The Fastest Way to Loop in Python: Using Built‑in Functions and Formulas Instead of While/For Loops

It is well known that Python is not a high‑performance language and that loops are generally time‑consuming; repeating a simple operation many times multiplies the execution time.

The two common loop keywords while and for have different runtimes. The following benchmark code measures their performance:

<code>import timeit

def while_loop(n=100_000_000):
    i = 0
    s = 0
    while i < n:
        s += i
        i += 1
    return s

def for_loop(n=100_000_000):
    s = 0
    for i in range(n):
        s += i
    return s

def main():
    print('while loop\t\t', timeit.timeit(while_loop, number=1))
    print('for loop\t\t', timeit.timeit(for_loop, number=1))

if __name__ == '__main__':
    main()
# => while loop           4.718853999860585
# => for loop             3.211570399813354</code>

The result shows that the for loop is about 1.5 seconds faster because the while loop performs an extra boundary check and an explicit increment on each iteration.

To highlight the impact of these extra operations, two additional functions add unnecessary checks and increments to a for loop:

<code>import timeit

def while_loop(n=100_000_000):
    i = 0
    s = 0
    while i < n:
        s += i
        i += 1
    return s

def for_loop(n=100_000_000):
    s = 0
    for i in range(n):
        s += i
    return s

def for_loop_with_inc(n=100_000_000):
    s = 0
    for i in range(n):
        s += i
        i += 1
    return s

def for_loop_with_test(n=100_000_000):
    s = 0
    for i in range(n):
        if i < n:
            pass
        s += i
    return s

def main():
    print('while loop\t\t', timeit.timeit(while_loop, number=1))
    print('for loop\t\t', timeit.timeit(for_loop, number=1))
    print('for loop with increment\t\t', timeit.timeit(for_loop_with_inc, number=1))
    print('for loop with test\t\t', timeit.timeit(for_loop_with_test, number=1))

if __name__ == '__main__':
    main()
# => while loop           4.718853999860585
# => for loop             3.211570399813354
# => for loop with increment          4.602369500091299
# => for loop with test               4.18337869993411</code>

These measurements confirm that the added boundary check and increment noticeably degrade the for loop’s speed.

Because Python’s interpreter and many built‑in functions are implemented in C, they run much faster than pure Python code. Replacing the explicit loops with the built‑in sum function yields a dramatic speedup:

<code>import timeit

def while_loop(n=100_000_000):
    i = 0
    s = 0
    while i < n:
        s += i
        i += 1
    return s

def for_loop(n=100_000_000):
    s = 0
    for i in range(n):
        s += i
    return s

def sum_range(n=100_000_000):
    return sum(range(n))

def main():
    print('while loop\t\t', timeit.timeit(while_loop, number=1))
    print('for loop\t\t', timeit.timeit(for_loop, number=1))
    print('sum range\t\t', timeit.timeit(sum_range, number=1))

if __name__ == '__main__':
    main()
# => while loop           4.718853999860585
# => for loop             3.211570399813354
# => sum range            0.8658821999561042</code>

The built‑in sum executes in C and is therefore orders of magnitude faster than the pure‑Python loops.

Even faster is to replace the loop entirely with the arithmetic formula for the sum of the first n integers, which can be expressed in a single Python statement:

<code>import timeit

def while_loop(n=100_000_000):
    i = 0
    s = 0
    while i < n:
        s += i
        i += 1
    return s

def for_loop(n=100_000_000):
    s = 0
    for i in range(n):
        s += i
    return s

def sum_range(n=100_000_000):
    return sum(range(n))

def math_sum(n=100_000_000):
    return (n * (n - 1)) // 2

def main():
    print('while loop\t\t', timeit.timeit(while_loop, number=1))
    print('for loop\t\t', timeit.timeit(for_loop, number=1))
    print('sum range\t\t', timeit.timeit(sum_range, number=1))
    print('math sum\t\t', timeit.timeit(math_sum, number=1))

if __name__ == '__main__':
    main()
# => while loop           4.718853999860585
# => for loop             3.211570399813354
# => sum range            0.8658821999561042
# => math sum             2.400018274784088e-06</code>

The arithmetic formula completes in microseconds, demonstrating that the fastest way to "loop" in Python is to avoid looping altogether and use built‑in functions or direct mathematical expressions.

Original article: https://www.starky.ltd/2021/11/23/the-fastest-way-to-loop-in-python