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> wrote:
Yes please!
>
> Is this the point when scikit-learn should build against it?> 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.
We didn't, and probably should... :-)
> Would you run our master tests? [did we ever finish this discussion?]