[Numpy-discussion] distributing wheels & SSE/superpack options

[Ralf Gommers]

Hi all,

There are a few discussions on packaging for the scientific Python stack
ongoing, on the NumFOCUS and distutils lists:
https://groups.google.com/forum/#!topic/numfocus/mVNakFqfpZg
https://groups.google.com/forum/#!topic/numfocus/HUcwXTM_jNY
http://thread.gmane.org/gmane.comp.python.distutils.devel/20202
http://thread.gmane.org/gmane.comp.python.distutils.devel/20296

One of the things that we should start doing for numpy is distribute
releases as wheels. On OS X at least this is quite simple, so I propose to
just experiment with it. I can create some to try out and put them on a
separate folder on SourceForge. If that works they can be put on PyPi.

For Windows things are less simple, because the wheel format doesn't handle
the multiple builds (no SSE, SSE2, SSE3) that are in the superpack
installers. A problem is that we don't really know how many users still
have old CPUs that don't support SSE3. The impact for those users is high,
numpy will install but crash (see https://github.com/scipy/scipy/issues/1697).
Questions:
1. does anyone have a good idea to obtain statistics?
2. in the absence of statistics, can we do an experiment by putting one
wheel up on PyPi which contains SSE3 instructions, for python 3.3 I
propose, and seeing for how many (if any) users this goes wrong?

Ralf

P.S. related question: did anyone check whether the recently merged
NPY_HAVE_SSE2_INTRINSIC puts SSE2 instructions into the no-SSE binary?
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