from fastapi import FastAPI
from fastapi.responses import ORJSONResponse

app = FastAPI()


@app.get("/items/", response_class=ORJSONResponse)
async def read_items():

from typing import Union

from fastapi import Depends, FastAPI
from fastapi.security import OAuth2PasswordBearer
from pydantic import BaseModel

app = FastAPI()

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")


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


def fake_decode_token(token):
    return User(

import secrets

from fastapi import Depends, FastAPI, HTTPException, status
from fastapi.security import HTTPBasic, HTTPBasicCredentials

app = FastAPI()

security = HTTPBasic()


def get_current_username(credentials: HTTPBasicCredentials = Depends(security)):
    current_username_bytes = credentials.username.encode("utf8")
    correct_username_bytes = b"stanleyjobson"
    is_correct_username = secrets.compare_digest(

### Фільтрація даних у FastAPI

Тепер для FastAPI він бачить тип повернення і переконується, що те, що Ви повертаєте, містить **тільки** поля, які оголошені у цьому типі.

Por exemplo, nós, a equipe por trás do FastAPI, criamos <a href="https://fastapicloud.com" class="external-link" target="_blank">**FastAPI Cloud**</a>, para tornar a implantação de aplicações FastAPI na nuvem o mais simples possível, com a mesma experiência de desenvolvimento de trabalhar com o FastAPI.

It will install all the dependencies and your local FastAPI in your local environment.

### Using your local FastAPI

If you create a Python file that imports and uses FastAPI, and run it with the Python from your local environment, it will use your cloned local FastAPI source code.

And if you update that local FastAPI source code when you run that Python file again, it will use the fresh version of FastAPI you just edited.

from fastapi import FastAPI

app = FastAPI()


@app.get("/app")
def read_main():
    return {"message": "Hello World from main app"}


subapi = FastAPI()


@subapi.get("/sub")
def read_sub():
    return {"message": "Hello World from sub API"}

///

**FastAPI** 将自动对请求中的数据进行转换，因此 `item` 参数将接收指定的内容，`user` 参数也是如此。

它将执行对复合数据的校验，并且像现在这样为 OpenAPI 模式和自动化文档对其进行记录。

## 请求体中的单一值

与使用 `Query` 和 `Path` 为查询参数和路径参数定义额外数据的方式相同，**FastAPI** 提供了一个同等的 `Body`。

例如，为了扩展先前的模型，你可能决定除了 `item` 和 `user` 之外，还想在同一请求体中具有另一个键 `importance`。

如果你就按原样声明它，因为它是一个单一值，**FastAPI** 将假定它是一个查询参数。

但是你可以使用 `Body` 指示 **FastAPI** 将其作为请求体的另一个键进行处理。

from typing import Annotated

from fastapi import Depends, FastAPI
from fastapi.security import HTTPBasic, HTTPBasicCredentials

app = FastAPI()

security = HTTPBasic()


@app.get("/users/me")
def read_current_user(credentials: Annotated[HTTPBasicCredentials, Depends(security)]):

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

app = FastAPI()


class Item(BaseModel):
    name: str | None = None
    description: str | None = None
    price: float | None = None
    tax: float = 10.5
    tags: list[str] = []


items = {
    "foo": {"name": "Foo", "price": 50.2},
    "bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},