What is the fastest way in python to build a c array from a list of tuples of floats?

Question

The context: my Python code pass arrays of 2D vertices to OpenGL.

I tested 2 approaches, one with ctypes, the other with struct, the latter being more than twice faster.

from random import random
points = [(random(), random()) for _ in xrange(1000)]

from ctypes import c_float
def array_ctypes(points):
    n = len(points)
    return n, (c_float*(2*n))(*[u for point in points for u in point])

from struct import pack
def array_struct(points):
    n = len(points)
    return n, pack("f"*2*n, *[u for point in points for u in point])

Any other alternative? Any hint on how to accelerate such code (and yes, this is one bottleneck of my code)?

Answer 1

You can pass numpy arrays to PyOpenGL without incurring any overhead. (The data attribute of the numpy array is a buffer that points to the underlying C data structure that contains the same information as the array you're building)

import numpy as np  
def array_numpy(points):
    n = len(points)
    return n, np.array(points, dtype=np.float32)

On my computer, this is about 40% faster than the struct-based approach.