New submission from Mark Lawrence:
Quoting Steven D'Aprano on c.l.p.
"But add a call to replace, and things are very different:
[steve@ando ~]$ python2.7 -m timeit -s "s = 'b'*1000" "s.replace('b', 'a')"
100000 loops, best of 3: 9.3 usec per loop
[steve@ando ~]$ python3.2 -m timeit -s "s = 'b'*1000" "s.replace('b', 'a')"
100000 loops, best of 3: 5.43 usec per loop
[steve@ando ~]$ python3.3 -m timeit -s "s = 'b'*1000" "s.replace('b', 'a')"
100000 loops, best of 3: 18.3 usec per loop
Three times slower, even for pure-ASCII strings. I get comparable results for
Unicode. Notice how slow Python 2.7 is:
[steve@ando ~]$ python2.7 -m timeit -s "s = u'你'*1000" "s.replace(u'你', u'a')"
10000 loops, best of 3: 65.6 usec per loop
[steve@ando ~]$ python3.2 -m timeit -s "s = '你'*1000" "s.replace('你', 'a')"
100000 loops, best of 3: 2.79 usec per loop
[steve@ando ~]$ python3.3 -m timeit -s "s = '你'*1000" "s.replace('你', 'a')"
10000 loops, best of 3: 23.7 usec per loop
Even with the performance regression, it is still over twice as fast as
Python 2.7.
Nevertheless, I think there is something here. The consequences are nowhere
near as dramatic as jmf claims, but it does seem that replace() has taken a
serious performance hit. Perhaps it is unavoidable, but perhaps not.
If anyone else can confirm similar results, I think this should be raised as a
performance regression.
Quoting Serhiy Storchaka in response.
"Yes, I confirm, it's a performance regression. It should be avoidable.
Almost any PEP393 performance regression can be avoided. At least for
such corner case. Just no one has yet optimized this case."
----------
messages: 171378
nosy: BreamoreBoy
priority: normal
severity: normal
status: open
title: performance regression in string replace for 3.3
type: performance
versions: Python 3.3
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Python tracker <rep...@bugs.python.org>
<http://bugs.python.org/issue16061>
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