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much respect to the PyPy contributors, but it seems like a pretty fair assessment
9 months since the last major release definitely feels like a short time in which to declare time-of-death on an open source project
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I'm not sure "major versions" is the most correct term here, but I think your point is spot on
For Python, 0.1 increases are major versions and 1.0 increases are cataclysmic shifts.
If anyone else is also barely aware and confused by the similar names, PyPI is the Python Package Index, which is up and maintained. PyPy is "A fast, compliant alternative implementation of Python." which doesn't have enough devs to release a version for 3.12[0]. [0]: https://github.com/orgs/pypy/discussions/5145
The short summary of it being that these people are beyond terrible at giving names to things.
What annoys me is the name. Early morning it took me a moment to realise that PyPy is not PyPi, so at first I thought they referred to PyPi. Really, just for the name confusion alone, one of those two should have to go. Edit: I understand the underlying issue and the PyPy developer's opinion. I don't disagree on that part; I only refer to the name similarity as a problem.
Still, at its core, PyPy is a Python interpreter which is itself written in Python and the name PyPy fittingly describes its technical design.
Odd how you still see announcements of this nature if Anthropic's marketing is be believed.
Yup. For me the biggest signifier is Spotify. They claim their (best) devs don't even code anymore, they use an internal AI tool that they just send prompts to which then checks out a personal test build that they can download off of Slack. "A new feature in 10 minutes!" Okay, if that is the case, why have we only seen like 3-4 minor new QoL improvements in Spotify the last ~12 months, with no new grand features? And…
No, they claimed they didn’t code during a time period. Around year end until early this year. Technically they could have just been on leave.
Also best dev = principal / staff engineers. They rarely code anyway.
AI or no AI anyone could have made that claim.
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Third party libraries like SciPy scikit-learn, pandas, tensorflow and pytorch have been critical to python’s success. Since CPython is written in C and exposes a nice C API, those libraries can leverage it to quickly move from (slow) python to (fast) C/C++, hitting an optimum between speed of development and speed of runtime. PyPy’s alternative, CFFI, was not attractive enough for the big players to adopt. And HPy, a…
PyPy on numpy heavy code is often a lot slower than CPython
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They don’t need to throw a stack of cash at them, Anthropic and OpenAI have programs for open source maintainers. https://claude.com/contact-sales/claude-for-oss https://openai.com/form/codex-for-oss/
I'd say they're less of "programs" as they are "six-month trials". What's the plan after six months? And for what's it worth, PyPy isn't even eligible for the Claude trial because they have a meager 1700 stars on GitHub.
wow, that would be a big shame. I hope many of the useful learnings are already ported to CPython.
And more
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For Python, 0.1 increases are major versions and 1.0 increases are cataclysmic shifts.
I don't know about that. For me, f-strings were the last great quality-of-life improvement that I wouldn't want to live without, and those landed in Python 3.6. Everything after that has not really made much of a difference to me.
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Most maintainers don't have a stack of cash to throw at tokens.
They don’t need to throw a stack of cash at them, Anthropic and OpenAI have programs for open source maintainers. https://claude.com/contact-sales/claude-for-oss https://openai.com/form/codex-for-oss/