Discussion:
Binary wheel packages for Linux are coming
(too old to reply)
Olivier Grisel
2016-04-03 20:26:51 UTC
Permalink
Hi all,

Over the past couple of days Nathaniel Smith, Robert McGibbon, Matthew
Brett and I did a bunch of testing and bug fixing to get a working
build environment to generate binary packages for cython, numpy,
scipy, numpexpr, pandas, scikit-learn and statsmodels using an
embedded OpenBLAS 0.2.17 on Linux (only x86_64 and i686 platforms).

Here is Matthew's call to tests of the resulting packages on the numpy
mailing list:

https://mail.scipy.org/pipermail/numpy-discussion/2016-April/075234.html

You need pip 8.1 or later to install them (they are ignored by
previous versions of pip).

Please test those wheels on your machines, especially if you run
exotic Linux versions or less common CPU architectures.

If nobody has an objection I plan to upload the wheels for
scikit-learn 0.17.1 to PyPI as soon as numpy and scipy have their own
wheel packages uploaded there (probably during the coming week if no
blocker is reported in the mean time).

For those interested in the technical details, here are the tools that
we use to generate those wheels:

- manylinux is the official docker image that is used to build the
original wheels from source for
various versions of Python a controlled binary environment (based on
Centos 5.11 and gcc/g++/gfortran 4.8).
- auditwheel is a Python program to embed compiled dependencies into
the wheel (e.g. libopenblas.so)
https://github.com/pypa/auditwheel
- Matthew's script to build wheels for the last releases of the scipy
stack projects "en masse":
https://github.com/matthew-brett/manylinux-builds/

The manylinux1 platform tag it-self is documented in:
https://www.python.org/dev/peps/pep-0513/

Note that those wheels will not install on Alpine Linux or any other
Linux distribution that does not use glibc. Alpine Linux in particular
uses MUSL libc.

Happy testing!
--
Olivier
http://twitter.com/ogrisel - http://github.com/ogrisel
Olivier Grisel
2016-04-13 21:52:22 UTC
Permalink
OpenBLAS 0.2.18 has been released yesterday with many fixes several
bugs found via testing the scipy stack on:

https://build.openblas.net/

Matthew Brett did a full-rebuild of BLAS dependent projects (including
numpy, scipy and scikit-learn) and the resulting wheels are being
uploaded to PyPI.

On most Linux distros you can now already do:

python -m pip install --upgrade pip # to upgrade to 8.1 or later
python -m pip install numpy scipy scikit-learn

And get the stack installed with an optimized BLAS/LAPACK without
having to compile anything.

Next I will work on updating our CI configuration to build and test
those wheels on our master branch and for future release tags.

Best,
--
Olivier
Andy
2016-04-13 22:58:00 UTC
Permalink
AMAZING!
Post by Olivier Grisel
OpenBLAS 0.2.18 has been released yesterday with many fixes several
https://build.openblas.net/
Matthew Brett did a full-rebuild of BLAS dependent projects (including
numpy, scipy and scikit-learn) and the resulting wheels are being
uploaded to PyPI.
python -m pip install --upgrade pip # to upgrade to 8.1 or later
python -m pip install numpy scipy scikit-learn
And get the stack installed with an optimized BLAS/LAPACK without
having to compile anything.
Next I will work on updating our CI configuration to build and test
those wheels on our master branch and for future release tags.
Best,
Gael Varoquaux
2016-04-14 07:18:34 UTC
Permalink
Yeah! That's really really really useful. Thanks a lot to everybody
involved for this.

G
Post by Andy
AMAZING!
Post by Olivier Grisel
OpenBLAS 0.2.18 has been released yesterday with many fixes several
https://build.openblas.net/
Matthew Brett did a full-rebuild of BLAS dependent projects (including
numpy, scipy and scikit-learn) and the resulting wheels are being
uploaded to PyPI.
python -m pip install --upgrade pip # to upgrade to 8.1 or later
python -m pip install numpy scipy scikit-learn
And get the stack installed with an optimized BLAS/LAPACK without
having to compile anything.
Next I will work on updating our CI configuration to build and test
those wheels on our master branch and for future release tags.
Best,
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Bertrand Thirion
2016-04-14 07:14:49 UTC
Permalink
Fantastic ! thanks,

Bertrand


----- Mail original -----
Envoyé: Mercredi 13 Avril 2016 23:52:22
Objet: Re: [Scikit-learn-general] Binary wheel packages for Linux are coming
OpenBLAS 0.2.18 has been released yesterday with many fixes several
https://build.openblas.net/
Matthew Brett did a full-rebuild of BLAS dependent projects (including
numpy, scipy and scikit-learn) and the resulting wheels are being
uploaded to PyPI.
python -m pip install --upgrade pip # to upgrade to 8.1 or later
python -m pip install numpy scipy scikit-learn
And get the stack installed with an optimized BLAS/LAPACK without
having to compile anything.
Next I will work on updating our CI configuration to build and test
those wheels on our master branch and for future release tags.
Best,
--
Olivier
------------------------------------------------------------------------------
Find and fix application performance issues faster with Applications Manager
Applications Manager provides deep performance insights into multiple tiers
of
your business applications. It resolves application problems quickly and
reduces your MTTR. Get your free trial!
https://ad.doubleclick.net/ddm/clk/302982198;130105516;z
_______________________________________________
Scikit-learn-general mailing list
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