On Wed, Jan 29, 2014 at 2:04 PM, David Cournapeau <cournape@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.

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.org binary 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".

-Chris

Just to clarify: you actually can install numpy on windows with python.org installers fairly easily by using easy_install already (we upload a bdist_wininst compatible binary which should not use any CPU-specific instructions). It looks like those are missing for 1.8.0, but we can fix this fairly easily.

presumably just as easy to do a binary wheel then -- I vote for that.

-Chris

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