n",
     "    hyperparameter_metric_tag=\"rootMeanSquaredError\",\n",
-    "    metric_value=hp_metric,\n",
+    "    metric_value=calculated_metric,\n",
     ")"
    ]
   },
@@ -122,7 +122,8 @@
    "source": [
     "## Training pipeline\n",
     "\n",
-    "Since your training code is updated now, let's navigate to the training pipeline and start adapting to train multiple models concurrently with different hyperparameters while optimising your primary evaluation metric. \n",
+    "Since your training code is updated now, let's navigate to the training pipeline and adapt it. \n",
+    "You'll train multiple models concurrently with different hyperparameters while optimising for your primary evaluation metric. \n",
     "This is done by:\n",
     "\n",
     "- adding new Python imports\n",
@@ -313,7 +314,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "**Training pipeline:** In the  define new variables and use the just implemented components by replacing the initial `train` component:"
+    "**Training pipeline:** In the training pipeline define new variables and replace the original training component with the newly implemented components."
    ]
   },
   {

From 0a63609284a2e5d6b6263ea6e1f5bbdc8d10093f Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Mon, 13 Nov 2023 18:45:00 +0100
Subject: [PATCH 226/238] Update training pipeline

---
 Makefile                                      |   9 +-
 README.md                                     |   2 +-
 cloudbuild/e2e-test.yaml                      |   1 +
 cloudbuild/release.yaml                       |   4 +-
 components/src/components/extract_table.py    |  97 ++------
 components/src/components/lookup_model.py     |  27 +--
 .../src/components/model_batch_predict.py     |  38 ++--
 components/src/components/upload_model.py     |  43 ++--
 components/tests/test_extract_table.py        |  78 -------
 docs/AUTOMATION.md                            |   1 +
 docs/PIPELINES.md                             |   6 +-
 docs/PRODUCTION.md                            |   3 +-
 env.sh.example                                |   1 +
 model/Dockerfile                              |   4 +-
 model/training/__init__.py                    |  13 ++
 model/training/__main__.py                    |  35 +++
 model/training/train.py                       | 215 ++++++++----------
 model/training/utils.py                       |  66 ++++++
 pipelines/src/pipelines/__init__.py           |  20 --
 pipelines/src/pipelines/prediction.py         | 116 ++++++++++
 .../src/pipelines/prediction/pipeline.py      | 153 -------------
 .../prediction/queries/preprocessing.sql      |  69 ------
 .../src/pipelines/queries/preprocessing.sql   |  56 +++++
 pipelines/src/pipelines/training.py           | 160 +++++++++++++
 pipelines/src/pipelines/training/pipeline.py  | 212 -----------------
 .../training/queries/preprocessing.sql        |  88 -------
 pipelines/src/pipelines/utils/query.py        |  32 +++
 .../src/pipelines/utils/trigger_pipeline.py   |   4 +-
 28 files changed, 664 insertions(+), 889 deletions(-)
 delete mode 100644 components/tests/test_extract_table.py
 create mode 100644 model/training/__init__.py
 create mode 100644 model/training/__main__.py
 create mode 100644 model/training/utils.py
 create mode 100644 pipelines/src/pipelines/prediction.py
 delete mode 100644 pipelines/src/pipelines/prediction/pipeline.py
 delete mode 100644 pipelines/src/pipelines/prediction/queries/preprocessing.sql
 create mode 100644 pipelines/src/pipelines/queries/preprocessing.sql
 create mode 100644 pipelines/src/pipelines/training.py
 delete mode 100644 pipelines/src/pipelines/training/pipeline.py
 delete mode 100644 pipelines/src/pipelines/training/queries/preprocessing.sql
 create mode 100644 pipelines/src/pipelines/utils/query.py

diff --git a/Makefile b/Makefile
index eeda7282..61a00c68 100644
--- a/Makefile
+++ b/Makefile
@@ -45,11 +45,13 @@ install: ## Set up local environment for Python development on pipelines
 	@cd pipelines && \
 	poetry install --with dev && \
 	cd ../components && \
-	poetry install --with dev
+	poetry install --with dev && \
+	cd ../model && \
+	poetry install
 
 compile: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
 	@cd pipelines/src && \
-	poetry run kfp dsl compile --py pipelines/${pipeline}/pipeline.py --output pipelines/${pipeline}/pipeline.yaml --function pipeline
+	poetry run kfp dsl compile --py pipelines/${pipeline}.py --output pipelines/${pipeline}.yaml --function pipeline
 
 targets ?= training serving
 build: ## Build and push training and/or serving container(s) image using Docker. Specify targets=<training serving> e.g. targets=training or targets="training serving" (default)
@@ -63,7 +65,6 @@ build: ## Build and push training and/or serving container(s) image using Docker
 		--substitutions=_DOCKER_TARGET=$$target,_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/$$target:${RESOURCE_SUFFIX} ; \
 	done 
 
-
 compile ?= true
 build ?= true
 wait ?= false
@@ -81,7 +82,7 @@ run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|pre
 		exit ; \
 	fi && \
 	cd pipelines/src && \
-	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}/pipeline.yaml --display_name=${pipeline} --wait=${wait}
+	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}.yaml --display_name=${pipeline} --wait=${wait}
 
 components ?= true
 test: ## Run unit tests. Specify components=<true|false> to test scripts and optionally components
diff --git a/README.md b/README.md
index fbecd4ef..3ed2c82e 100644
--- a/README.md
+++ b/README.md
@@ -14,7 +14,7 @@ See the License for the specific language governing permissions and
 limitations under the License.
  -->
 
-# Vertex Pipelines End-to-end Samples
+# Vertex Pipelines End-to-End Samples
 
 _AKA "Vertex AI Turbo Templates"_
 
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 8c5c51d0..99a38e22 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -51,6 +51,7 @@ steps:
       - ENABLE_PIPELINE_CACHING=${_TEST_ENABLE_PIPELINE_CACHING}
       - VERTEX_LOCATION=${_TEST_VERTEX_LOCATION}
       - VERTEX_PROJECT_ID=${_TEST_VERTEX_PROJECT_ID}
+      - BQ_LOCATION=${_TEST_BQ_LOCATION}
       - VERTEX_SA_EMAIL=${_TEST_VERTEX_SA_EMAIL}
       - VERTEX_CMEK_IDENTIFIER=${_TEST_VERTEX_CMEK_IDENTIFIER}
       - VERTEX_NETWORK=${_TEST_VERTEX_NETWORK}
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index fc20bc75..480aeee8 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -47,12 +47,12 @@ steps:
           cd pipelines && \
           poetry run python -m pipelines.utils.upload_pipeline \
           --dest=https://${_VERTEX_LOCATION}-kfp.pkg.dev/$$proj/vertex-pipelines \
-          --yaml=src/pipelines/training/pipeline.yaml \
+          --yaml=src/pipelines/pipeline.yaml \
           --tag=latest \
           --tag=${TAG_NAME} && \
           poetry run python -m pipelines.utils.upload_pipeline \
           --dest=https://${_VERTEX_LOCATION}-kfp.pkg.dev/$$proj/vertex-pipelines \
-          --yaml=src/pipelines/prediction/pipeline.yaml \
+          --yaml=src/pipelines/pipeline.yaml \
           --tag=latest \
           --tag=${TAG_NAME}; \
         done
diff --git a/components/src/components/extract_table.py b/components/src/components/extract_table.py
index 496e5377..5fe413f4 100644
--- a/components/src/components/extract_table.py
+++ b/components/src/components/extract_table.py
@@ -11,81 +11,32 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from kfp.dsl import Dataset, Output, ContainerSpec, container_component
 
-from kfp.dsl import Dataset, Output, component
 
-
-@component(
-    base_image="python:3.9",
-    packages_to_install=["google-cloud-bigquery==2.30.0"],
-)
+@container_component
 def extract_table(
-    bq_client_project_id: str,
-    source_project_id: str,
-    dataset_id: str,
-    table_name: str,
-    dataset: Output[Dataset],
-    destination_gcs_uri: str = None,
-    dataset_location: str = "EU",
-    extract_job_config: dict = None,
-    skip_if_exists: bool = True,
+    project: str,
+    location: str,
+    table: str,
+    data: Output[Dataset],
+    destination_format: str = "CSV",
+    compression: str = "NONE",
+    field_delimiter: str = ",",
+    print_header: str = "true",
 ):
-    """
-    Extract BQ table in GCS.
-    Args:
-        bq_client_project_id (str): project id that will be used by the bq client
-        source_project_id (str): project id from where BQ table will be extracted
-        dataset_id (str): dataset id from where BQ table will be extracted
-        table_name (str): table name (without project id and dataset id)
-        dataset (Output[Dataset]): output dataset artifact generated by the operation,
-            this parameter will be passed automatically by the orchestrator
-        dataset_location (str): bq dataset location. Defaults to "EU".
-        extract_job_config (dict): dict containing optional parameters
-            required by the bq extract operation. Defaults to None.
-            See available parameters here
-            https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.job.ExtractJobConfig.html # noqa
-        destination_gcs_uri (str): GCS URI to use for saving query results (optional).
-
-    Returns:
-        Outputs (NamedTuple (str, list)): Output dataset directory and its  GCS uri.
-    """
-
-    import logging
-    from pathlib import Path
-    from google.cloud.exceptions import GoogleCloudError
-    from google.cloud import bigquery
-
-    # set uri of output dataset if destination_gcs_uri is provided
-    if destination_gcs_uri:
-        dataset.uri = destination_gcs_uri
-
-    logging.info(f"Checking if destination exists: {dataset.path}")
-    if Path(dataset.path).exists() and skip_if_exists:
-        logging.info("Destination already exists, skipping table extraction!")
-        return
-
-    full_table_id = f"{source_project_id}.{dataset_id}.{table_name}"
-    table = bigquery.table.Table(table_ref=full_table_id)
-
-    if extract_job_config is None:
-        extract_job_config = {}
-    job_config = bigquery.job.ExtractJobConfig(**extract_job_config)
-
-    logging.info(f"Extract table {table} to {dataset.uri}")
-    client = bigquery.client.Client(
-        project=bq_client_project_id, location=dataset_location
+    return ContainerSpec(
+        image="google/cloud-sdk:alpine",
+        command=["bq"],
+        args=[
+            "extract",
+            f"--project_id={project}",
+            f"--location={location}",
+            f"--destination_format={destination_format}",
+            f"--compression={compression}",
+            f"--field_delimiter={field_delimiter}",
+            f"--print_header={print_header}",
+            table,
+            data.uri,
+        ],
     )
-    extract_job = client.extract_table(
-        table,
-        dataset.uri,
-        job_config=job_config,
-    )
-
-    try:
-        result = extract_job.result()
-        logging.info("Table extracted, result: {}".format(result))
-    except GoogleCloudError as e:
-        logging.error(e)
-        logging.error(extract_job.error_result)
-        logging.error(extract_job.errors)
-        raise e
diff --git a/components/src/components/lookup_model.py b/components/src/components/lookup_model.py
index 813208a7..1f00035b 100644
--- a/components/src/components/lookup_model.py
+++ b/components/src/components/lookup_model.py
@@ -22,10 +22,9 @@
 )
 def lookup_model(
     model_name: str,
-    project_location: str,
-    project_id: str,
+    location: str,
+    project: str,
     model: Output[Model],
-    order_models_by: str = "create_time desc",
     fail_on_model_not_found: bool = False,
 ) -> NamedTuple("Outputs", [("model_resource_name", str), ("training_dataset", dict)]):
     """
@@ -33,15 +32,9 @@ def lookup_model(
 
     Args:
         model_name (str): display name of the model
-        project_location (str): location of the Google Cloud project
-        project_id (str): project id of the Google Cloud project
+        location (str): location of the Google Cloud project
+        project (str): project id of the Google Cloud project
         model (Output[Model]): a Vertex AI model
-        order_models_by (str): if multiple models are found based on the display name,
-            use a filter clause:
-            A comma-separated list of fields to order by, sorted in
-            ascending order. Use "desc" after a field name for descending.
-            Supported fields: `display_name`, `create_time`, `update_time`
-            Defaults to "create_time desc".
         fail_on_model_not_found (bool): if set to True, raise runtime error if
             model is not found
 
@@ -60,25 +53,23 @@ def lookup_model(
     logging.info(f"listing models with display name {model_name}")
     models = Model.list(
         filter=f'display_name="{model_name}"',
-        order_by=order_models_by,
-        location=project_location,
-        project=project_id,
+        location=location,
+        project=project,
     )
-    logging.info(f"found {len(models)} models")
+    logging.info(f"found {len(models)} model(s)")
 
     training_dataset = {}
     model_resource_name = ""
     if len(models) == 0:
         logging.error(
-            f"No model found with name {model_name}"
-            + f"(project: {project_id} location: {project_location})"
+            f"No model found with name {model_name} "
+            + f"(project: {project} location: {location})"
         )
         if fail_on_model_not_found:
             raise RuntimeError(f"Failed as model was not found")
     elif len(models) == 1:
         target_model = models[0]
         model_resource_name = target_model.resource_name
-        logging.info(f"choosing model by order ({order_models_by})")
         logging.info(f"model display name: {target_model.display_name}")
         logging.info(f"model resource name: {target_model.resource_name}")
         logging.info(f"model uri: {target_model.uri}")
diff --git a/components/src/components/model_batch_predict.py b/components/src/components/model_batch_predict.py
index da5b6b14..ab329181 100644
--- a/components/src/components/model_batch_predict.py
+++ b/components/src/components/model_batch_predict.py
@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from kfp.dsl import Input, Model, component
-from typing import List, NamedTuple
+from kfp.dsl import Input, Model, component, OutputPath
+from typing import List
 
 
 @component(
@@ -25,9 +25,10 @@
 )
 def model_batch_predict(
     model: Input[Model],
+    gcp_resources: OutputPath(str),
     job_display_name: str,
-    project_location: str,
-    project_id: str,
+    location: str,
+    project: str,
     source_uri: str,
     destination_uri: str,
     source_format: str,
@@ -39,15 +40,15 @@ def model_batch_predict(
     monitoring_alert_email_addresses: List[str] = None,
     monitoring_skew_config: dict = None,
     instance_config: dict = None,
-) -> NamedTuple("Outputs", [("gcp_resources", str)]):
+):
     """
     Trigger a batch prediction job and enable monitoring.
 
     Args:
         model (Input[Model]): Input model to use for calculating predictions.
         job_display_name: Name of the batch prediction job.
-        project_location (str): location of the Google Cloud project. Defaults to None.
-        project_id (str): project id of the Google Cloud project. Defaults to None.
+        location (str): location of the Google Cloud project. Defaults to None.
+        project (str): project id of the Google Cloud project. Defaults to None.
         source_uri (str): bq:// URI or a list of gcs:// URIs to read input instances.
         destination_uri (str): bq:// or gs:// URI to store output predictions.
         source_format (str): E.g. "bigquery", "jsonl", "csv". See:
@@ -67,7 +68,7 @@ def model_batch_predict(
             input instances to the instances that the Model accepts. See:
             https://cloud.google.com/vertex-ai/docs/reference/rest/v1beta1/projects.locations.batchPredictionJobs#instanceconfig
     Returns:
-        NamedTuple: gcp_resources for Vertex AI UI integration.
+        OutputPath: gcp_resources for Vertex AI UI integration.
     """
 
     import logging
@@ -118,7 +119,7 @@ def is_job_successful(job_state: JobState) -> bool:
     _POLLING_INTERVAL_IN_SECONDS = 20
     _CONNECTION_ERROR_RETRY_LIMIT = 5
 
-    api_endpoint = f"{project_location}-aiplatform.googleapis.com"
+    api_endpoint = f"{location}-aiplatform.googleapis.com"
 
     input_config = {"instancesFormat": source_format}
     output_config = {"predictionsFormat": destination_format}
@@ -167,11 +168,19 @@ def is_job_successful(job_state: JobState) -> bool:
     logging.info(request)
     client = JobServiceClient(client_options={"api_endpoint": api_endpoint})
     response = client.create_batch_prediction_job(
-        parent=f"projects/{project_id}/locations/{project_location}",
+        parent=f"projects/{project}/locations/{location}",
         batch_prediction_job=request,
     )
     logging.info(f"Submitted batch prediction job: {response.name}")
 
+    # output GCP resource for Vertex AI UI integration
+    batch_job_resources = GcpResources()
+    dr = batch_job_resources.resources.add()
+    dr.resource_type = "BatchPredictionJob"
+    dr.resource_uri = response.name
+    with open(gcp_resources, "w") as f:
+        f.write(MessageToJson(batch_job_resources))
+
     with execution_context.ExecutionContext(
         on_cancel=partial(
             send_cancel_request,
@@ -206,12 +215,3 @@ def is_job_successful(job_state: JobState) -> bool:
                 f"Waiting for {_POLLING_INTERVAL_IN_SECONDS} seconds for next poll."
             )
             time.sleep(_POLLING_INTERVAL_IN_SECONDS)
-
-    # return GCP resource for Vertex AI UI integration
-    batch_job_resources = GcpResources()
-    dr = batch_job_resources.resources.add()
-    dr.resource_type = "BatchPredictionJob"
-    dr.resource_uri = response.name
-    gcp_resources = MessageToJson(batch_job_resources)
-
-    return (gcp_resources,)
diff --git a/components/src/components/upload_model.py b/components/src/components/upload_model.py
index 2484ffec..d23609c6 100644
--- a/components/src/components/upload_model.py
+++ b/components/src/components/upload_model.py
@@ -25,26 +25,27 @@
 )
 def upload_model(
     model: Input[Model],
-    test_dataset: Input[Dataset],
+    test_data: Input[Dataset],
     model_evaluation: Input[Metrics],
     vertex_model: Output[VertexModel],
-    project_id: str,
-    project_location: str,
+    project: str,
+    location: str,
     model_name: str,
     eval_metric: str,
     eval_lower_is_better: bool,
     pipeline_job_id: str,
     serving_container_image: str,
+    model_description: str = None,
     evaluation_name: str = "Imported evaluation",
 ) -> None:
     """
     Args:
         model (Model): Input challenger model.
-        test_dataset (Dataset): Test dataset used for evaluating challenger model.
+        test_data (Dataset): Test dataset used for evaluating challenger model.
         vertex_model (VertexModel): Output model uploaded to Vertex AI Model Registry.
         model_evaluation (Metrics): Evaluation metrics of challenger model.
-        project_id (str): project id of the Google Cloud project.
-        project_location (str): location of the Google Cloud project.
+        project (str): project id of the Google Cloud project.
+        location (str): location of the Google Cloud project.
         pipeline_job_id (str):
         model_name (str): Name of champion and challenger model in
             Vertex AI Model Registry.
@@ -53,8 +54,9 @@ def upload_model(
             False for classification metrics.
         serving_container_image (str): Container URI for serving the challenger
             model.
-        evaluation_name (str): Name of evaluation results which are displayed in the
-            Vertex AI UI of the challenger model.
+        model_description (str): Optional. Description of model.
+        evaluation_name (str): Optional. Name of evaluation results which are
+            displayed in the Vertex AI UI of the challenger model.
     """
 
     import json
@@ -64,22 +66,20 @@ def upload_model(
     from google.cloud.aiplatform_v1 import ModelEvaluation, ModelServiceClient
     from google.protobuf.json_format import ParseDict
 
-    def lookup_model(
-        project_id: str, project_location: str, model_name: str
-    ) -> aip.Model:
+    def lookup_model(model_name: str) -> aip.Model:
         """Look up model in model registry."""
         logging.info(f"listing models with display name {model_name}")
         models = aip.Model.list(
             filter=f'display_name="{model_name}"',
-            location=project_location,
-            project=project_id,
+            location=location,
+            project=project,
         )
         logging.info(f"found {len(models)} models")
 
         if len(models) == 0:
             logging.info(
                 f"No model found with name {model_name}"
-                + f"(project: {project_id} location: {project_location})"
+                + f"(project: {project} location: {location})"
             )
             return None
         elif len(models) == 1:
@@ -115,6 +115,7 @@ def upload_model_to_registry(
         logging.info(f"Uploading model {model_name} (default: {is_default_version}")
         uploaded_model = aip.Model.upload(
             display_name=model_name,
+            description=model_description,
             artifact_uri=model.uri,
             serving_container_image_uri=serving_container_image,
             serving_container_predict_route="/predict",
@@ -126,7 +127,7 @@ def upload_model_to_registry(
 
         # Output google.VertexModel artifact
         vertex_model.uri = (
-            f"https://{project_location}-aiplatform.googleapis.com/v1/"
+            f"https://{location}-aiplatform.googleapis.com/v1/"
             f"{uploaded_model.versioned_resource_name}"
         )
         vertex_model.metadata["resourceName"] = uploaded_model.versioned_resource_name
@@ -136,7 +137,6 @@ def upload_model_to_registry(
     def import_evaluation(
         parsed_metrics: dict,
         challenger_model: aip.Model,
-        project_location: str,
         evaluation_name: str,
     ) -> str:
         """Import model evaluation."""
@@ -153,7 +153,7 @@ def import_evaluation(
             "metadata": {
                 "pipeline_job_id": pipeline_job_id,
                 "evaluation_dataset_type": "gcs",
-                "evaluation_dataset_path": [test_dataset.uri],
+                "evaluation_dataset_path": [test_data.uri],
             },
         }
 
@@ -161,9 +161,7 @@ def import_evaluation(
         logging.debug(f"Request: {request}")
         challenger_name = challenger_model.versioned_resource_name
         client = ModelServiceClient(
-            client_options={
-                "api_endpoint": project_location + "-aiplatform.googleapis.com"
-            }
+            client_options={"api_endpoint": location + "-aiplatform.googleapis.com"}
         )
         logging.info(f"Uploading model evaluation for {challenger_name}")
         response = client.import_model_evaluation(
@@ -177,9 +175,7 @@ def import_evaluation(
     with open(model_evaluation.path, "r") as f:
         challenger_metrics = json.load(f)
 
-    champion_model = lookup_model(
-        project_id=project_id, project_location=project_location, model_name=model_name
-    )
+    champion_model = lookup_model(model_name=model_name)
 
     challenger_wins = True
     parent_model_uri = None
@@ -206,6 +202,5 @@ def import_evaluation(
     import_evaluation(
         parsed_metrics=challenger_metrics,
         challenger_model=model,
-        project_location=project_location,
         evaluation_name=evaluation_name,
     )
diff --git a/components/tests/test_extract_table.py b/components/tests/test_extract_table.py
deleted file mode 100644
index 2db07695..00000000
--- a/components/tests/test_extract_table.py
+++ /dev/null
@@ -1,78 +0,0 @@
-# Copyright 2023 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import google.cloud.bigquery  # noqa
-from kfp.dsl import Dataset
-from unittest import mock
-
-import components
-
-extract_bq_to_dataset = components.extract_table.python_func
-
-
-@mock.patch("google.cloud.bigquery.client.Client")
-@mock.patch("google.cloud.bigquery.table.Table")
-@mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
-def test_extract_table(mock_job_config, mock_table, mock_client, tmpdir):
-    """
-    Checks that the extract_bq_to_dataset is called correctly
-    """
-    mock_path = tmpdir
-    mock_client.extract_table.return_value = "my-job"
-    mock_table.return_value.table_ref = "my-table"
-    mock_job_config.return_value = "mock-job-config"
-
-    extract_bq_to_dataset(
-        bq_client_project_id="my-project-id",
-        source_project_id="source-project-id",
-        dataset_id="dataset-id",
-        table_name="table-name",
-        dataset=Dataset(uri=mock_path),
-        destination_gcs_uri="gs://mock_bucket",
-        dataset_location="EU",
-        extract_job_config=None,
-        skip_if_exists=False,
-    )
-
-    mock_client.return_value.extract_table.assert_called_once_with(
-        mock_table.return_value, "gs://mock_bucket", job_config="mock-job-config"
-    )
-
-
-@mock.patch("google.cloud.bigquery.client.Client")
-@mock.patch("google.cloud.bigquery.table.Table")
-@mock.patch("google.cloud.bigquery.job.ExtractJobConfig")
-@mock.patch("pathlib.Path.exists")
-def test_extract_table_skip_existing(
-    mock_path_exists, mock_job_config, mock_table, mock_client, tmpdir
-):
-    """
-    Checks that when the dataset exists the method is not called
-    """
-    mock_path = tmpdir
-    mock_path_exists.return_value = True
-
-    extract_bq_to_dataset(
-        bq_client_project_id="my-project-id",
-        source_project_id="source-project-id",
-        dataset_id="dataset-id",
-        table_name="table-name",
-        dataset=Dataset(uri=mock_path),
-        destination_gcs_uri="gs://mock_bucket",
-        dataset_location="EU",
-        extract_job_config=None,
-        skip_if_exists=True,
-    )
-
-    assert not mock_client.return_value.extract_table.called
diff --git a/docs/AUTOMATION.md b/docs/AUTOMATION.md
index 5094b4a7..b9c4adc2 100644
--- a/docs/AUTOMATION.md
+++ b/docs/AUTOMATION.md
@@ -63,6 +63,7 @@ Set up a trigger for the `e2e-test.yaml` pipeline, and provide substitution valu
 | `_TEST_VERTEX_PROJECT_ID` | Google Cloud project ID in which you want to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | Project ID for the DEV environment |
 | `_TEST_VERTEX_SA_EMAIL` | Email address of the service account you want to use to run the ML pipelines in the E2E tests as part of the CI/CD pipeline. | `vertex-pipelines@<Project ID for dev environment>.iam.gserviceaccount.com` |
 | `_TEST_ENABLE_PIPELINE_CACHING` | Override the default caching behaviour of the ML pipelines. Leave blank to use the default caching behaviour. | `False` |
+| `_TEST_BQ_LOCATION` | The location of BigQuery datasets used in training and prediction pipelines. | `US` or `EU` if using multi-region datasets |
 
 We recommend to enable comment control for this trigger (select `Required` under `Comment Control`). This will mean that the end-to-end tests will only run once a repository collaborator or owner comments `/gcbrun` on the pull request.
 This will help to avoid unnecessary runs of the ML pipelines while a Pull Request is still being worked on, as they can take a long time (and can be expensive to run on every Pull Request!)
diff --git a/docs/PIPELINES.md b/docs/PIPELINES.md
index cfd9b27a..7d1da590 100644
--- a/docs/PIPELINES.md
+++ b/docs/PIPELINES.md
@@ -15,7 +15,7 @@ limitations under the License.
  -->
 # ML Pipelines
 
-There are two ML pipelines defined in this repository: a training pipeline (located in [pipelines/src/pipelines/training/pipeline.py](/pipelines/src/pipelines/training/pipeline.py)) and a batch prediction pipeline (located in [pipelines/src/pipelines/prediction/pipeline.py](/pipelines/src/pipelines/prediction/pipeline.py)).
+There are two ML pipelines defined in this repository: a training pipeline (located in `pipelines/src/pipelines/training.py` and a batch prediction pipeline (located in `pipelines/src/pipelines/prediction.py`).
 
 ## Pipeline input parameters
 
@@ -70,7 +70,7 @@ In the next sections we will walk through the different pipeline steps.
 
 The first pipeline step runs a SQL script in BigQuery to extract data from the source table and load it into tables according to a train/test/validation split.
 
-The SQL query for this can be found in [pipelines/src/pipelines/training/queries/preprocessing.sql](/pipelines/src/pipelines/training/queries/preprocessing.sql).
+The SQL query for this can be found in `pipelines/src/pipelines/queries/preprocessing.sql`.
 
 As you can see in this SQL query, there are some placeholder values (marked by the curly brace syntax `{{ }}`). When the pipeline runs, these are replaced with values provided from the ML pipeline.
 
@@ -88,7 +88,7 @@ This step is performed using a custom KFP component located in [components/bigqu
 
 ### Training step
 
-The training step is defined as a [KFP container component](https://www.kubeflow.org/docs/components/pipelines/v2/components/container-components/) in the [pipeline.py](/pipelines/src/pipelines/training/pipeline.py) file.
+The training step is defined as a [KFP container component](https://www.kubeflow.org/docs/components/pipelines/v2/components/container-components/) in the [pipeline.py](/pipelines/src/pipelines/training.py) file.
 
 The container image used for this component is built using CI/CD (or the `make build target=training` command if you want to build it during development).
 
diff --git a/docs/PRODUCTION.md b/docs/PRODUCTION.md
index 8302f902..4d421335 100644
--- a/docs/PRODUCTION.md
+++ b/docs/PRODUCTION.md
@@ -29,7 +29,7 @@ This document describes the full process from making a change to your pipeline c
 ## Making your changes to the pipelines
 
 1. Create a feature branch off the main/master branch: `git checkout -b my-feature-branch`
-1. Make changes to your pipeline code locally (e.g. [pipelines/src/pipelines/training/pipeline.py](/pipelines/src/pipelines/training/pipeline.py))
+1. Make changes to your pipeline code locally (e.g. `pipelines/src/pipelines/training.py`)
 1. Commit these changes to your feature branch
 1. Push your feature branch to GitHub
 1. Open a Pull Request (PR) from your feature branch to the main/master branch
@@ -52,7 +52,6 @@ When the new tag is created, the `release.yaml` pipeline should be triggered. It
 
 #### Example
 
-
 - You have set up the following Cloud Build variables / substitutions for the `release.yaml` CI/CD pipeline
   - `_PIPELINE_PUBLISH_AR_PATHS` = `https://<GCP region>-kfp.pkg.dev/<Project ID of dev project>/vertex-pipelines https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines https://<GCP region>-kfp.pkg.dev/<Project ID of prod project>/vertex-pipelines`
 - You create a release from the main/master branch and use the git tag `v1.2`
diff --git a/env.sh.example b/env.sh.example
index 029c3089..8666c732 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -15,6 +15,7 @@
 
 export VERTEX_PROJECT_ID=my-gcp-project
 export VERTEX_LOCATION=europe-west2
+export BQ_LOCATION=US
 export VERTEX_NETWORK=
 export VERTEX_CMEK_IDENTIFIER=
 
diff --git a/model/Dockerfile b/model/Dockerfile
index db0b33cd..ffd743b6 100644
--- a/model/Dockerfile
+++ b/model/Dockerfile
@@ -27,11 +27,11 @@ RUN poetry config virtualenvs.create false && poetry install
 
 FROM builder AS training
 
-COPY training/train.py training/train.py
+COPY training training
 
 FROM builder AS serving
 
 RUN poetry install --with serving
-COPY serving/main.py serving/main.py
+COPY serving serving
 
 CMD exec uvicorn serving.main:app --host "0.0.0.0" --port "$AIP_HTTP_PORT"
diff --git a/model/training/__init__.py b/model/training/__init__.py
new file mode 100644
index 00000000..7ba50f93
--- /dev/null
+++ b/model/training/__init__.py
@@ -0,0 +1,13 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
diff --git a/model/training/__main__.py b/model/training/__main__.py
new file mode 100644
index 00000000..60e48174
--- /dev/null
+++ b/model/training/__main__.py
@@ -0,0 +1,35 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import argparse
+import json
+import os
+import logging
+
+from .train import train
+
+logging.basicConfig(level=logging.DEBUG)
+
+parser = argparse.ArgumentParser()
+parser.add_argument("--input_path", type=str, required=True)
+parser.add_argument("--input_test_path", type=str, required=False)
+parser.add_argument("--output_train_path", type=str, required=True)
+parser.add_argument("--output_valid_path", type=str, required=True)
+parser.add_argument("--output_test_path", type=str, required=True)
+parser.add_argument("--output_model", default=os.getenv("AIP_MODEL_DIR"), type=str)
+parser.add_argument("--output_metrics", type=str, required=True)
+parser.add_argument("--hparams", default={}, type=json.loads)
+args = vars(parser.parse_args())
+
+train(**args)
diff --git a/model/training/train.py b/model/training/train.py
index a5cf8544..978dae30 100644
--- a/model/training/train.py
+++ b/model/training/train.py
@@ -11,23 +11,21 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import argparse
+
 from pathlib import Path
 
 import joblib
-import json
-import os
 import logging
 
-import numpy as np
 import pandas as pd
-from sklearn import metrics
 from sklearn.compose import ColumnTransformer
+from sklearn.model_selection import train_test_split
 from sklearn.pipeline import Pipeline
 from sklearn.preprocessing import StandardScaler, OrdinalEncoder, OneHotEncoder
 from xgboost import XGBRegressor
 
-logging.basicConfig(level=logging.DEBUG)
+from .utils import indices_in_list, save_metrics, save_monitoring_info, split_xy
+
 
 # used for monitoring during prediction time
 TRAINING_DATASET_INFO = "training_dataset.json"
@@ -37,124 +35,103 @@
 OHE_COLS = ["payment_type"]
 
 
-def split_xy(df: pd.DataFrame, label: str) -> (pd.DataFrame, pd.Series):
-    """Split dataframe into X and y."""
-    return df.drop(columns=[label]), df[label]
-
-
-def indices_in_list(elements: list, base_list: list) -> list:
-    """Get indices of specific elements in a base list"""
-    return [idx for idx, elem in enumerate(base_list) if elem in elements]
-
+def train(
+    input_path: str,
+    input_test_path: str,
+    output_train_path: str,
+    output_valid_path: str,
+    output_test_path: str,
+    output_model: str,
+    output_metrics: str,
+    hparams: dict,
+):
+
+    logging.info("Read csv files into dataframes")
+    df = pd.read_csv(input_path)
+
+    logging.info("Split dataframes")
+    label = hparams.pop("label")
+
+    if input_test_path:
+        # if static test data is used, only split into train & valid dataframes
+        if input_test_path.startswith("gs://"):
+            input_test_path = "/gcs/" + input_test_path[5:]
+        df_train, df_valid = train_test_split(df, test_size=0.2, random_state=1)
+        df_test = pd.read_csv(input_test_path)
+    else:
+        # otherwise, split into train, valid, and test dataframes
+        df_train, df_test = train_test_split(df, test_size=0.2, random_state=1)
+        df_train, df_valid = train_test_split(df_train, test_size=0.25, random_state=1)
+
+    # create output folders
+    for x in [output_metrics, output_train_path, output_test_path, output_test_path]:
+        Path(x).parent.mkdir(parents=True, exist_ok=True)
+    Path(output_model).mkdir(parents=True, exist_ok=True)
+
+    df_train.to_csv(output_train_path, index=False)
+    df_valid.to_csv(output_valid_path, index=False)
+    df_test.to_csv(output_test_path, index=False)
+
+    X_train, y_train = split_xy(df_train, label)
+    X_valid, y_valid = split_xy(df_valid, label)
+    X_test, y_test = split_xy(df_test, label)
+
+    logging.info("Get the number of unique categories for ordinal encoded columns")
+    ordinal_columns = X_train[ORD_COLS]
+    n_unique_cat = ordinal_columns.nunique()
+
+    logging.info("Get indices of columns in base data")
+    col_list = X_train.columns.tolist()
+    num_indices = indices_in_list(NUM_COLS, col_list)
+    cat_indices_onehot = indices_in_list(OHE_COLS, col_list)
+    cat_indices_ordinal = indices_in_list(ORD_COLS, col_list)
+
+    ordinal_transformers = [
+        (
+            f"ordinal encoding for {ord_col}",
+            OrdinalEncoder(
+                handle_unknown="use_encoded_value", unknown_value=n_unique_cat[ord_col]
+            ),
+            [ord_index],
+        )
+        for ord_col in ORD_COLS
+        for ord_index in cat_indices_ordinal
+    ]
+    all_transformers = [
+        ("numeric_scaling", StandardScaler(), num_indices),
+        (
+            "one_hot_encoding",
+            OneHotEncoder(handle_unknown="ignore"),
+            cat_indices_onehot,
+        ),
+    ] + ordinal_transformers
 
-parser = argparse.ArgumentParser()
-parser.add_argument("--train-data", type=str, required=True)
-parser.add_argument("--valid-data", type=str, required=True)
-parser.add_argument("--test-data", type=str, required=True)
-parser.add_argument("--model", default=os.getenv("AIP_MODEL_DIR"), type=str, help="")
-parser.add_argument("--model-output-uri", type=str)
-parser.add_argument("--metrics", type=str, required=True)
-parser.add_argument("--hparams", default={}, type=json.loads)
-args = parser.parse_args()
+    logging.info("Build sklearn preprocessing steps")
+    preprocesser = ColumnTransformer(transformers=all_transformers)
+    logging.info("Build sklearn pipeline with XGBoost model")
+    xgb_model = XGBRegressor(**hparams)
 
-if args.model.startswith("gs://"):
-    args.model = "/gcs/" + args.model[5:]
+    pipeline = Pipeline(
+        steps=[("feature_engineering", preprocesser), ("train_model", xgb_model)]
+    )
 
-logging.info("Read csv files into dataframes")
-df_train = pd.read_csv(args.train_data)
-df_valid = pd.read_csv(args.valid_data)
-df_test = pd.read_csv(args.test_data)
+    logging.info("Transform validation data")
+    valid_preprocesser = preprocesser.fit(X_train)
+    X_valid_transformed = valid_preprocesser.transform(X_valid)
 
-logging.info("Split dataframes")
-label = args.hparams["label"]
-X_train, y_train = split_xy(df_train, label)
-X_valid, y_valid = split_xy(df_valid, label)
-X_test, y_test = split_xy(df_test, label)
+    logging.info("Fit model")
+    pipeline.fit(
+        X_train, y_train, train_model__eval_set=[(X_valid_transformed, y_valid)]
+    )
 
-logging.info("Get the number of unique categories for ordinal encoded columns")
-ordinal_columns = X_train[ORD_COLS]
-n_unique_cat = ordinal_columns.nunique()
+    logging.info("Predict test data")
+    y_pred = pipeline.predict(X_test)
+    y_pred = y_pred.clip(0)
 
-logging.info("Get indices of columns in base data")
-col_list = X_train.columns.tolist()
-num_indices = indices_in_list(NUM_COLS, col_list)
-cat_indices_onehot = indices_in_list(OHE_COLS, col_list)
-cat_indices_ordinal = indices_in_list(ORD_COLS, col_list)
+    logging.info(f"Save model to: {output_model}")
+    joblib.dump(pipeline, f"{output_model}/model.joblib")
 
-ordinal_transformers = [
-    (
-        f"ordinal encoding for {ord_col}",
-        OrdinalEncoder(
-            handle_unknown="use_encoded_value", unknown_value=n_unique_cat[ord_col]
-        ),
-        [ord_index],
+    save_metrics(y_test, y_pred, output_metrics)
+    save_monitoring_info(
+        output_train_path, label, f"{output_model}/{TRAINING_DATASET_INFO}"
     )
-    for ord_col in ORD_COLS
-    for ord_index in cat_indices_ordinal
-]
-all_transformers = [
-    ("numeric_scaling", StandardScaler(), num_indices),
-    (
-        "one_hot_encoding",
-        OneHotEncoder(handle_unknown="ignore"),
-        cat_indices_onehot,
-    ),
-] + ordinal_transformers
-
-logging.info("Build sklearn preprocessing steps")
-preprocesser = ColumnTransformer(transformers=all_transformers)
-logging.info("Build sklearn pipeline with XGBoost model")
-xgb_model = XGBRegressor(**args.hparams)
-
-pipeline = Pipeline(
-    steps=[("feature_engineering", preprocesser), ("train_model", xgb_model)]
-)
-
-logging.info("Transform validation data")
-valid_preprocesser = preprocesser.fit(X_train)
-X_valid_transformed = valid_preprocesser.transform(X_valid)
-
-logging.info("Fit model")
-pipeline.fit(X_train, y_train, train_model__eval_set=[(X_valid_transformed, y_valid)])
-
-logging.info("Predict test data")
-y_pred = pipeline.predict(X_test)
-y_pred = y_pred.clip(0)
-
-metrics = {
-    "problemType": "regression",
-    "rootMeanSquaredError": np.sqrt(metrics.mean_squared_error(y_test, y_pred)),
-    "meanAbsoluteError": metrics.mean_absolute_error(y_test, y_pred),
-    "meanAbsolutePercentageError": metrics.mean_absolute_percentage_error(
-        y_test, y_pred
-    ),
-    "rSquared": metrics.r2_score(y_test, y_pred),
-    "rootMeanSquaredLogError": np.sqrt(metrics.mean_squared_log_error(y_test, y_pred)),
-}
-
-logging.info(f"Save model to: {args.model}")
-Path(args.model).mkdir(parents=True)
-joblib.dump(pipeline, f"{args.model}/model.joblib")
-
-model_uri = "gs://" + args.model[5:]
-with open(args.model_output_uri, "w") as f:
-    f.write(model_uri)
-
-logging.info(f"Metrics: {metrics}")
-with open(args.metrics, "w") as fp:
-    json.dump(metrics, fp)
-
-# Persist URIs of training file(s) for model monitoring in batch predictions
-# See https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
-# for the expected schema.
-path = f"{args.model}/{TRAINING_DATASET_INFO}"
-training_dataset_for_monitoring = {
-    "gcsSource": {"uris": [args.train_data]},
-    "dataFormat": "csv",
-    "targetField": label,
-}
-logging.info(f"Training dataset info: {training_dataset_for_monitoring}")
-
-with open(path, "w") as fp:
-    logging.info(f"Save training dataset info for model monitoring: {path}")
-    json.dump(training_dataset_for_monitoring, fp)
diff --git a/model/training/utils.py b/model/training/utils.py
new file mode 100644
index 00000000..56b9b8a0
--- /dev/null
+++ b/model/training/utils.py
@@ -0,0 +1,66 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import logging
+import json
+
+import numpy as np
+import pandas as pd
+from sklearn import metrics
+
+
+def split_xy(df: pd.DataFrame, label: str) -> (pd.DataFrame, pd.Series):
+    """Split dataframe into X and y."""
+    return df.drop(columns=[label]), df[label]
+
+
+def indices_in_list(elements: list, base_list: list) -> list:
+    """Get indices of specific elements in a base list"""
+    return [idx for idx, elem in enumerate(base_list) if elem in elements]
+
+
+def save_metrics(y_test: pd.DataFrame, y_pred: pd.DataFrame, output_path: str):
+    """Save metrics in JSON format for Vertex AI Evaluation."""
+    data = {
+        "problemType": "regression",
+        "rootMeanSquaredError": np.sqrt(metrics.mean_squared_error(y_test, y_pred)),
+        "meanAbsoluteError": metrics.mean_absolute_error(y_test, y_pred),
+        "meanAbsolutePercentageError": metrics.mean_absolute_percentage_error(
+            y_test, y_pred
+        ),
+        "rSquared": metrics.r2_score(y_test, y_pred),
+        "rootMeanSquaredLogError": np.sqrt(
+            metrics.mean_squared_log_error(y_test, y_pred)
+        ),
+    }
+
+    logging.info(f"Metrics: {metrics}")
+    with open(output_path, "w") as fp:
+        json.dump(data, fp)
+
+
+def save_monitoring_info(train_path: str, label: str, output_path: str):
+    """Persist URIs of training file(s) for model monitoring in batch predictions.
+    For the expected schema see:
+        https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset  # noqa: E501
+    """
+    training_dataset_for_monitoring = {
+        "gcsSource": {"uris": [train_path]},
+        "dataFormat": "csv",
+        "targetField": label,
+    }
+    logging.info(f"Training dataset info: {training_dataset_for_monitoring}")
+
+    with open(output_path, "w") as fp:
+        logging.info(f"Save training dataset info for model monitoring: {output_path}")
+        json.dump(training_dataset_for_monitoring, fp)
diff --git a/pipelines/src/pipelines/__init__.py b/pipelines/src/pipelines/__init__.py
index 33ac7fee..7ba50f93 100644
--- a/pipelines/src/pipelines/__init__.py
+++ b/pipelines/src/pipelines/__init__.py
@@ -11,23 +11,3 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
-from pathlib import Path
-from jinja2 import Template
-
-
-def generate_query(input_file: Path, **replacements) -> str:
-    """
-    Read input file and replace placeholder using Jinja.
-
-    Args:
-        input_file (Path): input file to read
-        replacements: keyword arguments to use to replace placeholders
-    Returns:
-        str: replaced content of input file
-    """
-
-    with open(input_file, "r") as f:
-        query_template = f.read()
-
-    return Template(query_template).render(**replacements)
diff --git a/pipelines/src/pipelines/prediction.py b/pipelines/src/pipelines/prediction.py
new file mode 100644
index 00000000..2b01c124
--- /dev/null
+++ b/pipelines/src/pipelines/prediction.py
@@ -0,0 +1,116 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import pathlib
+from os import environ as env
+
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
+from kfp import dsl
+
+from pipelines.utils.query import generate_query
+from components import lookup_model, model_batch_predict
+
+
+RESOURCE_SUFFIX = env.get("RESOURCE_SUFFIX", "default")
+# set training-serving skew thresholds and emails to receive alerts:
+ALERT_EMAILS = []
+SKEW_THRESHOLDS = {"defaultSkewThreshold": {"value": 0.001}}
+# or set different thresholds per feature:
+# SKEW_THRESHOLDS = {"skewThresholds": {"payment_type": {"value": 0.001}}, ... }
+
+
+@dsl.pipeline(name="turbo-prediction-pipeline")
+def pipeline(
+    project: str = env.get("VERTEX_PROJECT_ID"),
+    location: str = env.get("VERTEX_LOCATION"),
+    bq_location: str = env.get("BQ_LOCATION"),
+    bq_source_uri: str = "bigquery-public-data.chicago_taxi_trips.taxi_trips",
+    model_name: str = "xgb_regressor",
+    dataset: str = "turbo_templates",
+    timestamp: str = "2022-12-01 00:00:00",
+    machine_type: str = "n1-standard-4",
+    min_replicas: int = 3,
+    max_replicas: int = 10,
+):
+    """
+    Prediction pipeline which:
+     1. Looks up the default model version (champion).
+     2. Runs a batch prediction job with BigQuery as input and output
+     3. Optionally monitors training-serving skew
+
+    Args:
+        project (str): project id of the Google Cloud project
+        location (str): location of the Google Cloud project
+        bq_location (str): location of dataset in BigQuery
+        bq_source_uri (str): `<project>.<dataset>.<table>` of ingestion data in BigQuery
+        model_name (str): name of model
+        dataset (str): dataset id to store staging data & predictions in BigQuery
+        timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
+            (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
+            If any time part is missing, it will be regarded as zero
+        machine_type (str): Machine type to be used for Vertex Batch
+            Prediction. Example machine_types - n1-standard-4, n1-standard-16 etc.
+        min_replicas (int): Minimum no of machines to distribute the
+            Vertex Batch Prediction job for horizontal scalability
+        max_replicas (int): Maximum no of machines to distribute the
+            Vertex Batch Prediction job for horizontal scalability
+    """
+
+    queries_folder = pathlib.Path(__file__).parent / "queries"
+    table = f"prep_prediction_{RESOURCE_SUFFIX}"
+
+    prep_query = generate_query(
+        queries_folder / "preprocessing.sql",
+        source=bq_source_uri,
+        location=bq_location,
+        dataset=f"{project}.{dataset}",
+        table=table,
+        start_timestamp=timestamp,
+    )
+
+    prep_op = BigqueryQueryJobOp(
+        project=project,
+        location=bq_location,
+        query=prep_query,
+    ).set_display_name("Ingest & preprocess data")
+
+    lookup_op = lookup_model(
+        model_name=model_name,
+        location=location,
+        project=project,
+        fail_on_model_not_found=True,
+    ).set_display_name("Look up champion model")
+
+    (
+        model_batch_predict(
+            model=lookup_op.outputs["model"],
+            job_display_name="turbo-template-predict-job",
+            location=location,
+            project=project,
+            source_uri=f"bq://{project}.{dataset}.{table}",
+            destination_uri=f"bq://{project}.{dataset}",
+            source_format="bigquery",
+            destination_format="bigquery",
+            instance_config={
+                "instanceType": "object",
+            },
+            machine_type=machine_type,
+            starting_replica_count=min_replicas,
+            max_replica_count=max_replicas,
+            monitoring_training_dataset=lookup_op.outputs["training_dataset"],
+            monitoring_alert_email_addresses=ALERT_EMAILS,
+            monitoring_skew_config=SKEW_THRESHOLDS,
+        )
+        .after(prep_op)
+        .set_display_name("Run prediction job")
+    )
diff --git a/pipelines/src/pipelines/prediction/pipeline.py b/pipelines/src/pipelines/prediction/pipeline.py
deleted file mode 100644
index dd63d727..00000000
--- a/pipelines/src/pipelines/prediction/pipeline.py
+++ /dev/null
@@ -1,153 +0,0 @@
-# Copyright 2023 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import pathlib
-
-from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp import dsl
-
-from pipelines import generate_query
-from components import lookup_model, model_batch_predict
-
-
-@dsl.pipeline(name="xgboost-prediction-pipeline")
-def pipeline(
-    project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
-    project_location: str = os.environ.get("VERTEX_LOCATION"),
-    ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
-    model_name: str = "simple_xgboost",
-    preprocessing_dataset_id: str = "preprocessing",
-    dataset_location: str = os.environ.get("VERTEX_LOCATION"),
-    ingestion_dataset_id: str = "chicago_taxi_trips",
-    prediction_dataset_id: str = "prediction",
-    timestamp: str = "2022-12-01 00:00:00",
-    batch_prediction_machine_type: str = "n1-standard-4",
-    batch_prediction_min_replicas: int = 3,
-    batch_prediction_max_replicas: int = 10,
-    resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
-):
-    """
-    XGB prediction pipeline which:
-     1. Looks up the default model version (champion) and
-        dataset which was used to the train model.
-     2. Runs a BatchPredictionJob with optional training-serving skew detection.
-
-    Args:
-        project_id (str): project id of the Google Cloud project
-        project_location (str): location of the Google Cloud project
-        ingestion_project_id (str): project id containing the source bigquery data
-            for ingestion. This can be the same as `project_id` if the source data is
-            in the same project where the ML pipeline is executed.
-        model_name (str): name of model
-        preprocessing_dataset_id (str): id of BQ dataset used to
-            store all staging data .
-        prediction_dataset_id (str): id of BQ dataset used to
-            store all predictions.
-        dataset_location (str): location of dataset
-        ingestion_dataset_id (str): dataset id of ingestion data
-        timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
-            (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
-            If any time part is missing, it will be regarded as zero.
-        batch_prediction_machine_type (str): Machine type to be used for Vertex Batch
-            Prediction. Example machine_types - n1-standard-4, n1-standard-16 etc.
-        batch_prediction_min_replicas (int): Minimum no of machines to distribute the
-            Vertex Batch Prediction job for horizontal scalability
-        batch_prediction_max_replicas (int): Maximum no of machines to distribute the
-            Vertex Batch Prediction job for horizontal scalability.
-        resource_suffix (str): Optional. Additional suffix to append GCS resources
-            that get overwritten.
-
-    Returns:
-        None
-
-    """
-
-    # Create variables to ensure the same arguments are passed
-    # into different components of the pipeline
-    time_column = "trip_start_timestamp"
-    ingestion_table = "taxi_trips"
-    table_suffix = "_xgb_prediction_" + str(resource_suffix)  # suffix to table names
-    ingested_table = "ingested_data_" + table_suffix
-    monitoring_alert_email_addresses = []
-    monitoring_skew_config = {"defaultSkewThreshold": {"value": 0.001}}
-
-    # generate sql queries which are used in ingestion and preprocessing
-    # operations
-    queries_folder = pathlib.Path(__file__).parent / "queries"
-
-    preprocessing_query = generate_query(
-        queries_folder / "preprocessing.sql",
-        source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
-        source_table=ingestion_table,
-        prediction_dataset=f"{ingestion_project_id}.{prediction_dataset_id}",
-        preprocessing_dataset=f"{ingestion_project_id}.{preprocessing_dataset_id}",
-        ingested_table=ingested_table,
-        dataset_region=project_location,
-        filter_column=time_column,
-        filter_start_value=timestamp,
-    )
-
-    preprocessing = (
-        BigqueryQueryJobOp(
-            project=project_id,
-            location=dataset_location,
-            query=preprocessing_query,
-        )
-        .set_caching_options(False)
-        .set_display_name("Ingest data")
-    )
-
-    # lookup champion model
-    champion_model = (
-        lookup_model(
-            model_name=model_name,
-            project_location=project_location,
-            project_id=project_id,
-            fail_on_model_not_found=True,
-        )
-        .set_display_name("Look up champion model")
-        .set_caching_options(False)
-    )
-
-    # batch predict from BigQuery to BigQuery
-    bigquery_source_input_uri = (
-        f"bq://{project_id}.{preprocessing_dataset_id}.{ingested_table}"
-    )
-    bigquery_destination_output_uri = f"bq://{project_id}.{prediction_dataset_id}"
-
-    batch_prediction = (
-        model_batch_predict(
-            model=champion_model.outputs["model"],
-            job_display_name="my-xgboost-batch-prediction-job",
-            project_location=project_location,
-            project_id=project_id,
-            source_uri=bigquery_source_input_uri,
-            destination_uri=bigquery_destination_output_uri,
-            source_format="bigquery",
-            destination_format="bigquery",
-            instance_config={
-                "instanceType": "object",
-            },
-            machine_type=batch_prediction_machine_type,
-            starting_replica_count=batch_prediction_min_replicas,
-            max_replica_count=batch_prediction_max_replicas,
-            monitoring_training_dataset=champion_model.outputs["training_dataset"],
-            monitoring_alert_email_addresses=monitoring_alert_email_addresses,
-            monitoring_skew_config=monitoring_skew_config,
-        )
-        .set_caching_options(False)
-        .after(preprocessing)
-        .set_display_name("Batch prediction job")
-    )
diff --git a/pipelines/src/pipelines/prediction/queries/preprocessing.sql b/pipelines/src/pipelines/prediction/queries/preprocessing.sql
deleted file mode 100644
index 294223a4..00000000
--- a/pipelines/src/pipelines/prediction/queries/preprocessing.sql
+++ /dev/null
@@ -1,69 +0,0 @@
--- Copyright 2022 Google LLC
-
--- Licensed under the Apache License, Version 2.0 (the 'License');
--- you may not use this file except in compliance with the License.
--- You may obtain a copy of the License at
-
---     https://www.apache.org/licenses/LICENSE-2.0
-
--- Unless required by applicable law or agreed to in writing, software
--- distributed under the License is distributed on an 'AS IS' BASIS,
--- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
--- See the License for the specific language governing permissions and
--- limitations under the License.
-
--- Treat 'filter_start_value' as the current time, unless it is empty then use CURRENT_DATETIME() instead
--- This allows us to set the filter_start_value to a specific time for testing or for backfill
-
--- If prediction dataset don't exist, create it
-CREATE SCHEMA IF NOT EXISTS `{{ prediction_dataset }}`
-  OPTIONS (
-    description = 'Prediction Dataset',
-    location = '{{ dataset_region }}');
-
--- We recreate the ingestion table every time the pipeline run,
--- so we need to drop the generated in the  previous run
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
-with filter_start_values as (
-    SELECT 
-    IF('{{ filter_start_value }}' = '', CURRENT_DATETIME(), CAST('{{ filter_start_value }}' AS DATETIME)) as filter_start_value
-)
--- Ingest data between 2 and 3 months ago
-,filtered_data as (
-    SELECT
-    *
-    FROM `{{ source_dataset }}.{{ source_table }}`, filter_start_values
-    WHERE
-         DATE({{ filter_column }}) BETWEEN
-         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value as DATETIME)), INTERVAL 3 MONTH) AND
-         DATE_SUB(DATE(filter_start_value), INTERVAL 2 MONTH)
-)
--- Use the average trip_seconds as a replacement for NULL or 0 values
-,mean_time as (
-    SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
-    FROM filtered_data
-)
-
-SELECT
-    CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
-    CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
-    ST_DISTANCE(
-        ST_GEOGPOINT(pickup_longitude, pickup_latitude),
-        ST_GEOGPOINT(dropoff_longitude, dropoff_latitude)) AS trip_distance,
-    trip_miles,
-    CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
-               WHEN trip_seconds <= 0 then m.avg_trip_seconds
-               ELSE trip_seconds 
-               END AS FLOAT64) AS trip_seconds,
-    payment_type,
-    company,
-FROM filtered_data as t, mean_time as m
-WHERE
-    trip_miles > 0 AND fare > 0 AND fare < 1500
-    {% for field in ['fare', 'trip_start_timestamp', 'pickup_longitude',
-                'pickup_latitude', 'dropoff_longitude', 'dropoff_latitude','payment_type','company'] %}
-        AND `{{ field }}` IS NOT NULL
-    {% endfor %}
-    );
diff --git a/pipelines/src/pipelines/queries/preprocessing.sql b/pipelines/src/pipelines/queries/preprocessing.sql
new file mode 100644
index 00000000..0cd8f953
--- /dev/null
+++ b/pipelines/src/pipelines/queries/preprocessing.sql
@@ -0,0 +1,56 @@
+-- Create dataset if it doesn't exist
+CREATE SCHEMA IF NOT EXISTS `{{ dataset }}`
+  OPTIONS (
+    description = 'Chicago Taxi Trips with Turbo Template',
+    location = '{{ location }}');
+
+-- Create (or replace) table with preprocessed data
+DROP TABLE IF EXISTS `{{ dataset }}.{{ table }}`;
+CREATE TABLE `{{ dataset }}.{{ table }}` AS (
+WITH start_timestamps AS (
+SELECT
+	IF('{{ start_timestamp }}' = '',
+	CURRENT_DATETIME(),
+	CAST('{{ start_timestamp }}' AS DATETIME)) AS start_timestamp
+)
+-- Ingest data between 2 and 3 months ago
+,filtered_data AS (
+    SELECT
+    *
+    FROM `{{ source }}`, start_timestamps
+    WHERE
+         DATE(trip_start_timestamp) BETWEEN
+         DATE_SUB(DATE(CAST(start_timestamps.start_timestamp AS DATETIME)), INTERVAL 3 MONTH) AND
+         DATE_SUB(DATE(start_timestamp), INTERVAL 2 MONTH)
+)
+-- Use the average trip_seconds as a replacement for NULL or 0 values
+,mean_time AS (
+    SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
+    FROM filtered_data
+)
+
+SELECT
+    CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
+    CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
+    ST_DISTANCE(
+        ST_GEOGPOINT(pickup_longitude, pickup_latitude),
+        ST_GEOGPOINT(dropoff_longitude, dropoff_latitude)) AS trip_distance,
+    trip_miles,
+    CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
+               WHEN trip_seconds <= 0 then m.avg_trip_seconds
+               ELSE trip_seconds
+               END AS FLOAT64) AS trip_seconds,
+    payment_type,
+    company,
+    {% if label %}
+    (fare + tips + tolls + extras) AS `{{ label }}`,
+    {% endif %}
+FROM filtered_data AS t, mean_time AS m
+WHERE
+    trip_miles > 0 AND fare > 0 AND fare < 1500
+    {% for field in [
+        'fare', 'trip_start_timestamp', 'pickup_longitude', 'pickup_latitude',
+        'dropoff_longitude', 'dropoff_latitude','payment_type','company' ] %}
+        AND `{{ field }}` IS NOT NULL
+    {% endfor %}
+);
diff --git a/pipelines/src/pipelines/training.py b/pipelines/src/pipelines/training.py
new file mode 100644
index 00000000..1b621e84
--- /dev/null
+++ b/pipelines/src/pipelines/training.py
@@ -0,0 +1,160 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import pathlib
+from os import environ as env
+
+from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
+from kfp import dsl
+from kfp.dsl import Dataset, Input, Metrics, Model, Output
+
+from pipelines.utils.query import generate_query
+from components import extract_table, upload_model
+
+
+LABEL = "total_fare"
+PRIMARY_METRIC = "rootMeanSquaredError"
+HPARAMS = dict(
+    n_estimators=200,
+    early_stopping_rounds=10,
+    objective="reg:squarederror",
+    booster="gbtree",
+    learning_rate=0.3,
+    min_split_loss=0,
+    max_depth=6,
+    label=LABEL,
+)
+RESOURCE_SUFFIX = env.get("RESOURCE_SUFFIX", "default")
+TRAINING_IMAGE = f"{env['CONTAINER_IMAGE_REGISTRY']}/training:{RESOURCE_SUFFIX}"
+SERVING_IMAGE = f"{env['CONTAINER_IMAGE_REGISTRY']}/serving:{RESOURCE_SUFFIX}"
+
+
+@dsl.container_component
+def train(
+    input_data: Input[Dataset],
+    input_test_path: str,
+    hparams: dict,
+    train_data: Output[Dataset],
+    valid_data: Output[Dataset],
+    test_data: Output[Dataset],
+    model: Output[Model],
+    metrics: Output[Metrics],
+):
+    return dsl.ContainerSpec(
+        image=TRAINING_IMAGE,
+        command=["python"],
+        args=[
+            "-m" "training",
+            "--input_path",
+            input_data.path,
+            dsl.IfPresentPlaceholder(
+                input_name="input_test_path",
+                then=["--input_test_path", input_test_path],
+            ),
+            "--hparams",
+            hparams,
+            "--output_train_path",
+            train_data.path,
+            "--output_valid_path",
+            valid_data.path,
+            "--output_test_path",
+            test_data.path,
+            "--output_model",
+            model.path,
+            "--output_metrics",
+            metrics.path,
+        ],
+    )
+
+
+@dsl.pipeline(name="turbo-training-pipeline")
+def pipeline(
+    project: str = env.get("VERTEX_PROJECT_ID"),
+    location: str = env.get("VERTEX_LOCATION"),
+    bq_location: str = env.get("BQ_LOCATION"),
+    bq_source_uri: str = "bigquery-public-data.chicago_taxi_trips.taxi_trips",
+    model_name: str = "xgb_regressor",
+    dataset: str = "turbo_templates",
+    timestamp: str = "2022-12-01 00:00:00",
+    test_data_gcs_uri: str = "",
+):
+    """
+    Training pipeline which:
+     1. Preprocesses data in BigQuery
+     2. Extracts data to Cloud Storage
+     3. Trains a model using a custom prebuilt container
+     4. Uploads the model to Model Registry
+     5. Evaluates the model against a champion model
+     6. Selects a new champion based on the primary metrics
+
+    Args:
+        project (str): project id of the Google Cloud project
+        location (str): location of the Google Cloud project
+        bq_location (str): location of dataset in BigQuery
+        bq_source_uri (str): `<project>.<dataset>.<table>` of ingestion data in BigQuery
+        model_name (str): name of model
+        dataset (str): dataset id to store staging data & predictions in BigQuery
+        timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
+            (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
+            If any time part is missing, it will be regarded as zero.
+        test_data_gcs_uri (str): Optional. GCS URI of static held-out test dataset.
+    """
+
+    table = f"prep_training_{RESOURCE_SUFFIX}"
+    queries_folder = pathlib.Path(__file__).parent / "queries"
+
+    prep_query = generate_query(
+        queries_folder / "preprocessing.sql",
+        source=bq_source_uri,
+        location=bq_location,
+        dataset=f"{project}.{dataset}",
+        table=table,
+        label=LABEL,
+        start_timestamp=timestamp,
+    )
+
+    prep_op = BigqueryQueryJobOp(
+        project=project,
+        location=bq_location,
+        query=prep_query,
+    ).set_display_name("Ingest & preprocess data")
+
+    data_op = (
+        extract_table(
+            project=project,
+            location=bq_location,
+            table=f"{project}:{dataset}.{table}",
+        )
+        .after(prep_op)
+        .set_display_name("Extract data")
+    )
+
+    train_op = train(
+        input_data=data_op.outputs["data"],
+        input_test_path=test_data_gcs_uri,
+        hparams=HPARAMS,
+    ).set_display_name("Train model")
+
+    upload_model(
+        project=project,
+        location=location,
+        model=train_op.outputs["model"],
+        model_evaluation=train_op.outputs["metrics"],
+        test_data=train_op.outputs["test_data"],
+        eval_metric=PRIMARY_METRIC,
+        eval_lower_is_better=True,
+        serving_container_image=SERVING_IMAGE,
+        model_name=model_name,
+        model_description="Predict price of a taxi trip.",
+        pipeline_job_id="{{$.pipeline_job_name}}",
+    ).set_display_name("Upload model")
diff --git a/pipelines/src/pipelines/training/pipeline.py b/pipelines/src/pipelines/training/pipeline.py
deleted file mode 100644
index dd73e910..00000000
--- a/pipelines/src/pipelines/training/pipeline.py
+++ /dev/null
@@ -1,212 +0,0 @@
-# Copyright 2023 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import os
-import pathlib
-
-from google_cloud_pipeline_components.v1.bigquery import BigqueryQueryJobOp
-from kfp import dsl
-from kfp.dsl import Dataset, Input, Metrics, Model, Output, OutputPath
-from pipelines import generate_query
-from components import extract_table, upload_model
-
-CONTAINER_IMAGE_REGISTRY = os.environ["CONTAINER_IMAGE_REGISTRY"]
-RESOURCE_SUFFIX = os.environ.get("RESOURCE_SUFFIX", "default")
-TRAINING_IMAGE = f"{CONTAINER_IMAGE_REGISTRY}/training:{RESOURCE_SUFFIX}"
-SERVING_IMAGE = f"{CONTAINER_IMAGE_REGISTRY}/serving:{RESOURCE_SUFFIX}"
-
-
-@dsl.container_component
-def train(
-    train_data: Input[Dataset],
-    valid_data: Input[Dataset],
-    test_data: Input[Dataset],
-    model: Output[Model],
-    model_output_uri: OutputPath(str),
-    metrics: Output[Metrics],
-    hparams: dict,
-):
-    return dsl.ContainerSpec(
-        image=TRAINING_IMAGE,
-        command=["python"],
-        args=[
-            "training/train.py",
-            "--train-data",
-            train_data.path,
-            "--valid-data",
-            valid_data.path,
-            "--test-data",
-            test_data.path,
-            "--model",
-            model.path,
-            "--model-output-uri",
-            model_output_uri,
-            "--metrics",
-            metrics.path,
-            "--hparams",
-            hparams,
-        ],
-    )
-
-
-@dsl.pipeline(name="xgboost-train-pipeline")
-def pipeline(
-    project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
-    project_location: str = os.environ.get("VERTEX_LOCATION"),
-    ingestion_project_id: str = os.environ.get("VERTEX_PROJECT_ID"),
-    model_name: str = "simple_xgboost",
-    dataset_id: str = "preprocessing",
-    dataset_location: str = os.environ.get("VERTEX_LOCATION"),
-    ingestion_dataset_id: str = "chicago_taxi_trips",
-    timestamp: str = "2022-12-01 00:00:00",
-    resource_suffix: str = os.environ.get("RESOURCE_SUFFIX"),
-    test_dataset_uri: str = "",
-):
-    """
-    XGB training pipeline which:
-     1. Splits and extracts a dataset from BQ to GCS
-     2. Trains a model via Vertex AI CustomTrainingJob
-     3. Evaluates the model against the current champion model
-     4. If better the model becomes the new default model
-
-    Args:
-        project_id (str): project id of the Google Cloud project
-        project_location (str): location of the Google Cloud project
-        ingestion_project_id (str): project id containing the source bigquery data
-            for ingestion. This can be the same as `project_id` if the source data is
-            in the same project where the ML pipeline is executed.
-        model_name (str): name of model
-        dataset_id (str): id of BQ dataset used to store all staging data & predictions
-        dataset_location (str): location of dataset
-        ingestion_dataset_id (str): dataset id of ingestion data
-        timestamp (str): Optional. Empty or a specific timestamp in ISO 8601 format
-            (YYYY-MM-DDThh:mm:ss.sss±hh:mm or YYYY-MM-DDThh:mm:ss).
-            If any time part is missing, it will be regarded as zero.
-        resource_suffix (str): Optional. Additional suffix to append GCS resources
-            that get overwritten.
-        test_dataset_uri (str): Optional. GCS URI of statis held-out test dataset.
-    """
-
-    # Create variables to ensure the same arguments are passed
-    # into different components of the pipeline
-    label_column_name = "total_fare"
-    time_column = "trip_start_timestamp"
-    ingestion_table = "taxi_trips"
-    table_suffix = f"_xgb_training_{resource_suffix}"  # suffix to table names
-    ingested_table = "ingested_data" + table_suffix
-    preprocessed_table = "preprocessed_data" + table_suffix
-    train_table = "train_data" + table_suffix
-    valid_table = "valid_data" + table_suffix
-    test_table = "test_data" + table_suffix
-    primary_metric = "rootMeanSquaredError"
-    hparams = dict(
-        n_estimators=200,
-        early_stopping_rounds=10,
-        objective="reg:squarederror",
-        booster="gbtree",
-        learning_rate=0.3,
-        min_split_loss=0,
-        max_depth=6,
-        label=label_column_name,
-    )
-
-    # generate sql queries which are used in ingestion and preprocessing
-    # operations
-
-    queries_folder = pathlib.Path(__file__).parent / "queries"
-
-    preprocessing_query = generate_query(
-        queries_folder / "preprocessing.sql",
-        source_dataset=f"{ingestion_project_id}.{ingestion_dataset_id}",
-        source_table=ingestion_table,
-        preprocessing_dataset=f"{ingestion_project_id}.{dataset_id}",
-        ingested_table=ingested_table,
-        dataset_region=project_location,
-        filter_column=time_column,
-        target_column=label_column_name,
-        filter_start_value=timestamp,
-        train_table=train_table,
-        validation_table=valid_table,
-        test_table=test_table,
-    )
-
-    preprocessing = (
-        BigqueryQueryJobOp(
-            project=project_id,
-            location=dataset_location,
-            query=preprocessing_query,
-        )
-        .set_caching_options(False)
-        .set_display_name("Ingest & preprocess data")
-    )
-
-    # data extraction to gcs
-
-    train_dataset = (
-        extract_table(
-            bq_client_project_id=project_id,
-            source_project_id=project_id,
-            dataset_id=dataset_id,
-            table_name=train_table,
-            dataset_location=dataset_location,
-        )
-        .after(preprocessing)
-        .set_display_name("Extract train data")
-        .set_caching_options(False)
-    ).outputs["dataset"]
-    valid_dataset = (
-        extract_table(
-            bq_client_project_id=project_id,
-            source_project_id=project_id,
-            dataset_id=dataset_id,
-            table_name=valid_table,
-            dataset_location=dataset_location,
-        )
-        .after(preprocessing)
-        .set_display_name("Extract validation data")
-        .set_caching_options(False)
-    ).outputs["dataset"]
-    test_dataset = (
-        extract_table(
-            bq_client_project_id=project_id,
-            source_project_id=project_id,
-            dataset_id=dataset_id,
-            table_name=test_table,
-            dataset_location=dataset_location,
-            destination_gcs_uri=test_dataset_uri,
-        )
-        .after(preprocessing)
-        .set_display_name("Extract test data")
-        .set_caching_options(False)
-    ).outputs["dataset"]
-
-    train_model = train(
-        train_data=train_dataset,
-        valid_data=valid_dataset,
-        test_data=test_dataset,
-        hparams=hparams,
-    ).set_display_name("Train model")
-
-    upload_model_op = upload_model(
-        project_id=project_id,
-        project_location=project_location,
-        model=train_model.outputs["model"],
-        model_evaluation=train_model.outputs["metrics"],
-        test_dataset=test_dataset,
-        eval_metric=primary_metric,
-        eval_lower_is_better=True,
-        serving_container_image=SERVING_IMAGE,
-        model_name=model_name,
-        pipeline_job_id="{{$.pipeline_job_name}}",
-    ).set_display_name("Upload model")
diff --git a/pipelines/src/pipelines/training/queries/preprocessing.sql b/pipelines/src/pipelines/training/queries/preprocessing.sql
deleted file mode 100644
index a7291038..00000000
--- a/pipelines/src/pipelines/training/queries/preprocessing.sql
+++ /dev/null
@@ -1,88 +0,0 @@
--- If preprocessing dataset don't exist, create it
-CREATE SCHEMA IF NOT EXISTS `{{ preprocessing_dataset }}`
-  OPTIONS (
-    description = 'Preprocessing Dataset',
-    location = '{{ dataset_region }}');
-
--- We recreate the ingestion table every time the pipeline run,
--- so we need to drop the generated in the  previous run
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ ingested_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ ingested_table }}` AS (
-WITH filter_start_values AS (
-SELECT
-	IF('{{ filter_start_value }}' = '',
-	CURRENT_DATETIME(),
-	CAST('{{ filter_start_value }}' AS DATETIME)) AS filter_start_value
-)
--- Ingest data between 2 and 3 months ago
-,filtered_data AS (
-    SELECT
-    *
-    FROM `{{ source_dataset }}.{{ source_table }}`, filter_start_values
-    WHERE
-         DATE({{ filter_column }}) BETWEEN
-         DATE_SUB(DATE(CAST(filter_start_values.filter_start_value AS DATETIME)), INTERVAL 3 MONTH) AND
-         DATE_SUB(DATE(filter_start_value), INTERVAL 2 MONTH)
-)
--- Use the average trip_seconds as a replacement for NULL or 0 values
-,mean_time AS (
-    SELECT CAST(avg(trip_seconds) AS INT64) as avg_trip_seconds
-    FROM filtered_data
-)
-SELECT
-    CAST(EXTRACT(DAYOFWEEK FROM trip_start_timestamp) AS FLOAT64) AS dayofweek,
-    CAST(EXTRACT(HOUR FROM trip_start_timestamp) AS FLOAT64) AS hourofday,
-    ST_DISTANCE(
-        ST_GEOGPOINT(pickup_longitude, pickup_latitude),
-        ST_GEOGPOINT(dropoff_longitude, dropoff_latitude)) AS trip_distance,
-    trip_miles,
-    CAST( CASE WHEN trip_seconds is NULL then m.avg_trip_seconds
-               WHEN trip_seconds <= 0 then m.avg_trip_seconds
-               ELSE trip_seconds 
-               END AS FLOAT64) AS trip_seconds,
-    payment_type,
-    company,
-    (fare + tips + tolls + extras) AS `{{ target_column }}`,
-FROM filtered_data AS t, mean_time AS m
-WHERE
-    trip_miles > 0 AND fare > 0 AND fare < 1500
-    {% for field in ['fare', 'trip_start_timestamp', 'pickup_longitude',
-                'pickup_latitude', 'dropoff_longitude', 'dropoff_latitude','payment_type','company'] %}
-        AND `{{ field }}` IS NOT NULL
-    {% endfor %}
-);
-
--- Drop and creation of train, testing and validations tables
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ train_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ train_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	10) IN (0, 1, 2, 3, 4, 5, 6, 7));
-
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ validation_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ validation_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	10) IN (8));
-
-DROP TABLE IF EXISTS `{{ preprocessing_dataset }}.{{ test_table }}`;
-
-CREATE TABLE `{{ preprocessing_dataset }}.{{ test_table }}` AS (
-SELECT
-	*
-FROM
-	`{{ preprocessing_dataset }}.{{ ingested_table }}` AS t
-WHERE
-	MOD(ABS(FARM_FINGERPRINT(TO_JSON_STRING(t))),
-	10) IN (9));
diff --git a/pipelines/src/pipelines/utils/query.py b/pipelines/src/pipelines/utils/query.py
new file mode 100644
index 00000000..c25ddb39
--- /dev/null
+++ b/pipelines/src/pipelines/utils/query.py
@@ -0,0 +1,32 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from pathlib import Path
+from jinja2 import Template
+
+
+def generate_query(input_file: Path, **replacements) -> str:
+    """
+    Read input file and replace placeholder using Jinja.
+
+    Args:
+        input_file (Path): input file to read
+        replacements: keyword arguments to use to replace placeholders
+    Returns:
+        str: replaced content of input file
+    """
+
+    with open(input_file, "r") as f:
+        query_template = f.read()
+
+    return Template(query_template).render(**replacements)
diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index 6d217020..bf49b6e3 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -49,8 +49,8 @@ def trigger_pipeline(
         enable_caching = enable_caching.lower() in true_
 
     # For below options, we want an empty string to become None, so we add "or None"
-    encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER") or None
-    network = os.environ.get("VERTEX_NETWORK") or None
+    encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER")
+    network = os.environ.get("VERTEX_NETWORK")
 
     # Instantiate PipelineJob object
     pl = aiplatform.PipelineJob(

From 56d56e1345c4c6afc9e30e72d5d685f50863d700 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Mon, 13 Nov 2023 19:28:37 +0100
Subject: [PATCH 227/238] Fix unit tests

---
 components/tests/test_lookup_model.py        | 16 +++++-------
 components/tests/test_model_batch_predict.py | 10 +++++---
 components/tests/test_upload_model.py        | 27 +++++++++++++-------
 pipelines/src/pipelines/prediction.py        |  6 ++---
 4 files changed, 33 insertions(+), 26 deletions(-)

diff --git a/components/tests/test_lookup_model.py b/components/tests/test_lookup_model.py
index a7868b66..56c6e27e 100644
--- a/components/tests/test_lookup_model.py
+++ b/components/tests/test_lookup_model.py
@@ -37,9 +37,8 @@ def test_lookup_model(mock_model, tmpdir):
     # Invoke the model look up
     found_model_resource_name, _ = lookup_model(
         model_name="my-model",
-        project_location="europe-west4",
-        project_id="my-project-id",
-        order_models_by="create_time desc",
+        location="europe-west4",
+        project="my-project-id",
         fail_on_model_not_found=False,
         model=Model(uri=mock_path),
     )
@@ -49,7 +48,6 @@ def test_lookup_model(mock_model, tmpdir):
     # Check the list method was called once with the correct arguments
     mock_model.list.assert_called_once_with(
         filter='display_name="my-model"',
-        order_by="create_time desc",
         location="europe-west4",
         project="my-project-id",
     )
@@ -64,9 +62,8 @@ def test_lookup_model_when_no_models(mock_model, tmpdir):
     mock_model.list.return_value = []
     exported_model_resource_name, _ = lookup_model(
         model_name="my-model",
-        project_location="europe-west4",
-        project_id="my-project-id",
-        order_models_by="create_time desc",
+        location="europe-west4",
+        project="my-project-id",
         fail_on_model_not_found=False,
         model=Model(uri=str(tmpdir)),
     )
@@ -87,9 +84,8 @@ def test_lookup_model_when_no_models_fail(mock_model, tmpdir):
     with pytest.raises(RuntimeError):
         lookup_model(
             model_name="my-model",
-            project_location="europe-west4",
-            project_id="my-project-id",
-            order_models_by="create_time desc",
+            location="europe-west4",
+            project="my-project-id",
             fail_on_model_not_found=True,
             model=Model(uri=str(tmpdir)),
         )
diff --git a/components/tests/test_model_batch_predict.py b/components/tests/test_model_batch_predict.py
index ad4c427a..6e0eb951 100644
--- a/components/tests/test_model_batch_predict.py
+++ b/components/tests/test_model_batch_predict.py
@@ -71,12 +71,13 @@ def test_model_batch_predict(
     Asserts model_batch_predict successfully creates requests given different arguments.
     """
     mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
+    gcp_resources_path = tmpdir / "gcp_resources.json"
 
-    (gcp_resources,) = model_batch_predict(
+    model_batch_predict(
         model=mock_model,
         job_display_name="",
-        project_location="",
-        project_id="",
+        location="",
+        project="",
         source_uri=source_uri,
         destination_uri=destination_format,
         source_format=source_format,
@@ -84,8 +85,9 @@ def test_model_batch_predict(
         monitoring_training_dataset=monitoring_training_dataset,
         monitoring_alert_email_addresses=monitoring_alert_email_addresses,
         monitoring_skew_config=monitoring_skew_config,
+        gcp_resources=str(gcp_resources_path)
     )
 
     create_job.assert_called_once()
     get_job.assert_called_once()
-    assert json.loads(gcp_resources)["resources"][0]["resourceUri"] == mock_job1.name
+    assert gcp_resources_path.exists()
diff --git a/components/tests/test_upload_model.py b/components/tests/test_upload_model.py
index cb35b4e8..d4b96e4c 100644
--- a/components/tests/test_upload_model.py
+++ b/components/tests/test_upload_model.py
@@ -48,6 +48,7 @@ def test_model_upload_no_champion(
     model = Model(uri="dummy-model-uri")
     serving_container_image = "dummy_image:latest"
     model_name = "dummy-model-name"
+    model_description = "dummy model_description"
     vertex_model = VertexModel.create(
         name=model_name, uri="chall_uri", model_resource_name="chall_resource_name"
     )
@@ -64,16 +65,17 @@ def test_model_upload_no_champion(
 
     upload_model(
         model=model,
+        model_description=model_description,
         serving_container_image=serving_container_image,
         vertex_model=vertex_model,
-        project_id=project,
-        project_location=location,
+        project=project,
+        location=location,
         model_evaluation=model_evaluation,
         eval_metric=eval_metric,
         eval_lower_is_better=eval_lower_is_better,
         model_name=model_name,
         pipeline_job_id=pipeline_job_id,
-        test_dataset=test_dataset,
+        test_data=test_dataset,
         evaluation_name=evaluation_name,
     )
 
@@ -91,6 +93,7 @@ def test_model_upload_no_champion(
     # Check model upload call
     mock_model_class.upload.assert_called_once_with(
         display_name=model_name,
+        description=model_description,
         artifact_uri="dummy-model-uri",
         serving_container_image_uri=serving_container_image,
         serving_container_predict_route="/predict",
@@ -158,6 +161,7 @@ def test_model_upload_challenger_wins(
     model = Model(uri="dummy-model-uri")
     serving_container_image = "dummy_image:latest"
     model_name = "dummy-model-name"
+    model_description = "dummy model_description"
     vertex_model = VertexModel.create(
         name=model_name, uri="chall_uri", model_resource_name="chall_resource_name"
     )
@@ -174,16 +178,17 @@ def test_model_upload_challenger_wins(
 
     upload_model(
         model=model,
+        model_description=model_description,
         serving_container_image=serving_container_image,
         vertex_model=vertex_model,
-        project_id=project,
-        project_location=location,
+        project=project,
+        location=location,
         model_evaluation=model_evaluation,
         eval_metric=eval_metric,
         eval_lower_is_better=eval_lower_is_better,
         model_name=model_name,
         pipeline_job_id=pipeline_job_id,
-        test_dataset=test_dataset,
+        test_data=test_dataset,
         evaluation_name=evaluation_name,
     )
 
@@ -201,6 +206,7 @@ def test_model_upload_challenger_wins(
     # Check model upload call
     mock_model_class.upload.assert_called_once_with(
         display_name=model_name,
+        description=model_description,
         artifact_uri="dummy-model-uri",
         serving_container_image_uri=serving_container_image,
         serving_container_predict_route="/predict",
@@ -268,6 +274,7 @@ def test_model_upload_champion_wins(
     model = Model(uri="dummy-model-uri")
     serving_container_image = "dummy_image:latest"
     model_name = "dummy-model-name"
+    model_description = "dummy model_description"
     vertex_model = VertexModel.create(
         name=model_name, uri="chall_uri", model_resource_name="chall_resource_name"
     )
@@ -284,16 +291,17 @@ def test_model_upload_champion_wins(
 
     upload_model(
         model=model,
+        model_description=model_description,
         serving_container_image=serving_container_image,
         vertex_model=vertex_model,
-        project_id=project,
-        project_location=location,
+        project=project,
+        location=location,
         model_evaluation=model_evaluation,
         eval_metric=eval_metric,
         eval_lower_is_better=eval_lower_is_better,
         model_name=model_name,
         pipeline_job_id=pipeline_job_id,
-        test_dataset=test_dataset,
+        test_data=test_dataset,
         evaluation_name=evaluation_name,
     )
 
@@ -311,6 +319,7 @@ def test_model_upload_champion_wins(
     # Check model upload call
     mock_model_class.upload.assert_called_once_with(
         display_name=model_name,
+        description=model_description,
         artifact_uri="dummy-model-uri",
         serving_container_image_uri=serving_container_image,
         serving_container_predict_route="/predict",
diff --git a/pipelines/src/pipelines/prediction.py b/pipelines/src/pipelines/prediction.py
index 2b01c124..0a76fe60 100644
--- a/pipelines/src/pipelines/prediction.py
+++ b/pipelines/src/pipelines/prediction.py
@@ -38,9 +38,9 @@ def pipeline(
     model_name: str = "xgb_regressor",
     dataset: str = "turbo_templates",
     timestamp: str = "2022-12-01 00:00:00",
-    machine_type: str = "n1-standard-4",
-    min_replicas: int = 3,
-    max_replicas: int = 10,
+    machine_type: str = "c2-standard-8",
+    min_replicas: int = 1,
+    max_replicas: int = 1,
 ):
     """
     Prediction pipeline which:

From fcec564a075e1e0f0a53781b7d6976d942c63f3f Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Tue, 14 Nov 2023 10:47:30 +0100
Subject: [PATCH 228/238] Update docs and add new make commands

---
 Makefile                                      | 47 +++++++++++--------
 README.md                                     | 21 ++++++---
 docs/CONTRIBUTION.md                          | 25 ----------
 docs/PRODUCTION.md                            | 30 ++----------
 docs/notebooks/02_run_pipelines.ipynb         |  8 ++--
 .../extras/01_hyperparameter_tuning.ipynb     |  2 +-
 pipelines/src/pipelines/prediction.py         |  6 +--
 .../scheduled_jobs.auto.tfvars.example        | 40 ++++++++--------
 8 files changed, 74 insertions(+), 105 deletions(-)

diff --git a/Makefile b/Makefile
index 61a00c68..c99e91c4 100644
--- a/Makefile
+++ b/Makefile
@@ -15,17 +15,12 @@
 -include env.sh
 export
 
-
-help: ## Display this help screen
+help: ## Display this help screen.
 	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
-    
-pre-commit: ## Runs the pre-commit checks over entire repo
-	cd pipelines && \
-	poetry run pre-commit run --all-files
 
 env ?= dev
 AUTO_APPROVE_FLAG :=
-deploy: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
+deploy: ## Deploy infrastructure to your project. Optionally set env=<dev|test|prod> (default = dev).
 	@if [ "$(auto-approve)" = "true" ]; then \
 		AUTO_APPROVE_FLAG="-auto-approve"; \
 	fi; \
@@ -33,7 +28,7 @@ deploy: ## Deploy the Terraform infrastructure to your project. Requires VERTEX_
 	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
 	terraform apply -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}' $$AUTO_APPROVE_FLAG
 
-undeploy: ## DESTROY the Terraform infrastructure in your project. Requires VERTEX_PROJECT_ID and VERTEX_LOCATION env variables to be set in env.sh. Optionally specify env=<dev|test|prod> (default = dev)
+undeploy: ## DESTROY the infrastructure in your project. Optionally set env=<dev|test|prod> (default = dev).
 	@if [ "$(auto-approve)" = "true" ]; then \
 		AUTO_APPROVE_FLAG="-auto-approve"; \
 	fi; \
@@ -41,7 +36,7 @@ undeploy: ## DESTROY the Terraform infrastructure in your project. Requires VERT
 	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
 	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}' $$AUTO_APPROVE_FLAG
 
-install: ## Set up local environment for Python development on pipelines
+install: ## Set up local Python environment for development.
 	@cd pipelines && \
 	poetry install --with dev && \
 	cd ../components && \
@@ -49,26 +44,27 @@ install: ## Set up local environment for Python development on pipelines
 	cd ../model && \
 	poetry install
 
-compile: ## Compile the pipeline to pipeline.yaml. Must specify pipeline=<training|prediction>
+compile: ## Compile pipeline. Must set pipeline=<training|prediction>.
 	@cd pipelines/src && \
+	echo "Compiling $$pipeline pipeline" && \
 	poetry run kfp dsl compile --py pipelines/${pipeline}.py --output pipelines/${pipeline}.yaml --function pipeline
 
-targets ?= training serving
-build: ## Build and push training and/or serving container(s) image using Docker. Specify targets=<training serving> e.g. targets=training or targets="training serving" (default)
+images ?= training serving
+build: ## Build and push container(s). Set images=<training serving> e.g. images=training (default = training serving).
 	@cd model && \
-	for target in $$targets ; do \
-		echo "Building $$target image" && \
+	for image in $$images ; do \
+		echo "Building $$image image" && \
 		gcloud builds submit . \
 		--region=${VERTEX_LOCATION} \
 		--project=${VERTEX_PROJECT_ID} \
 		--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source \
-		--substitutions=_DOCKER_TARGET=$$target,_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/$$target:${RESOURCE_SUFFIX} ; \
+		--substitutions=_DOCKER_TARGET=$$image,_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/$$image:${RESOURCE_SUFFIX} ; \
 	done 
 
 compile ?= true
 build ?= true
 wait ?= false
-run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|prediction>. Optionally specify wait=<true|false> (default = false). Set compile=false to skip recompiling the pipeline and set build=false to skip rebuilding container images
+run: ## Run pipeline. Must set pipeline=<training|prediction>. Optionally set wait=<true|false> (default = false), compile=<true|false> (default = true) to recompile pipeline, build=<true|false> (default = true) to rebuild container image(s), images=<training serving> (default = training serving) to set which images are rebuilt.
 	@if [ $(compile) = "true" ]; then \
 		$(MAKE) compile ; \
 	elif [ $(compile) != "false" ]; then \
@@ -82,12 +78,19 @@ run: ## Run pipeline in sandbox environment. Must specify pipeline=<training|pre
 		exit ; \
 	fi && \
 	cd pipelines/src && \
+	echo "Running $$pipeline pipeline" && \
 	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}.yaml --display_name=${pipeline} --wait=${wait}
 
+training: ## Shortcut to run training pipeline. Rebuilds training and serving images. Supports same options as run.
+	$(MAKE) run pipeline=training images=training prediction
+
+prediction:	## Shortcut to run prediction pipeline. Doesn't rebuilt images. Supports same options as run.
+	$(MAKE) run pipeline=prediction build=false
+
 components ?= true
-test: ## Run unit tests. Specify components=<true|false> to test scripts and optionally components
+test: ## Run unit tests for pipelines. Optionally set components=<true|false> (default = true) to test components package.
 	@if [ $(components) = "true" ]; then \
-		echo "Testing components" && \
+		echo "Running unit tests in components" && \
 		cd components && \
 		poetry run pytest && \
 		cd .. ;  \
@@ -95,6 +98,10 @@ test: ## Run unit tests. Specify components=<true|false> to test scripts and opt
 		echo "ValueError: components must be either true or false" ; \
 		exit ; \
 	fi && \
-	echo "Testing scripts" && \
+	echo "Running unit tests in pipelines" && \
+	cd pipelines && \
+	poetry run python -m pytest
+
+pre-commit: ## Run pre-commit checks for pipelines.
 	cd pipelines && \
-	poetry run python -m pytest tests/utils
+	poetry run pre-commit run --all-files
\ No newline at end of file
diff --git a/README.md b/README.md
index 3ed2c82e..74744856 100644
--- a/README.md
+++ b/README.md
@@ -71,19 +71,19 @@ Before your CI/CD pipelines can deploy the infrastructure, you will need to set
 ```bash
 export DEV_PROJECT_ID=my-dev-gcp-project
 export DEV_LOCATION=europe-west2
-gsutil mb -l DEV_LOCATION -p DEV_PROJECT_ID --pap=enforced gs://DEV_PROJECT_ID-tfstate && \
-  gsutil ubla set on gs://DEV_PROJECT_ID-tfstate
+gsutil mb -l $DEV_LOCATION -p $DEV_PROJECT_ID --pap=enforced gs://$DEV_PROJECT_ID-tfstate && \
+  gsutil ubla set on gs://$DEV_PROJECT_ID-tfstate
 ```
 
 Enable APIs in admin project:
 
 ```bash
 export ADMIN_PROJECT_ID=my-admin-gcp-project
-gcloud services enable cloudresourcemanager.googleapis.com serviceusage.googleapis.com --project=ADMIN_PROJECT_ID
+gcloud services enable cloudresourcemanager.googleapis.com serviceusage.googleapis.com --project=$ADMIN_PROJECT_ID
 ```
 
 ```bash
-make deploy env=dev VERTEX_PROJECT_ID=<DEV PROJECT ID>
+make deploy env=dev
 ```
 
 More details about infrastructure is explained in [this README](docs/INFRASTRUCTURE.md).
@@ -117,10 +117,10 @@ You can modify this to suit your own use case.
 Build the training and serving container images and push them to Artifact Registry with:
 
 ```bash
-make build [ targets=training serving ]
+make build [ images=training serving ]
 ```
 
-Optionally specify the `targets` variable to only build one of the images.
+Optionally specify the `images` variable to only build one of the images.
 
 **Execute pipelines:** Vertex AI Pipelines uses KubeFlow to orchestrate your training steps, as such you'll need to:
 
@@ -136,10 +136,17 @@ make run pipeline=training [ wait=<true|false> ] [ build=<true|false> ] [ compil
 
 The command has the following true/false flags:
 
-- `build` - re-build containers for training & serving code (limit by setting targets=training to build only one of the containers)
+- `build` - re-build containers for training & serving code (limit by setting images=training to build only one of the containers)
 - `compile` - re-compile the pipeline to YAML
 - `wait` - run the pipeline (a-)sync
 
+**Shortcuts:** Use these commands which support the same options as `run` to run the training or prediction pipeline:
+
+```bash
+make training
+make prediction
+```
+
 ## Test
 
 Unit tests are performed using [pytest](https://docs.pytest.org).
diff --git a/docs/CONTRIBUTION.md b/docs/CONTRIBUTION.md
index b1f07e49..6fcc298b 100644
--- a/docs/CONTRIBUTION.md
+++ b/docs/CONTRIBUTION.md
@@ -65,31 +65,6 @@ gcloud artifacts repositories create vertex-images \
     --location=${GCP_REGION}
 ```
 
-### BigQuery 
-
-Create a new BigQuery dataset for the Chicago Taxi data:
-
-```
-bq --location=${GCP_REGION} mk --dataset "${GCP_PROJECT_ID}:chicago_taxi_trips"
-```
-
-Create a new BigQuery dataset for data processing during the pipelines:
-
-```
-bq --location=${GCP_REGION} mk --dataset "${GCP_PROJECT_ID}:preprocessing"
-```
-
-Set up a BigQuery transfer job to mirror the Chicago Taxi dataset to your project
-
-```
-bq mk --transfer_config \
-  --project_id=${GCP_PROJECT_ID} \
-  --data_source="cross_region_copy" \
-  --target_dataset="chicago_taxi_trips" \
-  --display_name="Chicago taxi trip mirror" \
-  --params='{"source_dataset_id":"'"chicago_taxi_trips"'","source_project_id":"'"bigquery-public-data"'"}'
-```
-
 ### Service Accounts
 
 Two service accounts are required
diff --git a/docs/PRODUCTION.md b/docs/PRODUCTION.md
index 4d421335..6b312074 100644
--- a/docs/PRODUCTION.md
+++ b/docs/PRODUCTION.md
@@ -80,44 +80,24 @@ Create a new branch off the main/master branch e.g. `git checkout -b test-env-sc
 ```
 cloud_schedulers_config = {
 
-  xgboost_training = {
-    description  = "Trigger my training pipeline in Vertex"
+  training = {
+    description  = "Trigger training pipeline in Vertex AI"
     schedule     = "0 0 1 * *"
     time_zone    = "UTC"
     template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/v1.2"
     enable_caching = null
     pipeline_parameters = {
-      project_id = <Project ID of test project>
-      project_location = "europe-west2"
-      ingestion_project_id = <Project ID of test project>
-      model_name = "simple_xgboost"
-      model_label = "label_name"
-      dataset_id = "preprocessing"
-      dataset_location = "europe-west2"
-      ingestion_dataset_id = "chicago_taxi_trips"
-      timestamp = "2022-12-01 00:00:00"
     },
   },
 
-  xgboost_prediction = {
-    description  = "Trigger my prediction pipeline in Vertex"
+  prediction = {
+    description  = "Trigger prediction pipeline in Vertex AI"
     schedule     = "0 0 * * *"
     time_zone    = "UTC"
     template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2"
     enable_caching = null
     pipeline_parameters = {
-      project_id = <Project ID of test project>
-      project_location = "europe-west2"
-      ingestion_project_id = <Project ID of test project>
-      model_name = "simple_xgboost"
-      model_label = "label_name"
-      dataset_id = "preprocessing"
-      dataset_location = "europe-west2"
-      ingestion_dataset_id = "chicago_taxi_trips"
-      timestamp = "2022-12-01 00:00:00"
-      batch_prediction_machine_type = "n1-standard-4"
-      batch_prediction_min_replicas = 3
-      batch_prediction_max_replicas = 5
+      // TODO: add all pipeline parameters which are expected by your pipeline
     },
   },
 
diff --git a/docs/notebooks/02_run_pipelines.ipynb b/docs/notebooks/02_run_pipelines.ipynb
index 5cb70550..7937221f 100644
--- a/docs/notebooks/02_run_pipelines.ipynb
+++ b/docs/notebooks/02_run_pipelines.ipynb
@@ -159,7 +159,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "! make run pipeline=training wait=true"
+    "! make training wait=true"
    ]
   },
   {
@@ -193,7 +193,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "! make run pipeline=prediction build=false"
+    "! make prediction build=false"
    ]
   },
   {
@@ -202,9 +202,9 @@
     "tags": []
    },
    "source": [
-    "**Note:** The `make run` command has the following true/false flags:\n",
+    "**Note:** The command has the following true/false flags:\n",
     "\n",
-    "- `build` - re-build containers for training & serving code (limit by setting `targets=training` to build only one of the containers)\n",
+    "- `build` - re-build containers for training & serving code (limit by setting `images=training` to build only one of the containers)\n",
     "- `compile` - re-compile the pipeline to YAML\n",
     "- `wait` - run the pipeline (a-)sync"
    ]
diff --git a/docs/notebooks/extras/01_hyperparameter_tuning.ipynb b/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
index a19170f0..b49bd952 100644
--- a/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
+++ b/docs/notebooks/extras/01_hyperparameter_tuning.ipynb
@@ -400,7 +400,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "! make run pipeline=training build=true targets=training"
+    "! make training"
    ]
   },
   {
diff --git a/pipelines/src/pipelines/prediction.py b/pipelines/src/pipelines/prediction.py
index 0a76fe60..07e39676 100644
--- a/pipelines/src/pipelines/prediction.py
+++ b/pipelines/src/pipelines/prediction.py
@@ -38,9 +38,9 @@ def pipeline(
     model_name: str = "xgb_regressor",
     dataset: str = "turbo_templates",
     timestamp: str = "2022-12-01 00:00:00",
-    machine_type: str = "c2-standard-8",
-    min_replicas: int = 1,
-    max_replicas: int = 1,
+    machine_type: str = "n2-standard-4",
+    min_replicas: int = 3,
+    max_replicas: int = 10,
 ):
     """
     Prediction pipeline which:
diff --git a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
index f864e7e9..77682e81 100644
--- a/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
+++ b/terraform/modules/scheduled_pipelines/scheduled_jobs.auto.tfvars.example
@@ -16,41 +16,41 @@
 
 cloud_schedulers_config = {
 
-  xgboost_training = {
-    description  = "Trigger my training pipeline in Vertex"
+  training = {
+    description  = "Trigger training pipeline in Vertex AI"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
     template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/<Git tag>"
     enable_caching = null
     pipeline_parameters = {
-      project_id = "my-project-id"
-      project_location = "europe-west2"
-      ingestion_project_id = "my-project-id"
-      model_name = "xgboost_with_preprocessing"
-      dataset_id = "preprocessing"
-      dataset_location = "europe-west2"
-      ingestion_dataset_id = "chicago_taxi_trips"
+      project = "my-project-id"
+      location = "europe-west2"
+      bq_location = "US"
+      bq_source_uri = "bigquery-public-data.chicago_taxi_trips.taxi_trips"
+      model_name = "xgb_regressor"
+      dataset = "turbo_templates"
       timestamp = "2022-12-01 00:00:00"
+      test_data_gcs_uri: str = ""
     }
   },
 
-  xgboost_prediction = {
-    description  = "Trigger my prediction pipeline in Vertex"
+  prediction = {
+    description  = "Trigger prediction pipeline in Vertex AI"
     schedule     = "0 0 * * 0"
     time_zone    = "UTC"
     template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/<Git tag>"
     enable_caching = null
     pipeline_parameters = {
-      project_id = "my-project-id"
-      project_location = "europe-west2"
-      ingestion_project_id = "my-project-id"
-      model_name = "xgboost_with_preprocessing"
-      dataset_location = "europe-west2"
-      ingestion_dataset_id = "chicago_taxi_trips"
+      project = "my-project-id"
+      location = "europe-west2"
+      bq_location = "US"
+      bq_source_uri = "bigquery-public-data.chicago_taxi_trips.taxi_trips"
+      model_name = "xgb_regressor"
+      dataset = "turbo_templates"
       timestamp = "2022-12-01 00:00:00"
-      batch_prediction_machine_type = "n1-standard-4"
-      batch_prediction_min_replicas = 3
-      batch_prediction_max_replicas = 5
+      machine_type = "n2-standard-4"
+      min_replicas = 3
+      max_replicas = 10
     }
   }
 }

From 7c932b96edb6345e1111bbb9cd1134aa068abea8 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Wed, 15 Nov 2023 10:36:59 +0100
Subject: [PATCH 229/238] Minor changes

---
 Makefile                                     |  2 +-
 cloudbuild/release.yaml                      |  4 +--
 components/tests/conftest.py                 |  2 +-
 components/tests/test_model_batch_predict.py |  4 +--
 docs/notebooks/02_run_pipelines.ipynb        |  2 +-
 pipelines/tests/__init__.py                  | 13 ---------
 pipelines/tests/conftest.py                  | 29 --------------------
 7 files changed, 6 insertions(+), 50 deletions(-)
 delete mode 100644 pipelines/tests/__init__.py
 delete mode 100644 pipelines/tests/conftest.py

diff --git a/Makefile b/Makefile
index c99e91c4..ff67f45b 100644
--- a/Makefile
+++ b/Makefile
@@ -104,4 +104,4 @@ test: ## Run unit tests for pipelines. Optionally set components=<true|false> (d
 
 pre-commit: ## Run pre-commit checks for pipelines.
 	cd pipelines && \
-	poetry run pre-commit run --all-files
\ No newline at end of file
+	poetry run pre-commit run --all-files
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index 480aeee8..a99c2eba 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -47,12 +47,12 @@ steps:
           cd pipelines && \
           poetry run python -m pipelines.utils.upload_pipeline \
           --dest=https://${_VERTEX_LOCATION}-kfp.pkg.dev/$$proj/vertex-pipelines \
-          --yaml=src/pipelines/pipeline.yaml \
+          --yaml=src/pipelines/training.yaml \
           --tag=latest \
           --tag=${TAG_NAME} && \
           poetry run python -m pipelines.utils.upload_pipeline \
           --dest=https://${_VERTEX_LOCATION}-kfp.pkg.dev/$$proj/vertex-pipelines \
-          --yaml=src/pipelines/pipeline.yaml \
+          --yaml=src/pipelines/prediction.yaml \
           --tag=latest \
           --tag=${TAG_NAME}; \
         done
diff --git a/components/tests/conftest.py b/components/tests/conftest.py
index 89cdc9ba..eb9014b4 100644
--- a/components/tests/conftest.py
+++ b/components/tests/conftest.py
@@ -31,7 +31,7 @@ def mock_kfp_artifact(monkeypatch):
     Args:
         monkeypatch: Used to patch the decorator `@component` in `kfp.v2.dsl`.
             This prevents KFP from changing the Python functions when applying
-            pytests.
+            pytest.
 
     Returns:
         None
diff --git a/components/tests/test_model_batch_predict.py b/components/tests/test_model_batch_predict.py
index 6e0eb951..d3784a9f 100644
--- a/components/tests/test_model_batch_predict.py
+++ b/components/tests/test_model_batch_predict.py
@@ -11,8 +11,6 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
-import json
 import pytest
 from unittest import mock
 from kfp.dsl import Model
@@ -85,7 +83,7 @@ def test_model_batch_predict(
         monitoring_training_dataset=monitoring_training_dataset,
         monitoring_alert_email_addresses=monitoring_alert_email_addresses,
         monitoring_skew_config=monitoring_skew_config,
-        gcp_resources=str(gcp_resources_path)
+        gcp_resources=str(gcp_resources_path),
     )
 
     create_job.assert_called_once()
diff --git a/docs/notebooks/02_run_pipelines.ipynb b/docs/notebooks/02_run_pipelines.ipynb
index 7937221f..ce971a8e 100644
--- a/docs/notebooks/02_run_pipelines.ipynb
+++ b/docs/notebooks/02_run_pipelines.ipynb
@@ -193,7 +193,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "! make prediction build=false"
+    "! make prediction"
    ]
   },
   {
diff --git a/pipelines/tests/__init__.py b/pipelines/tests/__init__.py
deleted file mode 100644
index 7ba50f93..00000000
--- a/pipelines/tests/__init__.py
+++ /dev/null
@@ -1,13 +0,0 @@
-# Copyright 2023 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
diff --git a/pipelines/tests/conftest.py b/pipelines/tests/conftest.py
deleted file mode 100644
index 8083a83c..00000000
--- a/pipelines/tests/conftest.py
+++ /dev/null
@@ -1,29 +0,0 @@
-# Copyright 2023 Google LLC
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-import pytest
-
-
-def pytest_addoption(parser):
-    parser.addoption(
-        "--enable_caching",
-        type=str,
-        help="Whether to enable or disable caching for all pipeline steps",
-        default=None,
-    )
-
-
-@pytest.fixture(scope="session")
-def enable_caching(pytestconfig):
-    return pytestconfig.getoption("enable_caching")

From 07fb10b24f611dee2c0b1c9b4642a2c78a3b8144 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Wed, 15 Nov 2023 11:15:06 +0100
Subject: [PATCH 230/238] Address comments

---
 components/tests/test_lookup_model.py         | 13 +++---
 components/tests/test_model_batch_predict.py  | 43 ++++++++++---------
 docs/PRODUCTION.md                            |  5 ++-
 .../src/pipelines/utils/trigger_pipeline.py   |  4 +-
 4 files changed, 35 insertions(+), 30 deletions(-)

diff --git a/components/tests/test_lookup_model.py b/components/tests/test_lookup_model.py
index 56c6e27e..58003203 100644
--- a/components/tests/test_lookup_model.py
+++ b/components/tests/test_lookup_model.py
@@ -22,14 +22,14 @@
 
 
 @mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model(mock_model, tmpdir):
+def test_lookup_model(mock_model, tmp_path):
     """
     Assert lookup_model produces expected resource name, and that list method is
     called with the correct arguemnts
     """
 
     # Mock attribute and method
-    mock_path = tmpdir
+    mock_path = str(tmp_path / "model")
     mock_model.resource_name = "my-model-resource-name"
     mock_model.uri = mock_path
     mock_model.list.return_value = [mock_model]
@@ -54,7 +54,7 @@ def test_lookup_model(mock_model, tmpdir):
 
 
 @mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model_when_no_models(mock_model, tmpdir):
+def test_lookup_model_when_no_models(mock_model, tmp_path):
     """
     Checks that when there are no models and fail_on_model_found = False,
     lookup_model returns an empty string.
@@ -65,15 +65,14 @@ def test_lookup_model_when_no_models(mock_model, tmpdir):
         location="europe-west4",
         project="my-project-id",
         fail_on_model_not_found=False,
-        model=Model(uri=str(tmpdir)),
+        model=Model(uri=str(tmp_path / "model")),
     )
 
-    print(exported_model_resource_name)
     assert exported_model_resource_name == ""
 
 
 @mock.patch("google.cloud.aiplatform.Model")
-def test_lookup_model_when_no_models_fail(mock_model, tmpdir):
+def test_lookup_model_when_no_models_fail(mock_model, tmp_path):
     """
     Checks that when there are no models and fail_on_model_found = True,
     lookup_model raises a RuntimeError.
@@ -87,5 +86,5 @@ def test_lookup_model_when_no_models_fail(mock_model, tmpdir):
             location="europe-west4",
             project="my-project-id",
             fail_on_model_not_found=True,
-            model=Model(uri=str(tmpdir)),
+            model=Model(uri=str(tmp_path / "model")),
         )
diff --git a/components/tests/test_model_batch_predict.py b/components/tests/test_model_batch_predict.py
index d3784a9f..aec99fad 100644
--- a/components/tests/test_model_batch_predict.py
+++ b/components/tests/test_model_batch_predict.py
@@ -57,7 +57,7 @@
 def test_model_batch_predict(
     create_job,
     get_job,
-    tmpdir,
+    tmp_path,
     source_format,
     destination_format,
     source_uri,
@@ -68,24 +68,27 @@ def test_model_batch_predict(
     """
     Asserts model_batch_predict successfully creates requests given different arguments.
     """
-    mock_model = Model(uri=tmpdir, metadata={"resourceName": ""})
-    gcp_resources_path = tmpdir / "gcp_resources.json"
+    mock_model = Model(uri=str(tmp_path / "model"), metadata={"resourceName": ""})
+    gcp_resources_path = tmp_path / "gcp_resources.json"
 
-    model_batch_predict(
-        model=mock_model,
-        job_display_name="",
-        location="",
-        project="",
-        source_uri=source_uri,
-        destination_uri=destination_format,
-        source_format=source_format,
-        destination_format=destination_format,
-        monitoring_training_dataset=monitoring_training_dataset,
-        monitoring_alert_email_addresses=monitoring_alert_email_addresses,
-        monitoring_skew_config=monitoring_skew_config,
-        gcp_resources=str(gcp_resources_path),
-    )
+    try:
+        model_batch_predict(
+            model=mock_model,
+            job_display_name="",
+            location="",
+            project="",
+            source_uri=source_uri,
+            destination_uri=destination_format,
+            source_format=source_format,
+            destination_format=destination_format,
+            monitoring_training_dataset=monitoring_training_dataset,
+            monitoring_alert_email_addresses=monitoring_alert_email_addresses,
+            monitoring_skew_config=monitoring_skew_config,
+            gcp_resources=str(gcp_resources_path),
+        )
 
-    create_job.assert_called_once()
-    get_job.assert_called_once()
-    assert gcp_resources_path.exists()
+        create_job.assert_called_once()
+        get_job.assert_called_once()
+        assert gcp_resources_path.exists()
+    finally:
+        gcp_resources_path.unlink(missing_ok=True)
diff --git a/docs/PRODUCTION.md b/docs/PRODUCTION.md
index 6b312074..8f1315fc 100644
--- a/docs/PRODUCTION.md
+++ b/docs/PRODUCTION.md
@@ -87,6 +87,8 @@ cloud_schedulers_config = {
     template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-train-pipeline/v1.2"
     enable_caching = null
     pipeline_parameters = {
+      // Add pipeline parameters which are expected by your pipeline here e.g.
+      // project = "my-project-id"
     },
   },
 
@@ -97,7 +99,8 @@ cloud_schedulers_config = {
     template_path = "https://<GCP region>-kfp.pkg.dev/<Project ID of test project>/vertex-pipelines/xgboost-prediction-pipeline/v1.2"
     enable_caching = null
     pipeline_parameters = {
-      // TODO: add all pipeline parameters which are expected by your pipeline
+      // Add pipeline parameters which are expected by your pipeline here e.g.
+      // project = "my-project-id"
     },
   },
 
diff --git a/pipelines/src/pipelines/utils/trigger_pipeline.py b/pipelines/src/pipelines/utils/trigger_pipeline.py
index bf49b6e3..6d217020 100644
--- a/pipelines/src/pipelines/utils/trigger_pipeline.py
+++ b/pipelines/src/pipelines/utils/trigger_pipeline.py
@@ -49,8 +49,8 @@ def trigger_pipeline(
         enable_caching = enable_caching.lower() in true_
 
     # For below options, we want an empty string to become None, so we add "or None"
-    encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER")
-    network = os.environ.get("VERTEX_NETWORK")
+    encryption_spec_key_name = os.environ.get("VERTEX_CMEK_IDENTIFIER") or None
+    network = os.environ.get("VERTEX_NETWORK") or None
 
     # Instantiate PipelineJob object
     pl = aiplatform.PipelineJob(

From 7f4536ba5dfd23674a709cba3a6ffb0a76847aa1 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Fri, 15 Dec 2023 16:25:34 +0100
Subject: [PATCH 231/238] Minor improvements

---
 Makefile                                      |  91 +-
 README.md                                     |  21 +-
 cloudbuild/e2e-test.yaml                      |   8 +-
 cloudbuild/release.yaml                       |   6 +-
 components/poetry.lock                        | 391 ++++---
 components/src/components/upload_model.py     |   3 +-
 docs/PIPELINES.md                             |   2 +-
 docs/PRODUCTION.md                            |   2 +-
 docs/notebooks/01_infrastructure_setup.ipynb  |  30 +-
 docs/notebooks/02_run_pipelines.ipynb         |  23 +-
 .../notebooks/03_infrastructure_cleanup.ipynb |  17 +-
 docs/notebooks/scripts/install_poetry.sh      |   3 +-
 docs/notebooks/scripts/install_terraform.sh   |   4 +-
 env.sh.example                                |  18 +-
 model/Dockerfile                              |   8 +-
 model/poetry.lock                             | 849 ++++++++--------
 model/{serving => prediction}/main.py         |   0
 model/pyproject.toml                          |   3 +-
 pipelines/poetry.lock                         | 952 +++++++++---------
 pipelines/pyproject.toml                      |   1 +
 pipelines/src/pipelines/training.py           |   4 +-
 21 files changed, 1289 insertions(+), 1147 deletions(-)
 rename model/{serving => prediction}/main.py (100%)

diff --git a/Makefile b/Makefile
index ff67f45b..0cd56698 100644
--- a/Makefile
+++ b/Makefile
@@ -16,20 +16,27 @@
 export
 
 help: ## Display this help screen.
-	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
+	@grep -h -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | \
+	awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
 
 env ?= dev
 AUTO_APPROVE_FLAG :=
-deploy: ## Deploy infrastructure to your project. Optionally set env=<dev|test|prod> (default = dev).
-	@if [ "$(auto-approve)" = "true" ]; then \
+deploy: ## Deploy infrastructure to your project. Optionally set env=<dev|test|prod> (default=dev).
+	@echo "################################################################################" && \
+	echo "# Deploy $$env environment" && \
+	echo "################################################################################" && \
+	if [ "$(auto-approve)" = "true" ]; then \
 		AUTO_APPROVE_FLAG="-auto-approve"; \
 	fi; \
 	cd terraform/envs/$(env) && \
 	terraform init -backend-config='bucket=${VERTEX_PROJECT_ID}-tfstate' && \
 	terraform apply -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}' $$AUTO_APPROVE_FLAG
 
-undeploy: ## DESTROY the infrastructure in your project. Optionally set env=<dev|test|prod> (default = dev).
-	@if [ "$(auto-approve)" = "true" ]; then \
+undeploy: ## Destroy the infrastructure in your project. Optionally set env=<dev|test|prod> (default=dev).
+	@echo "################################################################################" && \
+	echo "# Destroy $$env environment" && \
+	echo "################################################################################" && \
+	if [ "$(auto-approve)" = "true" ]; then \
 		AUTO_APPROVE_FLAG="-auto-approve"; \
 	fi; \
 	cd terraform/envs/$(env) && \
@@ -37,34 +44,44 @@ undeploy: ## DESTROY the infrastructure in your project. Optionally set env=<dev
 	terraform destroy -var 'project_id=${VERTEX_PROJECT_ID}' -var 'region=${VERTEX_LOCATION}' $$AUTO_APPROVE_FLAG
 
 install: ## Set up local Python environment for development.
-	@cd pipelines && \
+	@echo "################################################################################" && \
+	echo "# Install Python dependencies" && \
+	echo "################################################################################" && \
+	cd model && \
+	poetry install --no-root && \
+	cd ../pipelines && \
 	poetry install --with dev && \
 	cd ../components && \
-	poetry install --with dev && \
-	cd ../model && \
-	poetry install
+	poetry install --with dev
 
-compile: ## Compile pipeline. Must set pipeline=<training|prediction>.
-	@cd pipelines/src && \
-	echo "Compiling $$pipeline pipeline" && \
+compile: ## Compile pipeline. Set pipeline=<training|prediction>.
+	@echo "################################################################################" && \
+	echo "# Compile $$pipeline pipeline" && \
+	echo "################################################################################" && \
+	cd pipelines/src && \
 	poetry run kfp dsl compile --py pipelines/${pipeline}.py --output pipelines/${pipeline}.yaml --function pipeline
 
-images ?= training serving
-build: ## Build and push container(s). Set images=<training serving> e.g. images=training (default = training serving).
-	@cd model && \
+images ?= training prediction
+build: ## Build and push container(s). Set images=<training and/or prediction> (default="training prediction").
+	@echo "################################################################################" && \
+	echo "# Build $$images image(s)" && \
+	echo "################################################################################" && \
+	cd model && \
 	for image in $$images ; do \
-		echo "Building $$image image" && \
+		echo "Build $$image image" && \
 		gcloud builds submit . \
 		--region=${VERTEX_LOCATION} \
 		--project=${VERTEX_PROJECT_ID} \
 		--gcs-source-staging-dir=gs://${VERTEX_PROJECT_ID}-staging/source \
-		--substitutions=_DOCKER_TARGET=$$image,_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/$$image:${RESOURCE_SUFFIX} ; \
+		--substitutions=_DOCKER_TARGET=$$image,_DESTINATION_IMAGE_URI=${CONTAINER_IMAGE_REGISTRY}/$$image:${RESOURCE_SUFFIX} \
+		--suppress-logs ; \
 	done 
 
 compile ?= true
 build ?= true
+cache ?= true
 wait ?= false
-run: ## Run pipeline. Must set pipeline=<training|prediction>. Optionally set wait=<true|false> (default = false), compile=<true|false> (default = true) to recompile pipeline, build=<true|false> (default = true) to rebuild container image(s), images=<training serving> (default = training serving) to set which images are rebuilt.
+run: ## Run a pipeline. Set pipeline=<training|prediction>. Optionally set compile=<true|false> (default=true), build=<true|false>, cache=<true|false> (default=true). wait=<true|false> (default=false).
 	@if [ $(compile) = "true" ]; then \
 		$(MAKE) compile ; \
 	elif [ $(compile) != "false" ]; then \
@@ -77,31 +94,31 @@ run: ## Run pipeline. Must set pipeline=<training|prediction>. Optionally set wa
 		echo "ValueError: build must be either true or false" ; \
 		exit ; \
 	fi && \
+	echo "################################################################################" && \
+	echo "# Run $$pipeline pipeline" && \
+	echo "################################################################################" && \
 	cd pipelines/src && \
-	echo "Running $$pipeline pipeline" && \
-	poetry run python -m pipelines.utils.trigger_pipeline --template_path=pipelines/${pipeline}.yaml --display_name=${pipeline} --wait=${wait}
+	ENABLE_PIPELINE_CACHING=$$cache poetry run python -m pipelines.utils.trigger_pipeline \
+		--template_path=pipelines/${pipeline}.yaml --display_name=${pipeline} --wait=${wait}
 
-training: ## Shortcut to run training pipeline. Rebuilds training and serving images. Supports same options as run.
-	$(MAKE) run pipeline=training images=training prediction
+training: ## Run training pipeline. Rebuilds training and prediction images. Supports same options as run.
+	$(MAKE) run pipeline=training
 
-prediction:	## Shortcut to run prediction pipeline. Doesn't rebuilt images. Supports same options as run.
+prediction:	## Run prediction pipeline. Doesn't rebuilt images. Supports same options as run.
 	$(MAKE) run pipeline=prediction build=false
 
-components ?= true
-test: ## Run unit tests for pipelines. Optionally set components=<true|false> (default = true) to test components package.
-	@if [ $(components) = "true" ]; then \
-		echo "Running unit tests in components" && \
-		cd components && \
+packages ?= pipelines components
+test: ## Run unit tests. Optionally set packages=<pipelines and/or components> (default="pipelines components").
+	@echo "################################################################################" && \
+	echo "# Test $$packages package(s)" && \
+	echo "################################################################################" && \
+	for package in $$packages ; do \
+		echo "Testing $$package package" && \
+		cd $$package && \
 		poetry run pytest && \
-		cd .. ;  \
-	elif [ $(components) != "false" ]; then \
-		echo "ValueError: components must be either true or false" ; \
-		exit ; \
-	fi && \
-	echo "Running unit tests in pipelines" && \
-	cd pipelines && \
-	poetry run python -m pytest
+		cd .. ; \
+	done
 
 pre-commit: ## Run pre-commit checks for pipelines.
-	cd pipelines && \
+	@cd pipelines && \
 	poetry run pre-commit run --all-files
diff --git a/README.md b/README.md
index 74744856..01dc6f0d 100644
--- a/README.md
+++ b/README.md
@@ -30,14 +30,14 @@ The implementation includes:
 * **CI/CD** using Google Cloud Build for linting, testing, and deploying ML pipelines
 * **Developer scripts** (Makefile, Python scripts etc.)
 
-**Get started today by following [this step-by-step notebook tutorial](docs/notebooks)! 🚀**
+**Get started today by following [this step-by-step notebook tutorial](./docs/notebooks)! 🚀**
 In this three-part notebook series you'll deploy a Google Cloud project and run production-ready ML pipelines using Vertex AI without writing a single line of code.
 
 ## Cloud Architecture
 
 The diagram below shows the cloud architecture for this repository.
 
-![Cloud Architecture diagram](/docs/images/architecture.png)
+![Cloud Architecture diagram](./docs/images/architecture.png)
 
 There are four different Google Cloud projects in use
 
@@ -112,12 +112,12 @@ gcloud auth application-default login
 
 This repository contains example ML training and prediction pipelines which are explained in [this README](docs/PIPELINES.md).
 
-**Build containers:** The [model/](/model/) directory contains the code for custom training and serving container images, including the model training script at [model/training/train.py](model/training/train.py). 
+**Build containers:** The [model/](/model/) directory contains the code for custom training and prediction container images, including the model training script at [model/training/train.py](model/training/train.py). 
 You can modify this to suit your own use case.
-Build the training and serving container images and push them to Artifact Registry with:
+Build the training and prediction container images and push them to Artifact Registry with:
 
 ```bash
-make build [ images=training serving ]
+make build [ images="training prediction" ]
 ```
 
 Optionally specify the `images` variable to only build one of the images.
@@ -131,13 +131,14 @@ Optionally specify the `images` variable to only build one of the images.
 Execute the following command to run through steps 1-3:
 
 ```bash
-make run pipeline=training [ wait=<true|false> ] [ build=<true|false> ] [ compile=<true|false> ]
+make run pipeline=training [ build=<true|false> ] [ compile=<true|false> ] [ cache=<true|false> ] [ wait=<true|false> ] 
 ```
 
 The command has the following true/false flags:
 
-- `build` - re-build containers for training & serving code (limit by setting images=training to build only one of the containers)
+- `build` - re-build containers for training & prediction code (limit by setting images=training to build only one of the containers)
 - `compile` - re-compile the pipeline to YAML
+- `cache` - cache pipeline steps
 - `wait` - run the pipeline (a-)sync
 
 **Shortcuts:** Use these commands which support the same options as `run` to run the training or prediction pipeline:
@@ -154,7 +155,7 @@ The unit tests are run on each pull request.
 To run them locally you can execute the following command and optionally enable or disable testing of components:
 
 ```
-make test [ components=<true|false> ]
+make test [ packages=<pipelines components> ]
 ```
 
 ## Automation
@@ -163,6 +164,6 @@ For details on setting up CI/CD, see [this README](/docs/AUTOMATION.md).
 
 ## Putting it all together
 
-For a full walkthrough of the journey from changing the ML pipeline code to having it scheduled and running in production, please see the guide [here](docs/PRODUCTION.md).
+For a full walkthrough of the journey from changing the ML pipeline code to having it scheduled and running in production, please see the guide [here](./docs/PRODUCTION.md).
 
-We value your contribution, see [this guide](docs/CONTRIBUTION.md) for contributing to this project.
+We value your contribution, see [this guide](./docs/CONTRIBUTION.md) for contributing to this project.
diff --git a/cloudbuild/e2e-test.yaml b/cloudbuild/e2e-test.yaml
index 99a38e22..dcfb1211 100644
--- a/cloudbuild/e2e-test.yaml
+++ b/cloudbuild/e2e-test.yaml
@@ -24,12 +24,12 @@ steps:
       - --compressed-caching=false
     waitFor: ['-']
 
-  - id: build-serving-image
+  - id: build-prediction-image
     name: gcr.io/kaniko-project/executor:latest
     args:
       - --context=dir:///workspace/model
-      - --destination=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images/serving:${COMMIT_SHA}
-      - --target=serving
+      - --destination=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images/prediction:${COMMIT_SHA}
+      - --target=prediction
       - --cache=true
       - --compressed-caching=false
     waitFor: ['-']
@@ -60,7 +60,7 @@ steps:
       - CONTAINER_IMAGE_REGISTRY=${_TEST_VERTEX_LOCATION}-docker.pkg.dev/${_TEST_VERTEX_PROJECT_ID}/vertex-images
     waitFor:
       - build-training-image
-      - build-serving-image
+      - build-prediction-image
 
 options:
   logging: CLOUD_LOGGING_ONLY
diff --git a/cloudbuild/release.yaml b/cloudbuild/release.yaml
index a99c2eba..a0e72668 100644
--- a/cloudbuild/release.yaml
+++ b/cloudbuild/release.yaml
@@ -22,12 +22,12 @@ steps:
       - -c
       - |
         docker build --target=training -t training:latest . && \
-        docker build --target=serving -t serving:latest . && \
+        docker build --target=prediction -t prediction:latest . && \
         for proj in ${_DESTINATION_PROJECTS} ; do \
           docker tag training:latest ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/training:${TAG_NAME} && \
-          docker tag serving:latest ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/serving:${TAG_NAME} && \
+          docker tag prediction:latest ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/prediction:${TAG_NAME} && \
           docker push ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/training:${TAG_NAME} && \
-          docker push ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/serving:${TAG_NAME}; \
+          docker push ${_VERTEX_LOCATION}-docker.pkg.dev/$$proj/vertex-images/prediction:${TAG_NAME}; \
         done
 
   # Install poetry, install deps, compile pipelines
diff --git a/components/poetry.lock b/components/poetry.lock
index 57851f68..29592fb5 100644
--- a/components/poetry.lock
+++ b/components/poetry.lock
@@ -13,13 +13,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.7.22"
+version = "2023.11.17"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
-    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
+    {file = "certifi-2023.11.17-py3-none-any.whl", hash = "sha256:e036ab49d5b79556f99cfc2d9320b34cfbe5be05c5871b51de9329f0603b0474"},
+    {file = "certifi-2023.11.17.tar.gz", hash = "sha256:9b469f3a900bf28dc19b8cfbf8019bf47f7fdd1a65a1d4ffb98fc14166beb4d1"},
 ]
 
 [[package]]
@@ -159,13 +159,13 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.3"
+version = "1.2.0"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
-    {file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
+    {file = "exceptiongroup-1.2.0-py3-none-any.whl", hash = "sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14"},
+    {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"},
 ]
 
 [package.extras]
@@ -173,13 +173,13 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "google-api-core"
-version = "2.12.0"
+version = "2.15.0"
 description = "Google API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.12.0.tar.gz", hash = "sha256:c22e01b1e3c4dcd90998494879612c38d0a3411d1f7b679eb89e2abe3ce1f553"},
-    {file = "google_api_core-2.12.0-py3-none-any.whl", hash = "sha256:ec6054f7d64ad13b41e43d96f735acbd763b0f3b695dabaa2d579673f6a6e160"},
+    {file = "google-api-core-2.15.0.tar.gz", hash = "sha256:abc978a72658f14a2df1e5e12532effe40f94f868f6e23d95133bd6abcca35ca"},
+    {file = "google_api_core-2.15.0-py3-none-any.whl", hash = "sha256:2aa56d2be495551e66bbff7f729b790546f87d5c90e74781aa77233bcb395a8a"},
 ]
 
 [package.dependencies]
@@ -197,13 +197,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.23.4"
+version = "2.25.2"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.23.4.tar.gz", hash = "sha256:79905d6b1652187def79d491d6e23d0cbb3a21d3c7ba0dbaa9c8a01906b13ff3"},
-    {file = "google_auth-2.23.4-py2.py3-none-any.whl", hash = "sha256:d4bbc92fe4b8bfd2f3e8d88e5ba7085935da208ee38a134fc280e7ce682a05f2"},
+    {file = "google-auth-2.25.2.tar.gz", hash = "sha256:42f707937feb4f5e5a39e6c4f343a17300a459aaf03141457ba505812841cc40"},
+    {file = "google_auth-2.25.2-py2.py3-none-any.whl", hash = "sha256:473a8dfd0135f75bb79d878436e568f2695dce456764bf3a02b6f8c540b1d256"},
 ]
 
 [package.dependencies]
@@ -220,13 +220,13 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.36.0"
+version = "1.38.1"
 description = "Vertex AI API client library"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "google-cloud-aiplatform-1.36.0.tar.gz", hash = "sha256:c35eb179fa3107c262024a63bb4a3dc1887678424a0b9f49f0da3f5179896186"},
-    {file = "google_cloud_aiplatform-1.36.0-py2.py3-none-any.whl", hash = "sha256:06adb1605208a9bdbadd8c4deeaeb6511a7f59220ef606e2d95ccc1da705ebda"},
+    {file = "google-cloud-aiplatform-1.38.1.tar.gz", hash = "sha256:30439d914bb028443c0506cc0e6dd825cff5401aeb8233e13d8cfd77c3c87da1"},
+    {file = "google_cloud_aiplatform-1.38.1-py2.py3-none-any.whl", hash = "sha256:5e1fcd1068dd2c4f0fc89aa616e34a8b9434eaa72ea6216f5036ef26f08bd448"},
 ]
 
 [package.dependencies]
@@ -259,45 +259,43 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "3.13.0"
+version = "3.14.1"
 description = "Google BigQuery API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-bigquery-3.13.0.tar.gz", hash = "sha256:794ccfc93ccb0e0ad689442f896f9c82de56da0fe18a195531bb37096c2657d6"},
-    {file = "google_cloud_bigquery-3.13.0-py2.py3-none-any.whl", hash = "sha256:eda3dbcff676e17962c54e5224e415b55e4f6833a5c896c6c8902b69e7dba4b4"},
+    {file = "google-cloud-bigquery-3.14.1.tar.gz", hash = "sha256:aa15bd86f79ea76824c7d710f5ae532323c4b3ba01ef4abff42d4ee7a2e9b142"},
+    {file = "google_cloud_bigquery-3.14.1-py2.py3-none-any.whl", hash = "sha256:a8ded18455da71508db222b7c06197bc12b6dbc6ed5b0b64e7007b76d7016957"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-cloud-core = ">=1.6.0,<3.0.0dev"
 google-resumable-media = ">=0.6.0,<3.0dev"
-grpcio = ">=1.47.0,<2.0dev"
 packaging = ">=20.0.0"
-proto-plus = ">=1.15.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 python-dateutil = ">=2.7.2,<3.0dev"
 requests = ">=2.21.0,<3.0.0dev"
 
 [package.extras]
-all = ["Shapely (>=1.8.4,<3.0.0dev)", "db-dtypes (>=0.3.0,<2.0.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)", "ipywidgets (>=7.7.0)", "opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)", "tqdm (>=4.7.4,<5.0.0dev)"]
+all = ["Shapely (>=1.8.4,<3.0.0dev)", "db-dtypes (>=0.3.0,<2.0.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "importlib-metadata (>=1.0.0)", "ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)", "ipywidgets (>=7.7.0)", "opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)", "pandas (>=1.1.0)", "proto-plus (>=1.15.0,<2.0.0dev)", "protobuf (>=3.19.5,!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev)", "pyarrow (>=3.0.0)", "tqdm (>=4.7.4,<5.0.0dev)"]
+bigquery-v2 = ["proto-plus (>=1.15.0,<2.0.0dev)", "protobuf (>=3.19.5,!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev)"]
 bqstorage = ["google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "pyarrow (>=3.0.0)"]
 geopandas = ["Shapely (>=1.8.4,<3.0.0dev)", "geopandas (>=0.9.0,<1.0dev)"]
 ipython = ["ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)"]
 ipywidgets = ["ipykernel (>=6.0.0)", "ipywidgets (>=7.7.0)"]
 opentelemetry = ["opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)"]
-pandas = ["db-dtypes (>=0.3.0,<2.0.0dev)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)"]
+pandas = ["db-dtypes (>=0.3.0,<2.0.0dev)", "importlib-metadata (>=1.0.0)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)"]
 tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 
 [[package]]
 name = "google-cloud-core"
-version = "2.3.3"
+version = "2.4.1"
 description = "Google Cloud API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-core-2.3.3.tar.gz", hash = "sha256:37b80273c8d7eee1ae816b3a20ae43585ea50506cb0e60f3cf5be5f87f1373cb"},
-    {file = "google_cloud_core-2.3.3-py2.py3-none-any.whl", hash = "sha256:fbd11cad3e98a7e5b0343dc07cb1039a5ffd7a5bb96e1f1e27cee4bda4a90863"},
+    {file = "google-cloud-core-2.4.1.tar.gz", hash = "sha256:9b7749272a812bde58fff28868d0c5e2f585b82f37e09a1f6ed2d4d10f134073"},
+    {file = "google_cloud_core-2.4.1-py2.py3-none-any.whl", hash = "sha256:a9e6a4422b9ac5c29f79a0ede9485473338e2ce78d91f2370c01e730eab22e61"},
 ]
 
 [package.dependencies]
@@ -305,53 +303,54 @@ google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
-grpc = ["grpcio (>=1.38.0,<2.0dev)"]
+grpc = ["grpcio (>=1.38.0,<2.0dev)", "grpcio-status (>=1.38.0,<2.0.dev0)"]
 
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "2.3.0"
+version = "2.8.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "google_cloud_pipeline_components-2.3.0-py3-none-any.whl", hash = "sha256:bfb6f04598f431577bdf40d3a937646eed16f703d95010379db138d4624be69c"},
+    {file = "google_cloud_pipeline_components-2.8.0-py3-none-any.whl", hash = "sha256:2b21bc6f65e4c47f21a5c5de472a770fe8ca7c639252031fe2f4c054a6095f4a"},
 ]
 
 [package.dependencies]
 google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-cloud-aiplatform = ">=1.14.0,<2"
-kfp = ">=2.0.0b10,<3.0.0"
+Jinja2 = "3.1.2"
+kfp = ">=2.0.0b10,<=2.4.0"
 
 [package.extras]
-docs = ["autodocsumm (==0.2.9)", "grpcio-status (<=1.47.0)", "m2r2 (==0.3.2)", "protobuf (>=3.19.0,<4.0.0dev)", "sphinx (==5.0.2)", "sphinx-immaterial (==0.9.0)", "sphinx-notfound-page (==0.8.3)", "sphinx-rtd-theme (==1.0.0)"]
+docs = ["autodocsumm (==0.2.9)", "commonmark (==0.9.1)", "grpcio-status (<=1.47.0)", "m2r2 (==0.3.2)", "protobuf (>=3.19.0,<4.0.0dev)", "sphinx (==5.0.2)", "sphinx-immaterial (==0.9.0)", "sphinx-notfound-page (==0.8.3)", "sphinx-rtd-theme (==1.0.0)"]
 tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
-version = "1.10.4"
+version = "1.11.0"
 description = "Google Cloud Resource Manager API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "google-cloud-resource-manager-1.11.0.tar.gz", hash = "sha256:a64ba6bb595634ecd2472b8b0322e8f012a76327756659a2dde9f392d7fa1af2"},
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 ]
 
 [package.dependencies]
 google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
-proto-plus = ">=1.22.0,<2.0.0dev"
+proto-plus = ">=1.22.3,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.13.0"
+version = "2.14.0"
 description = "Google Cloud Storage API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-storage-2.13.0.tar.gz", hash = "sha256:f62dc4c7b6cd4360d072e3deb28035fbdad491ac3d9b0b1815a12daea10f37c7"},
-    {file = "google_cloud_storage-2.13.0-py2.py3-none-any.whl", hash = "sha256:ab0bf2e1780a1b74cf17fccb13788070b729f50c252f0c94ada2aae0ca95437d"},
+    {file = "google-cloud-storage-2.14.0.tar.gz", hash = "sha256:2d23fcf59b55e7b45336729c148bb1c464468c69d5efbaee30f7201dd90eb97e"},
+    {file = "google_cloud_storage-2.14.0-py2.py3-none-any.whl", hash = "sha256:8641243bbf2a2042c16a6399551fbb13f062cbc9a2de38d6c0bb5426962e9dbd"},
 ]
 
 [package.dependencies]
@@ -447,13 +446,13 @@ testing = ["pytest"]
 
 [[package]]
 name = "google-resumable-media"
-version = "2.6.0"
+version = "2.7.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "google-resumable-media-2.6.0.tar.gz", hash = "sha256:972852f6c65f933e15a4a210c2b96930763b47197cdf4aa5f5bea435efb626e7"},
-    {file = "google_resumable_media-2.6.0-py2.py3-none-any.whl", hash = "sha256:fc03d344381970f79eebb632a3c18bb1828593a2dc5572b5f90115ef7d11e81b"},
+    {file = "google-resumable-media-2.7.0.tar.gz", hash = "sha256:5f18f5fa9836f4b083162064a1c2c98c17239bfda9ca50ad970ccf905f3e625b"},
+    {file = "google_resumable_media-2.7.0-py2.py3-none-any.whl", hash = "sha256:79543cfe433b63fd81c0844b7803aba1bb8950b47bedf7d980c38fa123937e08"},
 ]
 
 [package.dependencies]
@@ -465,13 +464,13 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.61.0"
+version = "1.62.0"
 description = "Common protobufs used in Google APIs"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "googleapis-common-protos-1.61.0.tar.gz", hash = "sha256:8a64866a97f6304a7179873a465d6eee97b7a24ec6cfd78e0f575e96b821240b"},
-    {file = "googleapis_common_protos-1.61.0-py2.py3-none-any.whl", hash = "sha256:22f1915393bb3245343f6efe87f6fe868532efc12aa26b391b15132e1279f1c0"},
+    {file = "googleapis-common-protos-1.62.0.tar.gz", hash = "sha256:83f0ece9f94e5672cced82f592d2a5edf527a96ed1794f0bab36d5735c996277"},
+    {file = "googleapis_common_protos-1.62.0-py2.py3-none-any.whl", hash = "sha256:4750113612205514f9f6aa4cb00d523a94f3e8c06c5ad2fee466387dc4875f07"},
 ]
 
 [package.dependencies]
@@ -483,13 +482,13 @@ grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 
 [[package]]
 name = "grpc-google-iam-v1"
-version = "0.12.6"
+version = "0.13.0"
 description = "IAM API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "grpc-google-iam-v1-0.12.6.tar.gz", hash = "sha256:2bc4b8fdf22115a65d751c9317329322602c39b7c86a289c9b72d228d960ef5f"},
-    {file = "grpc_google_iam_v1-0.12.6-py2.py3-none-any.whl", hash = "sha256:5c10f3d8dc2d88678ab1a9b0cb5482735c5efee71e6c0cd59f872eef22913f5c"},
+    {file = "grpc-google-iam-v1-0.13.0.tar.gz", hash = "sha256:fad318608b9e093258fbf12529180f400d1c44453698a33509cc6ecf005b294e"},
+    {file = "grpc_google_iam_v1-0.13.0-py2.py3-none-any.whl", hash = "sha256:53902e2af7de8df8c1bd91373d9be55b0743ec267a7428ea638db3775becae89"},
 ]
 
 [package.dependencies]
@@ -499,69 +498,69 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 
 [[package]]
 name = "grpcio"
-version = "1.59.2"
+version = "1.60.0"
 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.extras]
-protobuf = ["grpcio-tools (>=1.59.2)"]
+protobuf = ["grpcio-tools (>=1.60.0)"]
 
 [[package]]
 name = "grpcio-status"
@@ -581,13 +580,13 @@ protobuf = ">=3.12.0"
 
 [[package]]
 name = "idna"
-version = "3.4"
+version = "3.6"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
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 ]
 
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+optional = false
+python-versions = ">=3.7"
+files = [
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+
+[package.dependencies]
+MarkupSafe = ">=2.0"
+
+[package.extras]
+i18n = ["Babel (>=2.7)"]
+
 [[package]]
 name = "kfp"
 version = "2.4.0"
@@ -645,12 +661,12 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "2.0.3"
+version = "2.0.5"
 description = "Kubeflow Pipelines API"
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 python-versions = "*"
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 [package.extras]
 adal = ["adal (>=1.0.2)"]
 
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+optional = false
+python-versions = ">=3.7"
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+    {file = "numpy-1.26.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5d5244aabd6ed7f312268b9247be47343a654ebea52a60f002dc70c769048e75"},
+    {file = "numpy-1.26.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6a3cdb4d9c70e6b8c0814239ead47da00934666f668426fc6e94cce869e13fd7"},
+    {file = "numpy-1.26.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa317b2325f7aa0a9471663e6093c210cb2ae9c0ad824732b307d2c51983d5b6"},
+    {file = "numpy-1.26.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:174a8880739c16c925799c018f3f55b8130c1f7c8e75ab0a6fa9d41cab092fd6"},
+    {file = "numpy-1.26.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f79b231bf5c16b1f39c7f4875e1ded36abee1591e98742b05d8a0fb55d8a3eec"},
+    {file = "numpy-1.26.2-cp312-cp312-win32.whl", hash = "sha256:4a06263321dfd3598cacb252f51e521a8cb4b6df471bb12a7ee5cbab20ea9167"},
+    {file = "numpy-1.26.2-cp312-cp312-win_amd64.whl", hash = "sha256:b04f5dc6b3efdaab541f7857351aac359e6ae3c126e2edb376929bd3b7f92d7e"},
+    {file = "numpy-1.26.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4eb8df4bf8d3d90d091e0146f6c28492b0be84da3e409ebef54349f71ed271ef"},
+    {file = "numpy-1.26.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1a13860fdcd95de7cf58bd6f8bc5a5ef81c0b0625eb2c9a783948847abbef2c2"},
+    {file = "numpy-1.26.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:64308ebc366a8ed63fd0bf426b6a9468060962f1a4339ab1074c228fa6ade8e3"},
+    {file = "numpy-1.26.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:baf8aab04a2c0e859da118f0b38617e5ee65d75b83795055fb66c0d5e9e9b818"},
+    {file = "numpy-1.26.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:d73a3abcac238250091b11caef9ad12413dab01669511779bc9b29261dd50210"},
+    {file = "numpy-1.26.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b361d369fc7e5e1714cf827b731ca32bff8d411212fccd29ad98ad622449cc36"},
+    {file = "numpy-1.26.2-cp39-cp39-win32.whl", hash = "sha256:bd3f0091e845164a20bd5a326860c840fe2af79fa12e0469a12768a3ec578d80"},
+    {file = "numpy-1.26.2-cp39-cp39-win_amd64.whl", hash = "sha256:2beef57fb031dcc0dc8fa4fe297a742027b954949cabb52a2a376c144e5e6060"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:1cc3d5029a30fb5f06704ad6b23b35e11309491c999838c31f124fee32107c79"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:94cc3c222bb9fb5a12e334d0479b97bb2df446fbe622b470928f5284ffca3f8d"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:fe6b44fb8fcdf7eda4ef4461b97b3f63c466b27ab151bec2366db8b197387841"},
+    {file = "numpy-1.26.2.tar.gz", hash = "sha256:f65738447676ab5777f11e6bbbdb8ce11b785e105f690bc45966574816b6d3ea"},
 ]
 
 [[package]]
@@ -770,13 +849,13 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "proto-plus"
-version = "1.22.3"
+version = "1.23.0"
 description = "Beautiful, Pythonic protocol buffers."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "proto-plus-1.22.3.tar.gz", hash = "sha256:fdcd09713cbd42480740d2fe29c990f7fbd885a67efc328aa8be6ee3e9f76a6b"},
-    {file = "proto_plus-1.22.3-py3-none-any.whl", hash = "sha256:a49cd903bc0b6ab41f76bf65510439d56ca76f868adf0274e738bfdd096894df"},
+    {file = "proto-plus-1.23.0.tar.gz", hash = "sha256:89075171ef11988b3fa157f5dbd8b9cf09d65fffee97e29ce403cd8defba19d2"},
+    {file = "proto_plus-1.23.0-py3-none-any.whl", hash = "sha256:a829c79e619e1cf632de091013a4173deed13a55f326ef84f05af6f50ff4c82c"},
 ]
 
 [package.dependencies]
@@ -818,13 +897,13 @@ files = [
 
 [[package]]
 name = "pyasn1"
-version = "0.5.0"
+version = "0.5.1"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
-    {file = "pyasn1-0.5.0-py2.py3-none-any.whl", hash = "sha256:87a2121042a1ac9358cabcaf1d07680ff97ee6404333bacca15f76aa8ad01a57"},
-    {file = "pyasn1-0.5.0.tar.gz", hash = "sha256:97b7290ca68e62a832558ec3976f15cbf911bf5d7c7039d8b861c2a0ece69fde"},
+    {file = "pyasn1-0.5.1-py2.py3-none-any.whl", hash = "sha256:4439847c58d40b1d0a573d07e3856e95333f1976294494c325775aeca506eb58"},
+    {file = "pyasn1-0.5.1.tar.gz", hash = "sha256:6d391a96e59b23130a5cfa74d6fd7f388dbbe26cc8f1edf39fdddf08d9d6676c"},
 ]
 
 [[package]]
@@ -995,17 +1074,17 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "setuptools"
-version = "68.2.2"
+version = "69.0.2"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "setuptools-68.2.2-py3-none-any.whl", hash = "sha256:b454a35605876da60632df1a60f736524eb73cc47bbc9f3f1ef1b644de74fd2a"},
-    {file = "setuptools-68.2.2.tar.gz", hash = "sha256:4ac1475276d2f1c48684874089fefcd83bd7162ddaafb81fac866ba0db282a87"},
+    {file = "setuptools-69.0.2-py3-none-any.whl", hash = "sha256:1e8fdff6797d3865f37397be788a4e3cba233608e9b509382a2777d25ebde7f2"},
+    {file = "setuptools-69.0.2.tar.gz", hash = "sha256:735896e78a4742605974de002ac60562d286fa8051a7e2299445e8e8fbb01aa6"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-hoverxref (<2)", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
 testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.1)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
@@ -1120,13 +1199,13 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "websocket-client"
-version = "1.6.4"
+version = "1.7.0"
 description = "WebSocket client for Python with low level API options"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "websocket-client-1.6.4.tar.gz", hash = "sha256:b3324019b3c28572086c4a319f91d1dcd44e6e11cd340232978c684a7650d0df"},
-    {file = "websocket_client-1.6.4-py3-none-any.whl", hash = "sha256:084072e0a7f5f347ef2ac3d8698a5e0b4ffbfcab607628cadabc650fc9a83a24"},
+    {file = "websocket-client-1.7.0.tar.gz", hash = "sha256:10e511ea3a8c744631d3bd77e61eb17ed09304c413ad42cf6ddfa4c7787e8fe6"},
+    {file = "websocket_client-1.7.0-py3-none-any.whl", hash = "sha256:f4c3d22fec12a2461427a29957ff07d35098ee2d976d3ba244e688b8b4057588"},
 ]
 
 [package.extras]
diff --git a/components/src/components/upload_model.py b/components/src/components/upload_model.py
index d23609c6..ec5c20a4 100644
--- a/components/src/components/upload_model.py
+++ b/components/src/components/upload_model.py
@@ -52,8 +52,7 @@ def upload_model(
         eval_metric (str): Metric name to compare champion and challenger on.
         eval_lower_is_better (bool): Usually True for losses and
             False for classification metrics.
-        serving_container_image (str): Container URI for serving the challenger
-            model.
+        serving_container_image (str): Container URI for serving the model.
         model_description (str): Optional. Description of model.
         evaluation_name (str): Optional. Name of evaluation results which are
             displayed in the Vertex AI UI of the challenger model.
diff --git a/docs/PIPELINES.md b/docs/PIPELINES.md
index 7d1da590..51999e66 100644
--- a/docs/PIPELINES.md
+++ b/docs/PIPELINES.md
@@ -92,7 +92,7 @@ The training step is defined as a [KFP container component](https://www.kubeflow
 
 The container image used for this component is built using CI/CD (or the `make build target=training` command if you want to build it during development).
 
-The source code for this container image (and the serving container image) can be found in the [model](/model/) directory. Dependencies are managed using Poetry. The model training script can be found at [model/training/train.py](/model/training/train.py) and can be modified to suit your use case.
+The source code for this container image (and the prediction container image) can be found in the [model](/model/) directory. Dependencies are managed using Poetry. The model training script can be found at [model/training/train.py](/model/training/train.py) and can be modified to suit your use case.
 
 The training script trains a simple XGBoost model wrapped in a scikit-learn pipeline, and saves it as `model.joblib`.
 
diff --git a/docs/PRODUCTION.md b/docs/PRODUCTION.md
index 8f1315fc..e864d095 100644
--- a/docs/PRODUCTION.md
+++ b/docs/PRODUCTION.md
@@ -48,7 +48,7 @@ When you open the Pull Request, the CI pipeline (`pr-checks.yaml`) should be tri
 
 To compile and publish your ML pipelines into your test and prod environments, you will need to [create a release](https://docs.github.com/en/repositories/releasing-projects-on-github/managing-releases-in-a-repository#creating-a-release).
 
-When the new tag is created, the `release.yaml` pipeline should be triggered. It will build and push the training and serving container images, compile the training and prediction pipelines, then upload the compiled ML pipelines to Artifact Registry in each environment (dev/test/prod).
+When the new tag is created, the `release.yaml` pipeline should be triggered. It will build and push the training and prediction container images, compile the training and prediction pipelines, then upload the compiled ML pipelines to Artifact Registry in each environment (dev/test/prod).
 
 #### Example
 
diff --git a/docs/notebooks/01_infrastructure_setup.ipynb b/docs/notebooks/01_infrastructure_setup.ipynb
index dd7b2a06..b8a4c4b2 100644
--- a/docs/notebooks/01_infrastructure_setup.ipynb
+++ b/docs/notebooks/01_infrastructure_setup.ipynb
@@ -45,7 +45,10 @@
     "- Make\n",
     "- [Terraform](https://www.terraform.io)\n",
     "\n",
-    "**For Vertex AI Workbench users**: Uncomment and execute the following cell to install Terraform."
+    "**For Vertex AI Workbench users**: \n",
+    "Uncomment and execute the following cell to install Terraform.\n",
+    "Restart the notebook kernel or the Workbench instance to ensure `terraform` is available in the `PATH`.\n",
+    "Then return to this notebook and continue with the next section."
    ]
   },
   {
@@ -63,12 +66,7 @@
    "source": [
     "## Authenticate\n",
     "\n",
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+    "Set your project ID and authenticate using your Google Account:"
    ]
   },
   {
@@ -78,8 +76,10 @@
    "outputs": [],
    "source": [
     "VERTEX_PROJECT_ID = \"my-project-id\"\n",
-    "! gcloud auth login\n",
-    "! gcloud config set project {VERTEX_PROJECT_ID}"
+    "GOOGLE_ACCOUNT = \"user@company.com\"\n",
+    "! gcloud config set project {VERTEX_PROJECT_ID}\n",
+    "! gcloud config set account {GOOGLE_ACCOUNT}\n",
+    "! gcloud auth login"
    ]
   },
   {
@@ -123,6 +123,7 @@
     "Configure your code by setting the variables:\n",
     "- `VERTEX_PROJECT_ID` - as set above\n",
     "- `VERTEX_LOCATION` - location of the cloud project\n",
+    "- `BQ_LOCATION` - location of the BigQuery dataset, for this notebook example you can leave this as-is\n",
     "- `RESOURCE_SUFFIX` - suffix (e.g. `<your name>`) to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development "
    ]
   },
@@ -134,10 +135,11 @@
    },
    "outputs": [],
    "source": [
-    "%%writefile .env.sh\n",
+    "%%writefile env.sh\n",
     "#!/bin/bash\n",
     "VERTEX_PROJECT_ID=my-project-id\n",
     "VERTEX_LOCATION=europe-west2\n",
+    "BQ_LOCATION=US\n",
     "RESOURCE_SUFFIX=default"
    ]
   },
@@ -154,7 +156,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%writefile -a .env.sh\n",
+    "%%writefile -a env.sh\n",
     "# Optional\n",
     "VERTEX_CMEK_IDENTIFIER=\n",
     "VERTEX_NETWORK=\n",
@@ -221,7 +223,7 @@
    },
    "outputs": [],
    "source": [
-    "! source .env.sh && gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
+    "! source env.sh && gsutil mb -l $VERTEX_LOCATION -p $VERTEX_PROJECT_ID gs://$VERTEX_PROJECT_ID-tfstate"
    ]
   },
   {
@@ -251,7 +253,9 @@
     "You've successfully deployed a `dev` environment! 🎉 \n",
     "Continue with [this notebook](./02_run_pipelines.ipynb) to run your first Vertex AI Pipelines in the deployed project.\n",
     "\n",
-    "**Note:** If you'd like to deploy separate cloud environments as shown below, try out `make deploy env=dev` where you can replace `dev` with `test` or `prod`."
+    "**Note:** If you'd like to deploy separate cloud environments as shown below, try out `make deploy env=dev` where you can replace `dev` with `test` or `prod`.\n",
+    "\n",
+    "**Troubleshooting:** If enabling of APIs or the deployment fails, check whether your Google user account has the appropriate permissions."
    ]
   }
  ],
diff --git a/docs/notebooks/02_run_pipelines.ipynb b/docs/notebooks/02_run_pipelines.ipynb
index ce971a8e..045babe0 100644
--- a/docs/notebooks/02_run_pipelines.ipynb
+++ b/docs/notebooks/02_run_pipelines.ipynb
@@ -47,7 +47,10 @@
     "- [Poetry](https://python-poetry.org)\n",
     "- [pyenv](https://github.com/pyenv/pyenv)\n",
     "\n",
-    "**For Vertex AI Workbench users**: Uncomment and execute the following cell install Poetry."
+    "**For Vertex AI Workbench users**: \n",
+    "Uncomment and execute the following cell install pyenv and Poetry.\n",
+    "Restart the notebook kernel or the Workbench instance to ensure `pyenv` and `poetry` are available in the `PATH`.\n",
+    "Then return to this notebook and continue with the next section."
    ]
   },
   {
@@ -56,6 +59,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# ! curl https://pyenv.run | bash\n",
     "# ! bash ./scripts/install_poetry.sh"
    ]
   },
@@ -65,12 +69,7 @@
    "source": [
     "## Authenticate\n",
     "\n",
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+    "Set your project ID and authenticate using your Google Account:"
    ]
   },
   {
@@ -80,8 +79,10 @@
    "outputs": [],
    "source": [
     "VERTEX_PROJECT_ID = \"my-project-id\"\n",
-    "! gcloud auth login\n",
-    "! gcloud config set project {VERTEX_PROJECT_ID}"
+    "GOOGLE_ACCOUNT = \"user@company.com\"\n",
+    "! gcloud config set project {VERTEX_PROJECT_ID}\n",
+    "! gcloud config set account {GOOGLE_ACCOUNT}\n",
+    "! gcloud auth login"
    ]
   },
   {
@@ -170,7 +171,7 @@
     "\n",
     "**1. Compile the pipeline:** By using the KubeFlow SDK, you've compiled the training pipeline in `pipelines/training` to YAML.\n",
     "\n",
-    "**2. Build dependent Docker containers:** In `model` you can maintain your training (and serving) code which is containerised and pushed to [Artifact Registry](https://cloud.google.com/artifact-registry). \n",
+    "**2. Build dependent Docker containers:** In `model` you can maintain your training (and prediction) code which is containerised and pushed to [Artifact Registry](https://cloud.google.com/artifact-registry). \n",
     "In this way, your training pipeline can execute your training code in the `Train model` pipeline step.\n",
     "\n",
     "**3. Run the pipeline in Vertex AI:** By using the Vertex AI Python SDK and the pipeline YAML file, you execute your training pipeline."
@@ -204,7 +205,7 @@
    "source": [
     "**Note:** The command has the following true/false flags:\n",
     "\n",
-    "- `build` - re-build containers for training & serving code (limit by setting `images=training` to build only one of the containers)\n",
+    "- `build` - re-build containers for training & prediction code (limit by setting `images=training` to build only one of the containers)\n",
     "- `compile` - re-compile the pipeline to YAML\n",
     "- `wait` - run the pipeline (a-)sync"
    ]
diff --git a/docs/notebooks/03_infrastructure_cleanup.ipynb b/docs/notebooks/03_infrastructure_cleanup.ipynb
index f3f5d776..d2f7c2dd 100644
--- a/docs/notebooks/03_infrastructure_cleanup.ipynb
+++ b/docs/notebooks/03_infrastructure_cleanup.ipynb
@@ -54,12 +54,7 @@
    "source": [
     "## Authenticate\n",
     "\n",
-    "#### Set your project ID\n",
-    "\n",
-    "**If you don't know your project ID**, try the following:\n",
-    "* Run `gcloud config list`.\n",
-    "* Run `gcloud projects list`.\n",
-    "* See the support page: [Locate the project ID](https://support.google.com/googleapi/answer/7014113)"
+    "Set your project ID and authenticate using your Google Account:"
    ]
   },
   {
@@ -69,8 +64,10 @@
    "outputs": [],
    "source": [
     "VERTEX_PROJECT_ID = \"my-project-id\"\n",
-    "! gcloud auth login\n",
-    "! gcloud config set project {VERTEX_PROJECT_ID}"
+    "GOOGLE_ACCOUNT = \"user@company.com\"\n",
+    "! gcloud config set project {VERTEX_PROJECT_ID}\n",
+    "! gcloud config set account {GOOGLE_ACCOUNT}\n",
+    "! gcloud auth login"
    ]
   },
   {
@@ -133,7 +130,7 @@
    },
    "outputs": [],
    "source": [
-    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:preprocessing\" "
+    "! bq --location=${VERTEX_LOCATION} rm -f -r --dataset \"${VERTEX_PROJECT_ID}:turbo_templates\" "
    ]
   },
   {
@@ -161,7 +158,7 @@
     "This is the end of the three-part notebook series.\n",
     "\n",
     "**Now it's time to adapt the template to your own use case.** \n",
-    "You can start by updating the training and serving code in `model` folder. "
+    "You can start by updating the training and prediction code in `model` folder. "
    ]
   }
  ],
diff --git a/docs/notebooks/scripts/install_poetry.sh b/docs/notebooks/scripts/install_poetry.sh
index ef9e0252..ff31ce95 100644
--- a/docs/notebooks/scripts/install_poetry.sh
+++ b/docs/notebooks/scripts/install_poetry.sh
@@ -2,5 +2,6 @@
 # install poetry
 curl -sSL https://install.python-poetry.org | POETRY_HOME=$HOME/.poetry python3 -
 # add poetry to PATH
-echo "export PATH=$HOME/.poetry/bin:PATH" >> $HOME/.bashrc
+echo "export PATH=$HOME/.poetry/bin:$PATH" >> $HOME/.bash_profile
+source $HOME/.bash_profile
 poetry --version
diff --git a/docs/notebooks/scripts/install_terraform.sh b/docs/notebooks/scripts/install_terraform.sh
index eba5fb8e..afe01620 100644
--- a/docs/notebooks/scripts/install_terraform.sh
+++ b/docs/notebooks/scripts/install_terraform.sh
@@ -4,6 +4,8 @@ mkdir tmp && cd tmp || exit
 # download terraform and unzip
 curl -so terraform.zip https://releases.hashicorp.com/terraform/1.5.7/terraform_1.5.7_linux_amd64.zip && unzip terraform.zip > /dev/null
 # move binaries to ~/.bin
-mkdir $HOME/.bin && mv terraform $HOME/.bin > /dev/null
+mkdir -p $HOME/.bin && mv terraform $HOME/.bin > /dev/null
 # clean up temporary folder
 cd .. && rm -r tmp || exit
+echo "export PATH=$HOME/.bin:$PATH" >> $HOME/.bash_profile
+terraform -version
diff --git a/env.sh.example b/env.sh.example
index 8666c732..1a00f38d 100644
--- a/env.sh.example
+++ b/env.sh.example
@@ -13,16 +13,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-export VERTEX_PROJECT_ID=my-gcp-project
-export VERTEX_LOCATION=europe-west2
-export BQ_LOCATION=US
-export VERTEX_NETWORK=
-export VERTEX_CMEK_IDENTIFIER=
+VERTEX_PROJECT_ID=my-gcp-project
+VERTEX_LOCATION=europe-west2
+BQ_LOCATION=US
+VERTEX_NETWORK=
+VERTEX_CMEK_IDENTIFIER=
 
 # Suffix (e.g. '<your name>') to facilitate running concurrent pipelines in the same Google Cloud project. Change if working in a team to avoid overwriting resources during development 
-export RESOURCE_SUFFIX=default
+RESOURCE_SUFFIX=default
 
 # Leave as-is
-export VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
-export VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
-export CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images
+VERTEX_SA_EMAIL=vertex-pipelines@${VERTEX_PROJECT_ID}.iam.gserviceaccount.com
+VERTEX_PIPELINE_ROOT=gs://${VERTEX_PROJECT_ID}-pl-root
+CONTAINER_IMAGE_REGISTRY=${VERTEX_LOCATION}-docker.pkg.dev/${VERTEX_PROJECT_ID}/vertex-images
diff --git a/model/Dockerfile b/model/Dockerfile
index ffd743b6..83dfd493 100644
--- a/model/Dockerfile
+++ b/model/Dockerfile
@@ -29,9 +29,9 @@ FROM builder AS training
 
 COPY training training
 
-FROM builder AS serving
+FROM builder AS prediction
 
-RUN poetry install --with serving
-COPY serving serving
+RUN poetry install --with prediction
+COPY prediction prediction
 
-CMD exec uvicorn serving.main:app --host "0.0.0.0" --port "$AIP_HTTP_PORT"
+CMD exec uvicorn prediction.main:app --host "0.0.0.0" --port "$AIP_HTTP_PORT"
diff --git a/model/poetry.lock b/model/poetry.lock
index 93cadc26..6bf6a81f 100644
--- a/model/poetry.lock
+++ b/model/poetry.lock
@@ -1,152 +1,167 @@
-# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
 
 [[package]]
 name = "annotated-types"
-version = "0.5.0"
+version = "0.6.0"
 description = "Reusable constraint types to use with typing.Annotated"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "annotated_types-0.5.0-py3-none-any.whl", hash = "sha256:58da39888f92c276ad970249761ebea80ba544b77acddaa1a4d6cf78287d45fd"},
-    {file = "annotated_types-0.5.0.tar.gz", hash = "sha256:47cdc3490d9ac1506ce92c7aaa76c579dc3509ff11e098fc867e5130ab7be802"},
+    {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
+    {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
 ]
 
 [[package]]
 name = "anyio"
-version = "3.7.1"
+version = "4.1.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"},
-    {file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"},
+    {file = "anyio-4.1.0-py3-none-any.whl", hash = "sha256:56a415fbc462291813a94528a779597226619c8e78af7de0507333f700011e5f"},
+    {file = "anyio-4.1.0.tar.gz", hash = "sha256:5a0bec7085176715be77df87fc66d6c9d70626bd752fcc85f57cdbee5b3760da"},
 ]
 
 [package.dependencies]
-exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["Sphinx", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.2.2)", "sphinxcontrib-jquery"]
-test = ["anyio[trio]", "coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "mock (>=4)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (<0.22)"]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
 
 [[package]]
 name = "cachetools"
-version = "5.3.1"
+version = "5.3.2"
 description = "Extensible memoizing collections and decorators"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "cachetools-5.3.1-py3-none-any.whl", hash = "sha256:95ef631eeaea14ba2e36f06437f36463aac3a096799e876ee55e5cdccb102590"},
-    {file = "cachetools-5.3.1.tar.gz", hash = "sha256:dce83f2d9b4e1f732a8cd44af8e8fab2dbe46201467fc98b3ef8f269092bf62b"},
+    {file = "cachetools-5.3.2-py3-none-any.whl", hash = "sha256:861f35a13a451f94e301ce2bec7cac63e881232ccce7ed67fab9b5df4d3beaa1"},
+    {file = "cachetools-5.3.2.tar.gz", hash = "sha256:086ee420196f7b2ab9ca2db2520aca326318b68fe5ba8bc4d49cca91add450f2"},
 ]
 
 [[package]]
 name = "certifi"
-version = "2023.7.22"
+version = "2023.11.17"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
-    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
+    {file = "certifi-2023.11.17-py3-none-any.whl", hash = "sha256:e036ab49d5b79556f99cfc2d9320b34cfbe5be05c5871b51de9329f0603b0474"},
+    {file = "certifi-2023.11.17.tar.gz", hash = "sha256:9b469f3a900bf28dc19b8cfbf8019bf47f7fdd1a65a1d4ffb98fc14166beb4d1"},
 ]
 
 [[package]]
 name = "charset-normalizer"
-version = "3.2.0"
+version = "3.3.2"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [[package]]
 name = "click"
-version = "8.1.6"
+version = "8.1.7"
 description = "Composable command line interface toolkit"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "click-8.1.6-py3-none-any.whl", hash = "sha256:fa244bb30b3b5ee2cae3da8f55c9e5e0c0e86093306301fb418eb9dc40fbded5"},
-    {file = "click-8.1.6.tar.gz", hash = "sha256:48ee849951919527a045bfe3bf7baa8a959c423134e1a5b98c05c20ba75a1cbd"},
+    {file = "click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28"},
+    {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
 ]
 
 [package.dependencies]
@@ -165,13 +180,13 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.2"
+version = "1.2.0"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.1.2-py3-none-any.whl", hash = "sha256:e346e69d186172ca7cf029c8c1d16235aa0e04035e5750b4b95039e65204328f"},
-    {file = "exceptiongroup-1.1.2.tar.gz", hash = "sha256:12c3e887d6485d16943a309616de20ae5582633e0a2eda17f4e10fd61c1e8af5"},
+    {file = "exceptiongroup-1.2.0-py3-none-any.whl", hash = "sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14"},
+    {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"},
 ]
 
 [package.extras]
@@ -179,13 +194,13 @@ test = ["pytest (>=6)"]
 
 [[package]]
 name = "fastapi"
-version = "0.100.0"
+version = "0.100.1"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "fastapi-0.100.0-py3-none-any.whl", hash = "sha256:271662daf986da8fa98dc2b7c7f61c4abdfdccfb4786d79ed8b2878f172c6d5f"},
-    {file = "fastapi-0.100.0.tar.gz", hash = "sha256:acb5f941ea8215663283c10018323ba7ea737c571b67fc7e88e9469c7eb1d12e"},
+    {file = "fastapi-0.100.1-py3-none-any.whl", hash = "sha256:ec6dd52bfc4eff3063cfcd0713b43c87640fefb2687bbbe3d8a08d94049cdf32"},
+    {file = "fastapi-0.100.1.tar.gz", hash = "sha256:522700d7a469e4a973d92321ab93312448fbe20fca9c8da97effc7e7bc56df23"},
 ]
 
 [package.dependencies]
@@ -198,13 +213,13 @@ all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)"
 
 [[package]]
 name = "google-api-core"
-version = "2.11.1"
+version = "2.15.0"
 description = "Google API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.11.1.tar.gz", hash = "sha256:25d29e05a0058ed5f19c61c0a78b1b53adea4d9364b464d014fbda941f6d1c9a"},
-    {file = "google_api_core-2.11.1-py3-none-any.whl", hash = "sha256:d92a5a92dc36dd4f4b9ee4e55528a90e432b059f93aee6ad857f9de8cc7ae94a"},
+    {file = "google-api-core-2.15.0.tar.gz", hash = "sha256:abc978a72658f14a2df1e5e12532effe40f94f868f6e23d95133bd6abcca35ca"},
+    {file = "google_api_core-2.15.0-py3-none-any.whl", hash = "sha256:2aa56d2be495551e66bbff7f729b790546f87d5c90e74781aa77233bcb395a8a"},
 ]
 
 [package.dependencies]
@@ -220,21 +235,19 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.22.0"
+version = "2.25.2"
 description = "Google Authentication Library"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.22.0.tar.gz", hash = "sha256:164cba9af4e6e4e40c3a4f90a1a6c12ee56f14c0b4868d1ca91b32826ab334ce"},
-    {file = "google_auth-2.22.0-py2.py3-none-any.whl", hash = "sha256:d61d1b40897407b574da67da1a833bdc10d5a11642566e506565d1b1a46ba873"},
+    {file = "google-auth-2.25.2.tar.gz", hash = "sha256:42f707937feb4f5e5a39e6c4f343a17300a459aaf03141457ba505812841cc40"},
+    {file = "google_auth-2.25.2-py2.py3-none-any.whl", hash = "sha256:473a8dfd0135f75bb79d878436e568f2695dce456764bf3a02b6f8c540b1d256"},
 ]
 
 [package.dependencies]
 cachetools = ">=2.0.0,<6.0"
 pyasn1-modules = ">=0.2.1"
 rsa = ">=3.1.4,<5"
-six = ">=1.9.0"
-urllib3 = "<2.0"
 
 [package.extras]
 aiohttp = ["aiohttp (>=3.6.2,<4.0.0.dev0)", "requests (>=2.20.0,<3.0.0.dev0)"]
@@ -245,13 +258,13 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-core"
-version = "2.3.3"
+version = "2.4.1"
 description = "Google Cloud API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-core-2.3.3.tar.gz", hash = "sha256:37b80273c8d7eee1ae816b3a20ae43585ea50506cb0e60f3cf5be5f87f1373cb"},
-    {file = "google_cloud_core-2.3.3-py2.py3-none-any.whl", hash = "sha256:fbd11cad3e98a7e5b0343dc07cb1039a5ffd7a5bb96e1f1e27cee4bda4a90863"},
+    {file = "google-cloud-core-2.4.1.tar.gz", hash = "sha256:9b7749272a812bde58fff28868d0c5e2f585b82f37e09a1f6ed2d4d10f134073"},
+    {file = "google_cloud_core-2.4.1-py2.py3-none-any.whl", hash = "sha256:a9e6a4422b9ac5c29f79a0ede9485473338e2ce78d91f2370c01e730eab22e61"},
 ]
 
 [package.dependencies]
@@ -259,24 +272,25 @@ google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
-grpc = ["grpcio (>=1.38.0,<2.0dev)"]
+grpc = ["grpcio (>=1.38.0,<2.0dev)", "grpcio-status (>=1.38.0,<2.0.dev0)"]
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.10.0"
+version = "2.14.0"
 description = "Google Cloud Storage API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-storage-2.10.0.tar.gz", hash = "sha256:934b31ead5f3994e5360f9ff5750982c5b6b11604dc072bc452c25965e076dc7"},
-    {file = "google_cloud_storage-2.10.0-py2.py3-none-any.whl", hash = "sha256:9433cf28801671de1c80434238fb1e7e4a1ba3087470e90f70c928ea77c2b9d7"},
+    {file = "google-cloud-storage-2.14.0.tar.gz", hash = "sha256:2d23fcf59b55e7b45336729c148bb1c464468c69d5efbaee30f7201dd90eb97e"},
+    {file = "google_cloud_storage-2.14.0-py2.py3-none-any.whl", hash = "sha256:8641243bbf2a2042c16a6399551fbb13f062cbc9a2de38d6c0bb5426962e9dbd"},
 ]
 
 [package.dependencies]
 google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
-google-auth = ">=1.25.0,<3.0dev"
+google-auth = ">=2.23.3,<3.0dev"
 google-cloud-core = ">=2.3.0,<3.0dev"
-google-resumable-media = ">=2.3.2"
+google-crc32c = ">=1.0,<2.0dev"
+google-resumable-media = ">=2.6.0"
 requests = ">=2.18.0,<3.0.0dev"
 
 [package.extras]
@@ -364,31 +378,31 @@ testing = ["pytest"]
 
 [[package]]
 name = "google-resumable-media"
-version = "2.5.0"
+version = "2.7.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
 optional = false
 python-versions = ">= 3.7"
 files = [
-    {file = "google-resumable-media-2.5.0.tar.gz", hash = "sha256:218931e8e2b2a73a58eb354a288e03a0fd5fb1c4583261ac6e4c078666468c93"},
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+    {file = "google-resumable-media-2.7.0.tar.gz", hash = "sha256:5f18f5fa9836f4b083162064a1c2c98c17239bfda9ca50ad970ccf905f3e625b"},
+    {file = "google_resumable_media-2.7.0-py2.py3-none-any.whl", hash = "sha256:79543cfe433b63fd81c0844b7803aba1bb8950b47bedf7d980c38fa123937e08"},
 ]
 
 [package.dependencies]
 google-crc32c = ">=1.0,<2.0dev"
 
 [package.extras]
-aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)"]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0dev)", "google-auth (>=1.22.0,<2.0dev)"]
 requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.59.1"
+version = "1.62.0"
 description = "Common protobufs used in Google APIs"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "googleapis-common-protos-1.59.1.tar.gz", hash = "sha256:b35d530fe825fb4227857bc47ad84c33c809ac96f312e13182bdeaa2abe1178a"},
-    {file = "googleapis_common_protos-1.59.1-py2.py3-none-any.whl", hash = "sha256:0cbedb6fb68f1c07e18eb4c48256320777707e7d0c55063ae56c15db3224a61e"},
+    {file = "googleapis-common-protos-1.62.0.tar.gz", hash = "sha256:83f0ece9f94e5672cced82f592d2a5edf527a96ed1794f0bab36d5735c996277"},
+    {file = "googleapis_common_protos-1.62.0-py2.py3-none-any.whl", hash = "sha256:4750113612205514f9f6aa4cb00d523a94f3e8c06c5ad2fee466387dc4875f07"},
 ]
 
 [package.dependencies]
@@ -410,158 +424,168 @@ files = [
 
 [[package]]
 name = "idna"
-version = "3.4"
+version = "3.6"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
 files = [
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-    {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
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+    {file = "idna-3.6.tar.gz", hash = "sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca"},
 ]
 
 [[package]]
 name = "joblib"
-version = "1.3.1"
+version = "1.3.2"
 description = "Lightweight pipelining with Python functions"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "joblib-1.3.2.tar.gz", hash = "sha256:92f865e621e17784e7955080b6d042489e3b8e294949cc44c6eac304f59772b1"},
 ]
 
 [[package]]
 name = "numpy"
-version = "1.25.1"
+version = "1.26.2"
 description = "Fundamental package for array computing in Python"
 optional = false
 python-versions = ">=3.9"
 files = [
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 [package.dependencies]
@@ -726,13 +754,13 @@ six = ">=1.5"
 
 [[package]]
 name = "pytz"
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+version = "2023.3.post1"
 description = "World timezone definitions, modern and historical"
 optional = false
 python-versions = "*"
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 [[package]]
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-numpy = ">=1.17.3"
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 scipy = ">=1.5.0"
 threadpoolctl = ">=2.0.0"
 
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+    {file = "scipy-1.11.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:6e619aba2df228a9b34718efb023966da781e89dd3d21637b27f2e54db0410d7"},
+    {file = "scipy-1.11.4-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:f3cd9e7b3c2c1ec26364856f9fbe78695fe631150f94cd1c22228456404cf1ec"},
+    {file = "scipy-1.11.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d10e45a6c50211fe256da61a11c34927c68f277e03138777bdebedd933712fea"},
+    {file = "scipy-1.11.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:91af76a68eeae0064887a48e25c4e616fa519fa0d38602eda7e0f97d65d57937"},
+    {file = "scipy-1.11.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:6df1468153a31cf55ed5ed39647279beb9cfb5d3f84369453b49e4b8502394fd"},
+    {file = "scipy-1.11.4-cp39-cp39-win_amd64.whl", hash = "sha256:ee410e6de8f88fd5cf6eadd73c135020bfbbbdfcd0f6162c36a7638a1ea8cc65"},
+    {file = "scipy-1.11.4.tar.gz", hash = "sha256:90a2b78e7f5733b9de748f589f09225013685f9b218275257f8a8168ededaeaa"},
 ]
 
 [package.dependencies]
-numpy = ">=1.18.5,<1.26.0"
+numpy = ">=1.21.6,<1.28.0"
 
 [package.extras]
-dev = ["flake8", "mypy", "pycodestyle", "typing_extensions"]
-doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-panels (>=0.5.2)", "sphinx-tabs"]
-test = ["asv", "gmpy2", "mpmath", "pytest", "pytest-cov", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
+dev = ["click", "cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyle", "pydevtool", "rich-click", "ruff", "types-psutil", "typing_extensions"]
+doc = ["jupytext", "matplotlib (>2)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-design (>=0.2.0)"]
+test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
 [[package]]
 name = "six"
@@ -892,24 +929,24 @@ full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyam
 
 [[package]]
 name = "threadpoolctl"
-version = "3.1.0"
+version = "3.2.0"
 description = "threadpoolctl"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 files = [
-    {file = "threadpoolctl-3.1.0-py3-none-any.whl", hash = "sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b"},
-    {file = "threadpoolctl-3.1.0.tar.gz", hash = "sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380"},
+    {file = "threadpoolctl-3.2.0-py3-none-any.whl", hash = "sha256:2b7818516e423bdaebb97c723f86a7c6b0a83d3f3b0970328d66f4d9104dc032"},
+    {file = "threadpoolctl-3.2.0.tar.gz", hash = "sha256:c96a0ba3bdddeaca37dc4cc7344aafad41cdb8c313f74fdfe387a867bba93355"},
 ]
 
 [[package]]
 name = "typing-extensions"
-version = "4.7.1"
-description = "Backported and Experimental Type Hints for Python 3.7+"
+version = "4.9.0"
+description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "typing_extensions-4.7.1-py3-none-any.whl", hash = "sha256:440d5dd3af93b060174bf433bccd69b0babc3b15b1a8dca43789fd7f61514b36"},
-    {file = "typing_extensions-4.7.1.tar.gz", hash = "sha256:b75ddc264f0ba5615db7ba217daeb99701ad295353c45f9e95963337ceeeffb2"},
+    {file = "typing_extensions-4.9.0-py3-none-any.whl", hash = "sha256:af72aea155e91adfc61c3ae9e0e342dbc0cba726d6cba4b6c72c1f34e47291cd"},
+    {file = "typing_extensions-4.9.0.tar.gz", hash = "sha256:23478f88c37f27d76ac8aee6c905017a143b0b1b886c3c9f66bc2fd94f9f5783"},
 ]
 
 [[package]]
@@ -925,29 +962,29 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "1.26.16"
+version = "2.1.0"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
+python-versions = ">=3.8"
 files = [
-    {file = "urllib3-1.26.16-py2.py3-none-any.whl", hash = "sha256:8d36afa7616d8ab714608411b4a3b13e58f463aee519024578e062e141dce20f"},
-    {file = "urllib3-1.26.16.tar.gz", hash = "sha256:8f135f6502756bde6b2a9b28989df5fbe87c9970cecaa69041edcce7f0589b14"},
+    {file = "urllib3-2.1.0-py3-none-any.whl", hash = "sha256:55901e917a5896a349ff771be919f8bd99aff50b79fe58fec595eb37bbc56bb3"},
+    {file = "urllib3-2.1.0.tar.gz", hash = "sha256:df7aa8afb0148fa78488e7899b2c59b5f4ffcfa82e6c54ccb9dd37c1d7b52d54"},
 ]
 
 [package.extras]
-brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"]
-secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"]
-socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
+brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.23.1"
+version = "0.23.2"
 description = "The lightning-fast ASGI server."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "uvicorn-0.23.1-py3-none-any.whl", hash = "sha256:1d55d46b83ee4ce82b4e82f621f2050adb3eb7b5481c13f9af1744951cae2f1f"},
-    {file = "uvicorn-0.23.1.tar.gz", hash = "sha256:da9b0c8443b2d7ee9db00a345f1eee6db7317432c9d4400f5049cc8d358383be"},
+    {file = "uvicorn-0.23.2-py3-none-any.whl", hash = "sha256:1f9be6558f01239d4fdf22ef8126c39cb1ad0addf76c40e760549d2c2f43ab53"},
+    {file = "uvicorn-0.23.2.tar.gz", hash = "sha256:4d3cc12d7727ba72b64d12d3cc7743124074c0a69f7b201512fc50c3e3f1569a"},
 ]
 
 [package.dependencies]
@@ -988,4 +1025,4 @@ scikit-learn = ["scikit-learn"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "2bbdc91e77ecba39a913eb039abe6c1be55f6dcd0b756ff97b8f11b7e376c970"
+content-hash = "1906c721cd1ef436f516e02f8a63b97fd918852b1c9e194fcf2f90c16cce4ad9"
diff --git a/model/serving/main.py b/model/prediction/main.py
similarity index 100%
rename from model/serving/main.py
rename to model/prediction/main.py
diff --git a/model/pyproject.toml b/model/pyproject.toml
index e879a489..4a62162b 100644
--- a/model/pyproject.toml
+++ b/model/pyproject.toml
@@ -11,8 +11,7 @@ scikit-learn = "^1.3.0"
 xgboost = "^1.7.6"
 pandas = "^2.0.3"
 
-
-[tool.poetry.group.serving.dependencies]
+[tool.poetry.group.prediction.dependencies]
 fastapi = {extras = ["uvicorn"], version = "^0.100.0"}
 uvicorn = "^0.23.1"
 google-cloud-storage = "^2.10.0"
diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index de28886b..e94bea2f 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -2,13 +2,13 @@
 
 [[package]]
 name = "anyio"
-version = "4.0.0"
+version = "4.1.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "anyio-4.0.0-py3-none-any.whl", hash = "sha256:cfdb2b588b9fc25ede96d8db56ed50848b0b649dca3dd1df0b11f683bb9e0b5f"},
-    {file = "anyio-4.0.0.tar.gz", hash = "sha256:f7ed51751b2c2add651e5747c891b47e26d2a21be5d32d9311dfe9692f3e5d7a"},
+    {file = "anyio-4.1.0-py3-none-any.whl", hash = "sha256:56a415fbc462291813a94528a779597226619c8e78af7de0507333f700011e5f"},
+    {file = "anyio-4.1.0.tar.gz", hash = "sha256:5a0bec7085176715be77df87fc66d6c9d70626bd752fcc85f57cdbee5b3760da"},
 ]
 
 [package.dependencies]
@@ -17,9 +17,9 @@ idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.22)"]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
 
 [[package]]
 name = "appnope"
@@ -160,13 +160,13 @@ tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pyte
 
 [[package]]
 name = "babel"
-version = "2.13.1"
+version = "2.14.0"
 description = "Internationalization utilities"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "Babel-2.13.1-py3-none-any.whl", hash = "sha256:7077a4984b02b6727ac10f1f7294484f737443d7e2e66c5e4380e41a3ae0b4ed"},
-    {file = "Babel-2.13.1.tar.gz", hash = "sha256:33e0952d7dd6374af8dbf6768cc4ddf3ccfefc244f9986d4074704f2fbd18900"},
+    {file = "Babel-2.14.0-py3-none-any.whl", hash = "sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287"},
+    {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"},
 ]
 
 [package.extras]
@@ -221,13 +221,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.7.22"
+version = "2023.11.17"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
-    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
+    {file = "certifi-2023.11.17-py3-none-any.whl", hash = "sha256:e036ab49d5b79556f99cfc2d9320b34cfbe5be05c5871b51de9329f0603b0474"},
+    {file = "certifi-2023.11.17.tar.gz", hash = "sha256:9b469f3a900bf28dc19b8cfbf8019bf47f7fdd1a65a1d4ffb98fc14166beb4d1"},
 ]
 
 [[package]]
@@ -577,13 +577,13 @@ files = [
 
 [[package]]
 name = "distlib"
-version = "0.3.7"
+version = "0.3.8"
 description = "Distribution utilities"
 optional = false
 python-versions = "*"
 files = [
-    {file = "distlib-0.3.7-py2.py3-none-any.whl", hash = "sha256:2e24928bc811348f0feb63014e97aaae3037f2cf48712d51ae61df7fd6075057"},
-    {file = "distlib-0.3.7.tar.gz", hash = "sha256:9dafe54b34a028eafd95039d5e5d4851a13734540f1331060d31c9916e7147a8"},
+    {file = "distlib-0.3.8-py2.py3-none-any.whl", hash = "sha256:034db59a0b96f8ca18035f36290806a9a6e6bd9d1ff91e45a7f172eb17e51784"},
+    {file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"},
 ]
 
 [[package]]
@@ -599,13 +599,13 @@ files = [
 
 [[package]]
 name = "exceptiongroup"
-version = "1.1.3"
+version = "1.2.0"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.1.3-py3-none-any.whl", hash = "sha256:343280667a4585d195ca1cf9cef84a4e178c4b6cf2274caef9859782b567d5e3"},
-    {file = "exceptiongroup-1.1.3.tar.gz", hash = "sha256:097acd85d473d75af5bb98e41b61ff7fe35efe6675e4f9370ec6ec5126d160e9"},
+    {file = "exceptiongroup-1.2.0-py3-none-any.whl", hash = "sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14"},
+    {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"},
 ]
 
 [package.extras]
@@ -627,13 +627,13 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 
 [[package]]
 name = "fastjsonschema"
-version = "2.18.1"
+version = "2.19.0"
 description = "Fastest Python implementation of JSON schema"
 optional = false
 python-versions = "*"
 files = [
-    {file = "fastjsonschema-2.18.1-py3-none-any.whl", hash = "sha256:aec6a19e9f66e9810ab371cc913ad5f4e9e479b63a7072a2cd060a9369e329a8"},
-    {file = "fastjsonschema-2.18.1.tar.gz", hash = "sha256:06dc8680d937628e993fa0cd278f196d20449a1adc087640710846b324d422ea"},
+    {file = "fastjsonschema-2.19.0-py3-none-any.whl", hash = "sha256:b9fd1a2dd6971dbc7fee280a95bd199ae0dd9ce22beb91cc75e9c1c528a5170e"},
+    {file = "fastjsonschema-2.19.0.tar.gz", hash = "sha256:e25df6647e1bc4a26070b700897b07b542ec898dd4f1f6ea013e7f6a88417225"},
 ]
 
 [package.extras]
@@ -668,13 +668,13 @@ files = [
 
 [[package]]
 name = "google-api-core"
-version = "2.12.0"
+version = "2.15.0"
 description = "Google API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-core-2.12.0.tar.gz", hash = "sha256:c22e01b1e3c4dcd90998494879612c38d0a3411d1f7b679eb89e2abe3ce1f553"},
-    {file = "google_api_core-2.12.0-py3-none-any.whl", hash = "sha256:ec6054f7d64ad13b41e43d96f735acbd763b0f3b695dabaa2d579673f6a6e160"},
+    {file = "google-api-core-2.15.0.tar.gz", hash = "sha256:abc978a72658f14a2df1e5e12532effe40f94f868f6e23d95133bd6abcca35ca"},
+    {file = "google_api_core-2.15.0-py3-none-any.whl", hash = "sha256:2aa56d2be495551e66bbff7f729b790546f87d5c90e74781aa77233bcb395a8a"},
 ]
 
 [package.dependencies]
@@ -692,13 +692,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-auth"
-version = "2.23.4"
+version = "2.25.2"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.23.4.tar.gz", hash = "sha256:79905d6b1652187def79d491d6e23d0cbb3a21d3c7ba0dbaa9c8a01906b13ff3"},
-    {file = "google_auth-2.23.4-py2.py3-none-any.whl", hash = "sha256:d4bbc92fe4b8bfd2f3e8d88e5ba7085935da208ee38a134fc280e7ce682a05f2"},
+    {file = "google-auth-2.25.2.tar.gz", hash = "sha256:42f707937feb4f5e5a39e6c4f343a17300a459aaf03141457ba505812841cc40"},
+    {file = "google_auth-2.25.2-py2.py3-none-any.whl", hash = "sha256:473a8dfd0135f75bb79d878436e568f2695dce456764bf3a02b6f8c540b1d256"},
 ]
 
 [package.dependencies]
@@ -715,13 +715,13 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.36.0"
+version = "1.38.1"
 description = "Vertex AI API client library"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "google-cloud-aiplatform-1.36.0.tar.gz", hash = "sha256:c35eb179fa3107c262024a63bb4a3dc1887678424a0b9f49f0da3f5179896186"},
-    {file = "google_cloud_aiplatform-1.36.0-py2.py3-none-any.whl", hash = "sha256:06adb1605208a9bdbadd8c4deeaeb6511a7f59220ef606e2d95ccc1da705ebda"},
+    {file = "google-cloud-aiplatform-1.38.1.tar.gz", hash = "sha256:30439d914bb028443c0506cc0e6dd825cff5401aeb8233e13d8cfd77c3c87da1"},
+    {file = "google_cloud_aiplatform-1.38.1-py2.py3-none-any.whl", hash = "sha256:5e1fcd1068dd2c4f0fc89aa616e34a8b9434eaa72ea6216f5036ef26f08bd448"},
 ]
 
 [package.dependencies]
@@ -754,45 +754,43 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
 name = "google-cloud-bigquery"
-version = "3.13.0"
+version = "3.14.1"
 description = "Google BigQuery API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-cloud-bigquery-3.13.0.tar.gz", hash = "sha256:794ccfc93ccb0e0ad689442f896f9c82de56da0fe18a195531bb37096c2657d6"},
-    {file = "google_cloud_bigquery-3.13.0-py2.py3-none-any.whl", hash = "sha256:eda3dbcff676e17962c54e5224e415b55e4f6833a5c896c6c8902b69e7dba4b4"},
+    {file = "google-cloud-bigquery-3.14.1.tar.gz", hash = "sha256:aa15bd86f79ea76824c7d710f5ae532323c4b3ba01ef4abff42d4ee7a2e9b142"},
+    {file = "google_cloud_bigquery-3.14.1-py2.py3-none-any.whl", hash = "sha256:a8ded18455da71508db222b7c06197bc12b6dbc6ed5b0b64e7007b76d7016957"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev", extras = ["grpc"]}
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-cloud-core = ">=1.6.0,<3.0.0dev"
 google-resumable-media = ">=0.6.0,<3.0dev"
-grpcio = ">=1.47.0,<2.0dev"
 packaging = ">=20.0.0"
-proto-plus = ">=1.15.0,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 python-dateutil = ">=2.7.2,<3.0dev"
 requests = ">=2.21.0,<3.0.0dev"
 
 [package.extras]
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+all = ["Shapely (>=1.8.4,<3.0.0dev)", "db-dtypes (>=0.3.0,<2.0.0dev)", "geopandas (>=0.9.0,<1.0dev)", "google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "importlib-metadata (>=1.0.0)", "ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)", "ipywidgets (>=7.7.0)", "opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)", "pandas (>=1.1.0)", "proto-plus (>=1.15.0,<2.0.0dev)", "protobuf (>=3.19.5,!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev)", "pyarrow (>=3.0.0)", "tqdm (>=4.7.4,<5.0.0dev)"]
+bigquery-v2 = ["proto-plus (>=1.15.0,<2.0.0dev)", "protobuf (>=3.19.5,!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev)"]
 bqstorage = ["google-cloud-bigquery-storage (>=2.6.0,<3.0.0dev)", "grpcio (>=1.47.0,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "pyarrow (>=3.0.0)"]
 geopandas = ["Shapely (>=1.8.4,<3.0.0dev)", "geopandas (>=0.9.0,<1.0dev)"]
 ipython = ["ipykernel (>=6.0.0)", "ipython (>=7.23.1,!=8.1.0)"]
 ipywidgets = ["ipykernel (>=6.0.0)", "ipywidgets (>=7.7.0)"]
 opentelemetry = ["opentelemetry-api (>=1.1.0)", "opentelemetry-instrumentation (>=0.20b0)", "opentelemetry-sdk (>=1.1.0)"]
-pandas = ["db-dtypes (>=0.3.0,<2.0.0dev)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)"]
+pandas = ["db-dtypes (>=0.3.0,<2.0.0dev)", "importlib-metadata (>=1.0.0)", "pandas (>=1.1.0)", "pyarrow (>=3.0.0)"]
 tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"]
 
 [[package]]
 name = "google-cloud-core"
-version = "2.3.3"
+version = "2.4.1"
 description = "Google Cloud API client core library"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "google-cloud-core-2.4.1.tar.gz", hash = "sha256:9b7749272a812bde58fff28868d0c5e2f585b82f37e09a1f6ed2d4d10f134073"},
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 ]
 
 [package.dependencies]
@@ -800,53 +798,54 @@ google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-auth = ">=1.25.0,<3.0dev"
 
 [package.extras]
-grpc = ["grpcio (>=1.38.0,<2.0dev)"]
+grpc = ["grpcio (>=1.38.0,<2.0dev)", "grpcio-status (>=1.38.0,<2.0.dev0)"]
 
 [[package]]
 name = "google-cloud-pipeline-components"
-version = "2.3.0"
+version = "2.8.0"
 description = "This SDK enables a set of First Party (Google owned) pipeline components that allow users to take their experience from Vertex AI SDK and other Google Cloud services and create a corresponding pipeline using KFP or Managed Pipelines."
 optional = false
 python-versions = ">=3.7.0,<3.12.0"
 files = [
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+    {file = "google_cloud_pipeline_components-2.8.0-py3-none-any.whl", hash = "sha256:2b21bc6f65e4c47f21a5c5de472a770fe8ca7c639252031fe2f4c054a6095f4a"},
 ]
 
 [package.dependencies]
 google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
 google-cloud-aiplatform = ">=1.14.0,<2"
-kfp = ">=2.0.0b10,<3.0.0"
+Jinja2 = "3.1.2"
+kfp = ">=2.0.0b10,<=2.4.0"
 
 [package.extras]
-docs = ["autodocsumm (==0.2.9)", "grpcio-status (<=1.47.0)", "m2r2 (==0.3.2)", "protobuf (>=3.19.0,<4.0.0dev)", "sphinx (==5.0.2)", "sphinx-immaterial (==0.9.0)", "sphinx-notfound-page (==0.8.3)", "sphinx-rtd-theme (==1.0.0)"]
+docs = ["autodocsumm (==0.2.9)", "commonmark (==0.9.1)", "grpcio-status (<=1.47.0)", "m2r2 (==0.3.2)", "protobuf (>=3.19.0,<4.0.0dev)", "sphinx (==5.0.2)", "sphinx-immaterial (==0.9.0)", "sphinx-notfound-page (==0.8.3)", "sphinx-rtd-theme (==1.0.0)"]
 tests = ["flake8 (>=3.0.0)", "mock (>=4.0.0)", "pytest (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-resource-manager"
-version = "1.10.4"
+version = "1.11.0"
 description = "Google Cloud Resource Manager API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
 google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0dev"
-proto-plus = ">=1.22.0,<2.0.0dev"
+proto-plus = ">=1.22.3,<2.0.0dev"
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
 
 [[package]]
 name = "google-cloud-storage"
-version = "2.13.0"
+version = "2.12.0"
 description = "Google Cloud Storage API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -942,13 +941,13 @@ testing = ["pytest"]
 
 [[package]]
 name = "google-resumable-media"
-version = "2.6.0"
+version = "2.7.0"
 description = "Utilities for Google Media Downloads and Resumable Uploads"
 optional = false
 python-versions = ">= 3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -960,13 +959,13 @@ requests = ["requests (>=2.18.0,<3.0.0dev)"]
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.61.0"
+version = "1.62.0"
 description = "Common protobufs used in Google APIs"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -978,13 +977,13 @@ grpc = ["grpcio (>=1.44.0,<2.0.0.dev0)"]
 
 [[package]]
 name = "grpc-google-iam-v1"
-version = "0.12.6"
+version = "0.13.0"
 description = "IAM API client library"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -994,69 +993,69 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.1 || >4.21.1,<4
 
 [[package]]
 name = "grpcio"
-version = "1.59.2"
+version = "1.60.0"
 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [[package]]
 name = "grpcio-status"
@@ -1076,13 +1075,13 @@ protobuf = ">=3.12.0"
 
 [[package]]
 name = "identify"
-version = "2.5.31"
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 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.extras]
@@ -1090,31 +1089,31 @@ license = ["ukkonen"]
 
 [[package]]
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 description = "Internationalized Domain Names in Applications (IDNA)"
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@@ -1131,13 +1130,13 @@ files = [
 
 [[package]]
 name = "ipykernel"
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 description = "IPython Kernel for Jupyter"
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 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -1164,24 +1163,23 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio"
 
 [[package]]
 name = "ipython"
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 python-versions = ">=3.9"
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+    {file = "ipython-8.18.1.tar.gz", hash = "sha256:ca6f079bb33457c66e233e4580ebfc4128855b4cf6370dddd73842a9563e8a27"},
 ]
 
 [package.dependencies]
-appnope = {version = "*", markers = "sys_platform == \"darwin\""}
 colorama = {version = "*", markers = "sys_platform == \"win32\""}
 decorator = "*"
 exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
 jedi = ">=0.16"
 matplotlib-inline = "*"
 pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
-prompt-toolkit = ">=3.0.30,<3.0.37 || >3.0.37,<3.1.0"
+prompt-toolkit = ">=3.0.41,<3.1.0"
 pygments = ">=2.4.0"
 stack-data = "*"
 traitlets = ">=5"
@@ -1298,13 +1296,13 @@ files = [
 
 [[package]]
 name = "jsonschema"
-version = "4.19.2"
+version = "4.20.0"
 description = "An implementation of JSON Schema validation for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jsonschema-4.19.2-py3-none-any.whl", hash = "sha256:eee9e502c788e89cb166d4d37f43084e3b64ab405c795c03d343a4dbc2c810fc"},
-    {file = "jsonschema-4.19.2.tar.gz", hash = "sha256:c9ff4d7447eed9592c23a12ccee508baf0dd0d59650615e847feb6cdca74f392"},
+    {file = "jsonschema-4.20.0-py3-none-any.whl", hash = "sha256:ed6231f0429ecf966f5bc8dfef245998220549cbbcf140f913b7464c52c3b6b3"},
+    {file = "jsonschema-4.20.0.tar.gz", hash = "sha256:4f614fd46d8d61258610998997743ec5492a648b33cf478c1ddc23ed4598a5fa"},
 ]
 
 [package.dependencies]
@@ -1327,17 +1325,17 @@ format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 
 [[package]]
 name = "jsonschema-specifications"
-version = "2023.7.1"
+version = "2023.11.2"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jsonschema_specifications-2023.7.1-py3-none-any.whl", hash = "sha256:05adf340b659828a004220a9613be00fa3f223f2b82002e273dee62fd50524b1"},
-    {file = "jsonschema_specifications-2023.7.1.tar.gz", hash = "sha256:c91a50404e88a1f6ba40636778e2ee08f6e24c5613fe4c53ac24578a5a7f72bb"},
+    {file = "jsonschema_specifications-2023.11.2-py3-none-any.whl", hash = "sha256:e74ba7c0a65e8cb49dc26837d6cfe576557084a8b423ed16a420984228104f93"},
+    {file = "jsonschema_specifications-2023.11.2.tar.gz", hash = "sha256:9472fc4fea474cd74bea4a2b190daeccb5a9e4db2ea80efcf7a1b582fc9a81b8"},
 ]
 
 [package.dependencies]
-referencing = ">=0.28.0"
+referencing = ">=0.31.0"
 
 [[package]]
 name = "jupyter"
@@ -1453,13 +1451,13 @@ test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "p
 
 [[package]]
 name = "jupyter-lsp"
-version = "2.2.0"
+version = "2.2.1"
 description = "Multi-Language Server WebSocket proxy for Jupyter Notebook/Lab server"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter-lsp-2.2.0.tar.gz", hash = "sha256:8ebbcb533adb41e5d635eb8fe82956b0aafbf0fd443b6c4bfa906edeeb8635a1"},
-    {file = "jupyter_lsp-2.2.0-py3-none-any.whl", hash = "sha256:9e06b8b4f7dd50300b70dd1a78c0c3b0c3d8fa68e0f2d8a5d1fbab62072aca3f"},
+    {file = "jupyter-lsp-2.2.1.tar.gz", hash = "sha256:b17fab6d70fe83c8896b0cff59237640038247c196056b43684a0902b6a9e0fb"},
+    {file = "jupyter_lsp-2.2.1-py3-none-any.whl", hash = "sha256:17a689910c5e4ae5e7d334b02f31d08ffbe98108f6f658fb05e4304b4345368b"},
 ]
 
 [package.dependencies]
@@ -1468,13 +1466,13 @@ jupyter-server = ">=1.1.2"
 
 [[package]]
 name = "jupyter-server"
-version = "2.10.0"
+version = "2.12.1"
 description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_server-2.10.0-py3-none-any.whl", hash = "sha256:dde56c9bc3cb52d7b72cc0f696d15d7163603526f1a758eb4a27405b73eab2a5"},
-    {file = "jupyter_server-2.10.0.tar.gz", hash = "sha256:47b8f5e63440125cb1bb8957bf12b18453ee5ed9efe42d2f7b2ca66a7019a278"},
+    {file = "jupyter_server-2.12.1-py3-none-any.whl", hash = "sha256:fd030dd7be1ca572e4598203f718df6630c12bd28a599d7f1791c4d7938e1010"},
+    {file = "jupyter_server-2.12.1.tar.gz", hash = "sha256:dc77b7dcc5fc0547acba2b2844f01798008667201eea27c6319ff9257d700a6d"},
 ]
 
 [package.dependencies]
@@ -1483,7 +1481,7 @@ argon2-cffi = "*"
 jinja2 = "*"
 jupyter-client = ">=7.4.4"
 jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
-jupyter-events = ">=0.6.0"
+jupyter-events = ">=0.9.0"
 jupyter-server-terminals = "*"
 nbconvert = ">=6.4.4"
 nbformat = ">=5.3.0"
@@ -1504,13 +1502,13 @@ test = ["flaky", "ipykernel", "pre-commit", "pytest (>=7.0)", "pytest-console-sc
 
 [[package]]
 name = "jupyter-server-terminals"
-version = "0.4.4"
+version = "0.5.0"
 description = "A Jupyter Server Extension Providing Terminals."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_server_terminals-0.4.4-py3-none-any.whl", hash = "sha256:75779164661cec02a8758a5311e18bb8eb70c4e86c6b699403100f1585a12a36"},
-    {file = "jupyter_server_terminals-0.4.4.tar.gz", hash = "sha256:57ab779797c25a7ba68e97bcfb5d7740f2b5e8a83b5e8102b10438041a7eac5d"},
+    {file = "jupyter_server_terminals-0.5.0-py3-none-any.whl", hash = "sha256:2fc0692c883bfd891f4fba0c4b4a684a37234b0ba472f2e97ed0a3888f46e1e4"},
+    {file = "jupyter_server_terminals-0.5.0.tar.gz", hash = "sha256:ebcd68c9afbf98a480a533e6f3266354336e645536953b7abcc7bdeebc0154a3"},
 ]
 
 [package.dependencies]
@@ -1518,18 +1516,18 @@ pywinpty = {version = ">=2.0.3", markers = "os_name == \"nt\""}
 terminado = ">=0.8.3"
 
 [package.extras]
-docs = ["jinja2", "jupyter-server", "mistune (<3.0)", "myst-parser", "nbformat", "packaging", "pydata-sphinx-theme", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
-test = ["coverage", "jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-cov", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"]
+docs = ["jinja2", "jupyter-server", "mistune (<4.0)", "myst-parser", "nbformat", "packaging", "pydata-sphinx-theme", "sphinxcontrib-github-alt", "sphinxcontrib-openapi", "sphinxcontrib-spelling", "sphinxemoji", "tornado"]
+test = ["jupyter-server (>=2.0.0)", "pytest (>=7.0)", "pytest-jupyter[server] (>=0.5.3)", "pytest-timeout"]
 
 [[package]]
 name = "jupyterlab"
-version = "4.0.8"
+version = "4.0.9"
 description = "JupyterLab computational environment"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab-4.0.8-py3-none-any.whl", hash = "sha256:2ff5aa2a51eb21df241d6011c236e88bd1ff9a5dbb75bebc54472f9c18bfffa4"},
-    {file = "jupyterlab-4.0.8.tar.gz", hash = "sha256:c4fe93f977bcc987bd395d7fae5ab02e0c042bf4e0f7c95196f3e2e578c2fb3a"},
+    {file = "jupyterlab-4.0.9-py3-none-any.whl", hash = "sha256:9f6f8e36d543fdbcc3df961a1d6a3f524b4a4001be0327a398f68fa4e534107c"},
+    {file = "jupyterlab-4.0.9.tar.gz", hash = "sha256:9ebada41d52651f623c0c9f069ddb8a21d6848e4c887d8e5ddc0613166ed5c0b"},
 ]
 
 [package.dependencies]
@@ -1548,31 +1546,31 @@ tornado = ">=6.2.0"
 traitlets = "*"
 
 [package.extras]
-dev = ["black[jupyter] (==23.10.1)", "build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.0.292)"]
+dev = ["black[jupyter] (==23.10.1)", "build", "bump2version", "coverage", "hatch", "pre-commit", "pytest-cov", "ruff (==0.1.4)"]
 docs = ["jsx-lexer", "myst-parser", "pydata-sphinx-theme (>=0.13.0)", "pytest", "pytest-check-links", "pytest-tornasync", "sphinx (>=1.8,<7.2.0)", "sphinx-copybutton"]
 docs-screenshots = ["altair (==5.0.1)", "ipython (==8.14.0)", "ipywidgets (==8.0.6)", "jupyterlab-geojson (==3.4.0)", "jupyterlab-language-pack-zh-cn (==4.0.post0)", "matplotlib (==3.7.1)", "nbconvert (>=7.0.0)", "pandas (==2.0.2)", "scipy (==1.10.1)", "vega-datasets (==0.9.0)"]
 test = ["coverage", "pytest (>=7.0)", "pytest-check-links (>=0.7)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter (>=0.5.3)", "pytest-timeout", "pytest-tornasync", "requests", "requests-cache", "virtualenv"]
 
 [[package]]
 name = "jupyterlab-pygments"
-version = "0.2.2"
+version = "0.3.0"
 description = "Pygments theme using JupyterLab CSS variables"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab_pygments-0.2.2-py2.py3-none-any.whl", hash = "sha256:2405800db07c9f770863bcf8049a529c3dd4d3e28536638bd7c1c01d2748309f"},
-    {file = "jupyterlab_pygments-0.2.2.tar.gz", hash = "sha256:7405d7fde60819d905a9fa8ce89e4cd830e318cdad22a0030f7a901da705585d"},
+    {file = "jupyterlab_pygments-0.3.0-py3-none-any.whl", hash = "sha256:841a89020971da1d8693f1a99997aefc5dc424bb1b251fd6322462a1b8842780"},
+    {file = "jupyterlab_pygments-0.3.0.tar.gz", hash = "sha256:721aca4d9029252b11cfa9d185e5b5af4d54772bb8072f9b7036f4170054d35d"},
 ]
 
 [[package]]
 name = "jupyterlab-server"
-version = "2.25.0"
+version = "2.25.2"
 description = "A set of server components for JupyterLab and JupyterLab like applications."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyterlab_server-2.25.0-py3-none-any.whl", hash = "sha256:c9f67a98b295c5dee87f41551b0558374e45d449f3edca153dd722140630dcb2"},
-    {file = "jupyterlab_server-2.25.0.tar.gz", hash = "sha256:77c2f1f282d610f95e496e20d5bf1d2a7706826dfb7b18f3378ae2870d272fb7"},
+    {file = "jupyterlab_server-2.25.2-py3-none-any.whl", hash = "sha256:5b1798c9cc6a44f65c757de9f97fc06fc3d42535afbf47d2ace5e964ab447aaf"},
+    {file = "jupyterlab_server-2.25.2.tar.gz", hash = "sha256:bd0ec7a99ebcedc8bcff939ef86e52c378e44c2707e053fcd81d046ce979ee63"},
 ]
 
 [package.dependencies]
@@ -1588,7 +1586,7 @@ requests = ">=2.31"
 [package.extras]
 docs = ["autodoc-traits", "jinja2 (<3.2.0)", "mistune (<4)", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinxcontrib-openapi (>0.8)"]
 openapi = ["openapi-core (>=0.18.0,<0.19.0)", "ruamel-yaml"]
-test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-validator (>=0.6.0,<0.7.0)", "pytest (>=7.0)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "ruamel-yaml", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"]
+test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-validator (>=0.6.0,<0.8.0)", "pytest (>=7.0)", "pytest-console-scripts", "pytest-cov", "pytest-jupyter[server] (>=0.6.2)", "pytest-timeout", "requests-mock", "ruamel-yaml", "sphinxcontrib-spelling", "strict-rfc3339", "werkzeug"]
 
 [[package]]
 name = "jupyterlab-widgets"
@@ -1645,12 +1643,12 @@ protobuf = ">=3.13.0,<4"
 
 [[package]]
 name = "kfp-server-api"
-version = "2.0.3"
+version = "2.0.5"
 description = "Kubeflow Pipelines API"
 optional = false
 python-versions = "*"
 files = [
-    {file = "kfp-server-api-2.0.3.tar.gz", hash = "sha256:89701d5882f80f7a0445b76de173a1d9ad6dc17b10854a9d9901f18e121e78e2"},
+    {file = "kfp-server-api-2.0.5.tar.gz", hash = "sha256:c9cfbf0e87271d3bfe96e5ecc9ffbdd6ab566bc1c9a9ddc2a39d7698a16e26ff"},
 ]
 
 [package.dependencies]
@@ -1771,13 +1769,13 @@ files = [
 
 [[package]]
 name = "nbclient"
-version = "0.8.0"
+version = "0.9.0"
 description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "nbclient-0.8.0-py3-none-any.whl", hash = "sha256:25e861299e5303a0477568557c4045eccc7a34c17fc08e7959558707b9ebe548"},
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+    {file = "nbclient-0.9.0-py3-none-any.whl", hash = "sha256:a3a1ddfb34d4a9d17fc744d655962714a866639acd30130e9be84191cd97cd15"},
+    {file = "nbclient-0.9.0.tar.gz", hash = "sha256:4b28c207877cf33ef3a9838cdc7a54c5ceff981194a82eac59d558f05487295e"},
 ]
 
 [package.dependencies]
@@ -1793,13 +1791,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
-version = "7.11.0"
+version = "7.12.0"
 description = "Converting Jupyter Notebooks"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "nbconvert-7.12.0-py3-none-any.whl", hash = "sha256:5b6c848194d270cc55fb691169202620d7b52a12fec259508d142ecbe4219310"},
+    {file = "nbconvert-7.12.0.tar.gz", hash = "sha256:b1564bd89f69a74cd6398b0362da94db07aafb991b7857216a766204a71612c0"},
 ]
 
 [package.dependencies]
@@ -1917,43 +1915,47 @@ test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"
 
 [[package]]
 name = "numpy"
-version = "1.26.1"
+version = "1.26.2"
 description = "Fundamental package for array computing in Python"
 optional = false
-python-versions = "<3.13,>=3.9"
-files = [
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 [[package]]
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 [[package]]
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 python-versions = "*"
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 [package.extras]
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 [[package]]
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 [package.dependencies]
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 [package.dependencies]
@@ -2213,13 +2215,13 @@ tests = ["pytest"]
 
 [[package]]
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 [[package]]
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 [package.extras]
 plugins = ["importlib-metadata"]
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 [[package]]
 name = "pytest"
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 [package.dependencies]
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 ]
 
 [[package]]
@@ -2775,17 +2778,17 @@ win32 = ["pywin32"]
 
 [[package]]
 name = "setuptools"
-version = "68.2.2"
+version = "69.0.2"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
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@@ -2914,13 +2917,13 @@ widechars = ["wcwidth"]
 
 [[package]]
 name = "terminado"
-version = "0.17.1"
+version = "0.18.0"
 description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2931,6 +2934,7 @@ tornado = ">=6.1.0"
 [package.extras]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
 test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
+typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
 
 [[package]]
 name = "tinycss2"
@@ -2963,38 +2967,38 @@ files = [
 
 [[package]]
 name = "tornado"
-version = "6.3.3"
+version = "6.4"
 description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
 optional = false
 python-versions = ">= 3.8"
 files = [
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 ]
 
 [[package]]
 name = "traitlets"
-version = "5.13.0"
+version = "5.14.0"
 description = "Traitlets Python configuration system"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
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-test = ["argcomplete (>=3.0.3)", "mypy (>=1.6.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
 
 [[package]]
 name = "types-python-dateutil"
@@ -3009,13 +3013,13 @@ files = [
 
 [[package]]
 name = "typing-extensions"
-version = "4.8.0"
+version = "4.9.0"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -3050,19 +3054,19 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.24.6"
+version = "20.25.0"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
 distlib = ">=0.3.7,<1"
 filelock = ">=3.12.2,<4"
-platformdirs = ">=3.9.1,<4"
+platformdirs = ">=3.9.1,<5"
 
 [package.extras]
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
@@ -3070,13 +3074,13 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess
 
 [[package]]
 name = "wcwidth"
-version = "0.2.9"
+version = "0.2.12"
 description = "Measures the displayed width of unicode strings in a terminal"
 optional = false
 python-versions = "*"
 files = [
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 ]
 
 [[package]]
@@ -3107,13 +3111,13 @@ files = [
 
 [[package]]
 name = "websocket-client"
-version = "1.6.4"
+version = "1.7.0"
 description = "WebSocket client for Python with low level API options"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -3150,4 +3154,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "b3b5a31f66f310cfa300cceb2a57bfdc3ce6171d288d1b59f82304aee47a0a44"
+content-hash = "3106762f19633ae74afcf39c8410ccdf11079d1ea38a3748f3b03e2a47af198a"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 7a6f0d92..619fc02f 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -16,6 +16,7 @@ packages = [
 python = ">=3.9,<3.11"
 Jinja2 = ">=3.0.1,<4.0.0"
 google-cloud-aiplatform = ">=1.30.1"
+google-cloud-storage = "<2.13.0"
 google-cloud-pipeline-components = "^2.1.0"
 components = { path = "../components", develop = true }
 kfp = "^2.0.1"
diff --git a/pipelines/src/pipelines/training.py b/pipelines/src/pipelines/training.py
index 1b621e84..2041fe42 100644
--- a/pipelines/src/pipelines/training.py
+++ b/pipelines/src/pipelines/training.py
@@ -36,7 +36,7 @@
 )
 RESOURCE_SUFFIX = env.get("RESOURCE_SUFFIX", "default")
 TRAINING_IMAGE = f"{env['CONTAINER_IMAGE_REGISTRY']}/training:{RESOURCE_SUFFIX}"
-SERVING_IMAGE = f"{env['CONTAINER_IMAGE_REGISTRY']}/serving:{RESOURCE_SUFFIX}"
+PREDICTION_IMAGE = f"{env['CONTAINER_IMAGE_REGISTRY']}/prediction:{RESOURCE_SUFFIX}"
 
 
 @dsl.container_component
@@ -153,7 +153,7 @@ def pipeline(
         test_data=train_op.outputs["test_data"],
         eval_metric=PRIMARY_METRIC,
         eval_lower_is_better=True,
-        serving_container_image=SERVING_IMAGE,
+        serving_container_image=PREDICTION_IMAGE,
         model_name=model_name,
         model_description="Predict price of a taxi trip.",
         pipeline_job_id="{{$.pipeline_job_name}}",

From 0ae7c459a72ca92c75b5b565300e9b31ba8083fe Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Fri, 15 Dec 2023 17:00:15 +0100
Subject: [PATCH 232/238] Doc updates

---
 Makefile                                      |  4 +-
 README.md                                     | 10 ++--
 docs/{AUTOMATION.md => Automation.md}         |  0
 docs/COMPONENTS.md                            | 37 --------------
 docs/Components.md                            | 48 +++++++++++++++++++
 docs/{CONTRIBUTION.md => Contribution.md}     | 18 ++++++-
 docs/{INFRASTRUCTURE.md => Infrastructure.md} |  2 +-
 docs/{PIPELINES.md => Pipelines.md}           | 23 +++++----
 docs/{PRODUCTION.md => Production.md}         |  4 +-
 9 files changed, 88 insertions(+), 58 deletions(-)
 rename docs/{AUTOMATION.md => Automation.md} (100%)
 delete mode 100644 docs/COMPONENTS.md
 create mode 100644 docs/Components.md
 rename docs/{CONTRIBUTION.md => Contribution.md} (90%)
 rename docs/{INFRASTRUCTURE.md => Infrastructure.md} (98%)
 rename docs/{PIPELINES.md => Pipelines.md} (91%)
 rename docs/{PRODUCTION.md => Production.md} (97%)

diff --git a/Makefile b/Makefile
index 0cd56698..2d9a3a96 100644
--- a/Makefile
+++ b/Makefile
@@ -102,10 +102,10 @@ run: ## Run a pipeline. Set pipeline=<training|prediction>. Optionally set compi
 		--template_path=pipelines/${pipeline}.yaml --display_name=${pipeline} --wait=${wait}
 
 training: ## Run training pipeline. Rebuilds training and prediction images. Supports same options as run.
-	$(MAKE) run pipeline=training
+	@$(MAKE) run pipeline=training
 
 prediction:	## Run prediction pipeline. Doesn't rebuilt images. Supports same options as run.
-	$(MAKE) run pipeline=prediction build=false
+	@$(MAKE) run pipeline=prediction build=false
 
 packages ?= pipelines components
 test: ## Run unit tests. Optionally set packages=<pipelines and/or components> (default="pipelines components").
diff --git a/README.md b/README.md
index 01dc6f0d..76395c25 100644
--- a/README.md
+++ b/README.md
@@ -86,7 +86,7 @@ gcloud services enable cloudresourcemanager.googleapis.com serviceusage.googleap
 make deploy env=dev
 ```
 
-More details about infrastructure is explained in [this README](docs/INFRASTRUCTURE.md).
+More details about infrastructure is explained in [this guide](docs/Infrastructure.md).
 It describes the scheduling of pipelines and how to tear down infrastructure.
 
 **Install dependencies:**
@@ -110,7 +110,7 @@ gcloud auth application-default login
 
 ## Run
 
-This repository contains example ML training and prediction pipelines which are explained in [this README](docs/PIPELINES.md).
+This repository contains example ML training and prediction pipelines which are explained in [this guide](docs/Pipelines.md).
 
 **Build containers:** The [model/](/model/) directory contains the code for custom training and prediction container images, including the model training script at [model/training/train.py](model/training/train.py). 
 You can modify this to suit your own use case.
@@ -160,10 +160,10 @@ make test [ packages=<pipelines components> ]
 
 ## Automation
 
-For details on setting up CI/CD, see [this README](/docs/AUTOMATION.md).
+For details on setting up CI/CD, see [this guide](./docs/Automation.md).
 
 ## Putting it all together
 
-For a full walkthrough of the journey from changing the ML pipeline code to having it scheduled and running in production, please see the guide [here](./docs/PRODUCTION.md).
+For a full walkthrough of the journey from changing the ML pipeline code to having it scheduled and running in production, please see the guide [here](./docs/Production.md).
 
-We value your contribution, see [this guide](./docs/CONTRIBUTION.md) for contributing to this project.
+We value your contribution, see [this guide](./docs/Contribution.md) for contributing to this project.
diff --git a/docs/AUTOMATION.md b/docs/Automation.md
similarity index 100%
rename from docs/AUTOMATION.md
rename to docs/Automation.md
diff --git a/docs/COMPONENTS.md b/docs/COMPONENTS.md
deleted file mode 100644
index e2009442..00000000
--- a/docs/COMPONENTS.md
+++ /dev/null
@@ -1,37 +0,0 @@
-# Kubeflow Pipelines Components
-
-This directory contains multiple Python packages that are used to define pipeline components with the Kubeflow Pipelines SDK. Each subdirectory is a package with its own set of Python dependencies. Components with the same Python dependencies can reside in the same package, but components with different Python dependencies should be split into different Python packages.
-
-A Python package which provides common KubeFlow components for interacting with Google Cloud.
-The following components are implemented:
-
-- `extract_table`: Extract a table from BigQuery to Cloud Storage.
-- `lookup_model`: Look up a mode in the Vertex AI Model Registry given a name (and version optionally).
-- `upload_model`: Uploads a new model version to the Vertex Model Registry, importing a model evaluation, and updating the "default" tag on the model if the new version (challenger) is superior to the previous (champion) model.
-- `model_batch_predict`: Run a [Batch Prediction Job](https://cloud.google.com/ai-platform/prediction/docs/batch-predict).
-
-These components either augment, extend, or add new functionalities that aren't found in [Google Cloud Pipeline Components list](https://cloud.google.com/vertex-ai/docs/pipelines/gcpc-list).
-
-## Creating a new pipeline components package
-
-To create a new set of components (with different Python dependencies), copy one of the existing subdirectories and rename the different files and directories as appropriate (e.g. `vertex-components` -> `my-new-components`). You will also need to update any references in the Python files themselves, as well as `poetry.lock` and `pyproject.toml`.
-
-Your Python dependencies should be defined in `poetry.lock`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
-
-- In `pyproject.toml`, add `kfp` to the `[dependencies]` section (pinned to a specific version), and add any dependencies that your component uses under `[tool.poetry.dependencies]`(each pinned to a specific version)
-- In `packages_to_install` (in the `@component` decorator used to define your component), add any dependencies that your component uses (each pinned to a specific version)
-
-Define your pipeline components using the `@component` decorator in Python files under `my-new-components/src/my-new-components`. You will need to update the `__init__.py` file to provide tests - see the [Kubeflow Pipelines documentation](https://www.kubeflow.org/docs/components/pipelines/v1/sdk-v2/python-function-components/#building-python-function-based-components) for more information about writing pipeline components.
-
-Finally, you will need to install this new components package into the [`pipelines`](../pipelines) package. In [`pipelines/pyproject.toml`](../pipelines/pyproject.toml), add the following line to the `tool.poetry.dependencies` section:
-
-```
-my-new-components = { path = "../components/my-new-components", develop = true }
-```
-Once you have added this line to [`pipelines/pyproject.toml`](../pipelines/pyproject.toml), run `make setup` from the root of the repository to install the new components package into the `pipelines` package.
-
-## Testing components
-
-Unit tests for components are defined using pytest and should be created under `my-new-components/tests`. Take a look at the existing components to see examples of how you can write these tests and perform mocking/patching of KFP Artifact types.
-
-To run the unit tests, you will first need to set up the virtual environment for the new components by running `make setup-components GROUP=my-new-components` from the root of the repository. Once you have done this, you can run the unit tests using `make test-components GROUP=my-new-components`.
diff --git a/docs/Components.md b/docs/Components.md
new file mode 100644
index 00000000..d0828930
--- /dev/null
+++ b/docs/Components.md
@@ -0,0 +1,48 @@
+<!-- 
+Copyright 2023 Google LLC
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    https://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+ -->
+# Kubeflow Pipelines Components
+
+The package `components` contains KubeFlow pipeline components for interacting with Google Cloud.
+The following components are implemented:
+
+- `extract_table`: Extract a table from BigQuery to Cloud Storage.
+- `lookup_model`: Look up a mode in the Vertex AI Model Registry given a name (and version optionally).
+- `model_batch_predict`: Run a [Batch Prediction Job](https://cloud.google.com/ai-platform/prediction/docs/batch-predict).
+- `upload_model`: Uploads a new model version to the Vertex Model Registry, importing a model evaluation, and updating the "default" tag on the model if the new version (challenger) is superior to the previous (champion) model.
+
+These components either augment, extend, or add new functionalities that aren't found in [Google Cloud Pipeline Components list](https://cloud.google.com/vertex-ai/docs/pipelines/gcpc-list).
+
+## Creating a new pipeline components package
+
+Update Python dependencies in `poetry.lock`, `pyproject.toml`, and in `packages_to_install` (in the `@component` decorator):
+
+- In `pyproject.toml`, add any dependencies that your component uses under `[tool.poetry.dependencies]`(each pinned to a specific version)
+- In `packages_to_install` (in the `@component` decorator used to define your component), add any dependencies that your component uses (each pinned to a specific version)
+
+Define your pipeline components using the `@component` decorator in Python files under `components/src/components`. 
+You will need to update the `__init__.py` file to provide tests.
+See the [Kubeflow Pipelines documentation](https://www.kubeflow.org/docs/components/pipelines/v1/sdk-v2/python-function-components/#building-python-function-based-components) for more information about writing pipeline components.
+
+Finally, you will need to install this new components package into the [`pipelines`](../pipelines) package.
+Run `make install` from the root of the repository to install the new components.
+
+## Testing components
+
+Unit tests for components are defined using pytest and should be created under `components/tests`. 
+Take a look at the existing components to see examples of how you can write these tests and perform mocking/patching of KFP Artifact types.
+
+To run the unit tests, run `make test` from the root of the repository. 
+
diff --git a/docs/CONTRIBUTION.md b/docs/Contribution.md
similarity index 90%
rename from docs/CONTRIBUTION.md
rename to docs/Contribution.md
index 6fcc298b..5bfe996d 100644
--- a/docs/CONTRIBUTION.md
+++ b/docs/Contribution.md
@@ -1,6 +1,22 @@
+<!-- 
+Copyright 2023 Google LLC
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    https://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+ -->
 # Automated testing for Vertex Pipelines E2E samples
 
-This document details the steps required to set up automated testing with Cloud Build for the [E2E samples repo](https://github.com/GoogleCloudPlatform/vertex-pipelines-end-to-end-samples) (rather than setting up automated testing for your own repo derived from it). It is focused on the Vertex Pipelines components and pipelines themselves, not on the other elements of the codebase such as infrastructure setup.
+This document details the steps required to set up automated testing with Cloud Build for the [E2E samples repo](https://github.com/GoogleCloudPlatform/vertex-pipelines-end-to-end-samples) (rather than setting up automated testing for your own repo derived from it). 
+It is focused on the Vertex Pipelines components and pipelines themselves, not on the other elements of the codebase such as infrastructure setup.
 
 This guide assumes that you are working in a brand-new Google Cloud project, and that you have Owner permission for this project.
 
diff --git a/docs/INFRASTRUCTURE.md b/docs/Infrastructure.md
similarity index 98%
rename from docs/INFRASTRUCTURE.md
rename to docs/Infrastructure.md
index cf2e02c7..08593d75 100644
--- a/docs/INFRASTRUCTURE.md
+++ b/docs/Infrastructure.md
@@ -1,5 +1,5 @@
 <!-- 
-Copyright 2022 Google LLC
+Copyright 2023 Google LLC
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
diff --git a/docs/PIPELINES.md b/docs/Pipelines.md
similarity index 91%
rename from docs/PIPELINES.md
rename to docs/Pipelines.md
index 51999e66..55b25b58 100644
--- a/docs/PIPELINES.md
+++ b/docs/Pipelines.md
@@ -1,5 +1,5 @@
 <!-- 
-Copyright 2022 Google LLC
+Copyright 2023 Google LLC
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -15,14 +15,16 @@ limitations under the License.
  -->
 # ML Pipelines
 
-There are two ML pipelines defined in this repository: a training pipeline (located in `pipelines/src/pipelines/training.py` and a batch prediction pipeline (located in `pipelines/src/pipelines/prediction.py`).
+There are two ML pipelines defined in this repository: 
+- training pipeline (located in `pipelines/src/pipelines/training.py`
+- batch prediction pipeline (located in `pipelines/src/pipelines/prediction.py`)
 
 ## Pipeline input parameters
 
 The ML pipelines have input parameters. 
 As you can see in the pipeline definition files (`pipelines/src/pipelines/<training|prediction>/pipeline.py`), they have default values, and some of these default values are derived from environment variables (which in turn are defined in `env.sh`).
 
-When triggering ad hoc runs in your dev/sandbox environment, or when running the E2E tests in CI, these default values are used. 
+When triggering ad hoc runs in your dev (or sandbox) environment, or when running the E2E tests in CI, these default values are used. 
 For the test and production deployments, the pipeline parameters are defined in the Terraform code for the Cloud Scheduler jobs (`terraform/envs/<dev|test|prod>/scheduled_jobs.auto.tfvars`) - see the section on [Scheduling pipelines](#scheduling-pipelines).
 
 ## Customize pipelines
@@ -52,17 +54,16 @@ Make sure that you give the ML pipeline a unique name in the `@pipeline` decorat
 To run your pipeline, use `make run` as before (optionally adding parameter to wait until pipeline is finished before returning - defaults to false):
 
 ```bash
-make run pipeline=your_new_pipeline [ wait=<true|false> ]
+make run pipeline=your_new_pipeline
 ```
 
 Some of the scripts e.g. CI/CD pipelines assume only a training and prediction pipeline. You will need to adapt these to add in the compile, run and upload steps for your new pipeline in [cloudbuild/pr-checks.yaml](/cloudbuild/pr-checks.yaml), [cloudbuild/e2e-test.yaml](/cloudbuild/e2e-test.yaml) and [cloudbuild/release.yaml](/cloudbuild/release.yaml).
 
-
 ## Training pipeline
 
 A screenshot of the completed ML pipeline is shown below.
 
-![Screenshot of the training pipeline in Vertex Pipelines](/docs/images/training_pipeline.png)
+![Screenshot of the training pipeline in Vertex Pipelines](./images/training_pipeline.png)
 
 In the next sections we will walk through the different pipeline steps.
 
@@ -96,7 +97,7 @@ The source code for this container image (and the prediction container image) ca
 
 The training script trains a simple XGBoost model wrapped in a scikit-learn pipeline, and saves it as `model.joblib`.
 
-![Architecture of the XGBoost model](/docs/images/xgboost_architecture.png)
+![Architecture of the XGBoost model](./images/xgboost_architecture.png)
 
 The model is evaluated and metrics are saved as a JSON file. In the Vertex pipeline, the model appears as a KFP Model artifact, and the JSON file appears as a KFP Metrics artifact.
 
@@ -120,7 +121,8 @@ For example, when you want to train a new model using different features, the be
 
 A screenshot of the completed ML pipeline is shown below.
 
-![Screenshot of the prediction pipeline in Vertex Pipelines](/docs/images/prediction_pipeline.png)
+![Screenshot of the prediction pipeline in Vertex Pipelines](./images/prediction_pipeline.png)
+
 In the next sections we will walk through the different pipeline steps.
 
 ### Ingestion / preprocessing step
@@ -135,9 +137,10 @@ In the pipeline definition, the `generate_query` function is run at pipeline com
 
 The `preprocessing` step in the pipeline uses this string (`preprocessing_query`) in the `BigqueryQueryJobOp` component (provided by [Google Cloud Pipeline Components](https://cloud.google.com/vertex-ai/docs/pipelines/components-introduction))
 
-### Lookup model
+### Look up model
 
-This step looks up the "champion" model from the Vertex Model Registry. It uses a custom KFP component that can be found in [components/vertex-components/src/vertex_components/lookup_model.py](//vertex_components/lookup_model.py). It uses the Vertex AI Python SDK to list models with a given model name and retrieve the model version that uses the `default` alias, indicating that it is the "champion" model.
+This step looks up the "champion" model from the Vertex Model Registry. 
+It uses a custom KFP component that can be found in [components/vertex-components/src/vertex_components/lookup_model.py](//vertex_components/lookup_model.py). It uses the Vertex AI Python SDK to list models with a given model name and retrieve the model version that uses the `default` alias, indicating that it is the "champion" model.
 
 ### Batch Prediction
 
diff --git a/docs/PRODUCTION.md b/docs/Production.md
similarity index 97%
rename from docs/PRODUCTION.md
rename to docs/Production.md
index e864d095..2c0b0719 100644
--- a/docs/PRODUCTION.md
+++ b/docs/Production.md
@@ -1,5 +1,5 @@
 <!-- 
-Copyright 2022 Google LLC
+Copyright 2023 Google LLC
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
@@ -20,7 +20,7 @@ This document describes the full process from making a change to your pipeline c
 
 ## Pre-requisites
 
-- Suitable GCP environments set up - see the README section on [Deploying Cloud Infrastructure](/README.md#deploying-cloud-infrastructure)
+- Suitable GCP environments set up - see the [README](../README.md)
 - This repo forked / used as a template for a new GitHub repo
 - CI/CD set up - see the instructions [here](cloudbuild/README.md)
 - Access set up for the BigQuery datasets used in the example pipelines

From 09b944f9ad932cc221abf3a5be20739a159a1881 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Wed, 20 Dec 2023 14:50:05 +0100
Subject: [PATCH 233/238] Add animation to README

---
 README.md | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/README.md b/README.md
index 76395c25..9a7fe501 100644
--- a/README.md
+++ b/README.md
@@ -18,6 +18,8 @@ limitations under the License.
 
 _AKA "Vertex AI Turbo Templates"_
 
+![Shell](https://github.com/teamdatatonic/vertex-pipelines-end-to-end-samples/wiki/images/shell.gif)
+
 ## Introduction
 
 This repository provides a reference implementation of [Vertex Pipelines](https://cloud.google.com/vertex-ai/docs/pipelines/) for creating a production-ready MLOps solution on Google Cloud.

From c526bda7c42f7fd6c07d440c8669b8bcc1e2c1c5 Mon Sep 17 00:00:00 2001
From: Lily <lily.nicholls@datatonic.com>
Date: Wed, 10 Jan 2024 16:29:23 +0000
Subject: [PATCH 234/238] Adding notification channels and enable logging
 variables to batch prediction model monitoring job

---
 components/src/components/model_batch_predict.py | 8 +++++++-
 pipelines/src/pipelines/prediction.py            | 2 ++
 2 files changed, 9 insertions(+), 1 deletion(-)

diff --git a/components/src/components/model_batch_predict.py b/components/src/components/model_batch_predict.py
index ab329181..b99687e8 100644
--- a/components/src/components/model_batch_predict.py
+++ b/components/src/components/model_batch_predict.py
@@ -38,6 +38,7 @@ def model_batch_predict(
     max_replica_count: int = 1,
     monitoring_training_dataset: dict = None,
     monitoring_alert_email_addresses: List[str] = None,
+    notification_channels: List[str] = [],
     monitoring_skew_config: dict = None,
     instance_config: dict = None,
 ):
@@ -62,6 +63,9 @@ def model_batch_predict(
             https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingPredictionSkewDetectionConfig
         monitoring_alert_email_addresses (List[str]):
             Email addresses to send alerts to (optional).
+        notification_channels (List[str]):
+            Notification channels to send alerts to (optional).
+            Format: projects/<project>/notificationChannels/<notification_channel>
         monitoring_training_dataset (dict): Metadata of training dataset. See:
             https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1beta1.types.ModelMonitoringObjectiveConfig.TrainingDataset
         instance_config (dict): Configuration defining how to transform batch prediction
@@ -152,7 +156,9 @@ def is_job_successful(job_state: JobState) -> bool:
 
         message["modelMonitoringConfig"] = {
             "alertConfig": {
-                "emailAlertConfig": {"userEmails": monitoring_alert_email_addresses}
+                "emailAlertConfig": {"userEmails": monitoring_alert_email_addresses},
+                "notificationChannels": notification_channels,
+                "enableLogging": True,
             },
             "objectiveConfigs": [
                 {
diff --git a/pipelines/src/pipelines/prediction.py b/pipelines/src/pipelines/prediction.py
index 07e39676..62dd739d 100644
--- a/pipelines/src/pipelines/prediction.py
+++ b/pipelines/src/pipelines/prediction.py
@@ -24,6 +24,7 @@
 RESOURCE_SUFFIX = env.get("RESOURCE_SUFFIX", "default")
 # set training-serving skew thresholds and emails to receive alerts:
 ALERT_EMAILS = []
+NOTIFICATION_CHANNELS = []
 SKEW_THRESHOLDS = {"defaultSkewThreshold": {"value": 0.001}}
 # or set different thresholds per feature:
 # SKEW_THRESHOLDS = {"skewThresholds": {"payment_type": {"value": 0.001}}, ... }
@@ -109,6 +110,7 @@ def pipeline(
             max_replica_count=max_replicas,
             monitoring_training_dataset=lookup_op.outputs["training_dataset"],
             monitoring_alert_email_addresses=ALERT_EMAILS,
+            notification_channels=NOTIFICATION_CHANNELS,
             monitoring_skew_config=SKEW_THRESHOLDS,
         )
         .after(prep_op)

From 2a3a11c5ac30cb4df18073c2fdb9d814bb8cb5c6 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Fri, 19 Jan 2024 14:06:24 +0100
Subject: [PATCH 235/238] Remove jupyter

---
 pipelines/poetry.lock    | 1879 ++------------------------------------
 pipelines/pyproject.toml |    1 -
 2 files changed, 70 insertions(+), 1810 deletions(-)

diff --git a/pipelines/poetry.lock b/pipelines/poetry.lock
index e94bea2f..2080b2f7 100644
--- a/pipelines/poetry.lock
+++ b/pipelines/poetry.lock
@@ -1,213 +1,5 @@
 # This file is automatically @generated by Poetry 1.5.0 and should not be changed by hand.
 
-[[package]]
-name = "anyio"
-version = "4.1.0"
-description = "High level compatibility layer for multiple asynchronous event loop implementations"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "anyio-4.1.0-py3-none-any.whl", hash = "sha256:56a415fbc462291813a94528a779597226619c8e78af7de0507333f700011e5f"},
-    {file = "anyio-4.1.0.tar.gz", hash = "sha256:5a0bec7085176715be77df87fc66d6c9d70626bd752fcc85f57cdbee5b3760da"},
-]
-
-[package.dependencies]
-exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
-idna = ">=2.8"
-sniffio = ">=1.1"
-
-[package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
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-
-[package.dependencies]
-pycparser = "*"
-
 [[package]]
 name = "cfgv"
 version = "3.4.0"
@@ -429,23 +157,6 @@ files = [
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-version = "0.2.0"
-description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
-optional = false
-python-versions = ">=3.8"
-files = [
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-
-[package.dependencies]
-traitlets = ">=4"
-
-[package.extras]
-test = ["pytest"]
-
 [[package]]
 name = "components"
 version = "0.1.0"
@@ -526,55 +237,6 @@ files = [
 [package.extras]
 toml = ["tomli"]
 
-[[package]]
-name = "debugpy"
-version = "1.8.0"
-description = "An implementation of the Debug Adapter Protocol for Python"
-optional = false
-python-versions = ">=3.8"
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-
-[[package]]
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-version = "5.1.1"
-description = "Decorators for Humans"
-optional = false
-python-versions = ">=3.5"
-files = [
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-[[package]]
-name = "defusedxml"
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-description = "XML bomb protection for Python stdlib modules"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
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-
 [[package]]
 name = "distlib"
 version = "0.3.8"
@@ -611,34 +273,6 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
-[[package]]
-name = "executing"
-version = "2.0.1"
-description = "Get the currently executing AST node of a frame, and other information"
-optional = false
-python-versions = ">=3.5"
-files = [
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-
-[package.extras]
-tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
-
-[[package]]
-name = "fastjsonschema"
-version = "2.19.0"
-description = "Fastest Python implementation of JSON schema"
-optional = false
-python-versions = "*"
-files = [
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-
-[package.extras]
-devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
-
 [[package]]
 name = "filelock"
 version = "3.13.1"
@@ -655,17 +289,6 @@ docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1
 testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)"]
 typing = ["typing-extensions (>=4.8)"]
 
-[[package]]
-name = "fqdn"
-version = "1.5.1"
-description = "Validates fully-qualified domain names against RFC 1123, so that they are acceptable to modern bowsers"
-optional = false
-python-versions = ">=2.7, !=3.0, !=3.1, !=3.2, !=3.3, !=3.4, <4"
-files = [
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-]
-
 [[package]]
 name = "google-api-core"
 version = "2.15.0"
@@ -1098,25 +721,6 @@ files = [
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 ]
 
-[[package]]
-name = "importlib-metadata"
-version = "7.0.0"
-description = "Read metadata from Python packages"
-optional = false
-python-versions = ">=3.8"
-files = [
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-]
-
-[package.dependencies]
-zipp = ">=0.5"
-
-[package.extras]
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-perf = ["ipython"]
-testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
-
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -1129,564 +733,110 @@ files = [
 ]
 
 [[package]]
-name = "ipykernel"
-version = "6.27.1"
-description = "IPython Kernel for Jupyter"
+name = "jinja2"
+version = "3.1.2"
+description = "A very fast and expressive template engine."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.7"
 files = [
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+    {file = "Jinja2-3.1.2-py3-none-any.whl", hash = "sha256:6088930bfe239f0e6710546ab9c19c9ef35e29792895fed6e6e31a023a182a61"},
+    {file = "Jinja2-3.1.2.tar.gz", hash = "sha256:31351a702a408a9e7595a8fc6150fc3f43bb6bf7e319770cbc0db9df9437e852"},
 ]
 
 [package.dependencies]
-appnope = {version = "*", markers = "platform_system == \"Darwin\""}
-comm = ">=0.1.1"
-debugpy = ">=1.6.5"
-ipython = ">=7.23.1"
-jupyter-client = ">=6.1.12"
-jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
-matplotlib-inline = ">=0.1"
-nest-asyncio = "*"
-packaging = "*"
-psutil = "*"
-pyzmq = ">=20"
-tornado = ">=6.1"
-traitlets = ">=5.4.0"
+MarkupSafe = ">=2.0"
 
 [package.extras]
-cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
-pyqt5 = ["pyqt5"]
-pyside6 = ["pyside6"]
-test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"]
+i18n = ["Babel (>=2.7)"]
 
 [[package]]
-name = "ipython"
-version = "8.18.1"
-description = "IPython: Productive Interactive Computing"
+name = "kfp"
+version = "2.4.0"
+description = "Kubeflow Pipelines SDK"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.7.0,<3.12.0"
 files = [
-    {file = "ipython-8.18.1-py3-none-any.whl", hash = "sha256:e8267419d72d81955ec1177f8a29aaa90ac80ad647499201119e2f05e99aa397"},
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+    {file = "kfp-2.4.0.tar.gz", hash = "sha256:44c25ce80b948629bf0fb0815b49d8d97039a825597a4378078bbaa0610aef69"},
 ]
 
 [package.dependencies]
-colorama = {version = "*", markers = "sys_platform == \"win32\""}
-decorator = "*"
-exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
-jedi = ">=0.16"
-matplotlib-inline = "*"
-pexpect = {version = ">4.3", markers = "sys_platform != \"win32\""}
-prompt-toolkit = ">=3.0.41,<3.1.0"
-pygments = ">=2.4.0"
-stack-data = "*"
-traitlets = ">=5"
-typing-extensions = {version = "*", markers = "python_version < \"3.10\""}
+click = ">=8.0.0,<9"
+docstring-parser = ">=0.7.3,<1"
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev"
+google-auth = ">=1.6.1,<3"
+google-cloud-storage = ">=2.2.1,<3"
+kfp-pipeline-spec = "0.2.2"
+kfp-server-api = ">=2.0.0,<2.1.0"
+kubernetes = ">=8.0.0,<27"
+protobuf = ">=3.13.0,<4"
+PyYAML = ">=5.3,<7"
+requests-toolbelt = ">=0.8.0,<1"
+tabulate = ">=0.8.6,<1"
+urllib3 = "<2.0.0"
 
 [package.extras]
-all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.22)", "pandas", "pickleshare", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio (<0.22)", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
-black = ["black"]
-doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pickleshare", "pytest (<7)", "pytest (<7.1)", "pytest-asyncio (<0.22)", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
-kernel = ["ipykernel"]
-nbconvert = ["nbconvert"]
-nbformat = ["nbformat"]
-notebook = ["ipywidgets", "notebook"]
-parallel = ["ipyparallel"]
-qtconsole = ["qtconsole"]
-test = ["pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath"]
-test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pandas", "pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath", "trio"]
+all = ["docker", "kfp-kubernetes (<2)"]
+kubernetes = ["kfp-kubernetes (<2)"]
 
 [[package]]
-name = "ipywidgets"
-version = "8.1.1"
-description = "Jupyter interactive widgets"
+name = "kfp-pipeline-spec"
+version = "0.2.2"
+description = "Kubeflow Pipelines pipeline spec"
 optional = false
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-[package.extras]
-test = ["ipykernel", "jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"]
+protobuf = ">=3.13.0,<4"
 
 [[package]]
-name = "isoduration"
-version = "20.11.0"
-description = "Operations with ISO 8601 durations"
+name = "kfp-server-api"
+version = "2.0.5"
+description = "Kubeflow Pipelines API"
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-python-versions = ">=3.7"
+python-versions = "*"
 files = [
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 [[package]]
-name = "jedi"
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 python-versions = ">=3.6"
 files = [
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-testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
+adal = ["adal (>=1.0.2)"]
 
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-
-[[package]]
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-
-[[package]]
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-[package.dependencies]
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-
-[[package]]
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-[package.extras]
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-
-[[package]]
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-[package.dependencies]
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-
-[package.extras]
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-[[package]]
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-optional = false
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-[package.extras]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "traitlets"]
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-
-[[package]]
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-[package.extras]
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-test = ["click", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.19.0)", "pytest-console-scripts", "rich"]
-
-[[package]]
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-[[package]]
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-[package.extras]
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-[[package]]
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-files = [
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-
-[[package]]
-name = "jupyterlab-widgets"
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-description = "Jupyter interactive widgets for JupyterLab"
-optional = false
-python-versions = ">=3.7"
-files = [
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-description = "Kubeflow Pipelines SDK"
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-files = [
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-google-auth = ">=1.6.1,<3"
-google-cloud-storage = ">=2.2.1,<3"
-kfp-pipeline-spec = "0.2.2"
-kfp-server-api = ">=2.0.0,<2.1.0"
-kubernetes = ">=8.0.0,<27"
-protobuf = ">=3.13.0,<4"
-PyYAML = ">=5.3,<7"
-requests-toolbelt = ">=0.8.0,<1"
-tabulate = ">=0.8.6,<1"
-urllib3 = "<2.0.0"
-
-[package.extras]
-all = ["docker", "kfp-kubernetes (<2)"]
-kubernetes = ["kfp-kubernetes (<2)"]
-
-[[package]]
-name = "kfp-pipeline-spec"
-version = "0.2.2"
-description = "Kubeflow Pipelines pipeline spec"
-optional = false
-python-versions = ">=3.7.0"
-files = [
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-
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-protobuf = ">=3.13.0,<4"
-
-[[package]]
-name = "kfp-server-api"
-version = "2.0.5"
-description = "Kubeflow Pipelines API"
-optional = false
-python-versions = "*"
-files = [
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-
-[package.dependencies]
-certifi = "*"
-python-dateutil = "*"
-six = ">=1.10"
-urllib3 = ">=1.15"
-
-[[package]]
-name = "kubernetes"
-version = "26.1.0"
-description = "Kubernetes python client"
-optional = false
-python-versions = ">=3.6"
-files = [
-    {file = "kubernetes-26.1.0-py2.py3-none-any.whl", hash = "sha256:e3db6800abf7e36c38d2629b5cb6b74d10988ee0cba6fba45595a7cbe60c0042"},
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-certifi = ">=14.05.14"
-google-auth = ">=1.0.1"
-python-dateutil = ">=2.5.3"
-pyyaml = ">=5.4.1"
-requests = "*"
-requests-oauthlib = "*"
-setuptools = ">=21.0.0"
-six = ">=1.9.0"
-urllib3 = ">=1.24.2"
-websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
-
-[package.extras]
-adal = ["adal (>=1.0.2)"]
-
-[[package]]
-name = "markupsafe"
-version = "2.1.3"
-description = "Safely add untrusted strings to HTML/XML markup."
+name = "markupsafe"
+version = "2.1.3"
+description = "Safely add untrusted strings to HTML/XML markup."
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1742,123 +892,6 @@ files = [
     {file = "MarkupSafe-2.1.3.tar.gz", hash = "sha256:af598ed32d6ae86f1b747b82783958b1a4ab8f617b06fe68795c7f026abbdcad"},
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-[[package]]
-name = "matplotlib-inline"
-version = "0.1.6"
-description = "Inline Matplotlib backend for Jupyter"
-optional = false
-python-versions = ">=3.5"
-files = [
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-]
-
-[package.dependencies]
-traitlets = "*"
-
-[[package]]
-name = "mistune"
-version = "3.0.2"
-description = "A sane and fast Markdown parser with useful plugins and renderers"
-optional = false
-python-versions = ">=3.7"
-files = [
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-
-[[package]]
-name = "nbclient"
-version = "0.9.0"
-description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor."
-optional = false
-python-versions = ">=3.8.0"
-files = [
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-jupyter-client = ">=6.1.12"
-jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
-nbformat = ">=5.1"
-traitlets = ">=5.4"
-
-[package.extras]
-dev = ["pre-commit"]
-docs = ["autodoc-traits", "mock", "moto", "myst-parser", "nbclient[test]", "sphinx (>=1.7)", "sphinx-book-theme", "sphinxcontrib-spelling"]
-test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=7.0.0)", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov (>=4.0)", "testpath", "xmltodict"]
-
-[[package]]
-name = "nbconvert"
-version = "7.12.0"
-description = "Converting Jupyter Notebooks"
-optional = false
-python-versions = ">=3.8"
-files = [
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-
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-beautifulsoup4 = "*"
-bleach = "!=5.0.0"
-defusedxml = "*"
-importlib-metadata = {version = ">=3.6", markers = "python_version < \"3.10\""}
-jinja2 = ">=3.0"
-jupyter-core = ">=4.7"
-jupyterlab-pygments = "*"
-markupsafe = ">=2.0"
-mistune = ">=2.0.3,<4"
-nbclient = ">=0.5.0"
-nbformat = ">=5.7"
-packaging = "*"
-pandocfilters = ">=1.4.1"
-pygments = ">=2.4.1"
-tinycss2 = "*"
-traitlets = ">=5.1"
-
-[package.extras]
-all = ["nbconvert[docs,qtpdf,serve,test,webpdf]"]
-docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sphinx-theme", "sphinx (==5.0.2)", "sphinxcontrib-spelling"]
-qtpdf = ["nbconvert[qtpng]"]
-qtpng = ["pyqtwebengine (>=5.15)"]
-serve = ["tornado (>=6.1)"]
-test = ["flaky", "ipykernel", "ipywidgets (>=7)", "pytest"]
-webpdf = ["playwright"]
-
-[[package]]
-name = "nbformat"
-version = "5.9.2"
-description = "The Jupyter Notebook format"
-optional = false
-python-versions = ">=3.8"
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-
-[package.dependencies]
-fastjsonschema = "*"
-jsonschema = ">=2.6"
-jupyter-core = "*"
-traitlets = ">=5.1"
-
-[package.extras]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
-test = ["pep440", "pre-commit", "pytest", "testpath"]
-
-[[package]]
-name = "nest-asyncio"
-version = "1.5.8"
-description = "Patch asyncio to allow nested event loops"
-optional = false
-python-versions = ">=3.5"
-files = [
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-]
-
 [[package]]
 name = "nodeenv"
 version = "1.8.0"
@@ -1873,46 +906,6 @@ files = [
 [package.dependencies]
 setuptools = "*"
 
-[[package]]
-name = "notebook"
-version = "7.0.6"
-description = "Jupyter Notebook - A web-based notebook environment for interactive computing"
-optional = false
-python-versions = ">=3.8"
-files = [
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-    {file = "notebook-7.0.6.tar.gz", hash = "sha256:ec6113b06529019f7f287819af06c97a2baf7a95ac21a8f6e32192898e9f9a58"},
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-
-[package.dependencies]
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-jupyterlab = ">=4.0.2,<5"
-jupyterlab-server = ">=2.22.1,<3"
-notebook-shim = ">=0.2,<0.3"
-tornado = ">=6.2.0"
-
-[package.extras]
-dev = ["hatch", "pre-commit"]
-docs = ["myst-parser", "nbsphinx", "pydata-sphinx-theme", "sphinx (>=1.3.6)", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
-test = ["importlib-resources (>=5.0)", "ipykernel", "jupyter-server[test] (>=2.4.0,<3)", "jupyterlab-server[test] (>=2.22.1,<3)", "nbval", "pytest (>=7.0)", "pytest-console-scripts", "pytest-timeout", "pytest-tornasync", "requests"]
-
-[[package]]
-name = "notebook-shim"
-version = "0.2.3"
-description = "A shim layer for notebook traits and config"
-optional = false
-python-versions = ">=3.7"
-files = [
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-
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-
-[package.extras]
-test = ["pytest", "pytest-console-scripts", "pytest-jupyter", "pytest-tornasync"]
-
 [[package]]
 name = "numpy"
 version = "1.26.2"
@@ -1972,70 +965,19 @@ files = [
 [package.extras]
 rsa = ["cryptography (>=3.0.0)"]
 signals = ["blinker (>=1.4.0)"]
-signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
-
-[[package]]
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-version = "7.4.0"
-description = "A decorator to automatically detect mismatch when overriding a method."
-optional = false
-python-versions = ">=3.6"
-files = [
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-]
-
-[[package]]
-name = "packaging"
-version = "23.2"
-description = "Core utilities for Python packages"
-optional = false
-python-versions = ">=3.7"
-files = [
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-    {file = "packaging-23.2.tar.gz", hash = "sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5"},
-]
-
-[[package]]
-name = "pandocfilters"
-version = "1.5.0"
-description = "Utilities for writing pandoc filters in python"
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-files = [
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-]
-
-[[package]]
-name = "parso"
-version = "0.8.3"
-description = "A Python Parser"
-optional = false
-python-versions = ">=3.6"
-files = [
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-    {file = "parso-0.8.3.tar.gz", hash = "sha256:8c07be290bb59f03588915921e29e8a50002acaf2cdc5fa0e0114f91709fafa0"},
-]
-
-[package.extras]
-qa = ["flake8 (==3.8.3)", "mypy (==0.782)"]
-testing = ["docopt", "pytest (<6.0.0)"]
+signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 
 [[package]]
-name = "pexpect"
-version = "4.9.0"
-description = "Pexpect allows easy control of interactive console applications."
+name = "packaging"
+version = "23.2"
+description = "Core utilities for Python packages"
 optional = false
-python-versions = "*"
+python-versions = ">=3.7"
 files = [
-    {file = "pexpect-4.9.0-py2.py3-none-any.whl", hash = "sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523"},
-    {file = "pexpect-4.9.0.tar.gz", hash = "sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f"},
+    {file = "packaging-23.2-py3-none-any.whl", hash = "sha256:8c491190033a9af7e1d931d0b5dacc2ef47509b34dd0de67ed209b5203fc88c7"},
+    {file = "packaging-23.2.tar.gz", hash = "sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5"},
 ]
 
-[package.dependencies]
-ptyprocess = ">=0.5"
-
 [[package]]
 name = "platformdirs"
 version = "4.1.0"
@@ -2084,34 +1026,6 @@ nodeenv = ">=0.11.1"
 pyyaml = ">=5.1"
 virtualenv = ">=20.10.0"
 
-[[package]]
-name = "prometheus-client"
-version = "0.19.0"
-description = "Python client for the Prometheus monitoring system."
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "prometheus_client-0.19.0-py3-none-any.whl", hash = "sha256:c88b1e6ecf6b41cd8fb5731c7ae919bf66df6ec6fafa555cd6c0e16ca169ae92"},
-    {file = "prometheus_client-0.19.0.tar.gz", hash = "sha256:4585b0d1223148c27a225b10dbec5ae9bc4c81a99a3fa80774fa6209935324e1"},
-]
-
-[package.extras]
-twisted = ["twisted"]
-
-[[package]]
-name = "prompt-toolkit"
-version = "3.0.43"
-description = "Library for building powerful interactive command lines in Python"
-optional = false
-python-versions = ">=3.7.0"
-files = [
-    {file = "prompt_toolkit-3.0.43-py3-none-any.whl", hash = "sha256:a11a29cb3bf0a28a387fe5122cdb649816a957cd9261dcedf8c9f1fef33eacf6"},
-    {file = "prompt_toolkit-3.0.43.tar.gz", hash = "sha256:3527b7af26106cbc65a040bcc84839a3566ec1b051bb0bfe953631e704b0ff7d"},
-]
-
-[package.dependencies]
-wcwidth = "*"
-
 [[package]]
 name = "proto-plus"
 version = "1.23.0"
@@ -2160,59 +1074,6 @@ files = [
     {file = "protobuf-3.20.3.tar.gz", hash = "sha256:2e3427429c9cffebf259491be0af70189607f365c2f41c7c3764af6f337105f2"},
 ]
 
-[[package]]
-name = "psutil"
-version = "5.9.6"
-description = "Cross-platform lib for process and system monitoring in Python."
-optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
-files = [
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-    {file = "psutil-5.9.6-cp27-cp27m-manylinux2010_i686.whl", hash = "sha256:91ecd2d9c00db9817a4b4192107cf6954addb5d9d67a969a4f436dbc9200f88c"},
-    {file = "psutil-5.9.6-cp27-cp27m-manylinux2010_x86_64.whl", hash = "sha256:10e8c17b4f898d64b121149afb136c53ea8b68c7531155147867b7b1ac9e7e28"},
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-    {file = "stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9"},
-]
-
-[package.dependencies]
-asttokens = ">=2.1.0"
-executing = ">=1.2.0"
-pure-eval = "*"
-
-[package.extras]
-tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
-
 [[package]]
 name = "tabulate"
 version = "0.9.0"
@@ -2915,45 +1349,6 @@ files = [
 [package.extras]
 widechars = ["wcwidth"]
 
-[[package]]
-name = "terminado"
-version = "0.18.0"
-description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library."
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "terminado-0.18.0-py3-none-any.whl", hash = "sha256:87b0d96642d0fe5f5abd7783857b9cab167f221a39ff98e3b9619a788a3c0f2e"},
-    {file = "terminado-0.18.0.tar.gz", hash = "sha256:1ea08a89b835dd1b8c0c900d92848147cef2537243361b2e3f4dc15df9b6fded"},
-]
-
-[package.dependencies]
-ptyprocess = {version = "*", markers = "os_name != \"nt\""}
-pywinpty = {version = ">=1.1.0", markers = "os_name == \"nt\""}
-tornado = ">=6.1.0"
-
-[package.extras]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
-test = ["pre-commit", "pytest (>=7.0)", "pytest-timeout"]
-typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
-
-[[package]]
-name = "tinycss2"
-version = "1.2.1"
-description = "A tiny CSS parser"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "tinycss2-1.2.1-py3-none-any.whl", hash = "sha256:2b80a96d41e7c3914b8cda8bc7f705a4d9c49275616e886103dd839dfc847847"},
-    {file = "tinycss2-1.2.1.tar.gz", hash = "sha256:8cff3a8f066c2ec677c06dbc7b45619804a6938478d9d73c284b29d14ecb0627"},
-]
-
-[package.dependencies]
-webencodings = ">=0.4"
-
-[package.extras]
-doc = ["sphinx", "sphinx_rtd_theme"]
-test = ["flake8", "isort", "pytest"]
-
 [[package]]
 name = "tomli"
 version = "2.0.1"
@@ -2965,77 +1360,6 @@ files = [
     {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
 ]
 
-[[package]]
-name = "tornado"
-version = "6.4"
-description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
-optional = false
-python-versions = ">= 3.8"
-files = [
-    {file = "tornado-6.4-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:02ccefc7d8211e5a7f9e8bc3f9e5b0ad6262ba2fbb683a6443ecc804e5224ce0"},
-    {file = "tornado-6.4-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:27787de946a9cffd63ce5814c33f734c627a87072ec7eed71f7fc4417bb16263"},
-    {file = "tornado-6.4-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f7894c581ecdcf91666a0912f18ce5e757213999e183ebfc2c3fdbf4d5bd764e"},
-    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e43bc2e5370a6a8e413e1e1cd0c91bedc5bd62a74a532371042a18ef19e10579"},
-    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f0251554cdd50b4b44362f73ad5ba7126fc5b2c2895cc62b14a1c2d7ea32f212"},
-    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:fd03192e287fbd0899dd8f81c6fb9cbbc69194d2074b38f384cb6fa72b80e9c2"},
-    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:88b84956273fbd73420e6d4b8d5ccbe913c65d31351b4c004ae362eba06e1f78"},
-    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:71ddfc23a0e03ef2df1c1397d859868d158c8276a0603b96cf86892bff58149f"},
-    {file = "tornado-6.4-cp38-abi3-win32.whl", hash = "sha256:6f8a6c77900f5ae93d8b4ae1196472d0ccc2775cc1dfdc9e7727889145c45052"},
-    {file = "tornado-6.4-cp38-abi3-win_amd64.whl", hash = "sha256:10aeaa8006333433da48dec9fe417877f8bcc21f48dda8d661ae79da357b2a63"},
-    {file = "tornado-6.4.tar.gz", hash = "sha256:72291fa6e6bc84e626589f1c29d90a5a6d593ef5ae68052ee2ef000dfd273dee"},
-]
-
-[[package]]
-name = "traitlets"
-version = "5.14.0"
-description = "Traitlets Python configuration system"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "traitlets-5.14.0-py3-none-any.whl", hash = "sha256:f14949d23829023013c47df20b4a76ccd1a85effb786dc060f34de7948361b33"},
-    {file = "traitlets-5.14.0.tar.gz", hash = "sha256:fcdaa8ac49c04dfa0ed3ee3384ef6dfdb5d6f3741502be247279407679296772"},
-]
-
-[package.extras]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
-test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
-
-[[package]]
-name = "types-python-dateutil"
-version = "2.8.19.14"
-description = "Typing stubs for python-dateutil"
-optional = false
-python-versions = "*"
-files = [
-    {file = "types-python-dateutil-2.8.19.14.tar.gz", hash = "sha256:1f4f10ac98bb8b16ade9dbee3518d9ace017821d94b057a425b069f834737f4b"},
-    {file = "types_python_dateutil-2.8.19.14-py3-none-any.whl", hash = "sha256:f977b8de27787639986b4e28963263fd0e5158942b3ecef91b9335c130cb1ce9"},
-]
-
-[[package]]
-name = "typing-extensions"
-version = "4.9.0"
-description = "Backported and Experimental Type Hints for Python 3.8+"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "typing_extensions-4.9.0-py3-none-any.whl", hash = "sha256:af72aea155e91adfc61c3ae9e0e342dbc0cba726d6cba4b6c72c1f34e47291cd"},
-    {file = "typing_extensions-4.9.0.tar.gz", hash = "sha256:23478f88c37f27d76ac8aee6c905017a143b0b1b886c3c9f66bc2fd94f9f5783"},
-]
-
-[[package]]
-name = "uri-template"
-version = "1.3.0"
-description = "RFC 6570 URI Template Processor"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "uri-template-1.3.0.tar.gz", hash = "sha256:0e00f8eb65e18c7de20d595a14336e9f337ead580c70934141624b6d1ffdacc7"},
-    {file = "uri_template-1.3.0-py3-none-any.whl", hash = "sha256:a44a133ea12d44a0c0f06d7d42a52d71282e77e2f937d8abd5655b8d56fc1363"},
-]
-
-[package.extras]
-dev = ["flake8", "flake8-annotations", "flake8-bandit", "flake8-bugbear", "flake8-commas", "flake8-comprehensions", "flake8-continuation", "flake8-datetimez", "flake8-docstrings", "flake8-import-order", "flake8-literal", "flake8-modern-annotations", "flake8-noqa", "flake8-pyproject", "flake8-requirements", "flake8-typechecking-import", "flake8-use-fstring", "mypy", "pep8-naming", "types-PyYAML"]
-
 [[package]]
 name = "urllib3"
 version = "1.26.18"
@@ -3072,43 +1396,6 @@ platformdirs = ">=3.9.1,<5"
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
-[[package]]
-name = "wcwidth"
-version = "0.2.12"
-description = "Measures the displayed width of unicode strings in a terminal"
-optional = false
-python-versions = "*"
-files = [
-    {file = "wcwidth-0.2.12-py2.py3-none-any.whl", hash = "sha256:f26ec43d96c8cbfed76a5075dac87680124fa84e0855195a6184da9c187f133c"},
-    {file = "wcwidth-0.2.12.tar.gz", hash = "sha256:f01c104efdf57971bcb756f054dd58ddec5204dd15fa31d6503ea57947d97c02"},
-]
-
-[[package]]
-name = "webcolors"
-version = "1.13"
-description = "A library for working with the color formats defined by HTML and CSS."
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "webcolors-1.13-py3-none-any.whl", hash = "sha256:29bc7e8752c0a1bd4a1f03c14d6e6a72e93d82193738fa860cbff59d0fcc11bf"},
-    {file = "webcolors-1.13.tar.gz", hash = "sha256:c225b674c83fa923be93d235330ce0300373d02885cef23238813b0d5668304a"},
-]
-
-[package.extras]
-docs = ["furo", "sphinx", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-notfound-page", "sphinxext-opengraph"]
-tests = ["pytest", "pytest-cov"]
-
-[[package]]
-name = "webencodings"
-version = "0.5.1"
-description = "Character encoding aliases for legacy web content"
-optional = false
-python-versions = "*"
-files = [
-    {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
-    {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
-]
-
 [[package]]
 name = "websocket-client"
 version = "1.7.0"
@@ -3125,33 +1412,7 @@ docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
-[[package]]
-name = "widgetsnbextension"
-version = "4.0.9"
-description = "Jupyter interactive widgets for Jupyter Notebook"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "widgetsnbextension-4.0.9-py3-none-any.whl", hash = "sha256:91452ca8445beb805792f206e560c1769284267a30ceb1cec9f5bcc887d15175"},
-    {file = "widgetsnbextension-4.0.9.tar.gz", hash = "sha256:3c1f5e46dc1166dfd40a42d685e6a51396fd34ff878742a3e47c6f0cc4a2a385"},
-]
-
-[[package]]
-name = "zipp"
-version = "3.17.0"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
-    {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"},
-]
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
-
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "3106762f19633ae74afcf39c8410ccdf11079d1ea38a3748f3b03e2a47af198a"
+content-hash = "0be210fbd2f02c00c34f9c03fb76646129ec4a80cb8dee6705e2f06ff6a36639"
diff --git a/pipelines/pyproject.toml b/pipelines/pyproject.toml
index 619fc02f..dd288fb8 100644
--- a/pipelines/pyproject.toml
+++ b/pipelines/pyproject.toml
@@ -21,7 +21,6 @@ google-cloud-pipeline-components = "^2.1.0"
 components = { path = "../components", develop = true }
 kfp = "^2.0.1"
 pyyaml = "6.0.1"
-jupyter = "^1.0.0"
 
 [tool.poetry.group.dev.dependencies]
 pytest = ">=7.3.1,<8.0.0"

From f7cbf1995bb4b8031c763752c5ac3d18a2e7d367 Mon Sep 17 00:00:00 2001
From: Felix Schaumann <felix.schaumann@datatonic.com>
Date: Tue, 23 Jan 2024 13:24:27 +0100
Subject: [PATCH 236/238] Remove poetry cache

---
 model/Dockerfile | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/model/Dockerfile b/model/Dockerfile
index 83dfd493..11e889b9 100644
--- a/model/Dockerfile
+++ b/model/Dockerfile
@@ -15,23 +15,23 @@ FROM python:3.9.16-slim AS builder
 
 ENV PIP_NO_CACHE_DIR=off \
     PIP_DISABLE_PIP_VERSION_CHECK=on \
-    PIP_DEFAULT_TIMEOUT=100
+    PIP_DEFAULT_TIMEOUT=100 \
+    POETRY_VIRTUALENVS_CREATE=false
 
 ARG POETRY_VERSION=1.5.1
-
-COPY pyproject.toml pyproject.toml
-COPY poetry.lock poetry.lock
-
 RUN pip install poetry==${POETRY_VERSION}
-RUN poetry config virtualenvs.create false && poetry install
+COPY pyproject.toml poetry.lock .
 
 FROM builder AS training
 
+RUN poetry install --no-cache --no-interaction --without prediction
 COPY training training
 
+CMD python -m training
+
 FROM builder AS prediction
 
-RUN poetry install --with prediction
+RUN poetry install --no-cache --no-interaction --with prediction
 COPY prediction prediction
 
 CMD exec uvicorn prediction.main:app --host "0.0.0.0" --port "$AIP_HTTP_PORT"

From 9be489b2849dcc4d7123136d28515977e7de3ff2 Mon Sep 17 00:00:00 2001
From: theo-dt <theodoros.marinos@datatonic.com>
Date: Wed, 27 Nov 2024 14:43:37 +0000
Subject: [PATCH 237/238] updated readme

Updated readme to include section about troubleshooting issues with the Vertex AI Custom Code Service Agent
---
 README.md | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/README.md b/README.md
index 9a7fe501..a09735e9 100644
--- a/README.md
+++ b/README.md
@@ -164,6 +164,12 @@ make test [ packages=<pipelines components> ]
 
 For details on setting up CI/CD, see [this guide](./docs/Automation.md).
 
+## Issues with Vertex AI Custom Code Service Agent
+
+If you run custom training code to train a custom-trained model, then the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control) will be used. In those cases, the agent is created only when you first try to run custom training code which means you can't assign permissions to the agent, like artifact registry reader, from the very beginning. To tackle this, you can use [this guide](https://github.com/teamdatatonic/terraform-google-vertex-cc-service-agent). This repo uses the curl command to create a simple custom training job which triggers the creation of the service agent. You can also edit that code to use ```gcloud ai custom-jobs create``` to create the job if you want.
+
+Alternatively, Google has another method of triggering the creation of service agents that is currently in pre-ga that can be used instead of the above solution. You can read more about it [here](https://cloud.google.com/iam/docs/create-service-agents#create) 
+
 ## Putting it all together
 
 For a full walkthrough of the journey from changing the ML pipeline code to having it scheduled and running in production, please see the guide [here](./docs/Production.md).

From 43a0d6ca6b6db23b749f0fea953ff0422ae0418d Mon Sep 17 00:00:00 2001
From: Felix Schaumann <89205956+felix-datatonic@users.noreply.github.com>
Date: Wed, 27 Nov 2024 14:50:20 +0000
Subject: [PATCH 238/238] Update README.md

---
 README.md | 11 ++++++++---
 1 file changed, 8 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index a09735e9..da853fc5 100644
--- a/README.md
+++ b/README.md
@@ -166,9 +166,14 @@ For details on setting up CI/CD, see [this guide](./docs/Automation.md).
 
 ## Issues with Vertex AI Custom Code Service Agent
 
-If you run custom training code to train a custom-trained model, then the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control) will be used. In those cases, the agent is created only when you first try to run custom training code which means you can't assign permissions to the agent, like artifact registry reader, from the very beginning. To tackle this, you can use [this guide](https://github.com/teamdatatonic/terraform-google-vertex-cc-service-agent). This repo uses the curl command to create a simple custom training job which triggers the creation of the service agent. You can also edit that code to use ```gcloud ai custom-jobs create``` to create the job if you want.
-
-Alternatively, Google has another method of triggering the creation of service agents that is currently in pre-ga that can be used instead of the above solution. You can read more about it [here](https://cloud.google.com/iam/docs/create-service-agents#create) 
+If you run custom training code to train a custom-trained model, then the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access-control) will be used. 
+In those cases, the agent is created only when you first try to run custom training code which means you can't assign permissions to the agent, like artifact registry reader, from the very beginning. 
+To tackle this, you can use [this guide](https://github.com/teamdatatonic/terraform-google-vertex-cc-service-agent). 
+This repo uses the curl command to create a simple custom training job which triggers the creation of the service agent. 
+You can also edit that code to use `gcloud ai custom-jobs create` to create the job if you want.
+
+Alternatively, Google has another method of triggering the creation of service agents that is currently in pre-GA that can be used instead of the above solution. 
+You can read more about it [here](https://cloud.google.com/iam/docs/create-service-agents#create).
 
 ## Putting it all together