zephyring commented on code in PR #23021:
URL: https://github.com/apache/superset/pull/23021#discussion_r1309449085
##########
superset/common/query_context_factory.py:
##########
@@ -99,3 +103,89 @@ def _convert_to_model(self, datasource: DatasourceDict) ->
BaseDatasource:
def _get_slice(self, slice_id: Any) -> Optional[Slice]:
return ChartDAO.find_by_id(slice_id)
+
+ def _process_query_object(
+ self,
+ datasource: BaseDatasource,
+ form_data: Optional[Dict[str, Any]],
+ query_object: QueryObject,
+ ) -> QueryObject:
+ self._apply_granularity(query_object, form_data, datasource)
+ self._apply_filters(query_object)
+ return query_object
+
+ def _apply_granularity(
+ self,
+ query_object: QueryObject,
+ form_data: Optional[Dict[str, Any]],
+ datasource: BaseDatasource,
+ ) -> None:
+ temporal_columns = {
+ column.column_name
+ for column in datasource.columns
+ if (column["is_dttm"] if isinstance(column, dict) else
column.is_dttm)
+ }
+ granularity = query_object.granularity
+ x_axis = form_data and form_data.get("x_axis")
+
+ if granularity:
+ filter_to_remove = None
+ if x_axis and x_axis in temporal_columns:
Review Comment:
hey @michael-s-molina we recently found a regression where the `x_axis`
could be a `dict` while `temporal_columns` is a set of string and it throws.
Steps to reproduce:
```
1. Create a Bar Chart using the Vehicle Sales dataset.
2. Use Custom SQL for the X-Axis field and type in order_date.
3. Use SUM(price_each) for the Metrics field.
4. Use the SQL Lab to duplicate the Vehicle Sales dataset.
5. Perform a dataset swap to the duplicated Vehicle Sales dataset.
6. Update and Save the chart.
```
I am trying to use `x_axis["sqlExpression"]` to get the proper str to
compare down the road and it doesn't seem to have the same effect.
Would love your thoughts here thanks!
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