🐛 Make generics work with SQLModel as base class #1275

Original file line number	Diff line number	Diff line change
Expand Up		@@ -539,6 +539,12 @@ def __new__(
		config_kwargs = {
		key: kwargs[key] for key in kwargs.keys() & allowed_config_kwargs
		}
	# Also include pydantic's internal kwargs
	config_kwargs.update(
	(key, value)
	for key, value in kwargs.items()
	if key.startswith("__pydantic_")
	)
		new_cls = super().__new__(cls, name, bases, dict_used, **config_kwargs)
		new_cls.__annotations__ = {
		**relationship_annotations,
Expand Down

83 changes: 83 additions & 0 deletions tests/test_pydantic/test_generic.py

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Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,83 @@
	from typing import Generic, List, Optional, TypeVar

	import pydantic
	import pytest
	from sqlmodel import SQLModel

	from tests.conftest import needs_pydanticv2

	# Example adapted from
	# https://docs.pydantic.dev/2.10/concepts/models/#generic-models
	DataT = TypeVar("DataT")


	class DataModel(SQLModel):
	numbers: List[int]
	people: List[str]


	class Response(SQLModel, Generic[DataT]):
	data: Optional[DataT] = None


	@needs_pydanticv2
	@pytest.mark.parametrize(
	["data_type", "data_value"],
	[
	(int, 1),
	(str, "value"),
	(DataModel, DataModel(numbers=[1, 2, 3], people=[])),
	(DataModel, {"numbers": [1, 2, 3], "people": []}),
	],
	)
	def test_valid_generics(data_type, data_value):
	# Should be able to create a model without an error.
	response = Response[data_type](data=data_value)
	assert Response[data_type](**response.model_dump()) == response


	@needs_pydanticv2
	@pytest.mark.parametrize(
	["data_type", "data_value", "error_loc", "error_type"],
	[
	(
	str,
	1,
	("data",),
	"string_type",
	),
	(
	int,
	"some-string",
	("data",),
	"int_parsing",
	),
	(
	DataModel,
	"some-string",
	("data",),
	"model_attributes_type",
	),
	(
	DataModel,
	{"numbers": [1, 2, "unexpected string"], "people": []},
	("data", "numbers", 2),
	"int_parsing",
	),
	],
	)
	def test_invalid_generics(data_type, data_value, error_loc, error_type):
	with pytest.raises(pydantic.ValidationError) as raised:
	Response[data_type](data=data_value)
	[error_dict] = raised.value.errors()
	assert error_dict["loc"] == error_loc
	assert error_dict["type"] == error_type


	@needs_pydanticv2
	def test_generic_json_schema():
	schema = Response[DataModel].model_json_schema()
	# Should have referenced the schema in $defs
	assert schema["properties"]["data"]["anyOf"][0] == {"$ref": "#/$defs/DataModel"}
	# Schema in $defs should match DataModel's schema.
	assert schema["$defs"]["DataModel"] == DataModel.model_json_schema()

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