new_field.required = field.required  # type: ignore[misc]
    new_field.model_config = field.model_config  # type: ignore[attr-defined]
    new_field.field_info = field.field_info
    new_field.allow_none = field.allow_none  # type: ignore[attr-defined]
    new_field.validate_always = field.validate_always  # type: ignore[attr-defined]
    if field.sub_fields:  # type: ignore[attr-defined]

    from fastapi._compat import is_pv1_scalar_field

    field_info = FieldInfo()
    field = ModelField(
        name="foo",
        field_info=field_info,
        type_=Union[str, List[int]],
        class_validators={},
        model_config=BaseConfig,
    )
    assert not is_pv1_scalar_field(field)


@needs_pydanticv2
def test_get_model_config():

## Importe `Field`

Primeiro, você tem que importá-lo:

```Python hl_lines="4"
{!../../../docs_src/body_fields/tutorial001.py!}
```

!!! warning "Aviso"
    Note que `Field` é importado diretamente do `pydantic`, não do `fastapi` como todo o resto (`Query`, `Path`, `Body`, etc).

                    "msg": "Field required",
                    "input": None,
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "password"],
                    "msg": "field required",
                    "type": "value_error.missing",

!!! tip
    Notice how each model's attribute with a type, default value and `Field` has the same structure as a *path operation function's* parameter, with `Field` instead of `Path`, `Query` and `Body`.

## Add extra information

You can declare extra information in `Field`, `Query`, `Body`, etc. And it will be included in the generated JSON Schema.

!!! tip "提示"

    注意，模型属性的类型、默认值及 `Field` 的代码结构与*路径操作函数*的参数相同，只不过是用 `Field` 替换了`Path`、`Query`、`Body`。

## 添加更多信息

`Field`、`Query`、`Body` 等对象里可以声明更多信息，并且 JSON Schema 中也会集成这些信息。

*声明示例*一章中将详细介绍添加更多信息的知识。

## 小结

Pydantic 的 `Field` 可以为模型属性声明更多校验和元数据。

                    "type": "missing",
                    "loc": ["header", "x-token"],
                    "msg": "Field required",
                    "input": None,
                },
                {
                    "type": "missing",
                    "loc": ["header", "x-key"],
                    "msg": "Field required",
                    "input": None,
                },
            ]
        }
    ) | IsDict(

from .utils import needs_pydanticv2


@pytest.fixture(name="client")
def get_client():
    app = FastAPI()

    from pydantic import BaseModel, computed_field

    class Rectangle(BaseModel):
        width: int
        length: int

        @computed_field
        @property
        def area(self) -> int:
            return self.width * self.length

    @app.get("/")
    def read_root() -> Rectangle:

    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "missing",
                    "loc": ["query", "needy"],
                    "msg": "Field required",
                    "input": None,
                },
                {
                    "type": "int_parsing",
                    "loc": ["query", "skip"],

import strawberry
from fastapi import FastAPI
from strawberry.asgi import GraphQL


@strawberry.type
class User:
    name: str
    age: int


@strawberry.type
class Query:
    @strawberry.field
    def user(self) -> User:
        return User(name="Patrick", age=100)


schema = strawberry.Schema(query=Query)


graphql_app = GraphQL(schema)

app = FastAPI()
app.add_route("/graphql", graphql_app)