Hi, On Fri, May 15, 2015 at 1:07 PM, Chris Barker <chris.barker@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--lapa.... 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