from typing import Annotated, Union

from fastapi import Cookie, Depends, FastAPI

app = FastAPI()


def query_extractor(q: Union[str, None] = None):
    return q


def query_or_cookie_extractor(
    q: Annotated[str, Depends(query_extractor)],
    last_query: Annotated[Union[str, None], Cookie()] = None,
):
    if not q:
        return last_query
    return q


@app.get("/items/")
async def read_query(

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[
        str | None,
        Query(
            title="Query string",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
        ),
    ] = None,
):

### Filtrado de Datos en FastAPI { #fastapi-data-filtering }

Ahora, para FastAPI, verá el tipo de retorno y se asegurará de que lo que devuelves incluya **solo** los campos que están declarados en el tipo.

Eine Python-Klasse ist also auch ein **Callable**.

Darum können Sie in **FastAPI** auch eine Python-Klasse als Abhängigkeit verwenden.

Was FastAPI tatsächlich prüft, ist, ob es sich um ein „Callable“ (Funktion, Klasse oder irgendetwas anderes) handelt und ob die Parameter definiert sind.

from fastapi import FastAPI, Path, Query
from fastapi.testclient import TestClient

app = FastAPI()


@app.get("/int/{param:int}")
def int_convertor(param: int = Path()):
    return {"int": param}


@app.get("/float/{param:float}")
def float_convertor(param: float = Path()):
    return {"float": param}


@app.get("/path/{param:path}")
def path_convertor(param: str = Path()):
    return {"path": param}

Isto é suportado desde a versão `0.113.0` do FastAPI. 🤓

///

## Modelos Pydantic para Formulários { #pydantic-models-for-forms }

Você precisa apenas declarar um **modelo Pydantic** com os campos que deseja receber como **campos de formulários**, e então declarar o parâmetro como um `Form`:

{* ../../docs_src/request_form_models/tutorial001_an_py39.py hl[9:11,15] *}

from fastapi import APIRouter, FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel


class ResponseModel(BaseModel):
    message: str


app = FastAPI()
router = APIRouter()


@router.get("/a", responses={501: {"description": "Error 1"}})
async def a():
    return "a"


@router.get(
    "/b",
    responses={
        502: {"description": "Error 2"},

而且有許多替代方案，所有這些都是基於 OpenAPI。你可以輕鬆地將任何這些替代方案添加到使用 **FastAPI** 建置的應用程式中。

你也可以用它自動生成程式碼，讓前端、手機應用程式或物聯網設備等與你的 API 進行通訊。

## 逐步回顧

### 第一步：引入 `FastAPI`

{* ../../docs_src/first_steps/tutorial001.py h1[1] *}

`FastAPI` 是一個 Python 類別，提供所有 API 的全部功能。

/// note | Technical Details

`FastAPI` 是一個直接繼承自 `Starlette` 的類別。

```Dockerfile
FROM python:3.7

RUN pip install fastapi uvicorn

EXPOSE 80

COPY ./app /app

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]
```

## Créer le code **FastAPI**.

* Créer un répertoire `app` et y entrer.
* Créez un fichier `main.py` avec :

```Python
from typing import Optional

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def read_root():

# Возможности { #features }

## Возможности FastAPI { #fastapi-features }

**FastAPI** предлагает вам следующее:

### Основано на открытых стандартах { #based-on-open-standards }