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💚 Fix linting in CI #1340

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Merged
merged 11 commits into from
Apr 26, 2025
Merged

💚 Fix linting in CI #1340

merged 11 commits into from
Apr 26, 2025

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svlandeg
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@svlandeg svlandeg commented Apr 9, 2025

Recent PRs have been failing due to an issue with the linting step in the CI - I think caused by the recent release of Pydantic 2.11.

Overview of issues and proposed fixes:

  • Elaborate type warning for get_model_fields in _compat.py.
sqlmodel/_compat.py:106: error: Argument 1 to "__get__" of "deprecated_instance_property" has incompatible type "BaseModel | type[BaseModel]"; expected "BaseModel"  [arg-type]
sqlmodel/_compat.py:106: error: Argument 2 to "__get__" of "deprecated_instance_property" has incompatible type "type[BaseModel] | type[type[BaseModel]]"; expected "type[BaseModel]"  [arg-type]

I think it's fine to ignore this one?

  • model_fields in SQLModelMetaclass on the other hand, now can do without an ignore warning
  • SQLModel.model_validate() is supposed to overwrite BaseModel.model_validate() but an error gets raised because of the update input parameter, which is not present in BaseModel.model_validate(). The proposed solution here is to work via **kwargs, which I'm generally not a fan of, but the only other option I would see is adding yet another ignore, which feels wrong in this case.
  • SQLModel.model_dump() is supposed to overwrite BaseModel.model_dump() but an error gets raised because of context and alias having a wrong type, and fallback not being present. fallback was introduced in Pydantic v2.11. So instead of restricting Pydantic, I suggest to (again) work via **kwargs.

The linting test is failing for Python 3.8 in different ways than for all other Python versions, probably because Python 3.8 support was removed for Pydantic 2.11. Accordingly, I've updated the test.yml to skip the linting test for Python 3.8. This doesn't feel like a clean solution either, and I guess the other option is to (also) drop support for Python 3.8.

@svlandeg svlandeg self-assigned this Apr 9, 2025
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@tiangolo tiangolo left a comment

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Thank you @svlandeg! 🚀

I tweaked it a bit mainly to keep autocompletion and inline errors for final users. Although this reveals some areas that probably deserve some tweaking in the future. 🤔

I added some inline comments to share my mental process.

Thanks! 🚀

Comment on lines +109 to +113
if isinstance(model, type):
use_model = model
else:
use_model = model.__class__
return use_model.model_fields
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I was checking the error from Pydantic and I saw that they will deprecate accessing the model_fields from the instance in Pydantic v3, they should be accessed from the class (which makes sense).

I updated this logic here to handle that future use case. In a subsequent PR we can refactor the internal usage of this function to only pass the class and not the instance.

@@ -477,7 +477,7 @@ def Relationship(
class SQLModelMetaclass(ModelMetaclass, DeclarativeMeta):
__sqlmodel_relationships__: Dict[str, RelationshipInfo]
model_config: SQLModelConfig
model_fields: Dict[str, FieldInfo] # type: ignore[assignment]
model_fields: ClassVar[Dict[str, FieldInfo]]
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As the idea is that this should now be only in the class and not instances, I think it's good to type it right away. It won't affect at runtime if people are using it, but will start warning them in their linters, so they can start preparing for this change in Pydantic v3.

@@ -839,7 +839,7 @@ def __tablename__(cls) -> str:
return cls.__name__.lower()

@classmethod
def model_validate(
def model_validate( # type: ignore[override]
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I changed this to not use kwargs and instead ignore the type here, that way people will keep having autocompletion for the params, and kwargs won't swallow extra / invald params.

Seeing this, I realize it was probably not the best idea to include the extra update here. 🤔

Also, it's probably not needed for most use cases, maybe it would make sense to remove those docs, explain how to extend data to validate an object using just dicts, then deprecate using it, and finally at some point dropping the update...

But anyway, for now, it probably works to just # type: ignore and handle it on our side so that final users get the best developer experience / editor support.

context: Union[Dict[str, Any], None] = None,
by_alias: bool = False,
context: Union[Any, None] = None,
by_alias: Union[bool, None] = None,
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I like to keep the signature as close to the latest Pydantic, and then do the extra work internally to support the older versions, but this way people can get used to the new syntax and/or use it if they can already upgrade to the latest version.

@@ -896,7 +900,7 @@ def model_dump(
return super().dict(
include=include,
exclude=exclude,
by_alias=by_alias,
by_alias=by_alias or False,
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With this trick, we avoid the type when by_alias is None. 😅

serialize_as_any: bool = False,
) -> Dict[str, Any]:
if PYDANTIC_MINOR_VERSION < (2, 11):
by_alias = by_alias or False
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With this we can handle older Pydantic versions but keep the most recent signature.

@tiangolo tiangolo merged commit 4b5ad42 into fastapi:main Apr 26, 2025
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@svlandeg svlandeg deleted the fix/ci branch April 28, 2025 07:12
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3 participants