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# C-Types Foreign Function Interface (`numpy.ctypeslib`)

`numpy.ctypeslib.``as_array`(obj, shape=None)

  Create a numpy array from a ctypes array or a ctypes POINTER. The numpy array shares the memory with the ctypes object.

  The size parameter must be given if converting from a ctypes POINTER. The size parameter is ignored if converting from a ctypes array

`numpy.ctypeslib.``as_ctypes`(obj)

  Create and return a ctypes object from a numpy array. Actually anything that exposes the __array_interface__ is accepted.

`numpy.ctypeslib.``ctypes_load_library`(*args, **kwds)

  `ctypes_load_library` is deprecated, use `load_library` instead!

`numpy.ctypeslib.``load_library`(libname, loader_path)

`numpy.ctypeslib.``ndpointer`(dtype=None, ndim=None, shape=None, flags=None)

  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 : | 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: C_CONTIGUOUS / C / CONTIGUOUS F_CONTIGUOUS / F / FORTRAN OWNDATA / O WRITEABLE / W ALIGNED / A UPDATEIFCOPY / U
  Returns : | klass : ndpointer 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))
      ...

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