Python：为什么partition（sep）比split更快（sep，maxsplit = 1）

Question

I found an interesting thing that partition is faster than split when get whole substring after the separator. I have tested in Python 3.5 and 3.6 (Cpython)

In [1]: s = 'validate_field_name'

In [2]: s.partition('_')[-1]
Out[2]: 'field_name'

In [3]: s.split('_', maxsplit=1)[-1]
Out[3]: 'field_name'

In [4]: %timeit s.partition('_')[-1]
220 ns ± 1.12 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [5]: %timeit s.split('_', maxsplit=1)[-1]
745 ns ± 48.8 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [6]: %timeit s[s.find('_')+1:]
340 ns ± 1.44 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

I look through the Cpython source code and found the partition use the FASTSEARCH algorithm, see here . And the split only use FASTSEARCH when the separator string's length is larger than 1, see here . But I have tested on sep string which length is larger. I got same result.

I guess the reason is partition return a three elements tuple, instead of a list.

I want to know more details.

Answer 1

Microbenchmarks can be misleading

py -m timeit "'validate_field_name'.split('_', maxsplit=1)[-1]"
1000000 loops, best of 3: 0.568 usec per loop

py -m timeit "'validate_field_name'.split('_', 1)[-1]"
1000000 loops, best of 3: 0.317 usec per loop

Just passing the argument as positional or keyword changes the time significantly. So I would guess another reason partition is faster, because it does not need a second argument...