Python not as slow as you may think

I've read a lot of articles about how python is slow and you need to use modules like numpy to speed things up like: http://www.labri.fr/perso/nrougier/from-python-to-numpy/ where it was claimed that numpy was an order of magnitude slower than Python.

I decided to try one of the first examples out on my own, it resulted in the following script:

import random
import numpy as np
from timeit import timeit

Z1 = random.sample(range(1000), 100)
Z2 = random.sample(range(1000), 100)


def add_python():
    return [z1+z2 for (z1, z2) in zip(Z1, Z2)]


def add_numpy():
    return np.add(Z1, Z2)

assert add_python() == add_numpy().tolist()

setup_str = "from __main__ import Z1, Z2, add_python, add_numpy"

print("add_python:", timeit("add_python()", setup_str))
print("add_numpy:", timeit("add_numpy()", setup_str))

The result is that in both python 3.5.2 and 2.7.13 python is in fact faster than numpy :)