On Sat, Feb 6, 2016 at 9:28 PM, Nadav Horesh wrote:
> Test platform: python 3.4.1 on archlinux x86_64
>
> scipy test: OK
>
> OK (KNOWNFAIL=97, SKIP=1626)
>
>
> numpy tests: Failed on long double and int128 tests, and got one error:
>
> Traceback (most recent call last):
> File "/usr/lib/python3.
Test platform: python 3.4.1 on archlinux x86_64
scipy test: OK
OK (KNOWNFAIL=97, SKIP=1626)
numpy tests: Failed on long double and int128 tests, and got one error:
Traceback (most recent call last):
File "/usr/lib/python3.5/site-packages/nose/case.py", line 198, in runTest
self.test(*sel
On Sa, 2016-02-06 at 16:56 -0600, Elliot Hallmark wrote:
> Hi all,
>
> I have a program that uses resize-able arrays. I already over
> -provision the arrays and use slices, but every now and then the data
> outgrows that array and it needs to be resized.
>
> Now, I would like to have these arr
Robert,
Thanks for pointing out auditwheel. We're experimenting with a GCC 5.2
toolchain, and this tool will be invaluable.
Chris,
Both conda-build-all and obvious-ci are excellent projects, and we'll
leverage them where we can (particularly conda-build-all). Obvious CI and
conda-smithy are in
On Sat, Feb 6, 2016 at 3:42 PM, Michael Sarahan wrote:
> FWIW, we (Continuum) are working on a CI system that builds conda recipes.
>
great, could be handy. I hope you've looked at the open-source systems that
do this: obvious-ci and conda-build-all. And conda-smithy to help set it
all up..
Chr
> (we've had a few recent issues with libgfortran accidentally missing as a
requirement of scipy).
On this topic, you may be able to get some milage out of adapting
pypa/auditwheel, which can load
up extension module `.so` files inside a wheel (or conda package) and walk
the shared library depende
FWIW, we (Continuum) are working on a CI system that builds conda recipes.
Part of this is testing not only individual packages that change, but also
any downstream packages that are also in the repository of recipes. The
configuration for this is in
https://github.com/conda/conda-recipes/blob/mas
On Fri, Feb 5, 2016 at 3:24 PM, Nathaniel Smith wrote:
> On Fri, Feb 5, 2016 at 1:16 PM, Chris Barker
> wrote:
>
> >> > If we set up a numpy-testing conda channel, it could be used to cache
> >> > binary builds for all he versions of everything we want to test
> >> > against.
> Anaconda does
Hi all,
I have a program that uses resize-able arrays. I already over-provision
the arrays and use slices, but every now and then the data outgrows that
array and it needs to be resized.
Now, I would like to have these arrays shared between processes spawned via
multiprocessing (for fast interpr
Hi,
As some of you may have seen, Robert McGibbon and Nathaniel have just
guided a PEP for multi-distribution Linux wheels past the approval
process over on distutils-sig:
https://www.python.org/dev/peps/pep-0513/
The PEP includes a docker image on which y'all can build wheels which
match the PE
=
Announcing Numexpr 2.5
=
Numexpr is a fast numerical expression evaluator for NumPy. With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.
It wears multi-threa
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