from typing import Annotated


def say_hello(name: Annotated[str, "this is just metadata"]) -> str:

from fastapi import FastAPI, Response

app = FastAPI()


@app.get("/headers-and-object/")
def get_headers(response: Response):
    response.headers["X-Cat-Dog"] = "alone in the world"

from fastapi import FastAPI

app = FastAPI()


@app.get("/items/{item_id}")
async def read_item(item_id: str, q: str | None = None):
    if q:
        return {"item_id": item_id, "q": q}

from fastapi import FastAPI, Form
from pydantic import BaseModel

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str


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

from pydantic import BaseModel


def forwardref_method(input: "ForwardRefModel") -> "ForwardRefModel":
    return ForwardRefModel(x=input.x + 1)


class ForwardRefModel(BaseModel):

In diesem Fall können Sie die Generierung des Responsemodells abschalten, indem Sie `response_model=None` setzen:

{* ../../docs_src/response_model/tutorial003_05_py310.py hl[7] *}

Das bewirkt, dass FastAPI die Generierung des Responsemodells unterlässt, und damit können Sie jede gewünschte Rückgabetyp-Annotation haben, ohne dass es Ihre FastAPI-Anwendung beeinflusst. 🤓

from typing import Union

from fastapi import FastAPI, Header

app = FastAPI()


@app.get("/items/")
async def read_items(x_token: Union[list[str], None] = Header(default=None)):

from fastapi import FastAPI
from fastapi.responses import ORJSONResponse

app = FastAPI(default_response_class=ORJSONResponse)


@app.get("/items/")
async def read_items():

from fastapi import FastAPI

app = FastAPI()


@app.get("/items/", openapi_extra={"x-aperture-labs-portal": "blue"})
async def read_items():

from typing import Annotated, Union

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(q: Annotated[Union[list[str], None], Query()] = None):
    query_items = {"q": q}