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fix(sdk): make Filter type permissive of implicit and dict (#14569)
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@ -384,6 +384,21 @@ def _filter_discriminator(v: Any) -> Optional[str]:
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return None
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def _parse_and_like_filter(value: Any) -> Any:
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# Do not parse if filter is already of type and/or/not or a custom condition
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# also do not parse container filter if direct_descendants_only is specified
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if (
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isinstance(value, dict)
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and not set(value.keys()).intersection(
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{"and", "or", "not", "field", "condition", "direct_descendants_only"}
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)
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and len(value) > 1
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):
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return {"and": [{k: v} for k, v in value.items()]}
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return value
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if TYPE_CHECKING or not PYDANTIC_SUPPORTS_CALLABLE_DISCRIMINATOR:
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# The `not TYPE_CHECKING` bit is required to make the linter happy,
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# since we currently only run mypy with pydantic v1.
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@ -445,6 +460,7 @@ else:
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],
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Discriminator(_filter_discriminator),
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],
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pydantic.BeforeValidator(_parse_and_like_filter),
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pydantic.BeforeValidator(_parse_json_from_string),
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]
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@ -334,6 +334,12 @@ def test_tagged_union_error_messages() -> None:
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):
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load_filters({"and": [{"unknown_field": 6}]})
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@pytest.mark.skipif(
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not PYDANTIC_SUPPORTS_CALLABLE_DISCRIMINATOR,
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reason="Tagged union w/ callable discriminator is not supported by the current pydantic version",
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)
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def test_filter_before_validators() -> None:
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# Test that we can load a filter from a string.
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# Sometimes we get filters encoded as JSON, and we want to handle those gracefully.
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filter_str = '{\n "and": [\n {"entity_type": ["dataset"]},\n {"entity_subtype": ["Table"]},\n {"platform": ["snowflake"]}\n ]\n}'
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@ -350,6 +356,31 @@ def test_tagged_union_error_messages() -> None:
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):
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load_filters("this is invalid json but should not raise a json error")
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# Test that we can load a filter from and-like dictionary.
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# Sometimes we get filters that are not wrapped in an "and" clause.
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filter_str = '{"entity_type": ["dataset"], "entity_subtype": ["Table"], "platform": ["snowflake"]}'
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assert load_filters(filter_str) == F.and_(
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F.entity_type("dataset"),
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F.entity_subtype("Table"),
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F.platform("snowflake"),
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)
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filter_str = '{"entity_type": ["dataset"], "container": ["urn:li:container:f784c48c306ba1c775ef917e2f8c1560"]}'
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assert load_filters(filter_str) == F.and_(
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F.entity_type("dataset"),
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F.container("urn:li:container:f784c48c306ba1c775ef917e2f8c1560"),
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)
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filter_str = '{"entity_type": ["dataset"], "container": ["urn:li:container:f784c48c306ba1c775ef917e2f8c1560"], "direct_descendants_only": true}'
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with pytest.raises(
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ValidationError,
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match=re.compile(
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r"1 validation error.*container\.entity_type.*Extra inputs are not permitted.*",
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re.DOTALL,
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),
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):
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load_filters(filter_str)
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def test_invalid_filter() -> None:
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with pytest.raises(InvalidUrnError):
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