NumPy Reference, Release 1.11.0
This attribute creates an object that makes it easier to use arrays when calling shared libraries with the
ctypes module. The returned object has, among others, data, shape, and strides attributes (see Notes
below) which themselves return ctypes objects that can be used as arguments to a shared library.
Parameters
None
Returns
c : Python object
Possessing attributes data, shape, strides, etc.
See also:
numpy.ctypeslib
Notes
Below are the public attributes of this object which were documented in “Guide to NumPy” (we have
omitted undocumented public attributes, as well as documented private attributes):
•data: A pointer to the memory area of the array as a Python integer. This memory area may contain
data that is not aligned, or not in correct byte-order. The memory area may not even be writeable.
The array flags and data-type of this array should be respected when passing this attribute to arbitrary
C-code to avoid trouble that can include Python crashing. User Beware! The value of this attribute is
exactly the same as self._array_interface_[’data’][0].
•shape (c_intp*self.ndim): A ctypes array of length self.ndim where the basetype is the C-integer
corresponding to dtype(‘p’) on this platform. This base-type could be c_int, c_long, or c_longlong
depending on the platform. The c_intp type is defined accordingly in numpy.ctypeslib. The ctypes
array contains the shape of the underlying array.
•strides (c_intp*self.ndim): A ctypes array of length self.ndim where the basetype is the same as for
the shape attribute. This ctypes array contains the strides information from the underlying array.
This strides information is important for showing how many bytes must be jumped to get to the next
element in the array.
•data_as(obj): Return the data pointer cast to a particular c-types object. For example, calling
self._as_parameter_ is equivalent to self.data_as(ctypes.c_void_p). Perhaps you want to use the data
as a pointer to a ctypes array of floating-point data: self.data_as(ctypes.POINTER(ctypes.c_double)).
•shape_as(obj): Return the shape tuple as an array of some other c-types type. For example:
self.shape_as(ctypes.c_short).
•strides_as(obj): Return the strides tuple as an array of some other c-types type. For example:
self.strides_as(ctypes.c_longlong).
Be careful using the ctypes attribute - especially on temporary arrays or arrays constructed on the fly. For
example, calling (a+b).ctypes.data_as(ctypes.c_void_p) returns a pointer to memory that
is invalid because the array created as (a+b) is deallocated before the next Python statement. You can avoid
this problem using either c=a+b or ct=(a+b).ctypes. In the latter case, ct will hold a reference to
the array until ct is deleted or re-assigned.
If the ctypes module is not available, then the ctypes attribute of array objects still returns something useful,
but ctypes objects are not returned and errors may be raised instead. In particular, the object will still have
the as parameter attribute which will return an integer equal to the data attribute.
Examples
>>> import ctypes
>>> x
12 Chapter 1. Array objects
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