from fastapi import Cookie, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Cookies(BaseModel):
    model_config = {"extra": "forbid"}

    session_id: str
    fatebook_tracker: str | None = None
    googall_tracker: str | None = None


@app.get("/items/")
async def read_items(cookies: Cookies = Cookie()):

### Eine `Enum`-Klasse erstellen { #create-an-enum-class }

Importieren Sie `Enum` und erstellen Sie eine Unterklasse, die von `str` und `Enum` erbt.

Indem Sie von `str` erben, weiß die API-Dokumentation, dass die Werte vom Typ `str` sein müssen, und wird in der Lage sein, korrekt zu rendern.

Erstellen Sie dann Klassen-Attribute mit festgelegten Werten, welches die erlaubten Werte sein werden:

from fastapi import Depends, FastAPI, Header, HTTPException


async def verify_token(x_token: str = Header()):
    if x_token != "fake-super-secret-token":
        raise HTTPException(status_code=400, detail="X-Token header invalid")


async def verify_key(x_key: str = Header()):
    if x_key != "fake-super-secret-key":
        raise HTTPException(status_code=400, detail="X-Key header invalid")
    return x_key

from typing import Annotated

from fastapi import Cookie, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Cookies(BaseModel):
    session_id: str
    fatebook_tracker: str | None = None
    googall_tracker: str | None = None


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

from fastapi import FastAPI, Form
from pydantic import BaseModel

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str
    model_config = {"extra": "forbid"}


@app.post("/login/")
async def login(data: FormData = Form()):

from fastapi import FastAPI
from pydantic.v1 import BaseModel


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


app = FastAPI()


@app.post("/items/")
async def create_item(item: Item) -> Item:

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.post("/items/", summary="Create an item")
async def create_item(item: Item) -> Item:
    """
    Create an item with all the information:

    - **name**: each item must have a name

In this example, it would convert the Pydantic model to a `dict`, and the `datetime` to a `str`.

The result of calling it is something that can be encoded with the Python standard [`json.dumps()`](https://docs.python.org/3/library/json.html#json.dumps).

Por ejemplo, podrías declarar que algo podría ser un `str` o `None`:

```python
from typing import Union


def say_hi(name: Union[str, None]):
        print(f"Hi {name}!")
```

`typing` también tiene un atajo para declarar que algo podría ser `None`, con `Optional`.

For example, you could declare that something could be a `str` or `None`:

```python
from typing import Union


def say_hi(name: Union[str, None]):
        print(f"Hi {name}!")
```

`typing` also has a shortcut to declare that something could be `None`, with `Optional`.