In diesem Fall möchten Sie möglicherweise dokumentieren, wie diese externe API aussehen *sollte*. Welche *Pfadoperation* sie haben sollte, welchen Body sie erwarten sollte, welche Response sie zurückgeben sollte, usw.

## Eine Anwendung mit Callbacks

## Erstellung einer Middleware

Um eine Middleware zu erstellen, verwenden Sie den Dekorator `@app.middleware("http")` über einer Funktion.

Die Middleware-Funktion erhält:

* Den `request`.
* Eine Funktion `call_next`, die den `request` als Parameter erhält.
    * Diese Funktion gibt den `request` an die entsprechende *Pfadoperation* weiter.
    * Dann gibt es die von der entsprechenden *Pfadoperation* generierte `response` zurück.

    ```

## Zusammenfassung

Abgesehen von all den ausgefallenen Wörtern, die hier verwendet werden, ist das **Dependency Injection**-System recht simpel.

Einfach Funktionen, die genauso aussehen wie *Pfadoperation-Funktionen*.

Dennoch ist es sehr mächtig und ermöglicht Ihnen die Deklaration beliebig tief verschachtelter Abhängigkeits-„Graphen“ (Bäume).

!!! tip "Tipp"

<a href="https://fastapi.tiangolo.com/fastapi-people/#sponsors" class="external-link" target="_blank">Altri sponsor</a>

## Recensioni

"_[...] I'm using **FastAPI** a ton these days. [...] I'm actually planning to use it for all of my team's **ML services at Microsoft**. Some of them are getting integrated into the core **Windows** product and some **Office** products._"

def get_user(db, username: str):
    if username in db:
        user_dict = db[username]
        return UserInDB(**user_dict)


def fake_decode_token(token):
    # This doesn't provide any security at all
    # Check the next version
    user = get_user(fake_users_db, token)
    return user


async def get_current_user(token: Annotated[str, Depends(oauth2_scheme)]):
    user = fake_decode_token(token)

In this case, the original path `/app` would actually be served at `/api/v1/app`.

Even though all your code is written assuming there's just `/app`.

```Python hl_lines="6"
{!../../../docs_src/behind_a_proxy/tutorial001.py!}
```

## Instale o FastAPI

O primeiro passo é instalar o FastAPI.

Para o tutorial, você deve querer instalá-lo com todas as dependências e recursos opicionais.

<div class="termy">

```console
$ pip install "fastapi[all]"

---> 100%
```

</div>

...isso também inclui o `uvicorn`, que você pode usar como o servidor que rodará seu código.

!!! note "Nota"
    Você também pode instalar parte por parte.

---

## FastAPI 설치

첫 번째 단계는 FastAPI를 설치하는 것입니다.

자습시에는 모든 선택적인 의존성 및 기능을 함께 설치하는 것을 추천합니다:

<div class="termy">

```console
$ pip install "fastapi[all]"

---> 100%
```

</div>

...이는 코드를 실행하는 서버로 사용할 수 있는 `uvicorn` 또한 포함하고 있습니다.

!!! note "참고"
    부분적으로 설치할 수도 있습니다.

    애플리케이션을 운영 환경에 배포하려는 경우 다음과 같이 합니다:

    ```

The same way, there are many compatible tools. Including code generation tools for many languages.

## Pydantic

All the data validation is performed under the hood by <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>, so you get all the benefits from it. And you know you are in good hands.

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

    **FastAPI** provides the same `starlette.testclient` as `fastapi.testclient` just as a convenience for you, the developer. But it comes directly from Starlette.

!!! tip
    If you want to call `async` functions in your tests apart from sending requests to your FastAPI application (e.g. asynchronous database functions), have a look at the [Async Tests](../advanced/async-tests.md){.internal-link target=_blank} in the advanced tutorial.