I have been working to get numfocus benchmarks written for numpy to run
on numpypy and pypy https://github.com/numfocus/python-benchmarks
The biggest obstacle is actually the need for matplotlib, which is used
internally to produce pretty comparisons between different benchmarks.
Luckily, Stefan H. Muller did much of what is needed to use matplotlib
(non-interactively) with pypy, I have taken over his work and it now
lives in two git repos: https://github.com/mattip/numpy on the pypy-hack
branch, and https://github.com/mattip/matplotlib master branch. These
work, download a nightly pypy,
virtualenv, "setup.py install", but there is some missing
low-lying-fruit kind of functionality to run the benchmarks, again, in
matplotlib.
That is the good news, the bad news is that in a perhaps hasty move, I
removed lib_pypy/numpy.py since it complicates the numpy install. I
fixed tests (one build too late, sorry for the failures), but now people
who were used to a nightly pypy being capable of "import numpy" will be
disappointed.
I did ask on IRC before the change, and got two positive votes, but feel
a need for wider consensus. So should we leave the file out, and
hopefully encourage people to start trying the pypy-hack branch, or put
it back? In an unrelated-but-related issue, should the github repo of
numpy be moved to a more pypy-like place (bitbucket.org/pypy)?
Matti
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