On 01/30/2016 06:27 PM, Ralf Gommers wrote:
>
>
> On Fri, Jan 29, 2016 at 11:39 PM, Nathaniel Smith <njs@pobox.com
> <mailto:njs@pobox.com>> wrote:
>
> It occurs to me that the best solution might be to put together a
> .travis.yml for the release branches that does: "for pkg in
> IMPORTANT_PACKAGES: pip install $pkg; python -c 'import pkg;
> pkg.test()'"
> This might not be viable right now, but will be made more viable if
> pypi starts allowing official Linux wheels, which looks likely to
> happen before 1.12... (see PEP 513)
>
> On Jan 29, 2016 9:46 AM, "Andreas Mueller" <t3kcit@gmail.com
It would be nice but its not realistic, I doubt most upstreams that are> <mailto:t3kcit@gmail.com>> wrote:
> >
> > Is this the point when scikit-learn should build against it?
>
> Yes please!
>
> > Or do we wait for an RC?
>
> This is still all in flux, but I think we might actually want a rule
> that says it can't become an RC until after we've tested
> scikit-learn (and a list of similarly prominent packages). On the
> theory that RC means "we think this is actually good enough to
> release" :-). OTOH I'm not sure the alpha/beta/RC distinction is
> very helpful; maybe they should all just be betas.
>
> > Also, we need a scipy build against it. Who does that?
>
> Like Julian says, it shouldn't be necessary. In fact using old
> builds of scipy and scikit-learn is even better than rebuilding
> them, because it tests numpy's ABI compatibility -- if you find you
> *have* to rebuild something then we *definitely* want to know that.
>
> > Our continuous integration doesn't usually build scipy or numpy, so it will be a bit tricky to add to our config.
> > Would you run our master tests? [did we ever finish this discussion?]
>
> We didn't, and probably should... :-)
>
> Why would that be necessary if scikit-learn simply tests pre-releases of
> numpy as you suggested earlier in the thread (with --pre)?
>
> There's also https://github.com/MacPython/scipy-stack-osx-testing by the
> way, which could have scikit-learn and scikit-image added to it.
>
> That's two options that are imho both better than adding more workload
> for the numpy release manager. Also from a principled point of view,
> packages should test with new versions of their dependencies, not the
> other way around.
not themselves major downstreams are even subscribed to this list.
Testing or delegating testing of least our major downstreams should be
the job of the release manager.