alt Hacker NewsThis is silly, there's no killer feature for scientific computing being added to python that would make an existing pypy codebase drop that dependency, getting a code validated takes a long time and dropping something like pypy will require re-valditating the entire thing.
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The phenomena you're describing is why Cobol programmers still exist, and simultaneously, why it's increasingly irrelevant to most programmers
The killer feature is ecosystem: Easily and reliably reusing other libraries and tools that work out-of-the-box with other Python code written in the last few years . There are individually neato features motivating the efforts involved in upgrading a widely-used language & engine as well, but that kind of thinking misses the forest for the trees unfortunately.
It's a bit surprising to me, in the age of AI coding, for this to be a problem. Most features seem friendly to bootstrapping with automation (ex: f-strings that support ' not just "), and it's interesting if any don't fall in that camp. The main discussion seems to still be framed by the 2024 comments, before Claude Code etc became widespread: https://github.com/orgs/pypy/discussions/5145 .
Unfortunately python does add features in a drip-drip kind of way that makes being behind an experience with a lot of niggles. This is particularly the case for the type annotation system, which is retrofit to a language that obviously didn't have one originally. So it's being added slowly in a very conservative way, and there are a lot of limitations and pain points that are gradually being improved (or at least progressed on). The upcoming lazy module loading will also immediately become a sticking point.