Bevorzugen Sie die `Annotated`-Version, falls möglich.

///

```Python hl_lines="10"
{!> ../../docs_src/dependencies/tutorial011.py!}
```

////

In diesem Fall ist dieses `__call__` das, was **FastAPI** verwendet, um nach zusätzlichen Parametern und Unterabhängigkeiten zu suchen, und das ist es auch, was später aufgerufen wird, um einen Wert an den Parameter in Ihrer *Pfadoperation-Funktion* zu übergeben.

from typing import Annotated, Union

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    q: Annotated[
        Union[str, None],
        Query(
            alias="item-query",
            title="Query string",
            description="Query string for the items to search in the database that have a good match",
            min_length=3,
            max_length=50,

from typing import Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


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


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


@app.put("/items/{item_id}")

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: 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=Depends(CommonQueryParams)):
    response = {}
    if commons.q:

from datetime import datetime, time, timedelta
from typing import Annotated
from uuid import UUID

from fastapi import Body, FastAPI

app = FastAPI()


@app.put("/items/{item_id}")
async def read_items(
    item_id: UUID,
    start_datetime: Annotated[datetime, Body()],
    end_datetime: Annotated[datetime, Body()],
    process_after: Annotated[timedelta, Body()],
    repeat_at: Annotated[time | None, Body()] = None,
):

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.post(
    "/items/",
    response_model=Item,
    summary="Create an item",

///

## Type hints in **FastAPI**

**FastAPI** takes advantage of these type hints to do several things.

With **FastAPI** you declare parameters with type hints and you get:

* **Editor support**.
* **Type checks**.

...and **FastAPI** uses the same declarations to:

## Metadata for API

You can set the following fields that are used in the OpenAPI specification and the automatic API docs UIs:

| Parameter | Type | Description |
|------------|------|-------------|
| `title` | `str` | The title of the API. |
| `summary` | `str` | A short summary of the API. <small>Available since OpenAPI 3.1.0, FastAPI 0.99.0.</small> |

        ("/items", {"X-Header": "notvalid"}, 200, {"User-Agent": "testclient"}),
        ("/items", {"User-Agent": "FastAPI test"}, 200, {"User-Agent": "FastAPI test"}),
    ],
)
def test(path, headers, expected_status, expected_response, client: TestClient):
    response = client.get(path, headers=headers)
    assert response.status_code == expected_status
    assert response.json() == expected_response


@needs_py310

<img src="/img/tutorial/response-status-code/image02.png">

/// note | "Technische Details"

Sie können auch `from starlette import status` verwenden.

**FastAPI** bietet dieselben `starlette.status`-Codes auch via `fastapi.status` an, als Annehmlichkeit für Sie, den Entwickler. Sie kommen aber direkt von Starlette.

///

## Den Defaultwert ändern