Fix various issues with dataclasses and use_attribute_docstrings#11246
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Fix various issues with dataclasses and use_attribute_docstrings#11246
use_attribute_docstrings#11246Conversation
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CodSpeed Performance ReportMerging #11246 will improve performances by 10.84%Comparing Summary
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sydney-runkle
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Nice work overall, left a few comments / questions. Thanks!
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| def _update_fields_from_docstrings(cls: type[Any], fields: dict[str, FieldInfo], use_inspect: bool = False) -> None: | ||
| fields_docs = extract_docstrings_from_cls(cls, use_inspect=use_inspect) | ||
| for ann_name, field_info in fields.items(): | ||
| if field_info.description is None and ann_name in fields_docs: | ||
| field_info.description = fields_docs[ann_name] |
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Re letting callers decide if this is necessary - I assume this is for general cleanliness and to avoid the overhead of a function call if not necessary?
…in the process of being built Do not rely on `__pydantic_validator__`, an attribute which is set only when the class is fully built. Because we check for this condition during schema building, we end up considering the class as a stdlib dataclass. As a consequence, the deepcopy logic of `FieldInfo` instances was tweaked, as in some tests, the deep copy would fail. Instead, make a shallow copy of every `FieldInfo` instance, this is enough (the same thing is done in `collect_model_fields` for Pydantic models, we make a shallow copy of the parent fields).
Let callers be responsible for checking if using docstrings is necessary.
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Change Summary
Fixes #11243.
Edit post 2.11 release: fixes #11133.
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