from typing import Union

from fastapi import FastAPI, Header, HTTPException
from pydantic import BaseModel

fake_secret_token = "coneofsilence"

fake_db = {
    "foo": {"id": "foo", "title": "Foo", "description": "There goes my hero"},
    "bar": {"id": "bar", "title": "Bar", "description": "The bartenders"},
}

app = FastAPI()


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

And then we validate that data with the Pydantic model (catching the `ValidationError` exception), and if we get an error reading the JWT token or validating the data with Pydantic, we raise the `HTTPException` we created before.

For that, we update the Pydantic model `TokenData` with a new property `scopes`.

///

## Что используется в **FastAPI** { #used-by-fastapi }

### <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> { #pydantic }

Pydantic — это библиотека для определения валидации данных, сериализации и документации (с использованием JSON Schema) на основе аннотаций типов Python.

Благодаря этому он чрезвычайно интуитивен.

from typing import Annotated, Union

from fastapi import Cookie, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Cookies(BaseModel):
    session_id: str
    fatebook_tracker: Union[str, None] = None
    googall_tracker: Union[str, None] = None


@app.get("/items/")
async def read_items(cookies: Annotated[Cookies, Cookie()]):

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str


items = [
    {"name": "Foo", "description": "There comes my hero"},
    {"name": "Red", "description": "It's my aeroplane"},
]


@app.get("/items/", response_model=list[Item])
async def read_items():

Si quieres asegurar tu API, hay varias cosas mejores que puedes hacer, por ejemplo:

* Asegúrate de tener modelos Pydantic bien definidos para tus request bodies y responses.
* Configura los permisos y roles necesarios usando dependencias.
* Nunca guardes contraseñas en texto plano, solo hashes de contraseñas.

from datetime import datetime

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

fake_db = {}


class Item(BaseModel):
    title: str
    timestamp: datetime
    description: str | None = None


app = FastAPI()


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

from typing import Annotated, Union

from fastapi import FastAPI, Header, HTTPException
from pydantic import BaseModel

fake_secret_token = "coneofsilence"

fake_db = {
    "foo": {"id": "foo", "title": "Foo", "description": "There goes my hero"},
    "bar": {"id": "bar", "title": "Bar", "description": "The bartenders"},
}

app = FastAPI()


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

每个响应字典都可以有一个关键模型，其中包含一个 `Pydantic` 模型，就像 `response_model` 一样。

**FastAPI**将采用该模型，生成其`JSON Schema`并将其包含在`OpenAPI`中的正确位置。

例如，要声明另一个具有状态码 `404` 和`Pydantic`模型 `Message` 的响应，可以写：
{* ../../docs_src/additional_responses/tutorial001.py hl[18,22] *}

/// note

请记住，您必须直接返回 `JSONResponse` 。

///

/// info

`model` 密钥不是OpenAPI的一部分。
**FastAPI**将从那里获取`Pydantic`模型，生成` JSON Schema` ，并将其放在正确的位置。
- 正确的位置是：

from typing import Annotated, Union

from fastapi import FastAPI
from fastapi.temp_pydantic_v1_params import Body
from pydantic.v1 import BaseModel


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


app = FastAPI()


@app.post("/items/")
async def create_item(item: Annotated[Item, Body(embed=True)]) -> Item: