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from typing import Any, TypeVar, Type, overload, Optional, Genericimport ctypes as ct
from numpy import ndarray
_CastT = TypeVar("_CastT", bound=ct._CanCastTo) # Copied from `ctypes.cast`_CT = TypeVar("_CT", bound=ct._CData)_PT = TypeVar("_PT", bound=Optional[int])
# TODO: Let the likes of `shape_as` and `strides_as` return `None`# for 0D arrays once we've got shape-support
class _ctypes(Generic[_PT]): @overload def __new__(cls, array: ndarray[Any, Any], ptr: None = ...) -> _ctypes[None]: ... @overload def __new__(cls, array: ndarray[Any, Any], ptr: _PT) -> _ctypes[_PT]: ...
# NOTE: In practice `shape` and `strides` return one of the concrete # platform dependant array-types (`c_int`, `c_long` or `c_longlong`) # corresponding to C's `int_ptr_t`, as determined by `_getintp_ctype` # TODO: Hook this in to the mypy plugin so that a more appropiate # `ctypes._SimpleCData[int]` sub-type can be returned @property def data(self) -> _PT: ... @property def shape(self) -> ct.Array[ct.c_int64]: ... @property def strides(self) -> ct.Array[ct.c_int64]: ... @property def _as_parameter_(self) -> ct.c_void_p: ...
def data_as(self, obj: Type[_CastT]) -> _CastT: ... def shape_as(self, obj: Type[_CT]) -> ct.Array[_CT]: ... def strides_as(self, obj: Type[_CT]) -> ct.Array[_CT]: ...
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