Add Additional Args for Store Multiple TS Function (#276)

* Ensure we expose the multi thread option and enable store_multi_ts to handle needed params

* Update the multi ts tests to include the new kwargs

* Patch bump

* Set multithread default to true

Author: krowvin

cwms/timeseries/timeseries.py

@@ -469,6 +469,10 @@ def timeseries_df_to_json(
 def store_multi_timeseries_df(
     data: pd.DataFrame,
     office_id: str,
+    create_as_ltrs: Optional[bool] = False,
+    store_rule: Optional[str] = None,
+    override_protection: Optional[bool] = False,
+    multithread: Optional[bool] = True,
     max_workers: Optional[int] = 30,
 ) -> None:
     """stored mulitple timeseries from a dataframe.  The dataframe must be a metled dataframe with columns
@@ -489,6 +493,19 @@ def store_multi_timeseries_df(
                 2   2023-12-20T15:15:00.000-05:00  98.5           0   OMA.Stage.Inst.6Hours.0.Fcst-MRBWM-GRFT ft     2024-04-22 07:15:00-05:00
         office_id: string
             The owning office of the time series(s).
+        create_as_ltrs: bool, optional, default is False
+            Flag indicating if timeseries should be created as Local Regular Time Series.
+        store_rule: str, optional, default is None:
+            The business rule to use when merging the incoming with existing data. Available values :
+                REPLACE_ALL,
+                DO_NOT_REPLACE,
+                REPLACE_MISSING_VALUES_ONLY,
+                REPLACE_WITH_NON_MISSING,
+                DELETE_INSERT.
+        override_protection: bool, optional, default is False
+            A flag to ignore the protected data quality flag when storing data.
+        multithread: bool, default is false
+            Specifies whether to store chunked time series values using multiple threads.
         max_workers: Int, Optional, default is None
             It is a number of Threads aka size of pool in concurrent.futures.ThreadPoolExecutor.
 
@@ -502,7 +519,6 @@ def store_ts_ids(
         ts_id: str,
         office_id: str,
         version_date: Optional[datetime] = None,
-        multithread: bool = False,
     ) -> None:
         try:
             units = data["units"].iloc[0]
@@ -513,7 +529,13 @@ def store_ts_ids(
                 office_id=office_id,
                 version_date=version_date,
             )
-            store_timeseries(data=data_json, multithread=multithread)
+            store_timeseries(
+                data=data_json,
+                create_as_ltrs=create_as_ltrs,
+                store_rule=store_rule,
+                override_protection=override_protection,
+                multithread=multithread,
+            )
         except Exception as e:
             print(f"Error processing {ts_id}: {e}")
         return None

pyproject.toml

@@ -2,7 +2,7 @@
 name = "cwms-python"
 repository = "https://github.com/HydrologicEngineeringCenter/cwms-python"
 
-version = "1.0.6"
+version = "1.0.7"
 
 packages = [
     { include = "cwms" },

tests/cda/timeseries/timeseries_CDA_test.py

@@ -184,7 +184,12 @@ def test_store_multi_timeseries_df():
             "units": ["ft", "ft"],
         }
     )
-    ts.store_multi_timeseries_df(df, TEST_OFFICE)
+    ts.store_multi_timeseries_df(
+        df,
+        TEST_OFFICE,
+        store_rule="REPLACE_ALL",
+        override_protection=False,
+    )
     data1 = ts.get_timeseries(
         TEST_TSID_MULTI, TEST_OFFICE, multithread=False, begin=BEGIN, end=END
     ).json
@@ -203,7 +208,13 @@ def test_store_multi_timeseries_df():
 
 def test_store_multi_timeseries_chunks_df():
     # test getting multi timeseries while using the chunk method as well
-    ts.store_multi_timeseries_df(data=DF_MULTI_TIMESERIES, office_id=TEST_OFFICE)
+    ts.store_multi_timeseries_df(
+        data=DF_MULTI_TIMESERIES,
+        office_id=TEST_OFFICE,
+        store_rule="REPLACE_ALL",
+        override_protection=False,
+        multithread=True,
+    )
     data1 = ts.get_timeseries(
         ts_id=TEST_TSID_MULTI1,
         office_id=TEST_OFFICE,