만약 (나중에 문서에서 다룰) 백그라운드 작업이 있다면, 모든 미들웨어가 실행되고 *난 후에* 실행됩니다.

## 미들웨어 만들기

미들웨어를 작성하기 위해서 함수 상단에 `@app.middleware("http")` 데코레이터를 사용할 수 있습니다.

미들웨어 함수는 다음 항목들을 받습니다:

* `request`.
* `request`를 매개변수로 받는 `call_next` 함수.
    * 이 함수는 `request`를 해당하는 *경로 작업*으로 전달합니다.
    * 그런 다음, *경로 작업*에 의해 생성된 `response` 를 반환합니다.
* `response`를 반환하기 전에 추가로 `response`를 수정할 수 있습니다.

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

$ python main.py

// As we didn't set the env var, we get the default value

Hello World from Python

// But if we create an environment variable first
$ export MY_NAME="Wade Wilson"

// And then call the program again
$ python main.py

// Now it can read the environment variable

Hello Wade Wilson from Python
```

</div>

It's a very simple program.

But now imagine that you were writing it from scratch.

At some point you would have started the definition of the function, you had the parameters ready...

But then you have to call "that method that converts the first letter to upper case".

Was it `upper`? Was it `uppercase`? `first_uppercase`? `capitalize`?

Then, you try with the old programmer's friend, editor autocompletion.

Username: `johndoe`
Password: `secret`

!!! check
    Notice that nowhere in the code is the plaintext password "`secret`", we only have the hashed version.

<img src="/img/tutorial/security/image08.png">

Call the endpoint `/users/me/`, you will get the response as:

```JSON
{
  "username": "johndoe",
  "email": "******@****.***",
  "full_name": "John Doe",
  "disabled": false
}
```

This has **several benefits**, one of the main ones is that now the parameters of your functions with `Annotated` would **not be affected** at all.

## A "callable" instance

In Python there's a way to make an instance of a class a "callable".

Not the class itself (which is already a callable), but an instance of that class.

To do that, we declare a method `__call__`:

=== "Python 3.9+"

    ```Python hl_lines="12"
    {!> ../../../docs_src/dependencies/tutorial011_an_py39.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="11"

# OpenAPI Webhooks

There are cases where you want to tell your API **users** that your app could call *their* app (sending a request) with some data, normally to **notify** of some type of **event**.

This means that instead of the normal process of your users sending requests to your API, it's **your API** (or your app) that could **send requests to their system** (to their API, their app).

This is normally called a **webhook**.

## Webhooks steps

So we are going to use that same knowledge to document how the *external API* should look like... by creating the *path operation(s)* that the external API should implement (the ones your API will call).

!!! tip
    When writing the code to document a callback, it might be useful to imagine that you are that *external developer*. And that you are currently implementing the *external API*, not *your API*.

```Python
user_in = UserIn(username="john", password="secret", email="******@****.***")
```

and then we call:

```Python
user_dict = user_in.dict()
```

we now have a `dict` with the data in the variable `user_dict` (it's a `dict` instead of a Pydantic model object).

And if we call:

```Python
print(user_dict)
```

we would get a Python `dict` with:

```Python
{

You only give `Depends` a single parameter.

This parameter must be something like a function.

You **don't call it** directly (don't add the parenthesis at the end), you just pass it as a parameter to `Depends()`.

And that function takes parameters in the same way that *path operation functions* do.

!!! tip