sequence_annotation_to_type = {
    Sequence: list,
    list: list,
    tuple: tuple,
    set: set,
    frozenset: frozenset,
    deque: deque,
}

sequence_types = tuple(sequence_annotation_to_type.keys())

Url: type[Any]


# Copy of Pydantic v2, compatible with v1
def lenient_issubclass(
    cls: Any, class_or_tuple: Union[type[Any], tuple[type[Any], ...], None]
) -> bool:
    try:

    return named_session, session


BrokenSessionsDep = Annotated[
    tuple[NamedSession, Session], Depends(get_named_func_session)
]
NamedSessionsFuncDep = Annotated[
    tuple[NamedSession, Session], Depends(get_named_func_session, scope="function")
]

RegularSessionsDep = Annotated[
    tuple[NamedSession, Session], Depends(get_named_regular_func_session)
]

app = FastAPI()

    return named_session, session


BrokenSessionsDep = Annotated[
    tuple[NamedSession, Session], Depends(get_named_func_session)
]
NamedSessionsFuncDep = Annotated[
    tuple[NamedSession, Session], Depends(get_named_func_session, scope="function")
]

RegularSessionsDep = Annotated[
    tuple[NamedSession, Session], Depends(get_named_regular_func_session)
]

app = FastAPI()
router = APIRouter()

def post_form_param_list(items: list = Form()):
    return items


@app.post("/form/python-set")
def post_form_param_set(items: set = Form()):
    return items


@app.post("/form/python-tuple")
def post_form_param_tuple(items: tuple = Form()):
    return items


client = TestClient(app)


def test_python_list_param_as_form():
    response = client.post(

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/")
def post_tuple_of_models(square: tuple[Coordinate, Coordinate]):
    return square


@app.post("/tuple-form/")

def _remap_definitions_and_field_mappings(
    *,
    model_name_map: ModelNameMap,
    definitions: dict[str, Any],
    field_mapping: dict[
        tuple[ModelField, Literal["validation", "serialization"]], JsonSchemaValue
    ],
) -> tuple[
    dict[tuple[ModelField, Literal["validation", "serialization"]], JsonSchemaValue],
    dict[str, Any],
]:
    old_name_to_new_name_map = {}

UnionType = getattr(types, "UnionType", Union)
ModelNameMap = dict[Union[type[BaseModel], type[Enum]], str]
IncEx = Union[set[int], set[str], dict[int, Any], dict[str, Any]]

@needs_py310
def test_typing():
    types = {
        list[int]: [1, 2, 3],
        dict[str, list[int]]: {"a": [1, 2, 3], "b": [4, 5, 6]},
        set[int]: [1, 2, 3],  # `set` is converted to `list`
        tuple[int, ...]: [1, 2, 3],  # `tuple` is converted to `list`
    }
    for test_type, expect in types.items():
        app = FastAPI()

        @app.post("/", response_model=test_type)
        def post_endpoint(input: test_type):

E, ainda assim, o editor sabe que é um `str` e fornece suporte para isso.

#### Tuple e Set { #tuple-and-set }

Você faria o mesmo para declarar `tuple`s e `set`s:

{* ../../docs_src/python_types/tutorial007_py39.py hl[1] *}

Isso significa que:

* A variável `items_t` é uma `tuple` com 3 itens, um `int`, outro `int` e uma `str`.

Y aún así, el editor sabe que es un `str` y proporciona soporte para eso.

#### Tuple y Set { #tuple-and-set }

Harías lo mismo para declarar `tuple`s y `set`s:

{* ../../docs_src/python_types/tutorial007_py39.py hl[1] *}

Esto significa:

* La variable `items_t` es un `tuple` con 3 ítems, un `int`, otro `int`, y un `str`.