On Mon, Sep 26, 2011 at 10:18 PM, Maciej Fijalkowski <fij...@gmail.com> wrote: > On Mon, Sep 26, 2011 at 7:13 PM, Bob Ippolito <b...@redivi.com> wrote: >> You should also try the master branch of simplejson, the >> _pypy_speedups branch is not necessarily better (which is why it is >> not master). > > You should also look at https://bugs.pypy.org/issue866 for various patches.
Wrong link https://bugs.pypy.org/issue868 > >> >> On Mon, Sep 26, 2011 at 2:39 PM, Matthew Kaniaris <mkania...@gmail.com> >> wrote: >>> I did some testing to see where we stand on JSON. The pypy is from >>> the trunk and the simplejson used with pypy is the _pypy_speedups >>> branch. The speedups make pypy about 2x faster on dumps than with the >>> stdlib JSON module, slightly slower with loads, but up to ten times >>> slower than cpython with simplejson with the 32kb file. I'll try >>> profiling the speedups branch to see if there is any easy fruit left, >>> but I doubt we will get another 50% improvement out of it. >>> >>> -kans >>> >>> results: >>> python using json: >>> >>> /home/test/3.4kb.json >>> loads: 5 loops, best of 1000: 953 usec per loop >>> >>> dumps: 5 loops, best of 1000: 706 usec per loop >>> >>> /home/test/32kb.json >>> loads: 5 loops, best of 1000: 10.9 msec per loop >>> >>> dumps: 5 loops, best of 1000: 9.13 msec per loop >>> >>> ------------------------- >>> python using simplejson: >>> >>> /home/test/3.4kb.json >>> loads: 5 loops, best of 1000: 41.2 usec per loop >>> >>> dumps: 5 loops, best of 1000: 56 usec per loop >>> >>> /home/test/32kb.json >>> loads: 5 loops, best of 1000: 604 usec per loop >>> >>> dumps: 5 loops, best of 1000: 391 usec per loop >>> >>> ------------------------- >>> pypy using json: >>> >>> /home/test/3.4kb.json >>> loads: 5 loops, best of 1000: 146 usec per loop >>> >>> dumps: 5 loops, best of 1000: 429 usec per loop >>> >>> /home/test/32kb.json >>> loads: 5 loops, best of 1000: 2.93 msec per loop >>> >>> dumps: 5 loops, best of 1000: 7.16 msec per loop >>> >>> ------------------------- >>> pypy using simplejson: >>> >>> /home/test/3.4kb.json >>> loads: 5 loops, best of 1000: 197 usec per loop >>> >>> dumps: 5 loops, best of 1000: 148 usec per loop >>> >>> /home/test/32kb.json >>> loads: 5 loops, best of 1000: 3.47 msec per loop >>> >>> dumps: 5 loops, best of 1000: 3.2 msec per loop >>> >>> >>> >>> On Sun, Sep 25, 2011 at 1:53 PM, Alex Gaynor <alex.gay...@gmail.com> wrote: >>>> >>>> >>>> On Sun, Sep 25, 2011 at 1:49 PM, Bob Ippolito <b...@redivi.com> wrote: >>>>> >>>>> simplejson would be a good target for changes that would not be easy >>>>> to implement on top of the stdlib json. I'd be happy to accept any >>>>> contributions. I failed to make big differences in performance when I >>>>> tried at PyCon (at least that didn't regress performance for some >>>>> people). The other things I'm missing are a good suite of documents to >>>>> benchmark with, and a good tool to run the benchmarks so it's easy to >>>>> see if incremental changes are better or worse. >>>>> >>>>> However, if RPython is required to make it faster, maybe implementing >>>>> _json for the stdlib would actually be best. >>>>> >>>>> On Sun, Sep 25, 2011 at 10:30 AM, Zooko O'Whielacronx <zo...@zooko.com> >>>>> wrote: >>>>> > But don't people who need better json performance use simplejson >>>>> > explicitly instead of using the standard library's json? >>>>> > >>>>> > Regards, >>>>> > >>>>> > Zooko >>>>> > _______________________________________________ >>>>> > pypy-dev mailing list >>>>> > pypy-dev@python.org >>>>> > http://mail.python.org/mailman/listinfo/pypy-dev >>>>> > >>>>> _______________________________________________ >>>>> pypy-dev mailing list >>>>> pypy-dev@python.org >>>>> http://mail.python.org/mailman/listinfo/pypy-dev >>>> >>>> For what it's worth, I think we can get there, without needing to write any >>>> RPython, through a combination of careful Python, and more JIT >>>> optimizations. For example, I'd like to get the code input[i:i+4] == >>>> "NULL" >>>> to eventually generate: >>>> read str length >>>> check length >= 4 >>>> read 4 bytes out of input (single MOVL) >>>> integer compare to ('N' << 0) | ('U' << 8) | ('L' << 16) | ('L' << 24) >>>> in total about 7 x86 instructions. I think this is definitely possible! >>>> Alex >>>> >>>> -- >>>> "I disapprove of what you say, but I will defend to the death your right to >>>> say it." -- Evelyn Beatrice Hall (summarizing Voltaire) >>>> "The people's good is the highest law." -- Cicero >>>> >>>> >>>> _______________________________________________ >>>> pypy-dev mailing list >>>> pypy-dev@python.org >>>> http://mail.python.org/mailman/listinfo/pypy-dev >>>> >>>> >>> >> _______________________________________________ >> pypy-dev mailing list >> pypy-dev@python.org >> http://mail.python.org/mailman/listinfo/pypy-dev >> > _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
