"schema": {
                                        "title": "Response 500 Valid2 Valid2 Get",
                                        "type": "array",
                                        "items": {"type": "integer"},
                                    }
                                }
                            },
                        },
                    },
                }
            },

                        "properties": {
                            "loc": {
                                "title": "Location",
                                "type": "array",
                                "items": {
                                    "anyOf": [{"type": "string"}, {"type": "integer"}]
                                },
                            },

    name: str
    description: str | None = None
    price: float
    tax: float | None = None


class User(BaseModel):
    username: str
    full_name: str | None = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Item,
    user: User,
    importance: Annotated[int, Body(gt=0)],
    q: str | None = None,
):

                                        <td><c:forEach var="rt" varStatus="s"
                                                       items="${roleItems}">
                                            <c:forEach var="rtid" varStatus="s" items="${roles}">
                                                <c:if test="${rtid==rt.id}">
                                                    ${f:h(rt.name)}<br/>

And Python has a special data type for sets of unique items, the `set`.

Then we can declare `tags` as a set of strings:

{* ../../docs_src/body_nested_models/tutorial003_py310.py hl[12] *}

With this, even if you receive a request with duplicate data, it will be converted to a set of unique items.

And whenever you output that data, even if the source had duplicates, it will be output as a set of unique items.

) -> dict[Callable[[Any], Any], tuple[Any, ...]]:
    encoders_by_class_tuples: dict[Callable[[Any], Any], tuple[Any, ...]] = defaultdict(
        tuple
    )
    for type_, encoder in type_encoder_map.items():
        encoders_by_class_tuples[encoder] += (type_,)
    return encoders_by_class_tuples


encoders_by_class_tuples = generate_encoders_by_class_tuples(ENCODERS_BY_TYPE)


def jsonable_encoder(

    openapi = app.openapi()
    body_model_name = get_body_model_name(openapi, path)

    assert app.openapi()["components"]["schemas"][body_model_name] == {
        "properties": {
            "p": {
                "items": {"type": "string"},
                "title": "P",
                "type": "array",
            },
        },
        "required": ["p"],
        "title": body_model_name,
        "type": "object",
    }

        path: Annotated[
            str,
            Doc(
                """
                The URL path to be used for this *path operation*.

                For example, in `http://example.com/items`, the path is `/items`.
                """
            ),
        ],
        *,
        response_model: Annotated[
            Any,
            Doc(
                """

from pydantic import BaseModel

app = FastAPI()


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


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int = Path(title="The ID of the item to get", ge=0, le=1000),
    q: Union[str, None] = None,
    item: Union[Item, None] = None,
):

        raise HTTPException(status_code=400, detail="X-Key header invalid")
    return x_key


app = FastAPI(dependencies=[Depends(verify_token), Depends(verify_key)])


@app.get("/items/")
async def read_items():
    return [{"item": "Portal Gun"}, {"item": "Plumbus"}]


@app.get("/users/")
async def read_users():