[Numpy-discussion] linux wheels coming soon
matthew.brett at gmail.com
Tue Apr 19 03:17:40 EDT 2016
On Mon, Apr 18, 2016 at 2:49 PM, Matthew Brett <matthew.brett at gmail.com> wrote:
> On Sun, Apr 17, 2016 at 9:48 AM, Jens Nielsen <jenshnielsen at gmail.com> wrote:
>> I have tested the new cp27m wheels and they seem to work great.
>> @Matthew I am using the:
>> sudo: required
>> dist: trusty
>> images mentioned here https://docs.travis-ci.com/user/ci-environment/. As
>> far as I can see you are doing:
>> sudo: false
>> dist: trusty
>> I had no idea such an image exist since it's not documented on
>> Anyway your tests runs with python 2.7.9 where as the sudo: requires ships
>> python 2.7.10 so it's clearly a different python version:
>> @Olivier Grisel this only applies to Travis's own home build versions of
>> python 2.7 on the Trusty running on google compute engine.
>> It ships it's own prebuild python version. I don't have any issues with the
>> stock versions on Ubuntu which pip tells me are indeed cp27mu.
>> It seems like the new cp27m wheels works as expected. Thanks a lot
>> python -c "from pip import pep425tags;
>> print(pep425tags.have_compatible_glibc(2, 5));
>> pip install --timeout=60 --no-index --trusted-host
>> numpy scipy --upgrade
>> results in:
>> Ignoring indexes: https://pypi.python.org/simple
>> Collecting numpy
>> 100% |████████████████████████████████| 15.3MB 49.0MB/s
>> Collecting scipy
>> 100% |████████████████████████████████| 39.5MB 21.1MB/s
>> Installing collected packages: numpy, scipy
>> Found existing installation: numpy 1.10.1
>> Uninstalling numpy-1.10.1:
>> Successfully uninstalled numpy-1.10.1
>> Successfully installed numpy-1.11.0 scipy-0.17.0
>> And all my tests pass as expected.
> Thanks for testing.
I've also tested a range of numpy and scipy wheels built with the
manylinux docker image.
Built numpy and scipy wheels here:
Test script and output here:
There are some test failures in the logs there, but I think they are
all known failures from old numpy / scipy versions, particularly
Y'all can test for yourselves with something like:
python -m pip install -U pip
pip install -f https://nipy.bic.berkeley.edu/manylinux numpy==1.6.2
I propose to upload these historical wheels to pypi to make it easier
to test against older versions of numpy / scipy.
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