How to use the typing.Type function in typing

) -> BeaconState:
        eth1_block_hash, eth1_timestamp, deposits = inputs

        return initialize_beacon_state_from_eth1(
            eth1_block_hash=eth1_block_hash,
            eth1_timestamp=eth1_timestamp,
            deposits=deposits,
            config=config,
        )

    @staticmethod
    def condition(output: BeaconState, expected_output: BeaconState) -> None:
        validate_state(output, expected_output)


GenesisHandlerType = Tuple[Type[ValidityHandler], Type[InitializationHandler]]


class GenesisTestType(TestType[GenesisHandlerType]):
    name = "genesis"

    handlers = (ValidityHandler, InitializationHandler)

:param log_result_obj: log result of function call.
        :type log_result_obj: bool

        .. versionchanged:: 3.3.0 Extract func from log and do not use Union.
        .. versionchanged:: 5.1.0 log_traceback parameter
        .. versionchanged:: 8.0.0 pick up logger from target module if possible
        """
        super().__init__(func=func)

        # Typing fix:
        if blacklisted_names is None:
            self.__blacklisted_names: typing.List[str] = []
        else:
            self.__blacklisted_names = list(blacklisted_names)
        if blacklisted_exceptions is None:
            self.__blacklisted_exceptions: typing.List[typing.Type[Exception]] = []
        else:
            self.__blacklisted_exceptions = list(blacklisted_exceptions)

        if isinstance(log, logging.Logger):
            self.__logger: typing.Optional[logging.Logger] = log
        else:
            self.__logger = None

        if func is not None:  # Special case: we can prefetch logger
            self.__logger = self._get_logger_for_func(func)

        self.__log_level: int = log_level
        self.__exc_level: int = exc_level
        self.__max_indent: int = max_indent
        self.__spec: typing.Optional[typing.Callable[..., FuncResultType]] = spec or self._func  # type: ignore
        self.__log_call_args: bool = log_call_args

def factory() -> SiteManagement:
        if cmk_version.is_raw_edition():
            cls: Type[SiteManagement] = CRESiteManagement
        else:
            cls = CEESiteManagement

        return cls()

pass


class InvalidCredentialsError(EufySecurityError):
    """Define an error for unauthenticated accounts."""

    pass


class RequestError(EufySecurityError):
    """Define an error related to invalid requests."""

    pass


ERRORS: Dict[int, Type[EufySecurityError]] = {26006: InvalidCredentialsError}


def raise_error(data: dict) -> None:
    """Raise the appropriate error based upon a response code."""
    cls = ERRORS.get(data["code"], EufySecurityError)
    raise cls(data["msg"])

def penalize_queen(self, peer: ETHPeer) -> None:
        ...


class BeamStateBackfill(BaseService, PeerSubscriber, QueenTrackerAPI):
    """
    Use a very simple strategy to fill in state in the background.

    Ask each peer in sequence for some nodes, ignoring the lowest RTT node.
    Reduce memory pressure by using a depth-first strategy.

    An intended side-effect is to build & maintain an accurate measurement of
    the round-trip-time that peers take to respond to GetNodeData commands.
    """
    # We are only interested in peers entering or leaving the pool
    subscription_msg_types: FrozenSet[Type[CommandAPI[Any]]] = frozenset()

    # This is a rather arbitrary value, but when the sync is operating normally we never see
    # the msg queue grow past a few hundred items, so this should be a reasonable limit for
    # now.
    msg_queue_maxsize: int = 2000

    _total_processed_nodes = 0
    _num_added = 0
    _num_missed = 0
    _report_interval = 10

    _num_requests_by_peer: typing.Counter[ETHPeer]

    def __init__(
            self,
            db: AtomicDatabaseAPI,

...

    @abstractmethod
    def record_response(self,
                        elapsed: float,
                        request: TRequestCommand,
                        result: TResult) -> None:
        ...


class ResponseCandidateStreamAPI(AsyncioServiceAPI, Generic[TRequestCommand, TResponseCommand]):
    response_timeout: float

    pending_request: Optional[Tuple[float, 'asyncio.Future[TResponseCommand]']]

    request_protocol_type: Type[ProtocolAPI]
    response_cmd_type: Type[TResponseCommand]

    last_response_time: float

    @abstractmethod
    def __init__(
            self,
            connection: ConnectionAPI,
            request_protocol_type: Type[ProtocolAPI],
            response_cmd_type: Type[TResponseCommand]) -> None:
        ...

    @abstractmethod
    def payload_candidates(
            self,
            request: TRequestCommand,

from typing import Type

from .assets.numba_kernels import gpu_datatile
from .charts.core.core_chart import BaseChart


class DataTile:
    dtype: str = "pandas"
    cumsum: bool = True
    dimensions: int = 2
    active_chart: Type[BaseChart] = None
    passive_chart: Type[BaseChart] = None

    def __init__(
        self,
        active_chart: Type[BaseChart],
        passive_chart: Type[BaseChart],
        dtype: str = "pandas",
        dimensions: int = 2,
        cumsum: bool = True,
    ):
        """
        init function
        """
        self.dtype = dtype
        self.dimensions = dimensions
        self.active_chart = active_chart

def make_interval_emitter(
        center_xy: Point,
        filenames_and_textures: Sequence[FilenameOrTexture],
        emit_interval: float,
        emit_duration: float,
        particle_speed: float,
        particle_lifetime_min: float,
        particle_lifetime_max: float,
        particle_scale: float = 1.0,
        fade_particles: bool = True):
    """Returns an emitter that emits its particles at a constant rate for a given amount of time"""
    particle_factory: Type[arcade.LifetimeParticle] = arcade.LifetimeParticle
    if fade_particles:
        particle_factory = arcade.FadeParticle
    return arcade.Emitter(
        center_xy=center_xy,
        emit_controller=arcade.EmitterIntervalWithTime(emit_interval, emit_duration),
        particle_factory=lambda emitter: particle_factory(
            filename_or_texture=random.choice(filenames_and_textures),
            change_xy=arcade.rand_on_circle((0.0, 0.0), particle_speed),
            lifetime=random.uniform(particle_lifetime_min, particle_lifetime_max),
            scale=particle_scale
        )

async def get_remote_auras(
        self, aura_groups: WeakAuras
    ) -> Tuple[Type[WeakAuras], List[RemoteAura]]:
        if not aura_groups.entries:
            return (aura_groups.__class__, [])

        metadata = await self.get_wago_metadata(aura_groups)
        import_strings = await gather((self.get_wago_import_string(m.id) for m in metadata), False)
        return (
            aura_groups.__class__,
            list(zip(aura_groups.entries.values(), metadata, import_strings)),
        )

ScheduleType,
    SliceEmailSchedule,
)
from superset.models.slice import Slice
from superset.tasks.schedules import schedule_email_report
from superset.utils.core import get_email_address_list, json_iso_dttm_ser
from superset.views.core import json_success

from .base import DeleteMixin, SupersetModelView


class EmailScheduleView(
    SupersetModelView, DeleteMixin
):  # pylint: disable=too-many-ancestors
    _extra_data = {"test_email": False, "test_email_recipients": None}
    schedule_type: Optional[Type] = None
    schedule_type_model: Optional[Type] = None

    page_size = 20

    add_exclude_columns = [
        "user",
        "created_on",
        "changed_on",
        "created_by",
        "changed_by",
    ]

    edit_exclude_columns = add_exclude_columns

    description_columns = {
        "deliver_as_group": "If enabled, send a single email to all "