{
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["query", "query"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "42.5",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

        {
            "detail": [
                {
                    "type": "float_parsing",
                    "loc": ["body", "price"],
                    "msg": "Input should be a valid number, unable to parse string as a number",
                    "input": "twenty",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

        {
            "detail": [
                {
                    "type": "float_parsing",
                    "loc": ["body", "price"],
                    "msg": "Input should be a valid number, unable to parse string as a number",
                    "input": "twenty",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

    with pytest.raises(ResponseValidationError):
        client.get("/items/invalidnone")


def test_valid_none_data():
    response = client.get("/items/validnone")
    data = response.json()
    assert response.status_code == 200
    assert data == {"name": "invalid", "price": 3.2, "owner_ids": None}


def test_valid_none_none():
    response = client.get("/items/validnone", params={"send_none": "true"})
    data = response.json()

                    "loc": ["query", "skip"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "a",
                },
                {
                    "type": "int_parsing",
                    "loc": ["query", "limit"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "b",

app = FastAPI()


@dataclass
class Item:
    name: str
    date: datetime
    price: Optional[float] = None
    owner_ids: Optional[List[int]] = None


@app.get("/items/valid", response_model=Item)
def get_valid():
    return {"name": "valid", "date": datetime(2021, 7, 26), "price": 1.0}


@app.get("/items/object", response_model=Item)
def get_object():
    return Item(

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["body", "size"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "XL",
                }
            ],
            "body": {"title": "towel", "size": "XL"},
        }
    ) | IsDict(

    )
    assert response.status_code == 400, response.text
    assert response.json() == {"detail": "X-Key header invalid"}


def test_get_valid_headers_items():
    response = client.get(
        "/items/",
        headers={
            "X-Token": "fake-super-secret-token",
            "X-Key": "fake-super-secret-key",
        },
    )

        raise fastapi.exceptions.FastAPIError(
            "Invalid args for response field! Hint: "
            f"check that {type_} is a valid Pydantic field type. "
            "If you are using a return type annotation that is not a valid Pydantic "
            "field (e.g. Union[Response, dict, None]) you can disable generating the "

    return square


@app.post("/tuple-form/")
def hello(values: Tuple[int, int] = Form()):
    return values


client = TestClient(app)


def test_model_with_tuple_valid():
    data = {"items": [["foo", "bar"], ["baz", "whatelse"]]}
    response = client.post("/model-with-tuple/", json=data)
    assert response.status_code == 200, response.text
    assert response.json() == data