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chore(mypy): enable warn_unused_ignores (#20884)

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John Bodley 2022-07-29 00:47:53 -07:00 committed by GitHub
parent 50d2e5a15d
commit 8d0d778d1a
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3 changed files with 9 additions and 9 deletions
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2
setup.cfg
View File

@ -41,7 +41,7 @@ disallow_untyped_calls = true
disallow_untyped_defs = true disallow_untyped_defs = true
ignore_missing_imports = true ignore_missing_imports = true
no_implicit_optional = true no_implicit_optional = true
warn_unused_ignores = false warn_unused_ignores = true
[mypy-superset.migrations.versions.*] [mypy-superset.migrations.versions.*]
ignore_errors = true ignore_errors = true

14
superset/models/helpers.py
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@ -750,7 +750,7 @@ class ExploreMixin: # pylint: disable=too-many-public-methods
def get_extra_cache_keys(query_obj: Dict[str, Any]) -> List[str]: def get_extra_cache_keys(query_obj: Dict[str, Any]) -> List[str]:
raise NotImplementedError() raise NotImplementedError()
def _process_sql_expression( # type: ignore # pylint: disable=no-self-use def _process_sql_expression( # pylint: disable=no-self-use
self, self,
expression: Optional[str], expression: Optional[str],
database_id: int, database_id: int,
@ -1061,7 +1061,7 @@ class ExploreMixin: # pylint: disable=too-many-public-methods
sqla_column = sa.column(column_name) sqla_column = sa.column(column_name)
sqla_metric = self.sqla_aggregations[metric["aggregate"]](sqla_column) sqla_metric = self.sqla_aggregations[metric["aggregate"]](sqla_column)
elif expression_type == utils.AdhocMetricExpressionType.SQL: elif expression_type == utils.AdhocMetricExpressionType.SQL:
expression = self._process_sql_expression( # type: ignore expression = self._process_sql_expression(
expression=metric["sqlExpression"], expression=metric["sqlExpression"],
database_id=self.database_id, database_id=self.database_id,
schema=self.schema, schema=self.schema,
@ -1170,8 +1170,8 @@ class ExploreMixin: # pylint: disable=too-many-public-methods
:rtype: sqlalchemy.sql.column :rtype: sqlalchemy.sql.column
""" """
label = utils.get_column_name(col) # type: ignore label = utils.get_column_name(col) # type: ignore
expression = self._process_sql_expression( # type: ignore expression = self._process_sql_expression(
expression=col["sqlExpression"], # type: ignore expression=col["sqlExpression"],
database_id=self.database_id, database_id=self.database_id,
schema=self.schema, schema=self.schema,
template_processor=template_processor, template_processor=template_processor,
@ -1351,7 +1351,7 @@ class ExploreMixin: # pylint: disable=too-many-public-methods
metrics_exprs.append( metrics_exprs.append(
self.adhoc_metric_to_sqla( self.adhoc_metric_to_sqla(
metric=metric, metric=metric,
columns_by_name=columns_by_name, # type: ignore columns_by_name=columns_by_name,
template_processor=template_processor, template_processor=template_processor,
) )
) )
@ -1379,7 +1379,7 @@ class ExploreMixin: # pylint: disable=too-many-public-methods
if isinstance(col, dict): if isinstance(col, dict):
col = cast(AdhocMetric, col) col = cast(AdhocMetric, col)
if col.get("sqlExpression"): if col.get("sqlExpression"):
col["sqlExpression"] = self._process_sql_expression( # type: ignore col["sqlExpression"] = self._process_sql_expression(
expression=col["sqlExpression"], expression=col["sqlExpression"],
database_id=self.database_id, database_id=self.database_id,
schema=self.schema, schema=self.schema,
@ -1387,7 +1387,7 @@ class ExploreMixin: # pylint: disable=too-many-public-methods
) )
if utils.is_adhoc_metric(col): if utils.is_adhoc_metric(col):
# add adhoc sort by column to columns_by_name if not exists # add adhoc sort by column to columns_by_name if not exists
col = self.adhoc_metric_to_sqla(col, columns_by_name) # type: ignore col = self.adhoc_metric_to_sqla(col, columns_by_name)
# if the adhoc metric has been defined before # if the adhoc metric has been defined before
# use the existing instance. # use the existing instance.
col = metrics_exprs_by_expr.get(str(col), col) col = metrics_exprs_by_expr.get(str(col), col)

2
superset/utils/core.py
View File

@ -1689,7 +1689,7 @@ def extract_dataframe_dtypes(
column_object = columns_by_name.get(column) column_object = columns_by_name.get(column)
series = df[column] series = df[column]
inferred_type = infer_dtype(series) inferred_type = infer_dtype(series)
if isinstance(column_object, dict): # type: ignore if isinstance(column_object, dict):
generic_type = ( generic_type = (
GenericDataType.TEMPORAL GenericDataType.TEMPORAL
if column_object and column_object.get("is_dttm") if column_object and column_object.get("is_dttm")