Merge branch 'main' into feature/direct-access

src/atc/transformers/__init__.py

@@ -1,6 +1,8 @@
 from .drop_oldest_duplicate_transformer import (  # noqa: F401
     DropOldestDuplicatesTransformer,
 )
+from .dropColumnsTransformer import DropColumnsTransformer  # noqa: F401
+from .selectColumnsTransformer import SelectColumnsTransformer  # noqa: F401
 from .simple_sql_transformer import SimpleSqlServerTransformer  # noqa: F401
 from .timezone_transformer_nc import TimeZoneTransformerNC  # noqa: F401
 from .union_transformer import UnionTransformer  # noqa: F401

src/atc/transformers/dropColumnsTransformer.py

@@ -0,0 +1,22 @@
+from typing import List
+
+from pyspark.sql import DataFrame
+
+from atc.etl import TransformerNC
+
+
+class DropColumnsTransformer(TransformerNC):
+    def __init__(
+        self,
+        columnList: List[str],
+        dataset_input_key: str = None,
+        dataset_output_key: str = None,
+    ):
+        super().__init__(
+            dataset_input_key=dataset_input_key, dataset_output_key=dataset_output_key
+        )
+        self.columnList = columnList
+
+    def process(self, df: DataFrame) -> DataFrame:
+        df = df.drop(*self.columnList)
+        return df

src/atc/transformers/selectColumnsTransformer.py

@@ -0,0 +1,21 @@
+from typing import List
+
+from pyspark.sql import DataFrame
+
+from atc.etl import TransformerNC
+
+
+class SelectColumnsTransformer(TransformerNC):
+    def __init__(
+        self,
+        columnList: List[str],
+        dataset_input_key: str = None,
+        dataset_output_key: str = None,
+    ):
+        super().__init__(
+            dataset_input_key=dataset_input_key, dataset_output_key=dataset_output_key
+        )
+        self.columnList = columnList
+
+    def process(self, df: DataFrame) -> DataFrame:
+        return df.select(self.columnList)

tests/local/transformers/test_drop_columns.py

@@ -0,0 +1,36 @@
+import pyspark.sql.types as T
+from atc_tools.testing import DataframeTestCase
+
+from atc.spark import Spark
+from atc.transformers import DropColumnsTransformer
+
+
+class TestDropColumnsTransformer(DataframeTestCase):
+    def test_drop_columns_transformer(self):
+
+        inputSchema = T.StructType(
+            [
+                T.StructField("id", T.LongType(), True),
+                T.StructField("text1", T.StringType(), True),
+                T.StructField("text2", T.StringType(), True),
+            ]
+        )
+
+        inputData = [
+            (
+                1,
+                "text1",
+                "text2",
+            ),
+        ]
+
+        df_input = Spark.get().createDataFrame(data=inputData, schema=inputSchema)
+
+        expectedData = [
+            (1,),
+        ]
+
+        df_transformed = DropColumnsTransformer(columnList=["text1", "text2"]).process(
+            df_input
+        )
+        self.assertDataframeMatches(df_transformed, None, expectedData)

tests/local/transformers/test_select_columns.py

@@ -0,0 +1,30 @@
+import pyspark.sql.types as T
+from atc_tools.testing import DataframeTestCase
+
+from atc.spark import Spark
+from atc.transformers import SelectColumnsTransformer
+
+
+class TestSelectColumnsTransformer(DataframeTestCase):
+    def test_select_columns_transformer(self):
+
+        inputSchema = T.StructType(
+            [
+                T.StructField("Col1", T.StringType(), True),
+                T.StructField("Col2", T.IntegerType(), True),
+                T.StructField("Col3", T.DoubleType(), True),
+                T.StructField("Col4", T.StringType(), True),
+                T.StructField("Col5", T.StringType(), True),
+            ]
+        )
+        inputData = [("Col1Data", 42, 13.37, "Col4Data", "Col5Data")]
+
+        input_df = Spark.get().createDataFrame(data=inputData, schema=inputSchema)
+
+        expectedData = [(42, 13.37, "Col4Data")]
+
+        transformed_df = SelectColumnsTransformer(
+            columnList=["Col2", "Col3", "Col4"]
+        ).process(input_df)
+
+        self.assertDataframeMatches(transformed_df, None, expectedData)