On Jan 29, 2016 9:46 AM, "Andreas Mueller" <t3k...@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
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