Field(discriminator="value"),
    ]

    @app.post("/items/")
    def save_union_body_discriminator(
        item: Item, q: Annotated[str, Field(description="Query string")]
    ) -> dict[str, Any]:
        return {"item": item}

    client = TestClient(app)
    response = client.post("/items/?q=first", json={"value": "first", "price": 100})
    assert response.status_code == 200, response.text

from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class Items(BaseModel):
    items: dict[str, int]


@app.post("/foo")
def foo(items: Items):
    return items.items


client = TestClient(app)


def test_additional_properties_post():
    response = client.post("/foo", json={"items": {"foo": 1, "bar": 2}})

Zum Beispiel deklariert das obige Modell ein JSON „`object`“ (oder Python-<abbr title="Dictionary – Zuordnungstabelle: In anderen Sprachen auch Hash, Map, Objekt, Assoziatives Array genannt">`dict`</abbr>) wie dieses:

```JSON
{
    "name": "Foo",
    "description": "An optional description",
    "price": 45.2,
    "tax": 3.5
}
```

        username: str

    class ModelC(ModelB):
        password: str

    class ModelA(BaseModel):
        name: str
        description: Optional[str] = None
        foo: ModelB
        tags: dict[str, str] = {}

        @field_validator("name")
        def lower_username(cls, name: str, info: ValidationInfo):
            if not name.endswith("A"):
                raise ValueError("name must end in A")

    class ModelV1A(BaseModel):
        name: str

    app = FastAPI()

    with pytest.raises(PydanticV1NotSupportedError):

        @app.post("/union")
        def endpoint(data: Union[dict, ModelV1A]):  # pragma: no cover
            return data


def test_raises_pydantic_v1_model_in_sequence() -> None:
    class ModelV1A(BaseModel):
        name: str

    app = FastAPI()

And then you can set cookies in that *temporal* response object.

{* ../../docs_src/response_cookies/tutorial002_py39.py hl[1, 8:9] *}

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

And if you declared a `response_model`, it will still be used to filter and convert the object you returned.

Наприклад, ця модель вище оголошує JSON "`об'єкт`" (або Python `dict`), як:

```JSON
{
    "name": "Foo",
    "description": "An optional description",
    "price": 45.2,
    "tax": 3.5
}
```

В HTML, который содержит:

{% raw %}

```jinja
Item ID: {{ id }}
```

{% endraw %}

...будет показан `id`, взятый из переданного вами «context» `dict`:

```Python
{"id": id}
```

Например, для ID `42` это отрендерится как:

```html
Item ID: 42
```

### Аргументы `url_for` в шаблоне { #template-url-for-arguments }

* 将输出数据转换为其声明的类型。
* 校验数据。
* 在 OpenAPI 的*路径操作*中为响应添加一个 JSON Schema。
* 并在自动生成文档系统中使用。

但最重要的是：

* 会将输出数据限制在该模型定义内。下面我们会看到这一点有多重要。

/// note | 技术细节

响应模型在参数中被声明，而不是作为函数返回类型的注解，这是因为路径函数可能不会真正返回该响应模型，而是返回一个 `dict`、数据库对象或其他模型，然后再使用 `response_model` 来执行字段约束和序列化。

///

## 返回与输入相同的数据

现在我们声明一个 `UserIn` 模型，它将包含一个明文密码属性。

{* ../../docs_src/response_model/tutorial002.py hl[9,11] *}

我们正在使用此模型声明输入数据，并使用同一模型声明输出数据：

E então você pode definir cookies nesse objeto de resposta *temporário*.

{* ../../docs_src/response_cookies/tutorial002_py39.py hl[1, 8:9] *}

Em seguida, você pode retornar qualquer objeto que precise, como normalmente faria (um `dict`, um modelo de banco de dados, etc).

E se você declarou um `response_model`, ele ainda será usado para filtrar e converter o objeto que você retornou.