lint

india_forecast_app/adjuster.py

@@ -140,7 +140,7 @@ def get_me_values(
     return me_df
 
 
-def zero_out_nighttime(
+def zero_out_night_time_for_pv(
     db_session,
     forecast_values_df: pd.DataFrame,
     site_uuid: str,
@@ -153,6 +153,7 @@ def zero_out_nighttime(
     db_session: sqlalchemy session
     forecast_values_df: forecast values dataframe
     site_uuid: the site uuid
+    elevation_limit: the elevation limit to zero out values, this defaults to 0.
     """
     # get the site
     site = get_site_by_uuid(db_session, site_uuid)
@@ -246,7 +247,7 @@ def adjust_forecast_with_adjuster(
     forecast_values_df_adjust.drop(columns=["me_kw"], inplace=True)
 
     # make sure there are no positive values at nighttime
-    forecast_values_df_adjust = zero_out_nighttime(
+    forecast_values_df_adjust = zero_out_night_time_for_pv(
         db_session=db_session,
         forecast_values_df=forecast_values_df_adjust,
         site_uuid=forecast_meta["site_uuid"],

tests/test_adjuster.py

@@ -7,7 +7,7 @@
 from india_forecast_app.adjuster import (
     adjust_forecast_with_adjuster,
     get_me_values,
-    zero_out_nighttime,
+    zero_out_night_time_for_pv,
 )
 
 
@@ -112,7 +112,7 @@ def test_adjust_forecast_with_adjuster_no_values(db_session, sites):
 
 
 @pytest.mark.parametrize("asset_type", ["pv", "wind"])
-def test_zero_out_nighttime(asset_type, db_session, sites):
+def test_zero_out_night_time_for_pv(asset_type, db_session, sites):
     """ Test for zero_out_nighttime """
     forecast_values_df = pd.DataFrame(
         {
@@ -126,7 +126,7 @@ def test_zero_out_nighttime(asset_type, db_session, sites):
 
     sites[0].asset_type = asset_type
 
-    forecast_values_df = zero_out_nighttime(
+    forecast_values_df = zero_out_night_time_for_pv(
         db_session, forecast_values_df=forecast_values_df, site_uuid=sites[0].site_uuid
     )