John Nagle <na...@animats.com> wrote: > All the schemes to speed up Python as defined by CPython seem to hit > a wall on speed improvement. Some of the numeric benchmarks go faster > on implementations that don't box all numbers, but 2x seems to be about > as good as it gets, even with a JIT compiler.
That hasn't been the case with PyPy for quite some time: http://goo.gl/dA7v (link to specific speed.pypy.org comparison). Comparing the latest PyPy+JIT to CPython 2.6.2, there are 6 tests that perform worse and 12 that perform better. Of the 12 improvements, 9 are of an improvement of 3x or better, with one exceeding 12x and one 15x. The django benchmark is 6x faster under PyPy+JIT than CPython. (The PyPy guys have done a fantastic job with http://speed.pypy.org to help show the gains that they're getting.) Don't be so quick to condemn PyPy, especially as they're _actively_ working on this project, not just engaging in endless online rhetoric about how great life would be if only Python was faster. Achieving performance gains _without_ sacrificing the power of the language should be the ultimate goal. -- http://mail.python.org/mailman/listinfo/python-list
