FWIW, I'm not sure your commit helped, at least, it seems to be worse for
some usecases: (PyPy default vs 2.3.1):
$ ./pypy-c -mtimeit -s "import json" "json.dumps({u'': u'abcdef' * 10000})"
1000 loops, best of 3: 1.09 msec per loop
$ ./pypy-c -mtimeit -s "import json" "json.dumps({u'': u'abcdef' * 10000})"
1000 loops, best of 3: 1.1 msec per loop
$ ./pypy-c -mtimeit -s "import json" "json.dumps({u'': u'abcdef' * 10000})"
1000 loops, best of 3: 1.11 msec per loop
$ pypy -mtimeit -s "import json" "json.dumps({u'': u'abcdef' * 10000})
1000 loops, best of 3: 503 usec per loop
$ pypy -mtimeit -s "import json" "json.dumps({u'': u'abcdef' * 10000})"
1000 loops, best of 3: 491 usec per loop
$ pypy -mtimeit -s "import json" "json.dumps({u'': u'abcdef' * 10000})"
1000 loops, best of 3: 498 usec per loop
Alex
On Fri, Aug 29, 2014 at 9:52 AM, Phyo Arkar <phyo.arkarl...@gmail.com>
wrote:
> Thanks a lot! i am waiting to switch to PyPy.
>
> Also there is one performance problem. I haven't profile it properly
> yet just from looking at Chrome DEV Console.
>
> A simple Tornado async (callback) + pymongo + motor + reading 100
> records from db and returning them in json ,
> in Python its takes only 1 ms
> in Pypy it takes 4-6 ms
>
> I will make proper benchmark on it when i get time. and find which
> part is slowing down. But may be you can guess where it is slowing?
>
>
>
>
>
> On Fri, Aug 29, 2014 at 10:34 PM, Armin Rigo <ar...@tunes.org> wrote:
> > Hi Phyo,
> >
> > Thanks for the report! I may have fixed it in e80c25f01061. Please
> > try it out with tomorrow's nightly build.
> >
> >
> > A bientôt,
> >
> > Armin.
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