Calculating averages efficiently, using Python

means.py

# Timing script to compare various ways to compute the mean of list of ints
# Short explanation, and results of the experiment can be found here:
# www.faingezicht.com/articles/2016/12/25/means/

import random
import timeit
import statistics
import numpy as np

random.seed(1)
lengths = [10, 100, 1000]
lsts = [[random.randint(0, 100) for _ in range(length)] for length in lengths]

def mean1(lst):
    num = 0
    denom = 0
    for i in range(len(lst)):
        num += lst[i]
        denom += 1
    return num/denom

def mean2(lst):
    numer = 0
    denom = 0
    for num in lst:
        numer += num
        denom += 1
    return numer/denom

def mean3(lst):
    return sum(lst) / len(lst)

def numpy(lst):
    return np.mean(lst)

def stats(lst):
    return statistics.mean(lst)

funcs = [mean1, mean2, mean3, numpy, stats]

if __name__ == '__main__':
    for lst in lsts:
        print("\nLists of length", len(lst))
        for f in funcs:
            print(f.__name__, timeit.timeit('f(lst)', "from __main__ import f, lst"))