C-Types Foreign Function Interface (numpy.ctypeslib)

• 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:

  type	description
  dtype : dtype	The dtype to convert

  Returns:

  type	description
  ctype	A ctype scalar, union, array, or struct

  Raises:

  type	description
  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:

  type	description
  libname : str	Name of the library, which can have ‘lib’ as a prefix, but without an extension.
  loader_path : str	Where the library can be found.

  Returns:

  type	description
  ctypes.cdll[libpath] : library object	A ctypes library object

  Raises:

  type	description
  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:

  type	description
  libname : str	Name of the library, which can have ‘lib’ as a prefix, but without an extension.
  loader_path : str	Where the library can be found.

  Returns:

  type	description
  ctypes.cdll[libpath] : library object	A ctypes library object

  Raises:

  type	description
  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:

  type	description
  dtype : data-type, optional	Array data-type.
  ndim : int, optional	Number of array dimensions.
  shape : tuple of ints, optional	Array shape.
  flags : str or tuple of str	Array flags; may be one or more of:

  Possible items for flags:

  • C_CONTIGUOUS / C / CONTIGUOUS
  • F_CONTIGUOUS / F / FORTRAN
  • OWNDATA / O
  • WRITEABLE / W
  • ALIGNED / A
  • WRITEBACKIFCOPY / X
  • UPDATEIFCOPY / U

  Returns:

  type	description
  klass : ndpointer type object	A type object, which is an _ndtpr instance containing dtype, ndim, shape and flags information.

  Raises:

  type	description
  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')]
  ... #doctest: +SKIP
  >>> clib.somefunc(np.array([1, 2, 3], dtype=np.float64))
  ... #doctest: +SKIP