from starlette.routing import Route

app = FastAPI()


class APIRouteA(APIRoute):
    x_type = "A"


class APIRouteB(APIRoute):
    x_type = "B"


class APIRouteC(APIRoute):
    x_type = "C"


router_a = APIRouter(route_class=APIRouteA)
router_b = APIRouter(route_class=APIRouteB)
router_c = APIRouter(route_class=APIRouteC)


@router_a.get("/")
def get_a():
    return {"msg": "A"}

    E `Field` do Pydantic retorna uma instância de `FieldInfo` também.

    `Body` também retorna objetos de uma subclasse de `FieldInfo` diretamente. E tem outras que você verá mais tarde que são subclasses da classe `Body`.

```

в таком случае он является "вызываемым".

## Классы как зависимости

Вы можете заметить, что для создания экземпляра класса в Python используется тот же синтаксис.

Например:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

В данном случае `fluffy` является экземпляром класса `Cat`.

app = FastAPI()


class CallableDependency:
    def __call__(self, value: str) -> str:
        return value


class CallableGenDependency:
    def __call__(self, value: str) -> Generator[str, None, None]:
        yield value


class AsyncCallableDependency:
    async def __call__(self, value: str) -> str:
        return value


class AsyncCallableGenDependency:

### Création d'un `Enum`

Importez `Enum` et créez une sous-classe qui hérite de `str` et `Enum`.

En héritant de `str` la documentation sera capable de savoir que les valeurs doivent être de type `string` et pourra donc afficher cette `Enum` correctement.

Créez ensuite des attributs de classe avec des valeurs fixes, qui seront les valeurs autorisées pour cette énumération.

```Python hl_lines="1  6-9"

from fastapi import FastAPI
from fastapi.responses import ORJSONResponse
from fastapi.testclient import TestClient
from sqlalchemy.sql.elements import quoted_name

app = FastAPI(default_response_class=ORJSONResponse)


@app.get("/orjson_non_str_keys")
def get_orjson_non_str_keys():
    key = quoted_name(value="msg", quote=False)
    return {key: "Hello World", 1: 1}


client = TestClient(app)


def test_orjson_non_str_keys():

In the previous example, because the classes were different, we had to use the `response_model` parameter. But that also means that we don't get the support from the editor and tools checking the function return type.

But in most of the cases where we need to do something like this, we want the model just to **filter/remove** some of the data as in this example.

from pydantic import BaseModel

app = FastAPI()


class JsonApiResponse(JSONResponse):
    media_type = "application/vnd.api+json"


class Error(BaseModel):
    status: str
    title: str


class JsonApiError(BaseModel):
    errors: typing.List[Error]


@app.get(
    "/a",
    response_class=JsonApiResponse,
    responses={500: {"description": "Error", "model": JsonApiError}},
)

    {!> ../../../docs_src/cookie_params/tutorial001.py!}
    ```

!!! note "Detalles Técnicos"
    `Cookie` es una clase "hermana" de `Path` y `Query`. También hereda de la misma clase común `Param`.

    Pero recuerda que cuando importas `Query`, `Path`, `Cookie`  y otros de `fastapi`, en realidad son funciones que devuelven clases especiales.

!!! info

    And Pydantic's `Field` returns an instance of `FieldInfo` as well.

    `Body` also returns objects of a subclass of `FieldInfo` directly. And there are others you will see later that are subclasses of the `Body` class.