### `response_model` Priority

If you declare both a return type and a `response_model`, the `response_model` will take priority and be used by FastAPI.

### `response_model_include` 和 `response_model_exclude`

你还可以使用*路径操作装饰器*的 `response_model_include` 和 `response_model_exclude` 参数。

它们接收一个由属性名称 `str` 组成的 `set` 来包含（忽略其他的）或者排除（包含其他的）这些属性。

如果你只有一个 Pydantic 模型，并且想要从输出中移除一些数据，则可以使用这种快捷方法。

!!! tip
    但是依然建议你使用上面提到的主意，使用多个类而不是这些参数。

```Python hl_lines="9 11 16"
{!../../../docs_src/response_model/tutorial003.py!}
```

ここでは、*path operation関数*がパスワードを含む同じ入力ユーザーを返しているにもかかわらず:

```Python hl_lines="24"
{!../../../docs_src/response_model/tutorial003.py!}
```

...`response_model`を`UserOut`と宣言したことで、パスワードが含まれていません:

```Python hl_lines="22"
{!../../../docs_src/response_model/tutorial003.py!}
```

class CustomModel(BaseModel):
    a: int


app = FastAPI()

callback_router = APIRouter(default_response_class=JSONResponse)


@callback_router.get(
    "{$callback_url}/callback/", responses={400: {"model": CustomModel}}
)
def callback_route():
    pass  # pragma: no cover


@app.post("/", callbacks=callback_router.routes)
def main_route(callback_url: HttpUrl):
    pass  # pragma: no cover

def read_dict():
    return {"alias": "Foo"}


@app.get("/model", response_model=Model, response_model_by_alias=False)
def read_model():
    return Model(alias="Foo")


@app.get("/list", response_model=List[Model], response_model_by_alias=False)
def read_list():
    return [{"alias": "Foo"}, {"alias": "Bar"}]


@app.get("/by-alias/dict", response_model=Model)
def by_alias_dict():

            "field (e.g. Union[Response, dict, None]) you can disable generating the "
            "response model from the type annotation with the path operation decorator "
            "parameter response_model=None. Read more: "
            "https://fastapi.tiangolo.com/tutorial/response-model/"
        ) from None


def create_cloned_field(
    field: ModelField,
    *,

        type_=Union[str, List[int]],
        class_validators={},
        model_config=BaseConfig,
    )
    assert not is_pv1_scalar_field(field)


@needs_pydanticv2
def test_get_model_config():
    # For coverage in Pydantic v2
    class Foo(BaseModel):
        model_config = ConfigDict(from_attributes=True)

    foo = Foo()
    config = _get_model_config(foo)
    assert config == {"from_attributes": True}

    owner_ids: Optional[List[int]] = None


@app.get("/items/invalid", response_model=Item)
def get_invalid():
    return {"name": "invalid", "price": "foo"}


@app.get("/items/invalidnone", response_model=Item)
def get_invalid_none():
    return None


@app.get("/items/validnone", response_model=Union[Item, None])
def get_valid_none(send_none: bool = False):
    if send_none:
        return None

But you are not restricted to using some specific data model, class or type.

Do you want to have an `id` and `email` and not have any `username` in your model? Sure. You can use these same tools.

Do you want to just have a `str`? Or just a `dict`? Or a database class model instance directly? It all works the same way.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

```Python hl_lines="1  7-13  19"
{!../../../docs_src/dataclasses/tutorial002.py!}
```

The dataclass will be automatically converted to a Pydantic dataclass.