In that case, you wouldn't have to worry about any of this. 🤷

### Examples of Previous Steps Strategies

This will **depend heavily** on the way you **deploy your system**, and it would probably be connected to the way you start programs, handling restarts, etc.

Here are some possible ideas:

* An "Init Container" in Kubernetes that runs before your app container

    So, we declare the event handler function with standard `def` instead of `async def`.

### `startup` and `shutdown` together

There's a high chance that the logic for your *startup* and *shutdown* is connected, you might want to start something and then finish it, acquire a resource and then release it, etc.

!!! info
    Note that the `TestClient` receives data that can be converted to JSON, not Pydantic models.

컨테이너를 사용하지 않고서는, 어플리케이션을 구동하고 재시작하는 것이 매우 번거롭고 어려울 수 있습니다. 하지만 **컨테이너를 사용한다면** 대부분의 경우에 이런 기능은 기본적으로 포함되어 있습니다. ✨

## 복제 - 프로세스 개수

만약 여러분이 **쿠버네티스**와 머신 <abbr title="A group of machines that are configured to be connected and work together in some way.">클러스터</abbr>, 도커 스왐 모드, 노마드, 또는 다른 여러 머신 위에 분산 컨테이너를 관리하는 복잡한 시스템을 다루고 있다면, 여러분은 각 컨테이너에서 (워커와 함께 사용하는 Gunicorn 같은) **프로세스 매니저** 대신 **클러스터 레벨**에서 **복제를 다루**고 싶을 것입니다.

You can also use `dataclasses` in the `response_model` parameter:

```Python hl_lines="1  7-13  19"
{!../../../docs_src/dataclasses/tutorial002.py!}
```

The dataclass will be automatically converted to a Pydantic dataclass.

This way, its schema will show up in the API docs user interface:

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

## Dataclasses in Nested Data Structures

👆 💪 👈 ⏮️ `openapi_extra`:

```Python hl_lines="20-37  39-40"
{!../../../docs_src/path_operation_advanced_configuration/tutorial006.py!}
```

👉 🖼, 👥 🚫 📣 🙆 Pydantic 🏷. 👐, 📨 💪 🚫 <abbr title="converted from some plain format, like bytes, into Python objects">🎻</abbr> 🎻, ⚫️ ✍ 🔗 `bytes`, &amp; 🔢 `magic_data_reader()` 🔜 🈚 🎻 ⚫️ 🌌.

👐, 👥 💪 📣 📈 🔗 📨 💪.

### 🛃 🗄 🎚 🆎

#### Return *enumeration members*

You can return *enum members* from your *path operation*, even nested in a JSON body (e.g. a `dict`).

They will be converted to their corresponding values (strings in this case) before returning them to the client:

```Python hl_lines="18  21  23"
{!../../../docs_src/path_params/tutorial005.py!}
```

```

You can return a `dict`, `list`, singular values as `str`, `int`, etc.

You can also return Pydantic models (you'll see more about that later).

There are many other objects and models that will be automatically converted to JSON (including ORMs, etc). Try using your favorite ones, it's highly probable that they are already supported.

## Recap

* Import `FastAPI`.
* Create an `app` instance.

It would also mean that if you get data from the `Request` object directly (for example, read the body) it won't be validated, converted or documented (with OpenAPI, for the automatic API user interface) by FastAPI.

Although any other parameter declared normally (for example, the body with a Pydantic model) would still be validated, converted, annotated, etc.

But there are specific cases where it's useful to get the `Request` object.

# <abbr title="En anglais: Debugging">Débogage</abbr>

Vous pouvez connecter le <abbr title="En anglais: debugger">débogueur</abbr> dans votre éditeur, par exemple avec Visual Studio Code ou PyCharm.

## Faites appel à `uvicorn`

Dans votre application FastAPI, importez et exécutez directement `uvicorn` :

```Python hl_lines="1  15"
{!../../../docs_src/debugging/tutorial001.py!}
```

### À propos de `__name__ == "__main__"`