On Thu, Feb 16, 2017 at 3:55 AM, Ralf Gommers <ralf.gomm...@gmail.com>

> On Thu, Feb 16, 2017 at 3:53 PM, Sandro Tosi <mo...@debian.org> wrote:
>> > A recent post to the wheel-builders mailing list pointed out some
>> > links to places providing free PowerPC hosting for open source
>> > projects, if they agree to a submitted request:
>> The debian project has some powerpc machines (and we still build numpy
>> on those boxes when i upload a new revision to our archives) and they
>> also have hosts dedicated to let debian developers login and debug
>> issues with their packages on that architecture. I can sponsor access
>> to those machines for some of you, but it is not a place where you can
>> host a CI instance.
>> Just keep it in mind more broadly than powerpc, f.e. these are all the
>> archs where numpy was built after the last upload
>> https://buildd.debian.org/status/package.php?p=python-numpy&;
>> suite=unstable
>> (the grayed out archs are the ones non release critical, so packages
>> are built as best effort and if missing is not a big deal)
> Thanks Sandro. It looks like even for the release-critical ones, it's just
> the build that has to succeed and failures are not detected? For example,
> armel is green but has 9 failures: https://buildd.debian.org/stat
> us/fetch.php?pkg=python-numpy&arch=armel&ver=1%3A1.12.0-2&
> stamp=1484889563&raw=0
> Ralf

More general questions on this:

Are there any overviews over which packages in the python for science or
python for data anlaysis areas work correctly on different platforms:
Are there any platforms/processors, besides the standard x32/x54, where
this is important?

for example for statsmodels:
In early releases of statsmodels, maybe 5 to 7 years ago, Yarik and I were
still debugging problems on several machines like ppc and s390x during
Debian testing. Since then I haven't heard much about specific problems.
The current status for statsmodels on Debian machines is pretty mixed. In
several of them some dependencies are not available, in some cases we have
errors that might be caused by errors in dependencies, e.g. cvxopt.

ppc64el test run for statsmodels has a large number of failure
but checking scipy, it looks like it's also not working properly

In those cases it would be impossible to start debugging, if we would have
to debug through the entire dependency chain.

CI-testing for Windows, Apple and Linux for mainly x64 seems to be working
pretty well, with some delays while version incompatibilities are fixed.
But anything that is not in a CI testing setup looks pretty random to me.

(I'm mainly curious what the status for those machines are. I'm not really
eager to create more debugging work, but sometimes failures on a machine
point to code that is "fragile".)


> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> https://mail.scipy.org/mailman/listinfo/numpy-discussion
NumPy-Discussion mailing list

Reply via email to