[Numpy-discussion] binary wheels for numpy?

Matthew Brett matthew.brett at gmail.com
Fri May 15 16:35:36 EDT 2015


On Fri, May 15, 2015 at 1:07 PM, Chris Barker <chris.barker at 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 --
> 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
Also see discussion in the containing thread of

> 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


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



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