///

## Tags { #tags }

Sie können Ihrer *Pfadoperation* Tags hinzufügen, indem Sie dem Parameter `tags` eine `list`e von `str`s übergeben (in der Regel nur ein `str`):

{* ../../docs_src/path_operation_configuration/tutorial002_py310.py hl[15,20,25] *}

Diese werden zum OpenAPI-Schema hinzugefügt und von den automatischen Dokumentations-Benutzeroberflächen verwendet:

///

## Tags { #tags }

You can add tags to your *path operation*, pass the parameter `tags` with a `list` of `str` (commonly just one `str`):

{* ../../docs_src/path_operation_configuration/tutorial002_py310.py hl[15,20,25] *}

They will be added to the OpenAPI schema and used by the automatic documentation interfaces:

from fastapi import FastAPI, Form
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class ItemGroup(BaseModel):
    items: list[tuple[str, str]]


class Coordinate(BaseModel):
    x: float
    y: float


@app.post("/model-with-tuple/")
def post_model_with_tuple(item_group: ItemGroup):
    return item_group


@app.post("/tuple-of-models/")

        circuitBreaker.call(() -> "success");

        SimpleCircuitBreaker.Statistics stats = circuitBreaker.getStatistics();
        String str = stats.toString();

        assertNotNull(str);
        assertTrue(str.contains("test"));
        assertTrue(str.contains("CLOSED"));
        assertTrue(str.contains("100.00%"));
    }

    @Test
    @DisplayName("Test mixed success and failure pattern")

from fastapi import FastAPI, Path

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    item_id: Annotated[int, Path(title="The ID of the item to get", gt=0, le=1000)],
    q: str,
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})

from typing import Annotated, Union

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(
    hidden_query: Annotated[Union[str, None], Query(include_in_schema=False)] = None,
):
    if hidden_query:
        return {"hidden_query": hidden_query}
    else:

* 데이터 변환
* 데이터 검증
* 자동 문서화

## 특별한 타입과 검증

`str`, `int`, `float` 등과 같은 단일 타입과는 별개로, `str`을 상속하는 더 복잡한 단일 타입을 사용할 수 있습니다.

모든 옵션을 보려면, <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic's exotic types</a> 문서를 확인하세요. 다음 장에서 몇가지 예제를 볼 수 있습니다.

예를 들어 `Image` 모델 안에 `url` 필드를 `str` 대신 Pydantic의 `HttpUrl`로 선언할 수 있습니다:

    app = FastAPI()


    def write_notification(email: str, message=""):
        with open("log.txt", mode="w") as email_file:
            content = f"notification for {email}: {message}"
            email_file.write(content)


    @app.post("/send-notification/{email}")
    async def send_notification(email: str, background_tasks: BackgroundTasks):

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(q: Annotated[str | None, Query(min_length=3)]):
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})

def get_items(item_a: str, item_b: int, item_c: float, item_d: bool, item_e: bytes):