Sergey B Kirpichev <skirpic...@gmail.com> added the comment:
I have similar timings (for a draft version of PR, see f.patch) as for the last comment, though the small-dens overhead seems to be bigger(~20%): $ python3.10 -m timeit -r11 -s 'from fractions import Fraction as F' -s 'a=F(10,3)' -s 'b=F(6, 5)' 'a * b' 50000 loops, best of 11: 9.09 usec per loop $ python3.10 -m timeit -r11 -s 'from patched import Fraction as F' -s 'a=F(10,3)' -s 'b=F(6, 5)' 'a * b' 20000 loops, best of 11: 11.2 usec per loop On another hand, here are timings for bigger denominators: $ python3.10 -m timeit -r11 -s 'from fractions import Fraction as F' -s 'import random' -s 'n = [random.randint(1, 1000000) for _ in range(1000)]' -s 'd = [random.randint(1, 1000000) for _ in range(1000)]' -s 'a=list(map(lambda x: F(*x), zip(n, d)))' 'sum(a)' 1 loop, best of 11: 257 msec per loop $ ... from patched ... 10 loops, best of 11: 33.2 msec per loop It's not so clear what "are very large" does mean, that could be defined here. BTW, 10**6 denominators are (very!) small for mentioned above use case (CAS package). ---------- keywords: +patch Added file: https://bugs.python.org/file49854/f.patch _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue43420> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
