import time

from fastapi import FastAPI, Request

app = FastAPI()


@app.middleware("http")
async def add_process_time_header(request: Request, call_next):
    start_time = time.time()
    response = await call_next(request)
    process_time = time.time() - start_time
    response.headers["X-Process-Time"] = str(process_time)

!!! tip
    The next sections are **not necessarily "advanced"**.

    And it's possible that for your use case, the solution is in one of them.

## Read the Tutorial first

The next sections assume you already read the main [Tutorial - User Guide: Security](../../tutorial/security/index.md){.internal-link target=_blank}.

## Create a middleware

To create a middleware you use the decorator `@app.middleware("http")` on top of a function.

The middleware function receives:

* The `request`.
* A function `call_next` that will receive the `request` as a parameter.
    * This function will pass the `request` to the corresponding *path operation*.
    * Then it returns the `response` generated by the corresponding *path operation*.

## Integrated middlewares

**FastAPI** includes several middlewares for common use cases, we'll see next how to use them.

!!! note "Technical Details"
    For the next examples, you could also use `from starlette.middleware.something import SomethingMiddleware`.

    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)
    if not user:

    * If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers.
* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.

## 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.

!!! note "技术细节"
    如果你使用了 `yield` 关键字依赖, 依赖中的退出代码将在执行中间件*后*执行.

    如果有任何后台任务(稍后记录), 它们将在执行中间件*后*运行.

## 创建中间件

要创建中间件你可以在函数的顶部使用装饰器 `@app.middleware("http")`.

中间件参数接收如下参数:

* `request`.
* 一个函数 `call_next` 它将接收 `request` 作为参数.
    * 这个函数将 `request` 传递给相应的 *路径操作*.
    * 然后它将返回由相应的*路径操作*生成的 `response`.
* 然后你可以在返回 `response` 前进一步修改它.

```Python hl_lines="8-9  11  14"
{!../../../docs_src/middleware/tutorial001.py!}
```

    ```

`Field` works the same way as `Query`, `Path` and `Body`, it has all the same parameters, etc.

!!! note "Technical Details"
    Actually, `Query`, `Path` and others you'll see next create objects of subclasses of a common `Param` class, which is itself a subclass of Pydantic's `FieldInfo` class.

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

    バックグラウンドタスク (後述) がある場合は、それらは全てのミドルウェアの *後に* 実行されます。

## ミドルウェアの作成

ミドルウェアを作成するには、関数の上部でデコレータ `@app.middleware("http")` を使用します。

ミドルウェア関数は以下を受け取ります:

* `request`。
* パラメータとして `request` を受け取る関数 `call_next`。
    * この関数は、対応する*path operation*に `request` を渡します。
    * 次に、対応する*path operation*によって生成された `response` を返します。
* その後、`response` を返す前にさらに `response` を変更することもできます。

```Python hl_lines="8-9  11  14"