On Mon, May 12, 2008 at 10:02 AM, Christopher Hanley <[EMAIL PROTECTED]> wrote: > One circumstance in which you would need to upgrade is if you distribute > software with a numpy dependency. If your user base upgrades to the > latest numpy release, and that latest release breaks your code, you will > have unhappy users.
I see, the issue is whether you(plural) will need to update your code base to support your users who may have updated to a new NumPy/SciPy release. This concern really goes to whether we should ever break code with our releases, which is orthogonal to whether we should try using a time-based release cycle. It is very clear that our users are not happy with the amount of API breaks in 1.1. All I can say, is that I am sorry that the current release is going to break some code bases out there. I am trying to figure out if there is a way to mitigate the problems caused by this release and would be happy to hear comments about how we could best reduce the problems caused by this release. In particular, it would be useful if I could get some feedback on my suggestion about the MA transition. Thanks, -- Jarrod Millman Computational Infrastructure for Research Labs 10 Giannini Hall, UC Berkeley phone: 510.643.4014 http://cirl.berkeley.edu/ _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
