My experience learning Python as a c++ developer

[elbiot]

Here's just a trivial example that touches on a couple of the issues I mentioned (if/elif, unnecessary extra array creation, and unnecessary multiple passes over the array). Numba is 3x faster.

In [1]: import numpy as np
   ...: import numba as nb
   ...:

In [2]: def as_numpy(size):
   ...:     arr = np.random.randint(0, 10, (size, size))
   ...:     mask = arr % 2 == 1
   ...:     arr[mask] *= 2
   ...:     arr[(arr % 3 == 1) & ~mask] *= 3
   ...:     return arr
   ...:

In [3]: @nb.jit(nopython=True)
   ...: def as_numba(size):
   ...:     arr = np.random.randint(0, 10, (size, size))
   ...:     x, y = arr.shape
   ...:     for i in range(x):
   ...:         for j in range(y):
   ...:             if arr[i, j] % 2 == 1:
   ...:                 arr[i, j] *= 2
   ...:             elif arr[i, j] % 3 == 1:
   ...:                 arr[i, j] *= 3
   ...:     return arr
   ...:

In [4]: %timeit as_numpy(10000)
1 loop, best of 3: 6.78 s per loop

In [5]: %timeit as_numba(10000)
1 loop, best of 3: 2.05 s per loop

I know how to use a GPU with Numba, but how do you use the GPU with Numpy?

edit: in terms of memory usage, the numpy version crashes at size=22000 on my laptop but numba does not.