Compare the speed of a complex multiple if test and set containment replement.

speedy.py

import datetime


def main():
    count = 1000
    run_sets(count)
    run_ifs(count)


def run_sets(times):
    t0 = datetime.datetime.now()

    data = list(range(1, 21))
    for n in range(0, times):
        if n in set(data):
            pass

    dt = datetime.datetime.now() - t0
    print(f"Sets done in {dt.total_seconds() * 1000:,} ms.")


def run_ifs(times):
    t0 = datetime.datetime.now()

    for n in range(0, times):
        if (n == 1 or n == 2 or n == 3 or n == 4 or n == 5 or n == 6 or n == 7 or n == 8 or n == 9 or n == 10
                or n == 11 or n == 12 or n == 13 or n == 14 or n == 15 or n == 16 or n == 17 or n == 18 or n == 19 or n == 20):
            pass

    dt = datetime.datetime.now() - t0
    print(f"Ifs done in {dt.total_seconds() * 1000:,} ms.")


if __name__ == '__main__':
    main()

Hi,

The iteration is just to properly time it since doing fast things once is really hard to get any accuracy around. I guess the take away is is your test for truly fixed data then set is fine for perf, but if you have to take inputs, then the sudden it's slower. That is often the case which is why I said, generally speaking, the set style may be slower.

I understand - the use of timeit in the notebook I've linked to is done for the same reasons.
As shown in the example I linked, the time difference is negligible. In addition, if you take into account the time it takes to write or maintain the x==y approach, the use of set() becomes even more appealing.

Thanks again for your time, much appreciated.