Merge branch 'master' into deferred-init

Signed-off-by: Jan Vollmer <[email protected]>

docs/en/docs/release-notes.md

@@ -9,6 +9,13 @@ hide:
 
 ### Refactors
 
+* ♻️ Refactor and simplify Pydantic v2 (and v1) compatibility internal utils. PR [#14862](https://github.com/fastapi/fastapi/pull/14862) by [@tiangolo](https://github.com/tiangolo).
+
+## 0.128.4
+
+### Refactors
+
+* ♻️ Refactor internals, simplify Pydantic v2/v1 utils, `create_model_field`, better types for `lenient_issubclass`. PR [#14860](https://github.com/fastapi/fastapi/pull/14860) by [@tiangolo](https://github.com/tiangolo).
 * ♻️ Simplify internals, remove Pydantic v1 only logic, no longer needed. PR [#14857](https://github.com/fastapi/fastapi/pull/14857) by [@tiangolo](https://github.com/tiangolo).
 * ♻️ Refactor internals, cleanup unneeded Pydantic v1 specific logic. PR [#14856](https://github.com/fastapi/fastapi/pull/14856) by [@tiangolo](https://github.com/tiangolo).
 

fastapi/__init__.py

@@ -1,6 +1,6 @@
 """FastAPI framework, high performance, easy to learn, fast to code, ready for production"""
 
-__version__ = "0.128.3"
+__version__ = "0.128.4"
 
 from starlette import status as status
 

fastapi/_compat/__init__.py

@@ -1,7 +1,14 @@
 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 (
+    field_annotation_is_scalar_sequence as field_annotation_is_scalar_sequence,
+)
+from .shared import field_annotation_is_sequence as field_annotation_is_sequence
+from .shared import (
+    is_bytes_or_nonable_bytes_annotation as is_bytes_or_nonable_bytes_annotation,
+)
+from .shared import is_bytes_sequence_annotation as is_bytes_sequence_annotation
 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,
@@ -12,27 +19,21 @@ 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
 from .v2 import is_scalar_field as is_scalar_field
-from .v2 import is_scalar_sequence_field as is_scalar_sequence_field
-from .v2 import is_sequence_field as is_sequence_field
 from .v2 import serialize_sequence_value as serialize_sequence_value
 from .v2 import (
     with_info_plain_validator_function as with_info_plain_validator_function,

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
@@ -119,18 +102,10 @@ class ModelField:
         sa = self.field_info.serialization_alias
         return sa or None
 
-    @property
-    def required(self) -> bool:
-        return self.field_info.is_required()
-
     @property
     def default(self) -> Any:
         return self.get_default()
 
-    @property
-    def type_(self) -> Any:
-        return self.field_info.annotation
-
     def __post_init__(self) -> None:
         with warnings.catch_warnings():
             # Pydantic >= 2.12.0 warns about field specific metadata that is unused
@@ -143,8 +118,8 @@ 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"],
@@ -284,9 +259,9 @@ def get_definitions(
         for model in flat_serialization_models
     ]
     flat_model_fields = flat_validation_model_fields + flat_serialization_model_fields
-    input_types = {f.type_ for f in fields}
+    input_types = {f.field_info.annotation for f in fields}
     unique_flat_model_fields = {
-        f for f in flat_model_fields if f.type_ not in input_types
+        f for f in flat_model_fields if f.field_info.annotation not in input_types
     }
     inputs = [
         (
@@ -321,22 +296,6 @@ def is_scalar_field(field: ModelField) -> bool:
     ) and not isinstance(field.field_info, params.Body)
 
 
-def is_sequence_field(field: ModelField) -> bool:
-    return shared.field_annotation_is_sequence(field.field_info.annotation)
-
-
-def is_scalar_sequence_field(field: ModelField) -> bool:
-    return shared.field_annotation_is_scalar_sequence(field.field_info.annotation)
-
-
-def is_bytes_field(field: ModelField) -> bool:
-    return shared.is_bytes_or_nonable_bytes_annotation(field.type_)
-
-
-def is_bytes_sequence_field(field: ModelField) -> bool:
-    return shared.is_bytes_sequence_annotation(field.type_)
-
-
 def copy_field_info(*, field_info: FieldInfo, annotation: Any) -> FieldInfo:
     cls = type(field_info)
     merged_field_info = cls.from_annotation(annotation)
@@ -432,10 +391,11 @@ 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
@@ -444,7 +404,7 @@ def get_flat_models_from_annotation(
 def get_flat_models_from_field(
     field: ModelField, known_models: TypeModelSet
 ) -> TypeModelSet:
-    field_type = field.type_
+    field_type = field.field_info.annotation
     if lenient_issubclass(field_type, BaseModel):
         if field_type in known_models:
             return known_models

fastapi/dependencies/utils.py

@@ -25,13 +25,13 @@ from fastapi._compat import (
     create_body_model,
     evaluate_forwardref,
     field_annotation_is_scalar,
+    field_annotation_is_scalar_sequence,
+    field_annotation_is_sequence,
     get_cached_model_fields,
     get_missing_field_error,
-    is_bytes_field,
-    is_bytes_sequence_field,
+    is_bytes_or_nonable_bytes_annotation,
+    is_bytes_sequence_annotation,
     is_scalar_field,
-    is_scalar_sequence_field,
-    is_sequence_field,
     is_uploadfile_or_nonable_uploadfile_annotation,
     is_uploadfile_sequence_annotation,
     lenient_issubclass,
@@ -182,8 +182,10 @@ def _get_flat_fields_from_params(fields: list[ModelField]) -> list[ModelField]:
     if not fields:
         return fields
     first_field = fields[0]
-    if len(fields) == 1 and lenient_issubclass(first_field.type_, BaseModel):
-        fields_to_extract = get_cached_model_fields(first_field.type_)
+    if len(fields) == 1 and lenient_issubclass(
+        first_field.field_info.annotation, BaseModel
+    ):
+        fields_to_extract = get_cached_model_fields(first_field.field_info.annotation)
         return fields_to_extract
     return fields
 
@@ -512,7 +514,6 @@ 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:
@@ -522,12 +523,8 @@ def analyze_param(
         elif isinstance(field_info, params.Query):
             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 field_annotation_is_scalar_sequence(field.field_info.annotation)
+                or lenient_issubclass(field.field_info.annotation, BaseModel)
             ), f"Query parameter {param_name!r} must be one of the supported types"
 
     return ParamDetails(type_annotation=type_annotation, depends=depends, field=field)
@@ -713,7 +710,7 @@ def _validate_value_with_model_field(
     *, field: ModelField, value: Any, values: dict[str, Any], loc: tuple[str, ...]
 ) -> tuple[Any, list[Any]]:
     if value is None:
-        if field.required:
+        if field.field_info.is_required():
             return None, [get_missing_field_error(loc=loc)]
         else:
             return deepcopy(field.default), []
@@ -730,7 +727,7 @@ def _get_multidict_value(
     alias = alias or get_validation_alias(field)
     if (
         (not _is_json_field(field))
-        and is_sequence_field(field)
+        and field_annotation_is_sequence(field.field_info.annotation)
         and isinstance(values, (ImmutableMultiDict, Headers))
     ):
         value = values.getlist(alias)
@@ -743,9 +740,12 @@ def _get_multidict_value(
             and isinstance(value, str)  # For type checks
             and value == ""
         )
-        or (is_sequence_field(field) and len(value) == 0)
+        or (
+            field_annotation_is_sequence(field.field_info.annotation)
+            and len(value) == 0
+        )
     ):
-        if field.required:
+        if field.field_info.is_required():
             return
         else:
             return deepcopy(field.default)
@@ -766,8 +766,10 @@ def request_params_to_args(
     fields_to_extract = fields
     single_not_embedded_field = False
     default_convert_underscores = True
-    if len(fields) == 1 and lenient_issubclass(first_field.type_, BaseModel):
-        fields_to_extract = get_cached_model_fields(first_field.type_)
+    if len(fields) == 1 and lenient_issubclass(
+        first_field.field_info.annotation, BaseModel
+    ):
+        fields_to_extract = get_cached_model_fields(first_field.field_info.annotation)
         single_not_embedded_field = True
         # If headers are in a Pydantic model, the way to disable convert_underscores
         # would be with Header(convert_underscores=False) at the Pydantic model level
@@ -871,8 +873,8 @@ def _should_embed_body_fields(fields: list[ModelField]) -> bool:
     # otherwise it has to be embedded, so that the key value pair can be extracted
     if (
         isinstance(first_field.field_info, params.Form)
-        and not lenient_issubclass(first_field.type_, BaseModel)
-        and not is_union_of_base_models(first_field.type_)
+        and not lenient_issubclass(first_field.field_info.annotation, BaseModel)
+        and not is_union_of_base_models(first_field.field_info.annotation)
     ):
         return True
     return False
@@ -889,12 +891,12 @@ async def _extract_form_body(
         field_info = field.field_info
         if (
             isinstance(field_info, params.File)
-            and is_bytes_field(field)
+            and is_bytes_or_nonable_bytes_annotation(field.field_info.annotation)
             and isinstance(value, UploadFile)
         ):
             value = await value.read()
         elif (
-            is_bytes_sequence_field(field)
+            is_bytes_sequence_annotation(field.field_info.annotation)
             and isinstance(field_info, params.File)
             and value_is_sequence(value)
         ):
@@ -941,10 +943,10 @@ async def request_body_to_args(
 
     if (
         single_not_embedded_field
-        and lenient_issubclass(first_field.type_, BaseModel)
+        and lenient_issubclass(first_field.field_info.annotation, BaseModel)
         and isinstance(received_body, FormData)
     ):
-        fields_to_extract = get_cached_model_fields(first_field.type_)
+        fields_to_extract = get_cached_model_fields(first_field.field_info.annotation)
 
     if isinstance(received_body, FormData):
         body_to_process = await _extract_form_body(fields_to_extract, received_body)
@@ -997,7 +999,9 @@ def get_body_field(
     BodyModel = create_body_model(
         fields=flat_dependant.body_params, model_name=model_name
     )
-    required = any(True for f in flat_dependant.body_params if f.required)
+    required = any(
+        True for f in flat_dependant.body_params if f.field_info.is_required()
+    )
     BodyFieldInfo_kwargs: dict[str, Any] = {
         "annotation": BodyModel,
         "alias": "body",
@@ -1021,7 +1025,6 @@ 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
@@ -131,7 +129,7 @@ def _get_openapi_operation_parameters(
     default_convert_underscores = True
     if len(flat_dependant.header_params) == 1:
         first_field = flat_dependant.header_params[0]
-        if lenient_issubclass(first_field.type_, BaseModel):
+        if lenient_issubclass(first_field.field_info.annotation, BaseModel):
             default_convert_underscores = getattr(
                 first_field.field_info, "convert_underscores", True
             )
@@ -163,7 +161,7 @@ def _get_openapi_operation_parameters(
             parameter = {
                 "name": name,
                 "in": param_type.value,
-                "required": param.required,
+                "required": param.field_info.is_required(),
                 "schema": param_schema,
             }
             if field_info.description:
@@ -200,7 +198,7 @@ def get_openapi_operation_request_body(
     )
     field_info = cast(Body, body_field.field_info)
     request_media_type = field_info.media_type
-    required = body_field.required
+    required = body_field.field_info.is_required()
     request_body_oai: dict[str, Any] = {}
     if required:
         request_body_oai["required"] = required

fastapi/routing.py

@@ -35,7 +35,6 @@ from fastapi import params
 from fastapi._compat import (
     ModelField,
     Undefined,
-    annotation_is_pydantic_v1,
     lenient_issubclass,
 )
 from fastapi.datastructures import Default, DefaultPlaceholder
@@ -53,7 +52,6 @@ from fastapi.encoders import jsonable_encoder
 from fastapi.exceptions import (
     EndpointContext,
     FastAPIError,
-    PydanticV1NotSupportedError,
     RequestValidationError,
     ResponseValidationError,
     WebSocketRequestValidationError,
@@ -639,11 +637,7 @@ class APIRoute(routing.Route):
             assert is_body_allowed_for_status_code(status_code), (
                 f"Status code {status_code} must not have a response body"
             )
-            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.dependencies = list(dependencies or [])
         self.description = description or inspect.cleandoc(self.endpoint.__doc__ or "")
         # if a "form feed" character (page break) is found in the description text,
@@ -677,11 +671,6 @@ 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_)