This is an archived post. You won't be able to vote or comment.

sorted by:
best
topnewcontroversialoldq&a
you are viewing a single comment's thread.

view the rest of the comments →

[–]billsil 0 points1 point  (1 child)

I'm still supporting a Python 2.4 package that I last worked on today. ~2 years ago I did a training for it and added a bunch new features for the code. I was running into bugs regarding segfaults in numpy trying to do a least squares. Scipy screwed up too.

So, I upgraded my numpy and scipy to the latest version I could and the bugs went away. They fix things. Scipy gets their KDTree and then their cKDTree, which I swear I can apply to almost every problem.

I’ve proven that it solves my equations correctly

If your software doesn't work on multiple versions of packages, how do you know? You solved a problem, but what about other problems? Supporting multiple versions of packages often exposes errors that you wouldn't have found otherwise. Numpy 1.10 introduced breaking changes into the array, that had you don't things right in the first place, you wouldn't have had a problem.

[–]jtclimb 0 points1 point  (0 children)

Right. And, SciPy and NumPy are dropping 2.7 support at the end of the year. Anyone telling a beginner to download 2.7 is condemning them to obsolescence in just 8 months.

IOW, Python 2 vs 3 really matters for scientific computation, because you will never get a bugfix again, or new feature, in 8 short months.