## Instale o FastAPI

O primeiro passo é instalar o FastAPI.

Para o tutorial, você deve querer instalá-lo com todas as dependências e recursos opicionais.

<div class="termy">

```console
$ pip install "fastapi[all]"

---> 100%
```

</div>

...isso também inclui o `uvicorn`, que você pode usar como o servidor que rodará seu código.

!!! note "Nota"
    Você também pode instalar parte por parte.

        Union[str, None],
        Doc(
            """
            'Blacklist' validation step. The vanilla parameter field will be the
            single one of the alias' or set of aliases' fields and all the other
            fields will be ignored at serialization time.
            """
        ),
    ] = None,
    title: Annotated[
        Optional[str],
        Doc(
            """

@needs_py310
def test_get_car(client: TestClient):
    response = client.get("/items/item1")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "description": "All my friends drive a low rider",
        "type": "car",
    }


@needs_py310
def test_get_plane(client: TestClient):
    response = client.get("/items/item2")
    assert response.status_code == 200, response.text

!!! note "Technical Details"
    If you have dependencies with `yield`, the exit code will run *after* the middleware.

    If there were any background tasks (documented later), they will run *after* all the middleware.

## Create a middleware

To create a middleware you use the decorator `@app.middleware("http")` on top of a function.

The middleware function receives:

* The `request`.

---

## FastAPI 설치

첫 번째 단계는 FastAPI를 설치하는 것입니다.

자습시에는 모든 선택적인 의존성 및 기능을 함께 설치하는 것을 추천합니다:

<div class="termy">

```console
$ pip install "fastapi[all]"

---> 100%
```

</div>

...이는 코드를 실행하는 서버로 사용할 수 있는 `uvicorn` 또한 포함하고 있습니다.

!!! note "참고"
    부분적으로 설치할 수도 있습니다.

    애플리케이션을 운영 환경에 배포하려는 경우 다음과 같이 합니다:

    ```

The same way, there are many compatible tools. Including code generation tools for many languages.

## Pydantic

All the data validation is performed under the hood by <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>, so you get all the benefits from it. And you know you are in good hands.

You can use the same type declarations with `str`, `float`, `bool` and many other complex data types.

Just keep in mind that when you read "server" in general, it could refer to one of those two things.

When referring to the remote machine, it's common to call it **server**, but also **machine**, **VM** (virtual machine), **node**. Those all refer to some type of remote machine, normally running Linux, where you run programs.

## Install the Server Program

![ReDoc](https://fastapi.tiangolo.com/img/index/index-02-redoc-simple.png)

### OpenAPI

**FastAPI** generiert ein „Schema“ mit all Ihren APIs unter Verwendung des **OpenAPI**-Standards zur Definition von APIs.

#### „Schema“

ItemsService.createItemItemsPost({name: "Plumbus", price: 5})
```

...that's because the client generator uses the OpenAPI internal **operation ID** for each *path operation*.

OpenAPI requires that each operation ID is unique across all the *path operations*, so FastAPI uses the **function name**, the **path**, and the **HTTP method/operation** to generate that operation ID, because that way it can make sure that the operation IDs are unique.

If you need or want to work with **GraphQL**, <a href="https://strawberry.rocks/" class="external-link" target="_blank">**Strawberry**</a> is the **recommended** library as it has the design closest to **FastAPI's** design, it's all based on **type annotations**.

Depending on your use case, you might prefer to use a different library, but if you asked me, I would probably suggest you try **Strawberry**.