from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Item = Body(
        examples=[
            {
                "name": "Foo",
                "description": "A very nice Item",

from datetime import datetime

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Subscription(BaseModel):
    username: str
    monthly_fee: float
    start_date: datetime


@app.webhooks.post("new-subscription")
def new_subscription(body: Subscription):
    """
    When a new user subscribes to your service we'll send you a POST request with this

{* ../../docs_src/python_types/tutorial010.py hl[6] *}


І знову ж таки, ви отримуєте всю підтримку редактора:

<img src="/img/python-types/image06.png">

## Pydantic моделі

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> це бібліотека Python для валідації даних.

Ви оголошуєте «форму» даних як класи з атрибутами.

І кожен атрибут має тип.

<img src="https://fastapi.tiangolo.com/img/python-types/image06.png">

## Pydantic 模型

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> 是一个用来执行数据校验的 Python 库。

你可以将数据的"结构"声明为具有属性的类。

每个属性都拥有类型。

接着你用一些值来创建这个类的实例，这些值会被校验，并被转换为适当的类型（在需要的情况下），返回一个包含所有数据的对象。

然后，你将获得这个对象的所有编辑器支持。

下面的例子来自 Pydantic 官方文档：

//// tab | Python 3.10+

```Python

Agora você sabe que, sempre que precisar delas, pode usá-las no **FastAPI**.

### Pydantic v1 `regex` em vez de `pattern` { #pydantic-v1-regex-instead-of-pattern }

Antes da versão 2 do Pydantic e antes do FastAPI 0.100.0, o parâmetro se chamava `regex` em vez de `pattern`, mas agora está descontinuado.

Você ainda pode ver algum código usando isso:

//// tab | Pydantic v1

# OpenAPI `models`

OpenAPI Pydantic models used to generate and validate the generated OpenAPI.

from typing import Union

from fastapi import FastAPI
from fastapi.responses import FileResponse
from pydantic import BaseModel


class Item(BaseModel):
    id: str
    value: str


app = FastAPI()


@app.get(
    "/items/{item_id}",
    response_model=Item,
    responses={
        200: {
            "content": {"image/png": {}},
            "description": "Return the JSON item or an image.",
        }
    },

from typing import Annotated

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


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

# Return a Response Directly { #return-a-response-directly }

When you create a **FastAPI** *path operation* you can normally return any data from it: a `dict`, a `list`, a Pydantic model, a database model, etc.

By default, **FastAPI** would automatically convert that return value to JSON using the `jsonable_encoder` explained in [JSON Compatible Encoder](../tutorial/encoder.md){.internal-link target=_blank}.

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": {