On 12/6/2013 12:40 PM, David Cournapeau wrote: > > > > On Fri, Dec 6, 2013 at 8:38 PM, Christoph Gohlke <[email protected] > <mailto:[email protected]>> wrote: > > On 12/6/2013 10:06 AM, Ralf Gommers wrote: > > 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/#%21topic/numfocus/mVNakFqfpZg> > > <https://groups.google.com/forum/#%21topic/numfocus/mVNakFqfpZg> > >https://groups.google.com/forum/#!topic/numfocus/HUcwXTM_jNY > <https://groups.google.com/forum/#%21topic/numfocus/HUcwXTM_jNY> > > <https://groups.google.com/forum/#%21topic/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? > > > > > > Has anyone succeeded building wheels for numpy, scipy, and matplotlib? > > > I did for numpy and scipy. You had to hack a bit numpy.distutils to make > it work for scipy,but nothing that would be too complicated to really fix. > > In your case, the trick is to use the setupegg file: python setupegg.py > bdist_wheel > > David >
Thank you. The setupegg.py trick worked. Could the numpy.distutils hack be applied to the numpy 1.8.x and master branches? I'll try to fix the matplotlib issue. Christoph _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
