On Thu, Oct 10, 2013 at 9:38 AM, Antoine Pitrou <solip...@pitrou.net> wrote:
> Le Thu, 10 Oct 2013 14:36:26 +0200, > Dirkjan Ochtman <dirk...@ochtman.nl> a écrit : > > > On Thu, Oct 10, 2013 at 2:25 PM, Christian Heimes > > <christ...@python.org> wrote: > > > Benchmark of 1000 times "python -c ''" > > > > > > Python 3.4dev with all my experimental patches: > > > > > > Avg: 0.705161 -> 0.443613: 1.59x faster > > > > > > 2.7 -> 3.4dev: > > > > > > Avg: 0.316177 -> 0.669330: 2.12x slower > > > > > > 2.7 -> 3.4dev with all my patches: > > > > > > Avg: 0.314879 -> 0.449556: 1.43x slower > > > > > > http://pastebin.com/NFrpa7Jh > > > > > > Ain't bad! The benchmarks were conducted on a fast 8 core machine > > > with SSD. > > > > This seems promising. What OS are you using? On an older Linux server > > with old-style HD's, the difference between 2.7 and 3.2 is much larger > > for me: > > 3.2 isn't the same as 3.4. > And I think that is a key point as imports sped up a good deal in Python 3.3 thanks to the stat caching. So if you want to compare 3.4 to 3.3 that makes sense. And if you want to compare 2.7 to 3.4 as a selling point as startup is the worst benchmark performer in that comparison then fine. But otherwise leave 3.0 - 3.2 out of the discussion as they are red herrings. And as to the suggestion of speeding up import itself: good luck with that without changing semantics. =)
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