JITs are big nasty things that by their nature have to do a lot of things. You are basically saying "Give us a PEP for a new python interpreter and compiler".
What they do is fuzzy by their nature because optimizations are very rarely universally beneficial. It's a game of measuring, looking for regressions, and tackling the biggest problem next for whatever sample applications you have available. You always run into the risk of overfitting on top of all that (You may have made django faster, but you've made flask slower).
This is the sort of thing that, IMO, should not go through the PEP process. It's an implementation detail for the runtime.
Imagine, for example, if the JVM needed a bunch of JEPs for JIT improvements. They'd never get done. Or if any javascript engine needed ECMA acceptance before they could do a new JIT optimization.
They do:
Not every optimization requires a JEP, but certainly something as big as "add or remove a JIT" would 100% require a JEP.
FWIW, I definitely can find a bunch of both PEPs and JEPs for internal optimizations, random examples:
1. An outsider to the regular OpenJDK dev team proposing an optimization.
2. Advertising for a cool new performance tweak with potentially large impact.
You'll also notice that the JEP descriptions are very different from PEP descriptions.
Probably the largest JEP for the JVM, Valhalla
Does not have the same level of requirements being asked of the Python JIT. Further, it's well understood that this JEP will "live on main" for quite some time in preview before it's accepted and merged.
What the JEP does, instead, is simply describe the feature and potential risks.
The vast majority of JVM optimizations do not get a JEP.
> The vast majority of JVM optimizations do not get a JEP.
In Python too. Still, the JIT really is just a really big thing. I don’t know if there could be a better way to do it, as either 1. You develop it off-branch and… make an enormous PR when you’re done, with risks of getting rejected anyway? Or 2, you allow more experiments on main like Rust, but then you end up with hundreds of minor half-maintained nightly-only features, possibly conflicting with each other, and eventually go through bureaucracy to remove them anyway.
The Java governance allows for a lot more open ended projects with follow ups. Not that it's reckless, Valhalla is proof of that, but rather that once something is good enough they are pretty open to just shipping it as a preview feature and refining until it is worthy of being stable.
That's why, for example, we saw ZGC get merged, and then JDK after JDK seeing continuing development and improvement on ZGC (Or G1 for that matter). These GCs were fairly rough on their first release and now they are pretty much best in class.
I see a Python JIT as the same thing. Delivering the infrastructure for a JIT would need a PIP, but I wouldn't put in things like "acceptance criteria" beyond "doesn't break older code". I would expect such a project to get continual updates without PEPs.
Just for completeness: the original JIT PR was merged quite enthusiastically and only after the fact it was pointed out that it should have went through a PEP process [1]. The following PEP 744 was of the “informational” type, and the just-withdrawn PEP 836 was the first “standards track” PEP, which means that (in my understanding) it’s technically the first actual PEP that the SC would formally comment on. So in a way it’s not “can we update the JIT” PEP, but the first real “does SC want this JIT as proposed” PEP.
That said, I do agree with most of what you said, especially the acceptance criteria part.
The issue I have and find it hard to resolve is that since the code was already on main, the feature was already in “sunk cost” mode. It’s hard when the code is already on main and another 3 optimization PRs are always there behind the corner, but it needs to be possible for SC to say “we decided it’s not actually worth all this complexity for <some small number>% speed improvement” (I’m not commenting whether in this particular case it’d have been a right call), and the PEP (if not withdrawn) was the way to exercise that control.
[1] https://github.com/python/cpython/pull/113465#issuecomment-1...
And even then, Hotspot did not got a JSR, because all that work was done before Sun started collaborating with industry partners for Java evolution.
They "simply" ported the JIT compiler from the Strongtalk acquisition into Java.
Zero chance of shoehorning that into a standards-compliant Python runtime. Some things are too fundamental to change without affecting the user-visible language: JITting, lazy imports, threading, copying gc, ref counting, etc.
Dunno how much investment is needed into language optimization anymore.
A fairly massive undertaking for existing code, which jit was supposed to be useful for.
Which honestly, is the right approach.
Because having just the hot loop in the performant language is often deemed good enough. And there's tons of Python code out there where the "hot loop" is already automatically in C (the various operations implemented in C by the runtime) or where you can get close enough e.g. with Numpy. Consider that things like Pygame can exist; for a lot of the games people want to make, the only thing that really needs to happen anywhere near "bare-metal" speed is blitting.
It was done plenty. Just with extensions to python like numpy and opencv. There is no reason to translate everything versus just the critical pieces.