lint

superset/connectors/sqla/models.py

@@ -1006,17 +1006,17 @@ def adhoc_metric_to_sqla(
 
  return self.make_sqla_column_compatible(sqla_metric, label)
 
- def adhoc_column_to_sqla(
+ def adhoc_column_to_sqla( # pylint: disable=too-many-locals
  self,
  col: AdhocColumn,
- force_check_expression: bool = False,
+ force_type_check: bool = False,
  template_processor: Optional[BaseTemplateProcessor] = None,
  ) -> ColumnElement:
  """
  Turn an adhoc column into a sqlalchemy column.
 
  :param col: Adhoc column definition
- :param force_check_expression: Should the expression be checked in the db.
+ :param force_type_check: Should the column type be checked in the db.
  This is needed to validate if a filter with an adhoc column
  is applicable.
  :param template_processor: template_processor instance
@@ -1041,7 +1041,7 @@ def adhoc_column_to_sqla(
  is_dttm = col_in_metadata.is_temporal
  else:
  sqla_column = literal_column(expression)
- if has_timegrain or force_check_expression:
+ if has_timegrain or force_type_check:
  try:
  # probe adhoc column type
  tbl, _ = self.get_from_clause(template_processor)
@@ -1464,7 +1464,7 @@ def get_sqla_query( # pylint: disable=too-many-arguments,too-many-locals,too-ma
  try:
  sqla_col = self.adhoc_column_to_sqla(
  col=flt_col,
- force_check_expression=True,
+ force_type_check=True,
  template_processor=template_processor,
  )
  applied_adhoc_filters_columns.append(flt_col)

superset/utils/pandas_postprocessing/pivot.py

@@ -28,7 +28,7 @@
 
 
 @validate_column_args("index", "columns")
-def pivot( # pylint: disable=too-many-arguments,too-many-locals
+def pivot( # pylint: disable=too-many-arguments
  df: DataFrame,
  index: List[str],
  aggregates: Dict[str, Dict[str, Any]],