I do understand the issues around ABI breakage. I just want to speak up for the people who are affected by API breakage who are not as vocal on this list. I believe we should have similar frustration and concern at talk of API breakage as there is about talk of ABI breakage.
-Travis On Jun 27, 2012, at 12:59 AM, Fernando Perez wrote: > On Tue, Jun 26, 2012 at 10:25 PM, Ralf Gommers > <ralf.gomm...@googlemail.com> wrote: >> >> On Tue, Jun 26, 2012 at 5:33 AM, Travis Oliphant <tra...@continuum.io> >> wrote: >> ... >>> >>> What should have happened in this case, in my mind, is that NumPy 1.4.0 >>> should have been 1.5.0 and advertised that there was a break in the ABI and >>> that all extensions would have to be re-built against the new version. >>> This would have been some pain for one class of users (primarily package >>> maintainers) and no pain for another class. >> >> >> Please please stop asserting this. It's plain wrong. It has been explained >> to you multiple times by multiple people how bad the consequences of >> breaking the ABI are. It leads to random segfaults when existing installers >> are not updated or when users pick the wrong installer by accident (which >> undoubtedly some will). It also leads to a large increase in the number of >> installers that maintainers for every single package that depends on numpy >> will have to build. Including for releases they've already made in the past. > > An additional perspective on the issue of ABI breakage: even for those > of us who live in a distro-managed universe (ubuntu in my case), the > moment numpy breaks ABI means that it becomes *much* harder to use the > new numpy because I'd have to start recompiling all binary > dependencies, some of which are not pleasant to start rebuilding (such > as VTK for mayavi). So that means I'm much less likely to use an > ABI-incompatible numpy for everyday work, and therefore less likely to > find bugs, report them, etc. I typically run dev versions of numpy, > scipy and matplotlib all the time, except when numpy breaks ABI, > which means I have to 'pin' numpy to the system one and only update > the others. > > Now, obviously that doesn't mean that ABI can never be broken, but > it's just another data point for you as you evaluate the cost of ABI > breakage. It is significant even for those who operate under the > benefit of managed packages, because numpy is effectively the root > node of the dependency tree for virtually all scientific python > packages. > > I hope this is useful as additional data on the issue. > > Cheers, > > f > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
