[crote]

More specifically, the Scientific Python community through SPEC 0[0] recommends that support for Python versions is dropped three years after their release. Python 3.12 was released in October 2023[1], so that community is going to drop support for it in October 2026.

Considering that PyPy is only just now starting to seriously work on supporting 3.12, there's a pretty high chance that it won't even be ready for use before becoming obsolete. At that point it doesn't even matter whether you want to call it "in active development", it is simply too far behind to be relevant.

[0]: https://scientific-python.org/specs/spec-0000/

[1]: https://www.python.org/downloads/release/python-3120/

[apelapan]

What's the point of a three year window? It seems like a weird middle-point. Either you are in a position to choose/install your own interpreter and libraries or you are not.

If you can choose your own versions and care at all about new releases, you can track latest and greatest with at the very most a few months of lag. Six months of "support" is luxurious in this scenario.

If you can't choose your own versions, you are most likely stuck on some sort of LTS Linux and will need to make do with what they provide. In that case three years is a cruel joke, because almost everything will be more than three years old when it is first deployed in your environment.

[jcattle]

I guess the point of a three year window is to be able as an ecosystem to at some point adopt new language features.

When you have some kind of ecosystem rule for that, you can make these upgrade decisions with a lot more confidence.

For example in my project I have a dependency on zstandard. In 3.14 zstandard was added to the standard library. With this ecosystem wide 3 year support cycle I can in good confidence drop the dependency in three years and use the standard lib from then on.

I feel like it just prevents the ecosystem from going stale because some important core library is still supporting a really old version, thus preventing other smaller libraries from using new language features as well, to not exclude a large user base still on an old version.

[SiempreViernes]

This 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.

[lmeyerov]

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 .

[cozzyd]

The alternative is when you run a script that you last used a few years ago and now need it again for some reason (very common in research) and you might end up spending way too much time making it work with your now upgraded stack.

Sure you can were you should have pinned dependencies but that's a lot of overhead for a random script...

[SiempreViernes]

Most programmers aren't writing scientific software, which you can tell by claims that nicer f-strings is a pressing concern.

[lmeyerov]

We can play that game - items like GIL-free interpreters and memory views are pretty relevant to folks on the more demanding side of scientific computing. But my point is this is a head-in-sand game when the community vastly outweighs any individual feature. My experience with the scientific computing community is that the non-pypy portion of it is much bigger.

I'm not a pypy maintainer, so my only horse in this race is believing cpython folks benefit from seeing the pypy community prove Things Can Be Better. Part of that means I rather pypy live on by avoiding unforced errors.

[ajb]

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.

[quietbritishjim]

They appear to be talking about CPython implementations, taking into account when those versions continue to be sorted (in the sense of security updates). That's irrelevant for PyPy, which clearly supports version numbers on a different schedule.

[ameliaquining]

It's not irrelevant, because if SPEC 0 says that a particular Python version is no longer supported, then libraries that follow it won't avoid language or standard library features that that version doesn't have. And then those libraries won't work in the corresponding PyPy version. If there isn't a newer PyPy version to upgrade to, then they won't work in PyPy at all.

[Wowfunhappy]

You might make a different decision if you were targeting PyPy.