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.
The dtype to convert
A ctype scalar, union, array, or struct
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.Structure
s andctypes.Union
sconvert single-element
ctypes.Union
s into single-elementctypes.Structure
sinsert 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.
Name of the library, which can have ‘lib’ as a prefix, but without an extension.
Where the library can be found.
A ctypes library object
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.
Name of the library, which can have ‘lib’ as a prefix, but without an extension.
Where the library can be found.
A ctypes library object
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.
Array data-type.
Number of array dimensions.
Array shape.
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
A type object, which is an _ndtpr
instance containing
dtype, ndim, shape and flags information.
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))
...