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import abc
from collections.abc import Callable, Mapping, Sequence
from threading import Lock
from typing import (
Any,
ClassVar,
Literal,
NamedTuple,
Self,
TypeAlias,
TypedDict,
overload,
type_check_only,
)
from _typeshed import Incomplete
from typing_extensions import CapsuleType
import numpy as np
from numpy._typing import (
NDArray,
_ArrayLikeInt_co,
_DTypeLike,
_ShapeLike,
_UInt32Codes,
_UInt64Codes,
)
__all__ = ["BitGenerator", "SeedSequence"]
###
_DTypeLikeUint_: TypeAlias = _DTypeLike[np.uint32 | np.uint64] | _UInt32Codes | _UInt64Codes
@type_check_only
class _SeedSeqState(TypedDict):
entropy: int | Sequence[int] | None
spawn_key: tuple[int, ...]
pool_size: int
n_children_spawned: int
@type_check_only
class _Interface(NamedTuple):
state_address: Incomplete
state: Incomplete
next_uint64: Incomplete
next_uint32: Incomplete
next_double: Incomplete
bit_generator: Incomplete
@type_check_only
class _CythonMixin:
def __setstate_cython__(self, pyx_state: object, /) -> None: ...
def __reduce_cython__(self) -> Any: ... # noqa: ANN401
@type_check_only
class _GenerateStateMixin(_CythonMixin):
def generate_state(self, /, n_words: int, dtype: _DTypeLikeUint_ = ...) -> NDArray[np.uint32 | np.uint64]: ...
###
class ISeedSequence(abc.ABC):
@abc.abstractmethod
def generate_state(self, /, n_words: int, dtype: _DTypeLikeUint_ = ...) -> NDArray[np.uint32 | np.uint64]: ...
class ISpawnableSeedSequence(ISeedSequence, abc.ABC):
@abc.abstractmethod
def spawn(self, /, n_children: int) -> list[Self]: ...
class SeedlessSeedSequence(_GenerateStateMixin, ISpawnableSeedSequence):
def spawn(self, /, n_children: int) -> list[Self]: ...
class SeedSequence(_GenerateStateMixin, ISpawnableSeedSequence):
__pyx_vtable__: ClassVar[CapsuleType] = ...
entropy: int | Sequence[int] | None
spawn_key: tuple[int, ...]
pool_size: int
n_children_spawned: int
pool: NDArray[np.uint32]
def __init__(
self,
/,
entropy: _ArrayLikeInt_co | None = None,
*,
spawn_key: Sequence[int] = (),
pool_size: int = 4,
n_children_spawned: int = ...,
) -> None: ...
def spawn(self, /, n_children: int) -> list[Self]: ...
@property
def state(self) -> _SeedSeqState: ...
class BitGenerator(_CythonMixin, abc.ABC):
lock: Lock
@property
def state(self) -> Mapping[str, Any]: ...
@state.setter
def state(self, value: Mapping[str, Any], /) -> None: ...
@property
def seed_seq(self) -> ISeedSequence: ...
@property
def ctypes(self) -> _Interface: ...
@property
def cffi(self) -> _Interface: ...
@property
def capsule(self) -> CapsuleType: ...
#
def __init__(self, /, seed: _ArrayLikeInt_co | SeedSequence | None = None) -> None: ...
def __reduce__(self) -> tuple[Callable[[str], Self], tuple[str], tuple[Mapping[str, Any], ISeedSequence]]: ...
def spawn(self, /, n_children: int) -> list[Self]: ...
def _benchmark(self, /, cnt: int, method: str = "uint64") -> None: ...
#
@overload
def random_raw(self, /, size: None = None, output: Literal[True] = True) -> int: ...
@overload
def random_raw(self, /, size: _ShapeLike, output: Literal[True] = True) -> NDArray[np.uint64]: ...
@overload
def random_raw(self, /, size: _ShapeLike | None, output: Literal[False]) -> None: ...
@overload
def random_raw(self, /, size: _ShapeLike | None = None, *, output: Literal[False]) -> None: ...
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