On Jan 29, 2016 9:46 AM, "Andreas Mueller" <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... :-) 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) -n