C-Types Foreign Function Interface (numpy.ctypeslib) — NumPy v1.18 Manual (original) (raw)
numpy.ctypeslib.
as_array
(obj, shape=None)[source]¶
Create a numpy array from a ctypes array or POINTER.
The numpy array shares the memory with the ctypes object.
The shape parameter must be given if converting from a ctypes POINTER. The shape parameter is ignored if converting from a ctypes array
numpy.ctypeslib.
as_ctypes
(obj)[source]¶
Create and return a ctypes object from a numpy array. Actually anything that exposes the __array_interface__ is accepted.
numpy.ctypeslib.
as_ctypes_type
(dtype)[source]¶
Convert a dtype into a ctypes type.
Parameters
dtypedtype
The dtype to convert
Returns
ctype
A ctype scalar, union, array, or struct
Raises
NotImplementedError
If the conversion is not possible
Notes
This function does not losslessly round-trip in either direction.
np.dtype(as_ctypes_type(dt))
will:
- insert padding fields
- reorder fields to be sorted by offset
- discard field titles
as_ctypes_type(np.dtype(ctype))
will:
- discard the class names of ctypes.Structures andctypes.Unions
- convert single-element ctypes.Unions into single-elementctypes.Structures
- insert padding fields
numpy.ctypeslib.
ctypes_load_library
(*args, **kwds)[source]¶
ctypes_load_library is deprecated, use load_library instead!
It is possible to load a library using >>> lib = ctypes.cdll[<full_path_name>] # doctest: +SKIP
But there are cross-platform considerations, such as library file extensions, plus the fact Windows will just load the first library it finds with that name. NumPy supplies the load_library function as a convenience.
Parameters
libnamestr
Name of the library, which can have ‘lib’ as a prefix, but without an extension.
loader_pathstr
Where the library can be found.
Returns
ctypes.cdll[libpath]library object
A ctypes library object
Raises
OSError
If there is no library with the expected extension, or the library is defective and cannot be loaded.
numpy.ctypeslib.
load_library
(libname, loader_path)[source]¶
It is possible to load a library using >>> lib = ctypes.cdll[<full_path_name>] # doctest: +SKIP
But there are cross-platform considerations, such as library file extensions, plus the fact Windows will just load the first library it finds with that name. NumPy supplies the load_library function as a convenience.
Parameters
libnamestr
Name of the library, which can have ‘lib’ as a prefix, but without an extension.
loader_pathstr
Where the library can be found.
Returns
ctypes.cdll[libpath]library object
A ctypes library object
Raises
OSError
If there is no library with the expected extension, or the library is defective and cannot be loaded.
numpy.ctypeslib.
ndpointer
(dtype=None, ndim=None, shape=None, flags=None)[source]¶
Array-checking restype/argtypes.
An ndpointer instance is used to describe an ndarray in restypes and argtypes specifications. This approach is more flexible than using, for example, POINTER(c_double)
, since several restrictions can be specified, which are verified upon calling the ctypes function. These include data type, number of dimensions, shape and flags. If a given array does not satisfy the specified restrictions, a TypeError
is raised.
Parameters
dtypedata-type, optional
Array data-type.
ndimint, optional
Number of array dimensions.
shapetuple of ints, optional
Array shape.
flagsstr or tuple of str
Array flags; may be one or more of:
- C_CONTIGUOUS / C / CONTIGUOUS
- F_CONTIGUOUS / F / FORTRAN
- OWNDATA / O
- WRITEABLE / W
- ALIGNED / A
- WRITEBACKIFCOPY / X
- UPDATEIFCOPY / U
Returns
klassndpointer type object
A type object, which is an _ndtpr
instance containing dtype, ndim, shape and flags information.
Raises
TypeError
If a given array does not satisfy the specified restrictions.
Examples
clib.somefunc.argtypes = [np.ctypeslib.ndpointer(dtype=np.float64, ... ndim=1, ... flags='C_CONTIGUOUS')] ... clib.somefunc(np.array([1, 2, 3], dtype=np.float64)) ...