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