cfb wrote: > I thought I would start a new thread for discussing what PyPy needs to > become "production ready" (whatever that is) and succeed as a Python > implementation. > [...] > - Speed. The JIT is still not in a state where it really speeds up > arbitrary Python code. I expect this to change sooner or later. > However, it's not an area were a lot of people can help.
</lurk> Arbitrary code is less interesting to me than JIT-powered fast numerical code. Moreover, we numerics types have much lower standards of "production ready" than the general public, and are willing to turn on options with names like --make-dangerous-assumptions-about-code-for-speed -do-not-use-this-flag-really-do-not-use-it-i-warned-you. Currently there is no One Obvious Way to do heavy numerical programming in python. To actually get things done requires a mix of numpy, boost, psyco, pyrex, pyinline, SWIG, some of the existing pypy tools -- even wrapped shedskin if you're feeling brave. The toolset is unwieldy. Yes, it's true that these often suffice -- I've run hundreds of semianalytic models over the past week myself using numpy/pygsl -- but I can't write my main production codes in python. And it's frustrating when you write a nice piece of code and then bump up against speed limits you can't escape without ugly inline hacks I can't expect the people I encourage to use python for science to learn. This is probably the most low-hanging fruit there could be for a (fully float-aware) JIT. The functions tends to be embarrassingly simple, and seldom leave the int/float/list domain. Most numerical code is borderline RPython as-is. >From previous discussions, I suspect I'm not the only lurker-fan who would be willing to commit time to working on numericentric graph optimizations when that becomes a worthwhile investment. There's no reason that the mostly-fortran bits of python code shouldn't run almost as fast as fortran after amortizing the JIT costs. <relurk> Doug -- Queen Mary College, University of London "Still creating worlds.. Mathematical Sciences, Astronomy Unit .. but now with an accent!" _______________________________________________ [email protected] http://codespeak.net/mailman/listinfo/pypy-dev
