♻️ Refactor internals, simplify Pydantic v2/v1 utils, `create_model_field`, better types for `lenient_issubclass` (#14860)

fastapi/_compat/__init__.py

@@ -1,7 +1,6 @@
 from .shared import PYDANTIC_VERSION_MINOR_TUPLE as PYDANTIC_VERSION_MINOR_TUPLE
 from .shared import annotation_is_pydantic_v1 as annotation_is_pydantic_v1
 from .shared import field_annotation_is_scalar as field_annotation_is_scalar
-from .shared import is_pydantic_v1_model_class as is_pydantic_v1_model_class
 from .shared import is_pydantic_v1_model_instance as is_pydantic_v1_model_instance
 from .shared import (
     is_uploadfile_or_nonable_uploadfile_annotation as is_uploadfile_or_nonable_uploadfile_annotation,
@@ -12,21 +11,19 @@ from .shared import (
 from .shared import lenient_issubclass as lenient_issubclass
 from .shared import sequence_types as sequence_types
 from .shared import value_is_sequence as value_is_sequence
-from .v2 import BaseConfig as BaseConfig
 from .v2 import ModelField as ModelField
 from .v2 import PydanticSchemaGenerationError as PydanticSchemaGenerationError
 from .v2 import RequiredParam as RequiredParam
 from .v2 import Undefined as Undefined
-from .v2 import UndefinedType as UndefinedType
 from .v2 import Url as Url
-from .v2 import Validator as Validator
-from .v2 import _regenerate_error_with_loc as _regenerate_error_with_loc
 from .v2 import copy_field_info as copy_field_info
 from .v2 import create_body_model as create_body_model
 from .v2 import evaluate_forwardref as evaluate_forwardref
 from .v2 import get_cached_model_fields as get_cached_model_fields
 from .v2 import get_definitions as get_definitions
+from .v2 import get_flat_models_from_fields as get_flat_models_from_fields
 from .v2 import get_missing_field_error as get_missing_field_error
+from .v2 import get_model_name_map as get_model_name_map
 from .v2 import get_schema_from_model_field as get_schema_from_model_field
 from .v2 import is_bytes_field as is_bytes_field
 from .v2 import is_bytes_sequence_field as is_bytes_sequence_field

fastapi/_compat/shared.py

@@ -8,6 +8,7 @@ from dataclasses import is_dataclass
 from typing import (
     Annotated,
     Any,
+    TypeVar,
     Union,
 )
 
@@ -15,7 +16,9 @@ from fastapi.types import UnionType
 from pydantic import BaseModel
 from pydantic.version import VERSION as PYDANTIC_VERSION
 from starlette.datastructures import UploadFile
-from typing_extensions import get_args, get_origin
+from typing_extensions import TypeGuard, get_args, get_origin
+
+_T = TypeVar("_T")
 
 # Copy from Pydantic: pydantic/_internal/_typing_extra.py
 if sys.version_info < (3, 10):
@@ -39,15 +42,13 @@ sequence_annotation_to_type = {
     deque: deque,
 }
 
-sequence_types = tuple(sequence_annotation_to_type.keys())
-
-Url: type[Any]
+sequence_types: tuple[type[Any], ...] = tuple(sequence_annotation_to_type.keys())
 
 
-# Copy of Pydantic: pydantic/_internal/_utils.py
+# Copy of Pydantic: pydantic/_internal/_utils.py with added TypeGuard
 def lenient_issubclass(
-    cls: Any, class_or_tuple: Union[type[Any], tuple[type[Any], ...], None]
-) -> bool:
+    cls: Any, class_or_tuple: Union[type[_T], tuple[type[_T], ...], None]
+) -> TypeGuard[type[_T]]:
     try:
         return isinstance(cls, type) and issubclass(cls, class_or_tuple)  # type: ignore[arg-type]
     except TypeError:  # pragma: no cover
@@ -177,16 +178,26 @@ def is_uploadfile_sequence_annotation(annotation: Any) -> bool:
 
 
 def is_pydantic_v1_model_instance(obj: Any) -> bool:
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore", UserWarning)
-        from pydantic import v1
+    # TODO: remove this function once the required version of Pydantic fully
+    # removes pydantic.v1
+    try:
+        with warnings.catch_warnings():
+            warnings.simplefilter("ignore", UserWarning)
+            from pydantic import v1
+    except ImportError:  # pragma: no cover
+        return False
     return isinstance(obj, v1.BaseModel)
 
 
 def is_pydantic_v1_model_class(cls: Any) -> bool:
-    with warnings.catch_warnings():
-        warnings.simplefilter("ignore", UserWarning)
-        from pydantic import v1
+    # TODO: remove this function once the required version of Pydantic fully
+    # removes pydantic.v1
+    try:
+        with warnings.catch_warnings():
+            warnings.simplefilter("ignore", UserWarning)
+            from pydantic import v1
+    except ImportError:  # pragma: no cover
+        return False
     return lenient_issubclass(cls, v1.BaseModel)
 
 

fastapi/_compat/v2.py

@@ -12,7 +12,7 @@ from typing import (
     cast,
 )
 
-from fastapi._compat import shared
+from fastapi._compat import lenient_issubclass, shared
 from fastapi.openapi.constants import REF_TEMPLATE
 from fastapi.types import IncEx, ModelNameMap, UnionType
 from pydantic import BaseModel, ConfigDict, Field, TypeAdapter, create_model
@@ -23,29 +23,20 @@ from pydantic._internal._schema_generation_shared import (  # type: ignore[attr-
     GetJsonSchemaHandler as GetJsonSchemaHandler,
 )
 from pydantic._internal._typing_extra import eval_type_lenient
-from pydantic._internal._utils import lenient_issubclass as lenient_issubclass
 from pydantic.fields import FieldInfo as FieldInfo
 from pydantic.json_schema import GenerateJsonSchema as GenerateJsonSchema
 from pydantic.json_schema import JsonSchemaValue as JsonSchemaValue
 from pydantic_core import CoreSchema as CoreSchema
-from pydantic_core import PydanticUndefined, PydanticUndefinedType
+from pydantic_core import PydanticUndefined
 from pydantic_core import Url as Url
+from pydantic_core.core_schema import (
+    with_info_plain_validator_function as with_info_plain_validator_function,
+)
 from typing_extensions import Literal, get_args, get_origin
 
-try:
-    from pydantic_core.core_schema import (
-        with_info_plain_validator_function as with_info_plain_validator_function,
-    )
-except ImportError:  # pragma: no cover
-    from pydantic_core.core_schema import (
-        general_plain_validator_function as with_info_plain_validator_function,  # noqa: F401
-    )
-
 RequiredParam = PydanticUndefined
 Undefined = PydanticUndefined
-UndefinedType = PydanticUndefinedType
 evaluate_forwardref = eval_type_lenient
-Validator = Any
 
 # TODO: remove when dropping support for Pydantic < v2.12.3
 _Attrs = {
@@ -87,14 +78,6 @@ def asdict(field_info: FieldInfo) -> dict[str, Any]:
     }
 
 
-class BaseConfig:
-    pass
-
-
-class ErrorWrapper(Exception):
-    pass
-
-
 @dataclass
 class ModelField:
     field_info: FieldInfo
@@ -143,8 +126,8 @@ class ModelField:
                 warnings.simplefilter(
                     "ignore", category=UnsupportedFieldAttributeWarning
                 )
-            # TODO: remove after dropping support for Python 3.8 and
-            # setting the min Pydantic to v2.12.3 that adds asdict()
+            # TODO: remove after setting the min Pydantic to v2.12.3
+            # that adds asdict(), and use self.field_info.asdict() instead
             field_dict = asdict(self.field_info)
             annotated_args = (
                 field_dict["annotation"],
@@ -432,10 +415,11 @@ def get_flat_models_from_annotation(
     origin = get_origin(annotation)
     if origin is not None:
         for arg in get_args(annotation):
-            if lenient_issubclass(arg, (BaseModel, Enum)) and arg not in known_models:
-                known_models.add(arg)
-                if lenient_issubclass(arg, BaseModel):
-                    get_flat_models_from_model(arg, known_models=known_models)
+            if lenient_issubclass(arg, (BaseModel, Enum)):
+                if arg not in known_models:
+                    known_models.add(arg)  # type: ignore[arg-type]
+                    if lenient_issubclass(arg, BaseModel):
+                        get_flat_models_from_model(arg, known_models=known_models)
             else:
                 get_flat_models_from_annotation(arg, known_models=known_models)
     return known_models

fastapi/dependencies/utils.py

@@ -512,7 +512,6 @@ def analyze_param(
             type_=use_annotation_from_field_info,
             default=field_info.default,
             alias=alias,
-            required=field_info.default in (RequiredParam, Undefined),
             field_info=field_info,
         )
         if is_path_param:
@@ -523,11 +522,7 @@ def analyze_param(
             assert (
                 is_scalar_field(field)
                 or is_scalar_sequence_field(field)
-                or (
-                    lenient_issubclass(field.type_, BaseModel)
-                    # For Pydantic v1
-                    and getattr(field, "shape", 1) == 1
-                )
+                or lenient_issubclass(field.type_, BaseModel)
             ), f"Query parameter {param_name!r} must be one of the supported types"
 
     return ParamDetails(type_annotation=type_annotation, depends=depends, field=field)
@@ -1021,7 +1016,6 @@ def get_body_field(
     final_field = create_model_field(
         name="body",
         type_=BodyModel,
-        required=required,
         alias="body",
         field_info=BodyFieldInfo(**BodyFieldInfo_kwargs),
     )

fastapi/openapi/models.py

@@ -143,10 +143,7 @@ class Schema(BaseModelWithConfig):
     else_: Optional["SchemaOrBool"] = Field(default=None, alias="else")
     dependentSchemas: Optional[dict[str, "SchemaOrBool"]] = None
     prefixItems: Optional[list["SchemaOrBool"]] = None
-    # TODO: uncomment and remove below when deprecating Pydantic v1
-    # It generates a list of schemas for tuples, before prefixItems was available
-    # items: Optional["SchemaOrBool"] = None
-    items: Optional[Union["SchemaOrBool", list["SchemaOrBool"]]] = None
+    items: Optional["SchemaOrBool"] = None
     contains: Optional["SchemaOrBool"] = None
     properties: Optional[dict[str, "SchemaOrBool"]] = None
     patternProperties: Optional[dict[str, "SchemaOrBool"]] = None

fastapi/openapi/utils.py

@@ -10,12 +10,10 @@ from fastapi._compat import (
     ModelField,
     Undefined,
     get_definitions,
-    get_schema_from_model_field,
-    lenient_issubclass,
-)
-from fastapi._compat.v2 import (
     get_flat_models_from_fields,
     get_model_name_map,
+    get_schema_from_model_field,
+    lenient_issubclass,
 )
 from fastapi.datastructures import DefaultPlaceholder
 from fastapi.dependencies.models import Dependant

fastapi/routing.py

@@ -34,7 +34,6 @@ from fastapi import params
 from fastapi._compat import (
     ModelField,
     Undefined,
-    annotation_is_pydantic_v1,
     lenient_issubclass,
 )
 from fastapi.datastructures import Default, DefaultPlaceholder
@@ -52,7 +51,6 @@ from fastapi.encoders import jsonable_encoder
 from fastapi.exceptions import (
     EndpointContext,
     FastAPIError,
-    PydanticV1NotSupportedError,
     RequestValidationError,
     ResponseValidationError,
     WebSocketRequestValidationError,
@@ -638,11 +636,6 @@ class APIRoute(routing.Route):
                 f"Status code {status_code} must not have a response body"
             )
             response_name = "Response_" + self.unique_id
-            if annotation_is_pydantic_v1(self.response_model):
-                raise PydanticV1NotSupportedError(
-                    "pydantic.v1 models are no longer supported by FastAPI."
-                    f" Please update the response model {self.response_model!r}."
-                )
             self.response_field = create_model_field(
                 name=response_name,
                 type_=self.response_model,
@@ -664,11 +657,6 @@ class APIRoute(routing.Route):
                     f"Status code {additional_status_code} must not have a response body"
                 )
                 response_name = f"Response_{additional_status_code}_{self.unique_id}"
-                if annotation_is_pydantic_v1(model):
-                    raise PydanticV1NotSupportedError(
-                        "pydantic.v1 models are no longer supported by FastAPI."
-                        f" In responses={{}}, please update {model}."
-                    )
                 response_field = create_model_field(
                     name=response_name, type_=model, mode="serialization"
                 )

fastapi/utils.py

@@ -9,12 +9,9 @@ from typing import (
 
 import fastapi
 from fastapi._compat import (
-    BaseConfig,
     ModelField,
     PydanticSchemaGenerationError,
     Undefined,
-    UndefinedType,
-    Validator,
     annotation_is_pydantic_v1,
 )
 from fastapi.datastructures import DefaultPlaceholder, DefaultType
@@ -63,26 +60,19 @@ _invalid_args_message = (
 def create_model_field(
     name: str,
     type_: Any,
-    class_validators: Optional[dict[str, Validator]] = None,
     default: Optional[Any] = Undefined,
-    required: Union[bool, UndefinedType] = Undefined,
-    model_config: Union[type[BaseConfig], None] = None,
     field_info: Optional[FieldInfo] = None,
     alias: Optional[str] = None,
     mode: Literal["validation", "serialization"] = "validation",
-    version: Literal["1", "auto"] = "auto",
 ) -> ModelField:
     if annotation_is_pydantic_v1(type_):
         raise PydanticV1NotSupportedError(
             "pydantic.v1 models are no longer supported by FastAPI."
             f" Please update the response model {type_!r}."
         )
-    class_validators = class_validators or {}
-
     field_info = field_info or FieldInfo(annotation=type_, default=default, alias=alias)
-    kwargs = {"mode": mode, "name": name, "field_info": field_info}
     try:
-        return v2.ModelField(**kwargs)  # type: ignore[arg-type]
+        return v2.ModelField(mode=mode, name=name, field_info=field_info)
     except PydanticSchemaGenerationError:
         raise fastapi.exceptions.FastAPIError(
             _invalid_args_message.format(type_=type_)