[Distutils] pip on windows experience

[David Cournapeau]

On Wed, Jan 29, 2014 at 10:27 PM, Chris Barker <chris.barker at noaa.gov>wrote:

> On Wed, Jan 29, 2014 at 2:04 PM, David Cournapeau <cournape at gmail.com>wrote:
>
>> I think the SSE issue is a bit of a side discussion: most people who care
>> about performance already know how to install numpy. What we care about
>> here are people who don't care so much about fast eigenvalue decomposition,
>> but want to use e.g. pandas. Building numpy in a way that supports every
>> architecture is both doable and acceptable IMO.
>>
>
> Exactly -- I'm pretty sure SSE2 is being suggested because that's the
> lowest common denominator that we expect to see a lot of -- if their really
> are a lot of non-SSE-2 machines out there we could leave that off, too.
>

The failure mode is fairly horrible though, and the gain is not that
substantial anyway compared to really optimized installation (MKL, etc...
as provided by Continuum or us).


> Building numpy wheels is not hard, we can do that fairly easily (I have
>> already done so several times, the hard parts have nothing to do with wheel
>> or even python, and are related to mingw issues on win 64 bits).
>>
>
> David,
>
> Where is numpy as with building "out of the box" with the python.orgbinary for Windows, and the "standard" MS compilers that are used with
> those builds. That used to be an easy "python setup.py install" away -- has
> that changed? If so, is this a known bug, or a known
> we-aren't-supporting-that?
>
> i.e. it would be nice if anyone setup to build C extensions could "just
> build numpy".
>

This has always been possible, and if not, that's certainly considered as a
bug (I would be eager to fix).

Numpy is actually fairly easy to build if you have a C Compiler (which is
the obvious pain point on windows). Scipy, and fortran is where things fall
apart.

David
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