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.

@needs_py310
def test_typing():
    types = {
        list[int]: [1, 2, 3],
        dict[str, list[int]]: {"a": [1, 2, 3], "b": [4, 5, 6]},
        set[int]: [1, 2, 3],  # `set` is converted to `list`
        tuple[int, ...]: [1, 2, 3],  # `tuple` is converted to `list`
    }
    for test_type, expect in types.items():
        app = FastAPI()

        @app.post("/", response_model=test_type)
        def post_endpoint(input: test_type):

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.

                                            "tax": 3.2,
                                        },
                                    },
                                    "converted": {
                                        "summary": "An example with converted data",
                                        "description": "FastAPI can convert price `strings` to actual `numbers` automatically",

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

    """
    This is a dependency class to collect the `username` and `password` as form data
    for an OAuth2 password flow.

    The OAuth2 specification dictates that for a password flow the data should be
    collected using form data (instead of JSON) and that it should have the specific
    fields `username` and `password`.

    All the initialization parameters are extracted from the request.

    Read more about it in the

👆 💪 👈 ⏮️ `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!}
```