=== "Python 3.8+"

    ```Python hl_lines="9  11  16"
    {!> ../../../docs_src/response_model/tutorial003.py!}
    ```

Here, even though our *path operation function* is returning the same input user that contains the password:

=== "Python 3.10+"

    ```Python hl_lines="24"
    {!> ../../../docs_src/response_model/tutorial003_py310.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="24"

5. You can use other standard type annotations with dataclasses as the request body.

    In this case, it's a list of `Item` dataclasses.

6. Here we are returning a dictionary that contains `items` which is a list of dataclasses.

    FastAPI is still capable of <abbr title="converting the data to a format that can be transmitted">serializing</abbr> the data to JSON.

```

</div>

That would work for most of the cases. 😎

You could use that command for example to start your **FastAPI** app in a container, in a server, etc.

## ASGI Servers

Let's go a little deeper into the details.

!!! tip
    Don't worry if some of these items about **containers**, Docker, or Kubernetes don't make a lot of sense yet.

    For example, in `app/main.py` you could have a line like:

    ```
    from app.routers import items
    ```

* The `app` directory contains everything. And it has an empty file `app/__init__.py`, so it is a "Python package" (a collection of "Python modules"): `app`.
* It contains an `app/main.py` file. As it is inside a Python package (a directory with a file `__init__.py`), it is a "module" of that package: `app.main`.

For example, let's define a variable to be a `list` of `str`.

=== "Python 3.9+"

    Declare the variable, with the same colon (`:`) syntax.

    As the type, put `list`.

    As the list is a type that contains some internal types, you put them in square brackets:

    ```Python hl_lines="1"
    {!> ../../../docs_src/python_types/tutorial006_py39.py!}
    ```

=== "Python 3.8+"

`note.dict()` returns a `dict` with its data, something like:

```Python
{
    "text": "Some note",
    "completed": False,
}
```

but it doesn't have the `id` field.

So we create a new `dict`, that contains the key-value pairs from `note.dict()` with:

```Python
{**note.dict()}
```

`**note.dict()` "unpacks" the key value pairs directly, so, `{**note.dict()}` would be, more or less, a copy of `note.dict()`.

    "UP",  # pyupgrade
]
ignore = [
    "E501",  # line too long, handled by black
    "B008",  # do not perform function calls in argument defaults
    "C901",  # too complex
    "W191",  # indentation contains tabs
]

[tool.ruff.lint.per-file-ignores]
"__init__.py" = ["F401"]
"docs_src/dependencies/tutorial007.py" = ["F821"]
"docs_src/dependencies/tutorial008.py" = ["F821"]

!!! info "정보"
    만약 여러분이 쿠버네티스를 사용하고 있다면, 아마도 이는 <a href="https://kubernetes.io/docs/concepts/workloads/pods/init-containers/" class="external-link" target="_blank">Init Container</a>일 것입니다.

만약 여러분의 이용 사례에서 이전 단계들을 **병렬적으로 여러번** 수행하는데에 문제가 없다면 (예를 들어 데이터베이스 이전을 실행하지 않고 데이터베이스가 준비되었는지 확인만 하는 경우), 메인 프로세스를 시작하기 전에 이 단계들을 각 컨테이너에 넣을 수 있습니다.

### 단일 컨테이너

the `response_model` (e.g. you return a `UserInDB` that inherits from `User` but contains extra fields, like `hashed_password`, and `User` is used in the `response_model`), it would still pass the validation (because `UserInDB` is a subclass of `User`) and the object would be returned as-is, including the `hashed_password`. To fix this, the declared `response_model` is cloned, if it is a Pydantic model class (or contains Pydantic model classes in it, e.g. in a `List[Item]`), the Pydantic model class(es)...