On 2023-11-14 00:11:30 +0200, Dom Grigonis via Python-list wrote: > Benchmarks: > test1 = [False] * 100 + [True] * 2 > test2 = [True] * 100 + [False] * 2 > > TIMER.repeat([ > lambda: xor(test1), # 0.0168 > lambda: xor(test2), # 0.0172 > lambda: xor_ss(test1), # 0.1392 > lambda: xor_ss(test2), # 0.0084 > lambda: xor_new(test1), # 0.0116 > lambda: xor_new(test2), # 0.0074 > lambda: all(test1), # 0.0016 > lambda: all(test2) # 0.0046 > ]) > Your first function is fairly slow. > Second one deals with short-circuiting, but is super slow on full search. > > `xor_new` is the best what I could achieve using python builtins. > > But builtin `all` has the best performance.
One question worth asking is if a list of bool is the best data
structure for the job. This is essentially a bitmap, and a bitmap is
equivalent to a set of integers. len(s) == 1 is also a fairly quick
operation if s is small. On my system, len(test1s) == 1 (where test1s is
{100, 101}) is about as fast as all(test1) and len(test2s) == 1 (where
test2s is set(range(100))) is about twice as fast as all(test2).
If you are willing to stray from the standard library, you could e.g.
use pyroaring instead of sets: This is about as fast as all(test1)
whether there are two bits set or a hundred.
hp
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