from datetime import datetime
from typing import Union

from fastapi import FastAPI
from fastapi.encoders import jsonable_encoder
from fastapi.responses import JSONResponse
from pydantic import BaseModel


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: Union[str, None] = None


app = FastAPI()


@app.put("/items/{id}")
def update_item(id: str, item: Item):

from fastapi import Cookie, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Cookies(BaseModel):
    model_config = {"extra": "forbid"}

    session_id: str
    fatebook_tracker: str | None = None
    googall_tracker: str | None = None


@app.get("/items/")
async def read_items(cookies: Cookies = Cookie()):

from fastapi import FastAPI, Path

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(*, item_id: int = Path(title="The ID of the item to get"), q: str):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

Vous pourriez aussi l'utiliser pour générer du code automatiquement, pour les clients qui communiquent avec votre API. Comme par exemple, des applications frontend, mobiles ou IOT.

## Récapitulatif, étape par étape

### Étape 1 : import `FastAPI`

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

Wenn Sie die `async`-Methoden verwenden, führt **FastAPI** die Datei-Methoden in einem <abbr title="Mehrere unabhängige Kindprozesse">Threadpool</abbr> aus und erwartet sie.

///

/// note | Technische Details zu Starlette

**FastAPI**s `UploadFile` erbt direkt von **Starlette**s `UploadFile`, fügt aber ein paar notwendige Teile hinzu, um es kompatibel mit **Pydantic** und anderen Teilen von FastAPI zu machen.

///

Você pode iniciar vários trabalhadores com a opção de linha de comando `--workers`:

//// tab | `fastapi`

Se você usar o comando `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

  <span style="background-color:#009485"><font color="#D3D7CF"> FastAPI </font></span>  Starting production server 🚀

Они полезны главным образом, если у вас было приложение FastAPI версии ниже 0.121.0 и вы столкнулись с проблемами зависимостей с `yield`.

///

Зависимости с `yield` со временем изменялись, чтобы учитывать разные случаи применения и исправлять проблемы. Ниже — краткое резюме изменений.

### Зависимости с `yield` и `scope` { #dependencies-with-yield-and-scope }

from fastapi import FastAPI, UploadFile
from fastapi._compat import (
    Undefined,
    is_uploadfile_sequence_annotation,
)
from fastapi._compat.shared import is_bytes_sequence_annotation
from fastapi.testclient import TestClient
from pydantic import BaseModel, ConfigDict
from pydantic.fields import FieldInfo

from .utils import needs_py310


def test_model_field_default_required():
    from fastapi._compat import v2

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: str | None = Query(
        default=None, min_length=3, max_length=50, pattern="^fixedquery$"
    ),
):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

from functools import lru_cache

from fastapi import Depends, FastAPI

from .config import Settings

app = FastAPI()


@lru_cache
def get_settings():
    return Settings()


@app.get("/info")
async def info(settings: Settings = Depends(get_settings)):
    return {
        "app_name": settings.app_name,
        "admin_email": settings.admin_email,
        "items_per_user": settings.items_per_user,