I need some help. I want to help add more numpypy goodness to PyPy, so that I can rewrite my PyEphem astronomy module as pure Python instead of having to always maintain a C extension. I will then tell the users who are doing large calculations, and need extra speed, that they can run their script on PyPy and have it run blazing fast.
My problem is that I am not sure how to start adding code to PyPy in such a way that I can try out my code more than once within a single work day, because it is taking 5+ hours to build the translator on every platform to which I have access. This did not surprise me on my 2003 Dell PowerEdge 400SC, with its 2GB of kind-of-working RAM, which wound up taking 5h 28m to complete the build. But I just got finished trying the build on the fastest computer in the house - my wife's few-month-old iMac with 4GB of memory - and it actually took *longer*, finishing up a full 5h 53m (!) after it started. And, actually, that's not the big problem. The big problem is that whereas C Python uses Make, so it only re-compiles the files I have changed when I am in a tight development loop, it seems that PyPy starts the whole translation process over again when I run it. How does one actually iterate when working on part of PyPy and its libraries? Only now that it is past midnight, as I write this, do I realize that my subsequent builds of PyPy can be done with the PyPy interpreter itself, speeding things up considerably! But even if I can bring down the build time to under a half-hour, I can hardly imagine doing software development under the constraint of such delays - what am I missing? My first feat, should it success, will be writing load() for numpypy since that it the first missing feature I noticed when I tried running my prototype "jplephem" package - my first attempt at doing heavy-duty astronomy in pure Python. I had hoped to have the package run and walk away with a number to compare to the pure C performance, but instead I get the fun of contributing! :) -- Brandon Rhodes bran...@rhodesmill.org http://rhodesmill.org/brandon _______________________________________________ pypy-dev mailing list pypy-dev@python.org http://mail.python.org/mailman/listinfo/pypy-dev
