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