### Before and after the `response`

You can add code to be run with the `request`,  before any *path operation* receives it.

And also after the `response` is generated, before returning it.

For example, you could add a custom header `X-Process-Time` containing the time in seconds that it took to process the request and generate a response:

Now you can translate it all and see how it looks as you save the file.

#### New Language

Let's say that you want to add translations for a language that is not yet translated, not even some pages.

Let's say you want to add translations for Creole, and it's not yet there in the docs.

Checking the link from above, the code for "Creole" is `ht`.

    for key, value in build_config.items():
        context.config.build_config[key] = value
    # Get main dependencies
    dependencies: List[str] = metadata.get("dependencies", [])
    # Add optional dependencies to the default dependencies for this (non-slim) package
    for include_optional in include_optional_dependencies:
        optional_dependencies_group = optional_dependencies.get(include_optional, [])

```Python hl_lines="3"
{!../../../docs_src/app_testing/test_main.py!}
```

...and have the code for the tests just like before.

## Testing: extended example

Now let's extend this example and add more details to see how to test different parts.

### Extended **FastAPI** app file

Let's continue with the same file structure as before:

```
.
├── app
│   ├── __init__.py
│   ├── main.py

```Python hl_lines="6-9"
{!../../../docs_src/background_tasks/tutorial001.py!}
```

## バックグラウンドタスクの追加

*path operations 関数* 内で、`.add_task()` メソッドを使用してタスク関数を *background tasks* オブジェクトに渡します。

```Python hl_lines="14"
{!../../../docs_src/background_tasks/tutorial001.py!}
```

`.add_task()` は以下の引数を受け取ります:

* バックグラウンドで実行されるタスク関数 (`write_notification`)。
* タスク関数に順番に渡す必要のある引数の列 (`email`)。

    * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization...

## 디버거로 코드 실행

코드에서 직접 Uvicorn 서버를 실행하고 있기 때문에 디버거에서 직접 Python 프로그램(FastAPI 애플리케이션)을 호출할 수 있습니다.

---

예를 들어 Visual Studio Code에서 다음을 수행할 수 있습니다.

* "Debug" 패널로 이동합니다.
* "Add configuration...".
* "Python"을 선택합니다.
* "`Python: Current File (Integrated Terminal)`" 옵션으로 디버거를 실행합니다.

그런 다음 **FastAPI** 코드로 서버를 시작하고 중단점 등에서 중지합니다.

다음과 같이 표시됩니다.

<img src="/img/tutorial/debugging/image01.png">

* Add a **JSON Schema** for the response, in the OpenAPI *path operation*.
    * This will be used by the **automatic docs**.
    * It will also be used by automatic client code generation tools.

But most importantly:

And it's also used internally when mounting sub-applications.

## Proxy with a stripped path prefix

Having a proxy with a stripped path prefix, in this case, means that you could declare a path at `/app` in your code, but then, you add a layer on top (the proxy) that would put your **FastAPI** application under a path like `/api/v1`.

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

after compilation to JavaScript, it cannot rely on the types to define validation, serialization and documentation at the same time. Due to this and some design decisions, to get validation, serialization and automatic schema generation, it's needed to add decorators in many places. So, it becomes quite verbose.

It can't handle nested models very well. So, if the JSON body in the request is a JSON object that has inner fields that in turn are nested JSON objects, it cannot be properly documented...