Fix nested pydantic.v1 model detection in pydantic integration

RELEASE.md

@@ -0,0 +1,5 @@
+Release type: patch
+
+Fix `strawberry.experimental.pydantic` to correctly handle nested `pydantic.v1`
+models when running on Pydantic 2 (for example, `list[LegacyModel]` fields with
+`all_fields=True`), and add a regression test for this case.

strawberry/experimental/pydantic/_compat.py

@@ -19,6 +19,23 @@
 IS_PYDANTIC_V1: bool = not IS_PYDANTIC_V2
 
 
+def _get_base_model_types() -> tuple[type[Any], ...]:
+    model_types: list[type[Any]] = [BaseModel]
+
+    try:
+        from pydantic.v1 import BaseModel as BaseModelV1
+    except ImportError:
+        return tuple(model_types)
+
+    if BaseModelV1 not in model_types:
+        model_types.append(BaseModelV1)
+
+    return tuple(model_types)
+
+
+BASE_MODEL_TYPES = _get_base_model_types()
+
+
 @dataclass
 class CompatModelField:
     name: str
@@ -318,10 +335,21 @@ def new_type_supertype(type_: Any) -> Any:
         smart_deepcopy,
     )
 
+
+def is_model_class(type_: Any) -> bool:
+    return lenient_issubclass(type_, BASE_MODEL_TYPES)
+
+
+def is_model_instance(value: Any) -> bool:
+    return isinstance(value, BASE_MODEL_TYPES)
+
+
 __all__ = [
     "PydanticCompat",
     "get_args",
     "get_origin",
+    "is_model_class",
+    "is_model_instance",
     "is_new_type",
     "lenient_issubclass",
     "new_type_supertype",

strawberry/experimental/pydantic/error_type.py

@@ -9,12 +9,10 @@
     cast,
 )
 
-from pydantic import BaseModel
-
 from strawberry.experimental.pydantic._compat import (
     CompatModelField,
     PydanticCompat,
-    lenient_issubclass,
+    is_model_class,
 )
 from strawberry.experimental.pydantic.utils import (
     get_private_fields,
@@ -31,6 +29,8 @@
 if TYPE_CHECKING:
     from collections.abc import Callable, Sequence
 
+    from pydantic import BaseModel
+
     from strawberry.types.base import WithStrawberryObjectDefinition
 
 
@@ -49,13 +49,13 @@ def field_type_to_type(type_: type) -> Any | list[Any] | None:
 
         if is_list(child_type):
             strawberry_type = field_type_to_type(child_type)
-        elif lenient_issubclass(child_type, BaseModel):
+        elif is_model_class(child_type):
             strawberry_type = get_strawberry_type_from_model(child_type)
         else:
             strawberry_type = list[error_class]
 
         strawberry_type = Optional[strawberry_type]  # noqa: UP045
-    elif lenient_issubclass(type_, BaseModel):
+    elif is_model_class(type_):
         strawberry_type = get_strawberry_type_from_model(type_)
         return Optional[strawberry_type]  # noqa: UP045
 

strawberry/experimental/pydantic/fields.py

@@ -7,13 +7,11 @@
 )
 from typing import GenericAlias as TypingGenericAlias  # type: ignore
 
-from pydantic import BaseModel
-
 from strawberry.experimental.pydantic._compat import (
     PydanticCompat,
     get_args,
     get_origin,
-    lenient_issubclass,
+    is_model_class,
 )
 from strawberry.experimental.pydantic.exceptions import (
     UnregisteredTypeException,
@@ -22,7 +20,7 @@
 
 
 def replace_pydantic_types(type_: Any, is_input: bool) -> Any:
-    if lenient_issubclass(type_, BaseModel):
+    if is_model_class(type_):
         attr = "_strawberry_input_type" if is_input else "_strawberry_type"
         if hasattr(type_, attr):
             return getattr(type_, attr)

strawberry/experimental/pydantic/utils.py

@@ -8,11 +8,10 @@
     cast,
 )
 
-from pydantic import BaseModel
-
 from strawberry.experimental.pydantic._compat import (
     CompatModelField,
     PydanticCompat,
+    is_model_instance,
     smart_deepcopy,
 )
 from strawberry.experimental.pydantic.exceptions import (
@@ -30,6 +29,7 @@
 )
 
 if TYPE_CHECKING:
+    from pydantic import BaseModel
     from pydantic.typing import NoArgAnyCallable
 
 
@@ -102,7 +102,7 @@ def get_default_factory_for_field(
         # if the default value is a pydantic base model
         # we should return the serialized version of that default for
         # printing the value.
-        if isinstance(default, BaseModel):
+        if is_model_instance(default):
             return lambda: compat.model_dump(default)
         return lambda: smart_deepcopy(default)
 

tests/experimental/pydantic/schema/test_1_and_2.py

@@ -87,3 +87,48 @@ def user(self, id: strawberry.ID) -> User | LegacyUser:
 
     assert not result.errors
     assert result.data == {"user": {"__typename": "LegacyUser", "name": "legacy"}}
+
+
+@pytest.mark.skipif(
+    sys.version_info >= (3, 14),
+    reason="Pydantic v1 is not compatible with Python 3.14+",
+)
+@needs_pydantic_v2
+def test_can_use_nested_pydantic_v1_models():
+    from pydantic import v1 as pydantic_v1
+
+    class Book(pydantic_v1.BaseModel):
+        title: str
+
+    class Library(pydantic_v1.BaseModel):
+        books: list[Book]
+
+    @strawberry.experimental.pydantic.type(model=Book, all_fields=True)
+    class BookType:
+        pass
+
+    @strawberry.experimental.pydantic.type(model=Library, all_fields=True)
+    class LibraryType:
+        pass
+
+    @strawberry.type
+    class Query:
+        library: LibraryType
+
+    schema = strawberry.Schema(query=Query)
+
+    expected_schema = """
+    type BookType {
+      title: String!
+    }
+
+    type LibraryType {
+      books: [BookType!]!
+    }
+
+    type Query {
+      library: LibraryType!
+    }
+    """
+
+    assert str(schema) == textwrap.dedent(expected_schema).strip()