The corresponding ctypes type of a numpy.dtype?

Question

If I have a numpy ndarray with a certain dtype, how do I know what is the corresponding ctypes type?

For example, if I have a ndarray, I can do the following to convert it to a shared array:

import multiprocessing as mp
import numpy as np
import ctypes
x_np = np.random.rand(10, 10)
x_mp = mp.Array(ctypes.c_double, x_np)

However, I have to specify c_double here. It works if I don't specify the exact same type, but I would like to keep the type the same. How should I find out the ctypes type of the ndarray x_np automatically, at least for some common elementary data types?

Answer 1

This is now supported by numpy.ctypeslib.as_ctypes_type(dtype):

import numpy as np
x_np = np.random.rand(10, 10)
np.ctypeslib.as_ctypes_type(x_np.dtype)

Gives ctypes.c_double, as expected.

Answer 2

There is actually a way to do this that's built into Numpy:

x_np = np.random.rand(10, 10)
typecodes = np.ctypeslib._get_typecodes()
typecodes[x_np.__array_interface__['typestr']]

Output:

ctypes.c_double

The caveat is that the np.ctypeslib._get_typecodes function is marked as private (ie it's name starts with _). However, it doesn't seem like its implementation has changed in some time, so you can probably use it fairly reliably.

Alternatively, the implementation of _get_typecodes is pretty short, so you could just also copy the whole function over to your own code:

import ctypes
import numpy as np

def get_typecodes():
    ct = ctypes
    simple_types = [
        ct.c_byte, ct.c_short, ct.c_int, ct.c_long, ct.c_longlong,
        ct.c_ubyte, ct.c_ushort, ct.c_uint, ct.c_ulong, ct.c_ulonglong,
        ct.c_float, ct.c_double,
    ]

    return {np.dtype(ctype).str: ctype for ctype in simple_types}