diff options
Diffstat (limited to '.venv/lib/python3.12/site-packages/fastapi/_compat.py')
| -rw-r--r-- | .venv/lib/python3.12/site-packages/fastapi/_compat.py | 659 |
1 files changed, 659 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/fastapi/_compat.py b/.venv/lib/python3.12/site-packages/fastapi/_compat.py new file mode 100644 index 00000000..c07e4a3b --- /dev/null +++ b/.venv/lib/python3.12/site-packages/fastapi/_compat.py @@ -0,0 +1,659 @@ +from collections import deque +from copy import copy +from dataclasses import dataclass, is_dataclass +from enum import Enum +from functools import lru_cache +from typing import ( + Any, + Callable, + Deque, + Dict, + FrozenSet, + List, + Mapping, + Sequence, + Set, + Tuple, + Type, + Union, +) + +from fastapi.exceptions import RequestErrorModel +from fastapi.types import IncEx, ModelNameMap, UnionType +from pydantic import BaseModel, create_model +from pydantic.version import VERSION as PYDANTIC_VERSION +from starlette.datastructures import UploadFile +from typing_extensions import Annotated, Literal, get_args, get_origin + +PYDANTIC_VERSION_MINOR_TUPLE = tuple(int(x) for x in PYDANTIC_VERSION.split(".")[:2]) +PYDANTIC_V2 = PYDANTIC_VERSION_MINOR_TUPLE[0] == 2 + + +sequence_annotation_to_type = { + Sequence: list, + List: list, + list: list, + Tuple: tuple, + tuple: tuple, + Set: set, + set: set, + FrozenSet: frozenset, + frozenset: frozenset, + Deque: deque, + deque: deque, +} + +sequence_types = tuple(sequence_annotation_to_type.keys()) + +Url: Type[Any] + +if PYDANTIC_V2: + from pydantic import PydanticSchemaGenerationError as PydanticSchemaGenerationError + from pydantic import TypeAdapter + from pydantic import ValidationError as ValidationError + from pydantic._internal._schema_generation_shared import ( # type: ignore[attr-defined] + 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 + 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 Url as Url + + 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 + + class BaseConfig: + pass + + class ErrorWrapper(Exception): + pass + + @dataclass + class ModelField: + field_info: FieldInfo + name: str + mode: Literal["validation", "serialization"] = "validation" + + @property + def alias(self) -> str: + a = self.field_info.alias + return a if a is not None else self.name + + @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: + self._type_adapter: TypeAdapter[Any] = TypeAdapter( + Annotated[self.field_info.annotation, self.field_info] + ) + + def get_default(self) -> Any: + if self.field_info.is_required(): + return Undefined + return self.field_info.get_default(call_default_factory=True) + + def validate( + self, + value: Any, + values: Dict[str, Any] = {}, # noqa: B006 + *, + loc: Tuple[Union[int, str], ...] = (), + ) -> Tuple[Any, Union[List[Dict[str, Any]], None]]: + try: + return ( + self._type_adapter.validate_python(value, from_attributes=True), + None, + ) + except ValidationError as exc: + return None, _regenerate_error_with_loc( + errors=exc.errors(include_url=False), loc_prefix=loc + ) + + def serialize( + self, + value: Any, + *, + mode: Literal["json", "python"] = "json", + include: Union[IncEx, None] = None, + exclude: Union[IncEx, None] = None, + by_alias: bool = True, + exclude_unset: bool = False, + exclude_defaults: bool = False, + exclude_none: bool = False, + ) -> Any: + # What calls this code passes a value that already called + # self._type_adapter.validate_python(value) + return self._type_adapter.dump_python( + value, + mode=mode, + include=include, + exclude=exclude, + by_alias=by_alias, + exclude_unset=exclude_unset, + exclude_defaults=exclude_defaults, + exclude_none=exclude_none, + ) + + def __hash__(self) -> int: + # Each ModelField is unique for our purposes, to allow making a dict from + # ModelField to its JSON Schema. + return id(self) + + def get_annotation_from_field_info( + annotation: Any, field_info: FieldInfo, field_name: str + ) -> Any: + return annotation + + def _normalize_errors(errors: Sequence[Any]) -> List[Dict[str, Any]]: + return errors # type: ignore[return-value] + + def _model_rebuild(model: Type[BaseModel]) -> None: + model.model_rebuild() + + def _model_dump( + model: BaseModel, mode: Literal["json", "python"] = "json", **kwargs: Any + ) -> Any: + return model.model_dump(mode=mode, **kwargs) + + def _get_model_config(model: BaseModel) -> Any: + return model.model_config + + def get_schema_from_model_field( + *, + field: ModelField, + schema_generator: GenerateJsonSchema, + model_name_map: ModelNameMap, + field_mapping: Dict[ + Tuple[ModelField, Literal["validation", "serialization"]], JsonSchemaValue + ], + separate_input_output_schemas: bool = True, + ) -> Dict[str, Any]: + override_mode: Union[Literal["validation"], None] = ( + None if separate_input_output_schemas else "validation" + ) + # This expects that GenerateJsonSchema was already used to generate the definitions + json_schema = field_mapping[(field, override_mode or field.mode)] + if "$ref" not in json_schema: + # TODO remove when deprecating Pydantic v1 + # Ref: https://github.com/pydantic/pydantic/blob/d61792cc42c80b13b23e3ffa74bc37ec7c77f7d1/pydantic/schema.py#L207 + json_schema["title"] = ( + field.field_info.title or field.alias.title().replace("_", " ") + ) + return json_schema + + def get_compat_model_name_map(fields: List[ModelField]) -> ModelNameMap: + return {} + + def get_definitions( + *, + fields: List[ModelField], + schema_generator: GenerateJsonSchema, + model_name_map: ModelNameMap, + separate_input_output_schemas: bool = True, + ) -> Tuple[ + Dict[ + Tuple[ModelField, Literal["validation", "serialization"]], JsonSchemaValue + ], + Dict[str, Dict[str, Any]], + ]: + override_mode: Union[Literal["validation"], None] = ( + None if separate_input_output_schemas else "validation" + ) + inputs = [ + (field, override_mode or field.mode, field._type_adapter.core_schema) + for field in fields + ] + field_mapping, definitions = schema_generator.generate_definitions( + inputs=inputs + ) + return field_mapping, definitions # type: ignore[return-value] + + def is_scalar_field(field: ModelField) -> bool: + from fastapi import params + + return field_annotation_is_scalar( + field.field_info.annotation + ) and not isinstance(field.field_info, params.Body) + + def is_sequence_field(field: ModelField) -> bool: + return field_annotation_is_sequence(field.field_info.annotation) + + def is_scalar_sequence_field(field: ModelField) -> bool: + return field_annotation_is_scalar_sequence(field.field_info.annotation) + + def is_bytes_field(field: ModelField) -> bool: + return is_bytes_or_nonable_bytes_annotation(field.type_) + + def is_bytes_sequence_field(field: ModelField) -> bool: + return 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) + new_field_info = copy(field_info) + new_field_info.metadata = merged_field_info.metadata + new_field_info.annotation = merged_field_info.annotation + return new_field_info + + def serialize_sequence_value(*, field: ModelField, value: Any) -> Sequence[Any]: + origin_type = ( + get_origin(field.field_info.annotation) or field.field_info.annotation + ) + assert issubclass(origin_type, sequence_types) # type: ignore[arg-type] + return sequence_annotation_to_type[origin_type](value) # type: ignore[no-any-return] + + def get_missing_field_error(loc: Tuple[str, ...]) -> Dict[str, Any]: + error = ValidationError.from_exception_data( + "Field required", [{"type": "missing", "loc": loc, "input": {}}] + ).errors(include_url=False)[0] + error["input"] = None + return error # type: ignore[return-value] + + def create_body_model( + *, fields: Sequence[ModelField], model_name: str + ) -> Type[BaseModel]: + field_params = {f.name: (f.field_info.annotation, f.field_info) for f in fields} + BodyModel: Type[BaseModel] = create_model(model_name, **field_params) # type: ignore[call-overload] + return BodyModel + + def get_model_fields(model: Type[BaseModel]) -> List[ModelField]: + return [ + ModelField(field_info=field_info, name=name) + for name, field_info in model.model_fields.items() + ] + +else: + from fastapi.openapi.constants import REF_PREFIX as REF_PREFIX + from pydantic import AnyUrl as Url # noqa: F401 + from pydantic import ( # type: ignore[assignment] + BaseConfig as BaseConfig, # noqa: F401 + ) + from pydantic import ValidationError as ValidationError # noqa: F401 + from pydantic.class_validators import ( # type: ignore[no-redef] + Validator as Validator, # noqa: F401 + ) + from pydantic.error_wrappers import ( # type: ignore[no-redef] + ErrorWrapper as ErrorWrapper, # noqa: F401 + ) + from pydantic.errors import MissingError + from pydantic.fields import ( # type: ignore[attr-defined] + SHAPE_FROZENSET, + SHAPE_LIST, + SHAPE_SEQUENCE, + SHAPE_SET, + SHAPE_SINGLETON, + SHAPE_TUPLE, + SHAPE_TUPLE_ELLIPSIS, + ) + from pydantic.fields import FieldInfo as FieldInfo + from pydantic.fields import ( # type: ignore[no-redef,attr-defined] + ModelField as ModelField, # noqa: F401 + ) + + # Keeping old "Required" functionality from Pydantic V1, without + # shadowing typing.Required. + RequiredParam: Any = Ellipsis # type: ignore[no-redef] + from pydantic.fields import ( # type: ignore[no-redef,attr-defined] + Undefined as Undefined, + ) + from pydantic.fields import ( # type: ignore[no-redef, attr-defined] + UndefinedType as UndefinedType, # noqa: F401 + ) + from pydantic.schema import ( + field_schema, + get_flat_models_from_fields, + get_model_name_map, + model_process_schema, + ) + from pydantic.schema import ( # type: ignore[no-redef] # noqa: F401 + get_annotation_from_field_info as get_annotation_from_field_info, + ) + from pydantic.typing import ( # type: ignore[no-redef] + evaluate_forwardref as evaluate_forwardref, # noqa: F401 + ) + from pydantic.utils import ( # type: ignore[no-redef] + lenient_issubclass as lenient_issubclass, # noqa: F401 + ) + + GetJsonSchemaHandler = Any # type: ignore[assignment,misc] + JsonSchemaValue = Dict[str, Any] # type: ignore[misc] + CoreSchema = Any # type: ignore[assignment,misc] + + sequence_shapes = { + SHAPE_LIST, + SHAPE_SET, + SHAPE_FROZENSET, + SHAPE_TUPLE, + SHAPE_SEQUENCE, + SHAPE_TUPLE_ELLIPSIS, + } + sequence_shape_to_type = { + SHAPE_LIST: list, + SHAPE_SET: set, + SHAPE_TUPLE: tuple, + SHAPE_SEQUENCE: list, + SHAPE_TUPLE_ELLIPSIS: list, + } + + @dataclass + class GenerateJsonSchema: # type: ignore[no-redef] + ref_template: str + + class PydanticSchemaGenerationError(Exception): # type: ignore[no-redef] + pass + + def with_info_plain_validator_function( # type: ignore[misc] + function: Callable[..., Any], + *, + ref: Union[str, None] = None, + metadata: Any = None, + serialization: Any = None, + ) -> Any: + return {} + + def get_model_definitions( + *, + flat_models: Set[Union[Type[BaseModel], Type[Enum]]], + model_name_map: Dict[Union[Type[BaseModel], Type[Enum]], str], + ) -> Dict[str, Any]: + definitions: Dict[str, Dict[str, Any]] = {} + for model in flat_models: + m_schema, m_definitions, m_nested_models = model_process_schema( + model, model_name_map=model_name_map, ref_prefix=REF_PREFIX + ) + definitions.update(m_definitions) + model_name = model_name_map[model] + if "description" in m_schema: + m_schema["description"] = m_schema["description"].split("\f")[0] + definitions[model_name] = m_schema + return definitions + + def is_pv1_scalar_field(field: ModelField) -> bool: + from fastapi import params + + field_info = field.field_info + if not ( + field.shape == SHAPE_SINGLETON # type: ignore[attr-defined] + and not lenient_issubclass(field.type_, BaseModel) + and not lenient_issubclass(field.type_, dict) + and not field_annotation_is_sequence(field.type_) + and not is_dataclass(field.type_) + and not isinstance(field_info, params.Body) + ): + return False + if field.sub_fields: # type: ignore[attr-defined] + if not all( + is_pv1_scalar_field(f) + for f in field.sub_fields # type: ignore[attr-defined] + ): + return False + return True + + def is_pv1_scalar_sequence_field(field: ModelField) -> bool: + if (field.shape in sequence_shapes) and not lenient_issubclass( # type: ignore[attr-defined] + field.type_, BaseModel + ): + if field.sub_fields is not None: # type: ignore[attr-defined] + for sub_field in field.sub_fields: # type: ignore[attr-defined] + if not is_pv1_scalar_field(sub_field): + return False + return True + if _annotation_is_sequence(field.type_): + return True + return False + + def _normalize_errors(errors: Sequence[Any]) -> List[Dict[str, Any]]: + use_errors: List[Any] = [] + for error in errors: + if isinstance(error, ErrorWrapper): + new_errors = ValidationError( # type: ignore[call-arg] + errors=[error], model=RequestErrorModel + ).errors() + use_errors.extend(new_errors) + elif isinstance(error, list): + use_errors.extend(_normalize_errors(error)) + else: + use_errors.append(error) + return use_errors + + def _model_rebuild(model: Type[BaseModel]) -> None: + model.update_forward_refs() + + def _model_dump( + model: BaseModel, mode: Literal["json", "python"] = "json", **kwargs: Any + ) -> Any: + return model.dict(**kwargs) + + def _get_model_config(model: BaseModel) -> Any: + return model.__config__ # type: ignore[attr-defined] + + def get_schema_from_model_field( + *, + field: ModelField, + schema_generator: GenerateJsonSchema, + model_name_map: ModelNameMap, + field_mapping: Dict[ + Tuple[ModelField, Literal["validation", "serialization"]], JsonSchemaValue + ], + separate_input_output_schemas: bool = True, + ) -> Dict[str, Any]: + # This expects that GenerateJsonSchema was already used to generate the definitions + return field_schema( # type: ignore[no-any-return] + field, model_name_map=model_name_map, ref_prefix=REF_PREFIX + )[0] + + def get_compat_model_name_map(fields: List[ModelField]) -> ModelNameMap: + models = get_flat_models_from_fields(fields, known_models=set()) + return get_model_name_map(models) # type: ignore[no-any-return] + + def get_definitions( + *, + fields: List[ModelField], + schema_generator: GenerateJsonSchema, + model_name_map: ModelNameMap, + separate_input_output_schemas: bool = True, + ) -> Tuple[ + Dict[ + Tuple[ModelField, Literal["validation", "serialization"]], JsonSchemaValue + ], + Dict[str, Dict[str, Any]], + ]: + models = get_flat_models_from_fields(fields, known_models=set()) + return {}, get_model_definitions( + flat_models=models, model_name_map=model_name_map + ) + + def is_scalar_field(field: ModelField) -> bool: + return is_pv1_scalar_field(field) + + def is_sequence_field(field: ModelField) -> bool: + return field.shape in sequence_shapes or _annotation_is_sequence(field.type_) # type: ignore[attr-defined] + + def is_scalar_sequence_field(field: ModelField) -> bool: + return is_pv1_scalar_sequence_field(field) + + def is_bytes_field(field: ModelField) -> bool: + return lenient_issubclass(field.type_, bytes) + + def is_bytes_sequence_field(field: ModelField) -> bool: + return field.shape in sequence_shapes and lenient_issubclass(field.type_, bytes) # type: ignore[attr-defined] + + def copy_field_info(*, field_info: FieldInfo, annotation: Any) -> FieldInfo: + return copy(field_info) + + def serialize_sequence_value(*, field: ModelField, value: Any) -> Sequence[Any]: + return sequence_shape_to_type[field.shape](value) # type: ignore[no-any-return,attr-defined] + + def get_missing_field_error(loc: Tuple[str, ...]) -> Dict[str, Any]: + missing_field_error = ErrorWrapper(MissingError(), loc=loc) # type: ignore[call-arg] + new_error = ValidationError([missing_field_error], RequestErrorModel) + return new_error.errors()[0] # type: ignore[return-value] + + def create_body_model( + *, fields: Sequence[ModelField], model_name: str + ) -> Type[BaseModel]: + BodyModel = create_model(model_name) + for f in fields: + BodyModel.__fields__[f.name] = f # type: ignore[index] + return BodyModel + + def get_model_fields(model: Type[BaseModel]) -> List[ModelField]: + return list(model.__fields__.values()) # type: ignore[attr-defined] + + +def _regenerate_error_with_loc( + *, errors: Sequence[Any], loc_prefix: Tuple[Union[str, int], ...] +) -> List[Dict[str, Any]]: + updated_loc_errors: List[Any] = [ + {**err, "loc": loc_prefix + err.get("loc", ())} + for err in _normalize_errors(errors) + ] + + return updated_loc_errors + + +def _annotation_is_sequence(annotation: Union[Type[Any], None]) -> bool: + if lenient_issubclass(annotation, (str, bytes)): + return False + return lenient_issubclass(annotation, sequence_types) + + +def field_annotation_is_sequence(annotation: Union[Type[Any], None]) -> bool: + origin = get_origin(annotation) + if origin is Union or origin is UnionType: + for arg in get_args(annotation): + if field_annotation_is_sequence(arg): + return True + return False + return _annotation_is_sequence(annotation) or _annotation_is_sequence( + get_origin(annotation) + ) + + +def value_is_sequence(value: Any) -> bool: + return isinstance(value, sequence_types) and not isinstance(value, (str, bytes)) # type: ignore[arg-type] + + +def _annotation_is_complex(annotation: Union[Type[Any], None]) -> bool: + return ( + lenient_issubclass(annotation, (BaseModel, Mapping, UploadFile)) + or _annotation_is_sequence(annotation) + or is_dataclass(annotation) + ) + + +def field_annotation_is_complex(annotation: Union[Type[Any], None]) -> bool: + origin = get_origin(annotation) + if origin is Union or origin is UnionType: + return any(field_annotation_is_complex(arg) for arg in get_args(annotation)) + + return ( + _annotation_is_complex(annotation) + or _annotation_is_complex(origin) + or hasattr(origin, "__pydantic_core_schema__") + or hasattr(origin, "__get_pydantic_core_schema__") + ) + + +def field_annotation_is_scalar(annotation: Any) -> bool: + # handle Ellipsis here to make tuple[int, ...] work nicely + return annotation is Ellipsis or not field_annotation_is_complex(annotation) + + +def field_annotation_is_scalar_sequence(annotation: Union[Type[Any], None]) -> bool: + origin = get_origin(annotation) + if origin is Union or origin is UnionType: + at_least_one_scalar_sequence = False + for arg in get_args(annotation): + if field_annotation_is_scalar_sequence(arg): + at_least_one_scalar_sequence = True + continue + elif not field_annotation_is_scalar(arg): + return False + return at_least_one_scalar_sequence + return field_annotation_is_sequence(annotation) and all( + field_annotation_is_scalar(sub_annotation) + for sub_annotation in get_args(annotation) + ) + + +def is_bytes_or_nonable_bytes_annotation(annotation: Any) -> bool: + if lenient_issubclass(annotation, bytes): + return True + origin = get_origin(annotation) + if origin is Union or origin is UnionType: + for arg in get_args(annotation): + if lenient_issubclass(arg, bytes): + return True + return False + + +def is_uploadfile_or_nonable_uploadfile_annotation(annotation: Any) -> bool: + if lenient_issubclass(annotation, UploadFile): + return True + origin = get_origin(annotation) + if origin is Union or origin is UnionType: + for arg in get_args(annotation): + if lenient_issubclass(arg, UploadFile): + return True + return False + + +def is_bytes_sequence_annotation(annotation: Any) -> bool: + origin = get_origin(annotation) + if origin is Union or origin is UnionType: + at_least_one = False + for arg in get_args(annotation): + if is_bytes_sequence_annotation(arg): + at_least_one = True + continue + return at_least_one + return field_annotation_is_sequence(annotation) and all( + is_bytes_or_nonable_bytes_annotation(sub_annotation) + for sub_annotation in get_args(annotation) + ) + + +def is_uploadfile_sequence_annotation(annotation: Any) -> bool: + origin = get_origin(annotation) + if origin is Union or origin is UnionType: + at_least_one = False + for arg in get_args(annotation): + if is_uploadfile_sequence_annotation(arg): + at_least_one = True + continue + return at_least_one + return field_annotation_is_sequence(annotation) and all( + is_uploadfile_or_nonable_uploadfile_annotation(sub_annotation) + for sub_annotation in get_args(annotation) + ) + + +@lru_cache +def get_cached_model_fields(model: Type[BaseModel]) -> List[ModelField]: + return get_model_fields(model) |