resolving linting issues

Signed-off-by: dharmishadoshi@gmail.com <d0d0fmz@m-j2t66th1w2.homeoffice.wal-mart.com>
Signed-off-by: Dharmisha Doshi <dharmishadoshi@gmail.com>

sdk/python/feast/infra/offline_stores/bigquery.py

@@ -898,8 +898,7 @@ def arrow_schema_to_bq_schema(arrow_schema: pyarrow.Schema) -> List[SchemaField]
     {{ featureview.name }}__subquery AS (
         SELECT
             {{ featureview.timestamp_field }} as event_timestamp,
-            {{ featureview.created_timestamp_column ~ ' as created_timestamp,' if featureview.created_timestamp_column 
-            else '' }}
+            {{ featureview.created_timestamp_column ~ ' as created_timestamp,' if featureview.created_timestamp_column else '' }}
             {{ featureview.entity_selections | join(', ')}}{% if featureview.entity_selections %},{% else %}{% endif %}
             {% for feature in featureview.features %}
                 {{ feature | backticks }} as {% if full_feature_names %}

sdk/python/feast/infra/offline_stores/offline_utils.py

@@ -187,7 +187,7 @@ def build_point_in_time_query(
 ) -> str:
     """Build point-in-time query between each feature view table and the entity dataframe for Bigquery and Redshift"""
     env = Environment(loader=BaseLoader())
-    env.filters['backticks'] = enclose_in_backticks
+    env.filters["backticks"] = enclose_in_backticks
     template = env.from_string(source=query_template)
 
     final_output_feature_names = list(entity_df_columns)
@@ -259,6 +259,6 @@ def get_pyarrow_schema_from_batch_source(
 def enclose_in_backticks(value):
     # Check if the input is a list
     if isinstance(value, list):
-        return [f'`{v}`' for v in value]
+        return [f"`{v}`" for v in value]
     else:
-        return f'`{value}`'
+        return f"`{value}`"