Comparison between 'map', 'for' and 'enumerate'

from time import time


def clock(func):
    def wrapper(*args, **kwargs):
        start = time()
        result = func(*args, **kwargs)
        elapsed = (time() - start) * 1000
        print(f'{func.__name__:8} {elapsed:3.0f}ms')
        return result
    return wrapper


@clock
def arthur(nums):
    int(''.join(map(str, nums)))


@clock
def nick(nums):
    int(''.join(str(i) for i in nums))


@clock
def ryan(nums):
    sum(n * 10**i for i, n in enumerate(reversed(nums)))


if __name__ == '__main__':
    list_9k = [9] * 9000
    list_180k = [9] * 180000

    header = '9k size'
    print(f'{header:>14}\n--------------')
    arthur(list_9k)
    nick(list_9k)
    ryan(list_9k)

    header = '180k size'
    print(f'\n{header:>14}\n--------------')
    arthur(list_180k)
    nick(list_180k)
    print('ryan       n/a')  # ryan(list_180k) would take too long to run

# OUTPUT
#
#        9k size
# --------------
# arthur     3ms
# nick       4ms
# ryan     492ms
#
#      180k size
# --------------
# arthur   198ms
# nick     213ms
# ryan       n/a
#
# Ranked by speed:
# 1) map
# 2) for
# 3) for with enumerate