from fastapi import Depends, FastAPI

app = FastAPI()


fake_items_db = [{"item_name": "Foo"}, {"item_name": "Bar"}, {"item_name": "Baz"}]


class CommonQueryParams:
    def __init__(self, q: Union[str, None] = None, skip: int = 0, limit: int = 100):
        self.q = q
        self.skip = skip
        self.limit = limit


@app.get("/items/")

from fastapi import Depends, FastAPI

app = FastAPI()


fake_items_db = [{"item_name": "Foo"}, {"item_name": "Bar"}, {"item_name": "Baz"}]


class CommonQueryParams:
    def __init__(self, q: Union[str, None] = None, skip: int = 0, limit: int = 100):
        self.q = q
        self.skip = skip
        self.limit = limit


@app.get("/items/")

from fastapi import Depends, FastAPI

app = FastAPI()


fake_items_db = [{"item_name": "Foo"}, {"item_name": "Bar"}, {"item_name": "Baz"}]


class CommonQueryParams:
    def __init__(self, q: Union[str, None] = None, skip: int = 0, limit: int = 100):
        self.q = q
        self.skip = skip
        self.limit = limit


@app.get("/items/")
async def read_items(commons: Annotated[Any, Depends(CommonQueryParams)]):

from fastapi import FastAPI
from fastapi.testclient import TestClient

from .utils import needs_py310


@needs_py310
def test_typing():
    types = {
        list[int]: [1, 2, 3],
        dict[str, list[int]]: {"a": [1, 2, 3], "b": [4, 5, 6]},
        set[int]: [1, 2, 3],  # `set` is converted to `list`
        tuple[int, ...]: [1, 2, 3],  # `tuple` is converted to `list`
    }
    for test_type, expect in types.items():

* Если параметр объявлен как тип **модели Pydantic**, он будет интерпретирован как **тело** запроса.

/// note | Заметка

FastAPI понимает, что значение `q` не является обязательным из-за значения по умолчанию `= None`.

### `UploadFile` { #uploadfile }

`UploadFile` имеет следующие атрибуты:

* `filename`: Строка `str` с исходным именем файла, который был загружен (например, `myimage.jpg`).
* `content_type`: Строка `str` с типом содержимого (MIME type / media type) (например, `image/jpeg`).

Dazu aktualisieren wir das Pydantic-Modell `TokenData` mit einem neuen Attribut `scopes`.

Durch die Validierung der Daten mit Pydantic können wir sicherstellen, dass wir beispielsweise präzise eine `list`e von `str`s mit den Scopes und einen `str` mit dem `username` haben.

Anstelle beispielsweise eines `dict`s oder etwas anderem, was später in der Anwendung zu Fehlern führen könnte und darum ein Sicherheitsrisiko darstellt.

items = {}


@app.on_event("startup")
async def startup_event():
    items["foo"] = {"name": "Fighters"}
    items["bar"] = {"name": "Tenders"}


@app.get("/items/{item_id}")
async def read_items(item_id: str):
    return items[item_id]


def test_read_items():
    with TestClient(app) as client:
        response = client.get("/items/foo")
        assert response.status_code == 200

from typing import Annotated

from fastapi import Depends, FastAPI

app = FastAPI()


async def common_parameters(q: str | None = None, skip: int = 0, limit: int = 100):
    return {"q": q, "skip": skip, "limit": limit}


@app.get("/items/")
async def read_items(commons: Annotated[dict, Depends(common_parameters)]):
    return commons


@app.get("/users/")
async def read_users(commons: Annotated[dict, Depends(common_parameters)]):

app.mount("/static", StaticFiles(directory="static"), name="static")


templates = Jinja2Templates(directory="templates")


@app.get("/items/{id}", response_class=HTMLResponse)
async def read_item(request: Request, id: str):
    return templates.TemplateResponse(
        request=request, name="item.html", context={"id": id}