On Fri, Apr 15, 2011 at 05:03:55PM -0700, Bob Ippolito wrote: > On Fri, Apr 15, 2011 at 4:12 PM, Antoine Pitrou <solip...@pitrou.net> wrote: > > On Fri, 15 Apr 2011 14:27:04 -0700 > > Bob Ippolito <b...@redivi.com> wrote: > >> On Fri, Apr 15, 2011 at 2:20 PM, Antoine Pitrou <solip...@pitrou.net> > >> wrote: > > > > Well, here's a crude microbenchmark. I'm comparing 2.6+simplejson 2.1.3 > > to 3.3+json, so I'm avoiding integers: > > > > * json.dumps: > > > > $ python -m timeit -s "from simplejson import dumps, loads; \ > > ?? ??d = dict((str(i), str(i)) for i in range(1000))" \ > > ?? "dumps(d)" > > > > - 2.6+simplejson: 372 usec per loop > > - 3.2+json: 352 usec per loop > > > > * json.loads: > > > > $ python -m timeit -s "from simplejson import dumps, loads; \ > > ?? ??d = dict((str(i), str(i)) for i in range(1000)); s = dumps(d)" \ > > ?? ??"loads(s)" > > > > - 2.6+simplejson: 224 usec per loop > > - 3.2+json: 233 usec per loop > > > > > > The runtimes look quite similar. > > That's the problem with trivial benchmarks. With more typical data > (for us, anyway) you should see very different results.
Slightly less crude benchmark showing simplejson is quite a bit faster: http://pastebin.com/g1WqUPwm 250ms vs 5.5s encoding and decoding an 11KB json object 1000 times... m -- Matt Billenstein m...@vazor.com http://www.vazor.com/ _______________________________________________ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com