aminghadersohi commented on code in PR #45133:
URL: https://github.com/apache/superset/pull/45133#discussion_r4252878296
##########
superset/semantic_layers/mapper.py:
##########
@@ -771,30 +774,94 @@ def _convert_query_object_filter(
)
return filters or None
- value = _coerce_filter_value(value, dimension)
-
- operator = OPERATOR_MAP.get(operator_str)
+ operator: Operator | None = OPERATOR_MAP.get(operator_str)
if not operator:
# Unknown operator - raise error to prevent unauthorized access
raise ValueError(f"Unsupported filter operator: {operator_str}")
- return {
+ value: FilterValues | frozenset[FilterValues]
+ if operator in {Operator.IN, Operator.NOT_IN}:
+ # Coerce before deduplicating: equal raw values (0 and False) may
differ
+ # in validity for the selected dimension's type.
+ value = (
+ frozenset(
+ _coerce_scalar_filter_value(item, dimension) for item in
raw_value
+ )
+ if isinstance(raw_value, (list, tuple))
+ else _coerce_scalar_filter_value(raw_value, dimension)
+ )
+ elif operator in {Operator.IS_NULL, Operator.IS_NOT_NULL}:
+ value = None
+ else:
+ # Match the native datasource's scalar handling of collection inputs.
+ scalar: FilterValues = (
+ (raw_value[0] if raw_value else None)
+ if isinstance(raw_value, (list, tuple))
+ else raw_value
+ )
+ value = _coerce_scalar_filter_value(scalar, dimension)
+ if value is None and operator not in {Operator.EQUALS,
Operator.NOT_EQUALS}:
+ raise QueryObjectValidationError(
+ "Must specify a value for this comparison."
+ )
+
+ return _normalize_membership_filter(
Filter(
type=PredicateType.WHERE,
column=dimension,
operator=operator,
value=value,
)
- }
+ )
-def _coerce_filter_value(
- value: FilterValues | frozenset[FilterValues],
- dimension: Dimension,
-) -> FilterValues | frozenset[FilterValues]:
- if isinstance(value, frozenset):
- return frozenset(_coerce_scalar_filter_value(v, dimension) for v in
value)
- return _coerce_scalar_filter_value(value, dimension)
+def _normalize_membership_filter(filter_: Filter) -> set[FilterExpression]:
+ """Normalize NULL equality/membership and reject empty membership
selections."""
+ negated: bool = filter_.operator in {Operator.NOT_EQUALS, Operator.NOT_IN}
+ null_filter: Filter = replace(
+ filter_,
+ operator=Operator.IS_NOT_NULL if negated else Operator.IS_NULL,
+ value=None,
+ )
+ if filter_.operator in {Operator.EQUALS, Operator.NOT_EQUALS}:
+ return {null_filter} if filter_.value is None else {filter_}
+ if filter_.operator not in {Operator.IN, Operator.NOT_IN}:
+ return {filter_}
+
+ values: frozenset[FilterValues] = (
+ frozenset(filter_.value)
+ if isinstance(filter_.value, (tuple, frozenset))
+ else frozenset({filter_.value})
+ )
+ if not values:
+ raise QueryObjectValidationError("Semantic IN/NOT IN filters cannot be
empty.")
+ if None not in values:
+ return {filter_}
+
+ non_null_values: frozenset[FilterValues] = values - {None}
+ if not non_null_values:
+ return {null_filter}
+ comparison: Filter = replace(filter_, value=non_null_values)
+ if negated:
+ return {comparison, null_filter}
Review Comment:
`OrFilter` and `OR_FILTERS` are introduced by this PR, so no provider
declares the flag yet. That includes the Snowflake provider this change is
paired with. Input `{"col": "category", "op": "IN", "val": ["Music", null]}`
should return the `Music` and NULL rows. Instead `_validate_filter_features`
raises "This data source cannot combine NULL with other selected values... ask
your administrator to upgrade the provider". UPDATING (lines 9-10) does
document this. But a provider that already renders `IN {'Music', None}`
correctly as a plain `Filter` regresses from correct rows to a 400, and there
is no upgraded provider to move to yet. Simply declaring the flag is not enough
either: a provider that iterates filters and reads `.operator`/`.type` hits an
`AttributeError` on `OrFilter`. Please land the provider-side `OrFilter`
rendering, plus the flag, together with this PR rather than after it.
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