@pytest.mark.parametrize(
    "path,headers,expected_status,expected_response",
    [
        ("/items", None, 200, {"X-Token values": None}),
        ("/items", {"x-token": "foo"}, 200, {"X-Token values": ["foo"]}),
        (
            "/items",
            [("x-token", "foo"), ("x-token", "bar")],
            200,
            {"X-Token values": ["foo", "bar"]},
        ),
    ],
)
def test(path, headers, expected_status, expected_response):

        Doc(
            """
            Default value if the parameter field is not set.
            """
        ),
    ] = Undefined,
    *,
    default_factory: Annotated[
        Union[Callable[[], Any], None],
        Doc(
            """
            A callable to generate the default value.

            This doesn't affect `Path` parameters as the value is always required.

def deep_dict_update(main_dict: Dict[Any, Any], update_dict: Dict[Any, Any]) -> None:
    for key, value in update_dict.items():
        if (
            key in main_dict
            and isinstance(main_dict[key], dict)
            and isinstance(value, dict)
        ):
            deep_dict_update(main_dict[key], value)
        elif (
            key in main_dict
            and isinstance(main_dict[key], list)

                have their default values. This is different from
                `response_model_exclude_defaults` in that if the fields are set,
                they will be included in the response, even if the value is the same
                as the default.

                When `True`, default values are omitted from the response.

                Read more about it in the

                    async_exit_stack=async_exit_stack,
                )
                values, errors, background_tasks, sub_response, _ = solved_result
                if not errors:
                    raw_response = await run_endpoint_function(
                        dependant=dependant, values=values, is_coroutine=is_coroutine
                    )
                    if isinstance(raw_response, Response):

    >>> decimal_encoder(Decimal("1.0"))
    1.0

    >>> decimal_encoder(Decimal("1"))
    1
    """
    if dec_value.as_tuple().exponent >= 0:  # type: ignore[operator]
        return int(dec_value)
    else:
        return float(dec_value)


ENCODERS_BY_TYPE: Dict[Type[Any], Callable[[Any], Any]] = {
    bytes: lambda o: o.decode(),
    Color: str,
    datetime.date: isoformat,

    return _annotation_is_sequence(annotation) or _annotation_is_sequence(
        get_origin(annotation)
    )


def value_is_sequence(value: Any) -> bool:
    return isinstance(value, sequence_types) and not isinstance(value, (str, bytes))  # type: ignore[arg-type]


def _annotation_is_complex(annotation: Union[Type[Any], None]) -> bool:
    return (