New submission from Stefan Pochmann <stefan.pochm...@gmail.com>:
Using a list's insert function is much slower than using slice assignment: > python -m timeit -n 100000 -s "a=[]" "a.insert(0,0)" 100000 loops, best of 5: 19.2 usec per loop > python -m timeit -n 100000 -s "a=[]" "a[0:0]=[0]" 100000 loops, best of 5: 6.78 usec per loop (Note that the list starts empty but grows to 100,000 elements.) At first I thought maybe it's the attribute lookup or function call overhead or so, but inserting near the end shows that that's negligible: > python -m timeit -n 100000 -s "a=[]" "a.insert(-1,0)" 100000 loops, best of 5: 79.1 nsec per loop I asked at StackOverflow and someone pointed out that list.insert uses a manual loop instead of memmove: https://stackoverflow.com/a/60466572/12671057 ---------- components: Interpreter Core messages: 362986 nosy: Stefan Pochmann priority: normal severity: normal status: open title: list.insert is slow due to manual memmove type: performance versions: Python 3.8 _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue39801> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
