adding tests for create_backup_csv

_delphi_utils_python/delphi_utils/export.py

@@ -191,13 +191,16 @@ def create_backup_csv(
         backup_filename = [issue, geo_res, metric, sensor]
         backup_filename = "_".join(filter(None, backup_filename)) + ".csv.gz"
         backup_file = join(backup_dir, backup_filename)
-
-        with gzip.open(backup_file, "wt", newline="") as f:
-            df.to_csv(f, index=False, na_rep="NA")
-
-        if logger:
-            logger.info(
-                "Backup file created",
-                backup_file=backup_file,
-                backup_size=getsize(backup_file),
-            )
+        try:
+            with gzip.open(backup_file, "wt", newline="") as f:
+                df.to_csv(f, index=False, na_rep="NA")
+
+            if logger:
+                logger.info(
+                    "Backup file created",
+                    backup_file=backup_file,
+                    backup_size=getsize(backup_file),
+                )
+        #pylint: disable=W0703
+        except Exception as e:
+            logger.info("Backup file creation failed", msg=e)

_delphi_utils_python/tests/test_export.py

@@ -1,15 +1,16 @@
 """Tests for exporting CSV files."""
 from datetime import datetime
+import logging
 from os import listdir
 from os.path import join
-from typing import Any, Dict, List
+from typing import Any, Dict
 
 import mock
 import numpy as np
 import pandas as pd
 from pandas.testing import assert_frame_equal
 
-from delphi_utils import create_export_csv, Nans
+from delphi_utils import create_export_csv, Nans, create_backup_csv, get_structured_logger
 
 
 def _set_df_dtypes(df: pd.DataFrame, dtypes: Dict[str, Any]) -> pd.DataFrame:
@@ -386,3 +387,18 @@ def test_export_sort(self, tmp_path):
         })
         sorted_csv = _set_df_dtypes(pd.read_csv(join(tmp_path, "20200215_county_test.csv")), dtypes={"geo_id": str})
         assert_frame_equal(sorted_csv,expected_df)
+
+    def test_create_backup_regular(self, caplog, tmp_path):
+        caplog.set_level(logging.INFO)
+        logger = get_structured_logger()
+        today = datetime.strftime(datetime.today(), "%Y%m%d")
+        dtypes = self.DF.dtypes.to_dict()
+        del dtypes["timestamp"]
+        geo_res = "county"
+        metric = "test"
+        sensor = "deaths"
+        create_backup_csv(df=self.DF, backup_dir=tmp_path, custom_run=False, issue=None, geo_res=geo_res, metric=metric, sensor=sensor, logger=logger)
+        assert "Backup file created" in caplog.text
+
+        actual = pd.read_csv(join(tmp_path, f"{today}_{geo_res}_{metric}_{sensor}.csv.gz"), dtype=dtypes, parse_dates=["timestamp"])
+        assert self.DF.equals(actual)