from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class BaseItem(BaseModel):
    description: str
    type: str


class CarItem(BaseItem):
    type: str = "car"


class PlaneItem(BaseItem):
    type: str = "plane"
    size: int


items = {
    "item1": {"description": "All my friends drive a low rider", "type": "car"},
    "item2": {

from typing import Annotated, Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Annotated[
        Item,
        Body(
            examples=[

{* ../../docs_src/websockets/tutorial001.py hl[2,6:38,41:43] *}

## 创建 `websocket`

在您的 **FastAPI** 应用程序中，创建一个 `websocket`：

{* ../../docs_src/websockets/tutorial001.py hl[1,46:47] *}

/// note | 技术细节

您也可以使用 `from starlette.websockets import WebSocket`。

**FastAPI** 直接提供了相同的 `WebSocket`，只是为了方便开发人员。但它直接来自 Starlette。

///

## 等待消息并发送消息

在您的 WebSocket 路由中，您可以使用 `await` 等待消息并发送消息。

from fastapi.testclient import TestClient

from docs_src.path_operation_advanced_configuration.tutorial003_py39 import app

client = TestClient(app)


def test_get():
    response = client.get("/items/")
    assert response.status_code == 200, response.text
    assert response.json() == [{"item_id": "Foo"}]


def test_openapi_schema():
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text

from typing import Annotated, Union

from fastapi import BackgroundTasks, Depends, FastAPI

app = FastAPI()


def write_log(message: str):
    with open("log.txt", mode="a") as log:
        log.write(message)


def get_query(background_tasks: BackgroundTasks, q: Union[str, None] = None):
    if q:
        message = f"found query: {q}\n"
        background_tasks.add_task(write_log, message)
    return q

from typing import Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


class User(BaseModel):
    username: str
    full_name: Union[str, None] = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,

from typing import Annotated

from fastapi import Depends, FastAPI, HTTPException

app = FastAPI()


class InternalError(Exception):
    pass


def get_username():
    try:
        yield "Rick"
    except InternalError:
        print("Oops, we didn't raise again, Britney 😱")


@app.get("/items/{item_id}")
def get_item(item_id: str, username: Annotated[str, Depends(get_username)]):
    if item_id == "portal-gun":

You can limit the lines used from the docstring of a *path operation function* for OpenAPI.

Adding an `\f` (an escaped "form feed" character) causes **FastAPI** to truncate the output used for OpenAPI at this point.

It won't show up in the documentation, but other tools (such as Sphinx) will be able to use the rest.

## Importer Path

Tout d'abord, importez `Path` de `fastapi`, et importez `Annotated` :

{* ../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py hl[1,3] *}

/// info

FastAPI a ajouté le support pour `Annotated` (et a commencé à le recommander) dans la version 0.95.0.

Primeiro, importe `Path` de `fastapi`, e importe `Annotated`:

{* ../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py hl[1,3] *}

/// info | Informação

O FastAPI adicionou suporte a `Annotated` (e passou a recomendá-lo) na versão 0.95.0.

Se você tiver uma versão mais antiga, verá erros ao tentar usar `Annotated`.