Thanks for the update Matthew, it's great to see so much activity on this issue.
Looks like we are headed in the right direction --and getting close. Thanks to all that are putting time into this. -Chris > On May 15, 2015, at 1:37 PM, Matthew Brett <matthew.br...@gmail.com> wrote: > > Hi, > >> On Fri, May 15, 2015 at 1:07 PM, Chris Barker <chris.bar...@noaa.gov> wrote: >> Hi folks., >> >> I did a little "intro to scipy" session as part of a larger Python class the >> other day, and was dismayed to find that "pip install numpy" still dosn't >> work on Windows. >> >> Thanks mostly to Matthew Brett's work, the whole scipy stack is >> pip-installable on OS-X, it would be really nice if we had that for Windows. >> >> And no, saying "you should go get Python(x,y) or Anaconda, or Canopy, or...) >> is really not a good solution. That is indeed the way to go if someone is >> primarily focusing on computational programming, but if you have a web >> developer, or someone new to Python for general use, they really should be >> able to just grab numpy and play around with it a bit without having to >> start all over again. >> >> >> My solution was to point folks to Chris Gohlke's site -- which is a Fabulous >> resource -- >> >> THANK YOU CHRISTOPH! >> >> But I still think that we should have the basic scipy stack on PyPi as >> Windows Wheels... >> >> IIRC, the last run through on this discussion got stuck on the "what >> hardware should it support" -- wheels do not allow a selection at installc >> time, so we'd have to decide what instruction set to support, and just stick >> with that. Which would mean that: >> >> some folks would get a numpy/scipy that would run a bit slower than it might >> and >> some folks would get one that wouldn't run at all on their machine. >> >> But I don't see any reason that we can't find a compromise here -- do a >> build that supports most machines, and be done with it. Even now, people >> have to go get (one way or another) a MKL-based build to get optimum >> performance anyway -- so if we pick an instruction set support by, say (an >> arbitrary, and impossible to determine) 95% of machines out there -- we're >> good to go. >> >> I take it there are licensing issues that prevent us from putting Chris' >> Binaries up on PyPi? > > Yes, unfortunately we can't put MKL binaries on pypi because of the > MKL license - see > https://github.com/numpy/numpy/wiki/Numerical-software-on-Windows#blas--lapack-libraries. > Also see discussion in the containing thread of > http://mail.scipy.org/pipermail/numpy-discussion/2014-March/069701.html > . > >> But are there technical issues I'm forgetting here, or do we just need to >> come to a consensus as to hardware version to support and do it? > > There has been some progress on this - see > > https://github.com/scipy/scipy/issues/4829 > > I think there's a move afoot to have a Google hangout or similar on > this exact topic : > https://github.com/scipy/scipy/issues/2829#issuecomment-101303078 - > maybe we could hammer out a policy there? Once we have got numpy and > scipy built in a reasonable way, I think we will be most of the way > there... > > Cheers, > > Matthew > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion