Serialize unsubstituted type vars as Any (#7606)

docs/concepts/models.md

@@ -783,43 +783,113 @@ print(concrete_model(a=1, b=1))
 
     If you need to perform isinstance checks against parametrized generics, you can do this by subclassing the parametrized generic class. This looks like `class MyIntModel(MyGenericModel[int]): ...` and `isinstance(my_model, MyIntModel)`.
 
-If a Pydantic model is used in a `TypeVar` constraint, [`SerializeAsAny`](serialization.md#serializing-with-duck-typing) can be used to
-serialize it using the concrete model instead of the model `TypeVar` is bound to.
+If a Pydantic model is used in a `TypeVar` bound and the generic type is never parametrized then Pydantic will use the bound for validation but treat the value as `Any` in terms of serialization:
 
 ```py
-from typing import Generic, TypeVar
+from typing import Generic, Optional, TypeVar
 
-from pydantic import BaseModel, SerializeAsAny
+from pydantic import BaseModel
 
 
-class Model(BaseModel):
-    a: int = 42
+class ErrorDetails(BaseModel):
+    foo: str
 
 
-class DataModel(Model):
-    b: int = 2
-    c: int = 3
+ErrorDataT = TypeVar('ErrorDataT', bound=ErrorDetails)
+
+
+class Error(BaseModel, Generic[ErrorDataT]):
+    message: str
+    details: Optional[ErrorDataT]
 
 
-BoundT = TypeVar('BoundT', bound=Model)
+class MyErrorDetails(ErrorDetails):
+    bar: str
 
 
-class GenericModel(BaseModel, Generic[BoundT]):
-    data: BoundT
+# serialized as Any
+error = Error(
+    message='We just had an error',
+    details=MyErrorDetails(foo='var', bar='var2'),
+)
+assert error.model_dump() == {
+    'message': 'We just had an error',
+    'details': {
+        'foo': 'var',
+        'bar': 'var2',
+    },
+}
 
+# serialized using the concrete parametrization
+# note that `'bar': 'var2'` is missing
+error = Error[ErrorDetails](
+    message='We just had an error',
+    details=ErrorDetails(foo='var'),
+)
+assert error.model_dump() == {
+    'message': 'We just had an error',
+    'details': {
+        'foo': 'var',
+    },
+}
+```
 
-class SerializeAsAnyModel(BaseModel, Generic[BoundT]):
-    data: SerializeAsAny[BoundT]
+If you use a `default=...` (available in Python >= 3.13 or via `typing-extensions`) or constraints (`TypeVar('T', str, int)`; note that you rarely want to use this form of a `TypeVar`) then the default value or constraints will be used for both validation and serialization if the type variable is not parametrized. You can override this behavior using `pydantic.SerializeAsAny`:
 
+```py
+from typing import Generic, Optional
+
+from typing_extensions import TypeVar
 
-data_model = DataModel()
+from pydantic import BaseModel, SerializeAsAny
 
-print(GenericModel(data=data_model).model_dump())
-#> {'data': {'a': 42}}
 
+class ErrorDetails(BaseModel):
+    foo: str
 
-print(SerializeAsAnyModel(data=data_model).model_dump())
-#> {'data': {'a': 42, 'b': 2, 'c': 3}}
+
+ErrorDataT = TypeVar('ErrorDataT', default=ErrorDetails)
+
+
+class Error(BaseModel, Generic[ErrorDataT]):
+    message: str
+    details: Optional[ErrorDataT]
+
+
+class MyErrorDetails(ErrorDetails):
+    bar: str
+
+
+# serialized using the default's serializer
+error = Error(
+    message='We just had an error',
+    details=MyErrorDetails(foo='var', bar='var2'),
+)
+assert error.model_dump() == {
+    'message': 'We just had an error',
+    'details': {
+        'foo': 'var',
+    },
+}
+
+
+class SerializeAsAnyError(BaseModel, Generic[ErrorDataT]):
+    message: str
+    details: Optional[SerializeAsAny[ErrorDataT]]
+
+
+# serialized as Any
+error = SerializeAsAnyError(
+    message='We just had an error',
+    details=MyErrorDetails(foo='var', bar='baz'),
+)
+assert error.model_dump() == {
+    'message': 'We just had an error',
+    'details': {
+        'foo': 'var',
+        'bar': 'baz',
+    },
+}
 ```
 
 ## Dynamic model creation

pydantic/_internal/_generate_schema.py

@@ -1449,10 +1449,26 @@ def _callable_schema(self, function: Callable[..., Any]) -> core_schema.CallSche
     def _unsubstituted_typevar_schema(self, typevar: typing.TypeVar) -> core_schema.CoreSchema:
         assert isinstance(typevar, typing.TypeVar)
 
-        if typevar.__bound__:
-            return self.generate_schema(typevar.__bound__)
-        elif typevar.__constraints__:
-            return self._union_schema(typing.Union[typevar.__constraints__])  # type: ignore
+        bound = typevar.__bound__
+        constraints = typevar.__constraints__
+        not_set = object()
+        default = getattr(typevar, '__default__', not_set)
+
+        if (bound is not None) + (len(constraints) != 0) + (default is not not_set) > 1:
+            raise NotImplementedError(
+                'Pydantic does not support mixing more than one of TypeVar bounds, constraints and defaults'
+            )
+
+        if default is not not_set:
+            return self.generate_schema(default)
+        elif constraints:
+            return self._union_schema(typing.Union[constraints])  # type: ignore
+        elif bound:
+            schema = self.generate_schema(bound)
+            schema['serialization'] = core_schema.wrap_serializer_function_ser_schema(
+                lambda x, h: h(x), schema=core_schema.any_schema()
+            )
+            return schema
         else:
             return core_schema.any_schema()
 

tests/test_generics.py

@@ -32,7 +32,18 @@
 import pytest
 from dirty_equals import HasRepr, IsStr
 from pydantic_core import CoreSchema, core_schema
-from typing_extensions import Annotated, Literal, OrderedDict, ParamSpec, TypeVarTuple, Unpack, get_args
+from typing_extensions import (
+    Annotated,
+    Literal,
+    OrderedDict,
+    ParamSpec,
+    TypeVarTuple,
+    Unpack,
+    get_args,
+)
+from typing_extensions import (
+    TypeVar as TypingExtensionsTypeVar,
+)
 
 from pydantic import (
     BaseModel,
@@ -2622,3 +2633,140 @@ class Model(Generic[T], BaseModel):
     m1 = Model[int](x=1)
     m2 = Model[int](x=1)
     assert len({m1, m2}) == 1
+
+
+def test_serialize_unsubstituted_typevars_bound() -> None:
+    class ErrorDetails(BaseModel):
+        foo: str
+
+    ErrorDataT = TypeVar('ErrorDataT', bound=ErrorDetails)
+
+    class Error(BaseModel, Generic[ErrorDataT]):
+        message: str
+        details: ErrorDataT
+
+    class MyErrorDetails(ErrorDetails):
+        bar: str
+
+    sample_error = Error(
+        message='We just had an error',
+        details=MyErrorDetails(foo='var', bar='baz'),
+    )
+    assert sample_error.details.model_dump() == {
+        'foo': 'var',
+        'bar': 'baz',
+    }
+    assert sample_error.model_dump() == {
+        'message': 'We just had an error',
+        'details': {
+            'foo': 'var',
+            'bar': 'baz',
+        },
+    }
+
+    sample_error = Error[ErrorDetails](
+        message='We just had an error',
+        details=MyErrorDetails(foo='var', bar='baz'),
+    )
+    assert sample_error.details.model_dump() == {
+        'foo': 'var',
+        'bar': 'baz',
+    }
+    assert sample_error.model_dump() == {
+        'message': 'We just had an error',
+        'details': {
+            'foo': 'var',
+        },
+    }
+
+    sample_error = Error[MyErrorDetails](
+        message='We just had an error',
+        details=MyErrorDetails(foo='var', bar='baz'),
+    )
+    assert sample_error.details.model_dump() == {
+        'foo': 'var',
+        'bar': 'baz',
+    }
+    assert sample_error.model_dump() == {
+        'message': 'We just had an error',
+        'details': {
+            'foo': 'var',
+            'bar': 'baz',
+        },
+    }
+
+
+@pytest.mark.parametrize(
+    'type_var',
+    [
+        TypingExtensionsTypeVar('ErrorDataT', default=BaseModel),
+        TypeVar('ErrorDataT', BaseModel, str),
+    ],
+    ids=['default', 'constraint'],
+)
+def test_serialize_unsubstituted_typevars_bound(
+    type_var: Type[BaseModel],
+) -> None:
+    class ErrorDetails(BaseModel):
+        foo: str
+
+    class Error(BaseModel, Generic[type_var]):  # type: ignore
+        message: str
+        details: type_var
+
+    class MyErrorDetails(ErrorDetails):
+        bar: str
+
+    sample_error = Error(
+        message='We just had an error',
+        details=MyErrorDetails(foo='var', bar='baz'),
+    )
+    assert sample_error.details.model_dump() == {
+        'foo': 'var',
+        'bar': 'baz',
+    }
+    assert sample_error.model_dump() == {
+        'message': 'We just had an error',
+        'details': {},
+    }
+
+    sample_error = Error[ErrorDetails](
+        message='We just had an error',
+        details=MyErrorDetails(foo='var', bar='baz'),
+    )
+    assert sample_error.details.model_dump() == {
+        'foo': 'var',
+        'bar': 'baz',
+    }
+    assert sample_error.model_dump() == {
+        'message': 'We just had an error',
+        'details': {
+            'foo': 'var',
+        },
+    }
+
+    sample_error = Error[MyErrorDetails](
+        message='We just had an error',
+        details=MyErrorDetails(foo='var', bar='baz'),
+    )
+    assert sample_error.details.model_dump() == {
+        'foo': 'var',
+        'bar': 'baz',
+    }
+    assert sample_error.model_dump() == {
+        'message': 'We just had an error',
+        'details': {
+            'foo': 'var',
+            'bar': 'baz',
+        },
+    }
+
+
+def test_mix_default_and_constraints() -> None:
+    T = TypingExtensionsTypeVar('T', str, int, default=str)
+
+    msg = 'Pydantic does not support mixing more than one of TypeVar bounds, constraints and defaults'
+    with pytest.raises(NotImplementedError, match=msg):
+
+        class _(BaseModel, Generic[T]):
+            x: T