Wenn Sie mit **FastAPI** arbeiten, müssen Sie sich darüber keine Sorgen machen, da diese „erste“ Funktion Ihre *Pfadoperation-Funktion* sein wird und FastAPI weiß, was zu tun ist.

Wenn Sie jedoch `async` / `await` ohne FastAPI verwenden möchten, können Sie dies auch tun.

### Schreiben Sie Ihren eigenen asynchronen Code

from fastapi.testclient import TestClient

from docs_src.response_model.tutorial003_05 import app

client = TestClient(app)


def test_get_portal():
    response = client.get("/portal")
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "Here's your interdimensional portal."}


def test_get_redirect():
    response = client.get("/portal", params={"teleport": True}, follow_redirects=False)

import pytest
from fastapi.testclient import TestClient

from ...utils import needs_py310


@pytest.fixture(name="client")
def get_client():
    from docs_src.query_params_str_validations.tutorial014_an_py39 import app

    client = TestClient(app)
    return client


@needs_py310
def test_hidden_query(client: TestClient):
    response = client.get("/items?hidden_query=somevalue")

Örneğin `pip install python-multipart`.

///

## `Form` Sınıfını Projenize Dahil Edin

`Form` sınıfını `fastapi`'den projenize dahil edin:

//// tab | Python 3.9+

```Python hl_lines="3"
{!> ../../docs_src/request_forms/tutorial001_an_py39.py!}
```

////

//// tab | Python 3.8+

```Python hl_lines="1"

This would allow you to **re-use the model** in **multiple places** and also to declare validations and metadata for all the parameters at once. 😎

/// note

This is supported since FastAPI version `0.115.0`. 🤓

///

## Header Parameters with a Pydantic Model

Declare the **header parameters** that you need in a **Pydantic model**, and then declare the parameter as `Header`:

//// tab | Python 3.10+

---> 100%
```

</div>

Isso irá instalar todas as dependências e seu FastAPI local em seu ambiente local.

#### Usando seu FastAPI local

Se você cria um arquivo Python que importa e usa FastAPI, e roda com Python de seu ambiente local, ele irá utilizar o código fonte de seu FastAPI local.

import gzip
from typing import Callable, List

from fastapi import Body, FastAPI, Request, Response
from fastapi.routing import APIRoute


class GzipRequest(Request):
    async def body(self) -> bytes:
        if not hasattr(self, "_body"):
            body = await super().body()
            if "gzip" in self.headers.getlist("Content-Encoding"):
                body = gzip.decompress(body)
            self._body = body
        return self._body

from fastapi import FastAPI
from fastapi.routing import APIRoute
from pydantic import BaseModel


def custom_generate_unique_id(route: APIRoute):
    return f"{route.tags[0]}-{route.name}"


app = FastAPI(generate_unique_id_function=custom_generate_unique_id)


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


class User(BaseModel):
    username: str

# 子依赖项

FastAPI 支持创建含**子依赖项**的依赖项。

并且，可以按需声明任意**深度**的子依赖项嵌套层级。

**FastAPI** 负责处理解析不同深度的子依赖项。

### 第一层依赖项

下列代码创建了第一层依赖项：

```Python hl_lines="8-9"
{!../../docs_src/dependencies/tutorial005.py!}
```

这段代码声明了类型为 `str` 的可选查询参数 `q`，然后返回这个查询参数。

这个函数很简单（不过也没什么用），但却有助于让我们专注于了解子依赖项的工作方式。

### 第二层依赖项

接下来，创建另一个依赖项函数，并同时用该依赖项自身再声明一个依赖项（所以这也是一个「依赖项」）：

```Python hl_lines="13"

////

Esse código de status será usado na resposta e será adicionado ao esquema OpenAPI.

/// note | "Detalhes Técnicos"

Você também poderia usar `from starlette import status`.

**FastAPI** fornece o mesmo `starlette.status` como `fastapi.status` apenas como uma conveniência para você, o desenvolvedor. Mas vem diretamente do Starlette.

///

## Tags