- 새로운 오픈소스 프로젝트를 만들었을 때 확인하려면 팔로우 하십시오.

  - [**Twitter**에서 팔로우하기](https://twitter.com/tiangolo).
    - FastAPI의 사용 용도를 알려주세요 (그것을 듣는 것을 좋아합니다).
    - 발표 또는 새로운 툴 출시할 때 들으십시오.
    - [follow @fastapi on Twitter](https://twitter.com/fastapi) (별도 계정에서) 할 수 있습니다.

  - [**Linkedin**에서의 연결](https://www.linkedin.com/in/tiangolo/).
    - 새로운 툴의 발표나 릴리스를 들을 수 있습니다 (단, Twitter를 더 자주 사용합니다 🤷‍♂).

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server
    * **Starlette**: (uses Uvicorn) a web microframework

```console
$ hypercorn main:app --worker-class trio
```

</div>

And that will start Hypercorn with your app using Trio as the backend.

Now you can use Trio internally in your app. Or even better, you can use AnyIO, to keep your code compatible with both Trio and asyncio. 🎉

## Deployment Concepts

And if you click it, you have a little authorization form to type a `username` and `password` (and other optional fields):

<img src="/img/tutorial/security/image02.png">

!!! note
    It doesn't matter what you type in the form, it won't work yet. But we'll get there.

This is of course not the frontend for the final users, but it's a great automatic tool to document interactively all your API.

        return {"name": name, "description": "model-a-desc", "foo": model_c}

    client = TestClient(app)
    return client


@needs_pydanticv2
def test_filter_sub_model(client: TestClient):
    response = client.get("/model/modelA")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "name": "modelA",
        "description": "model-a-desc",

## Future

By this point, it's already clear that **FastAPI** with its ideas is being useful for many people.

It is being chosen over previous alternatives for suiting many use cases better.

Many developers and teams already depend on **FastAPI** for their projects (including me and my team).

But still, there are many improvements and features to come.

**FastAPI** has a great future ahead.

And these models are all sharing a lot of the data and duplicating attribute names and types.

We could do better.

We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).

### Tested

* 100% <abbr title="The amount of code that is automatically tested">test coverage</abbr>.
* 100% <abbr title="Python type annotations, with this your editor and external tools can give you better support">type annotated</abbr> code base.
* Used in production applications.

## Starlette features

<img src="/img/tutorial/body-nested-models/image01.png">

You couldn't get this kind of editor support if you were working directly with `dict` instead of Pydantic models.

But you don't have to worry about them either, incoming dicts are converted automatically and your output is converted automatically to JSON too.

## Bodies of arbitrary `dict`s

### 💯

* 1️⃣0️⃣0️⃣ 💯 <abbr title="The amount of code that is automatically tested">💯 💰</abbr>.
* 1️⃣0️⃣0️⃣ 💯 <abbr title="Python type annotations, with this your editor and external tools can give you better support">🆎 ✍</abbr> 📟 🧢.
* ⚙️ 🏭 🈸.

## 💃 ⚒

**FastAPI** 🍕 🔗 ⏮️ (&amp; ⚓️ 🔛) <a href="https://www.starlette.io/" class="external-link" target="_blank"><strong>💃</strong></a>. , 🙆 🌖 💃 📟 👆 ✔️, 🔜 👷.