add data copy

Author: Eric Novotny

tests/cda/timeseries/timeseries_CDA_test.py

@@ -19,6 +19,7 @@
 TEST_TSID_COPY = f"{TEST_LOCATION_ID}.Stage.Inst.15Minutes.0.Raw-Copy"
 TEST_TSID_DELETE = f"{TEST_LOCATION_ID}.Stage.Inst.15Minutes.0.Raw-Delete"
 TEST_TSID_CHUNK_NULLS = f"{TEST_LOCATION_ID}.Stage.Inst.15Minutes.0.Raw-Multi-Nulls"
+TEST_TSID_COPY_NULLS = f"{TEST_LOCATION_ID}.Stage.Inst.15Minutes.0.Raw-Copy-Nulls"
 TS_ID_REV_TEST = TEST_TSID_MULTI.replace("Raw-Multi", "Raw-Rev-Test")
 # Generate 15-minute interval timestamps
 START_DATE_CHUNK_MULTI = datetime(2025, 7, 31, 0, 0, tzinfo=timezone.utc)
@@ -33,6 +34,7 @@
     TEST_TSID_CHUNK_MULTI,
     TEST_TSID_COPY,
     TEST_TSID_CHUNK_NULLS,
+    TEST_TSID_COPY_NULLS,
 ]
 
 
@@ -50,6 +52,12 @@
         "quality-code": [0] * len(DT_CHUNK_MULTI),
     }
 )
+# Create a copy of the original DataFrame and introduce null values
+DF_WITH_NULLS = DF_CHUNK_MULTI.copy()
+# Set the 100 and 200 index value to null
+DF_WITH_NULLS.loc[100, "value"] = None
+DF_WITH_NULLS.loc[200, "value"] = None
+
 
 DF_MULTI_TIMESERIES1 = pd.DataFrame(
     {
@@ -283,14 +291,8 @@ def test_store_timesereis_chunk_to_with_null_values():
     office = TEST_OFFICE
     units = "m"
 
-    # Create a copy of the original DataFrame and introduce null values
-    df_with_nulls = DF_CHUNK_MULTI.copy()
-    # Set the 100 and 200 index value to null
-    df_with_nulls.loc[100, "value"] = None
-    df_with_nulls.loc[200, "value"] = None
-
     # Convert DataFrame to JSON format
-    ts_json = ts.timeseries_df_to_json(df_with_nulls, ts_id, units, office)
+    ts_json = ts.timeseries_df_to_json(DF_WITH_NULLS, ts_id, units, office)
 
     ts.store_timeseries(ts_json, multithread=True)
 
@@ -304,8 +306,35 @@ def test_store_timesereis_chunk_to_with_null_values():
     df_nulls = data_nulls.df
     # make sure the dataframe matches stored dataframe with null values
     pdt.assert_frame_equal(
-        df_nulls, df_with_nulls
-    ), f"Data frames do not match: original with nulls = {df_with_nulls.describe()}, stored = {df_nulls.describe()}"
+        df_nulls, DF_WITH_NULLS
+    ), f"Data frames do not match: original with nulls = {DF_WITH_NULLS.describe()}, stored = {df_nulls.describe()}"
+
+
+def test_copy_timeseries_chunk_json_with_nulls():
+    data_json = ts.get_timeseries(
+        ts_id=TEST_TSID_CHUNK_NULLS,
+        office_id=TEST_OFFICE,
+        begin=START_DATE_CHUNK_MULTI,
+        end=END_DATE_CHUNK_MULTI,
+        max_days_per_chunk=14,
+        unit="SI",
+    ).json
+    data_json["name"] = TEST_TSID_COPY_NULLS
+    ts.store_timeseries(data_json)
+
+    data_multithread = ts.get_timeseries(
+        ts_id=TEST_TSID_COPY_NULLS,
+        office_id=TEST_OFFICE,
+        begin=START_DATE_CHUNK_MULTI,
+        end=END_DATE_CHUNK_MULTI,
+        max_days_per_chunk=14,
+        unit="SI",
+    )
+    df = data_multithread.df
+    # make sure the dataframe matches stored dataframe with null values
+    pdt.assert_frame_equal(
+        df, DF_WITH_NULLS
+    ), f"Data frames do not match: original with nulls = {DF_WITH_NULLS.describe()}, stored = {df.describe()}"
 
 
 def test_copy_timeseries_chunk_json():