dict[str, dict[str, Any]],
]:
    schema_generator = GenerateJsonSchema(ref_template=REF_TEMPLATE)
    validation_fields = [field for field in fields if field.mode == "validation"]
    serialization_fields = [field for field in fields if field.mode == "serialization"]
    flat_validation_models = get_flat_models_from_fields(
        validation_fields, known_models=set()
    )

Mehr erfahren Sie am Ende dieser Seite.

///

## Zusätzliche Argumente für `Field` { #field-additional-arguments }

Wenn Sie `Field()` mit Pydantic-Modellen verwenden, können Sie ebenfalls zusätzliche `examples` deklarieren:

{* ../../docs_src/schema_extra_example/tutorial002_py310.py hl[2,8:11] *}

    return True


def _should_embed_body_fields(fields: list[ModelField]) -> bool:
    if not fields:
        return False
    # More than one dependency could have the same field, it would show up as multiple
    # fields but it's the same one, so count them by name
    body_param_names_set = {field.name for field in fields}
    # A top level field has to be a single field, not multiple
    if len(body_param_names_set) > 1:

            {
                "type": "missing",
                "loc": ["body", "name"],
                "msg": "Field required",
                "input": {},
            },
            {
                "type": "missing",
                "loc": ["body", "price"],
                "msg": "Field required",
                "input": {},
            },
        ]
    }

    return set(re.findall("{(.*?)}", path))


_invalid_args_message = (
    "Invalid args for response field! Hint: "
    "check that {type_} is a valid Pydantic field type. "
    "If you are using a return type annotation that is not a valid Pydantic "
    "field (e.g. Union[Response, dict, None]) you can disable generating the "
    "response model from the type annotation with the path operation decorator "

    # Core Vocabulary
    schema_: Optional[str] = Field(default=None, alias="$schema")
    vocabulary: Optional[str] = Field(default=None, alias="$vocabulary")
    id: Optional[str] = Field(default=None, alias="$id")
    anchor: Optional[str] = Field(default=None, alias="$anchor")
    dynamicAnchor: Optional[str] = Field(default=None, alias="$dynamicAnchor")
    ref: Optional[str] = Field(default=None, alias="$ref")

    is_coroutine: bool = True,
    endpoint_ctx: Optional[EndpointContext] = None,
) -> Any:
    if field:
        errors = []
        if is_coroutine:
            value, errors_ = field.validate(response_content, {}, loc=("response",))
        else:
            value, errors_ = await run_in_threadpool(
                field.validate, response_content, {}, loc=("response",)
            )
        if isinstance(errors_, list):

            fields will be ignored at serialization time.
            """
        ),
    ] = None,
    convert_underscores: Annotated[
        bool,
        Doc(
            """
            Automatically convert underscores to hyphens in the parameter field name.

            Read more about it in the

            Pydantic's `include` parameter, passed to Pydantic models to set the
            fields to include.
            """
        ),
    ] = None,
    exclude: Annotated[
        Optional[IncEx],
        Doc(
            """
            Pydantic's `exclude` parameter, passed to Pydantic models to set the
            fields to exclude.
            """
        ),
    ] = None,
    by_alias: Annotated[

    # For the test client
    "httpx >=0.23.0,<1.0.0",
    # For templates
    "jinja2 >=3.1.5",
    # For forms and file uploads
    "python-multipart >=0.0.18",
    # To validate email fields
    "email-validator >=2.0.0",
    # Uvicorn with uvloop
    "uvicorn[standard] >=0.12.0",
    # # Settings management
    "pydantic-settings >=2.0.0",
    # # Extra Pydantic data types