The release of NumPy 1.9 a few days ago was a bit of a revelation for me. For the first time in the combined history of NumPy and its predecessor Numeric, a new release broke my own code so severely thatI don't see any obvious way to fix it, given the limited means I can dedicate to software maintenance. And that makes me wonder for which scientific uses today's Python ecosystem can still be recommended, since the lack of means for code maintenance is a chronic and endemic problem in science.
