The state of NumPy

Konrad Hinsen's Blog

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.

I’ll start with a historical review, for which I am particularly well placed as one of the oldtimers in the community: I was a founding member of the Matrix-SIG, a small group of scientists who in 1995 set out to use the still young Python language for computational science, starting with the design and implementation of a module…

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