[Numpy-discussion] binary wheels for numpy?

[Chris Barker - NOAA Federal]

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.brett at gmail.com> wrote:
>
> Hi,
>
>> 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 --
>>
>> 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
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