On 24 January 2014 06:25, Thomas Heller <thel...@ctypes.org> wrote:
> Am 23.01.2014 19:52, schrieb Ralf Gommers:
>> On Thu, Jan 23, 2014 at 3:42 PM, Oscar Benjamin
>> <oscar.j.benja...@gmail.com <mailto:oscar.j.benja...@gmail.com>> wrote:
>>
>>     On Thu, Jan 23, 2014 at 12:16:02PM +0000, Paul Moore wrote:
>>      >
>>      > The official numpy installer uses some complex magic to select the
>>      > right binaries based on your CPU, and this means that the official
>>      > numpy "superpack" wininst files don't convert (at least I don't
>> think
>>      > they do, it's a while since I tried).
>>
>>     It's probably worth noting that numpy are toying around with wheels
>> and
>>     have uploaded a number of them to PyPI for testing:
>>     http://sourceforge.net/projects/numpy/files/wheels_to_test/
>>
>>     Currently there are only OSX wheels there (excluding the puer Python
>>     ones) and they're not available on PyPI. I assume that they're waiting
>>     for a solution for the Windows installer (a post-install script for
>>     wheels). That would give a lot more impetus to put wheels up on PyPI.
>>
>>
>> Indeed. We discussed just picking the SSE2 or SSE3 build and putting
>> that up as a wheel, but that was deemed a not so great idea:
>> http://article.gmane.org/gmane.comp.python.numeric.general/56072
>
>
> Did I say this before?  I would suggest that numpy develops a way
> where all the SSE binary variations would be installed, and the
> appropriate ones be loaded at runtime, depending on the user's CPU
> capabilities.  This would also allow py2exe'd distributions to include
> them all.

I believe I suggested that at one point, but the dependencies were
scattered throughout NumPy rather than being in one place (so you had
to toggle several modules, rather than just one), and it made for some
interesting build problems further up the stack.

Agreed that runtime selection would be better, though - the current
approach not only makes it difficult to do things like create
universal py2exe and wheel binaries, it also makes it difficult to run
NumPy from portable media like a USB key, because different systems
may need different SSE modules.

Cheers,
Nick.

-- 
Nick Coghlan   |   ncogh...@gmail.com   |   Brisbane, Australia
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