Comment by graemep
1 day ago
If you look at the reasons for this it seems like a good decision: https://discuss.python.org/t/pep-836-jit-go-brrr-the-path-to...
There are already many way of addressing Python performance (leaving aside whether Python is a good choice if performance matters) such as Cython, Numba, Pypy and C extensions.
The problem with PyPy, which I'm a huge fan of BTW, is it's on life-support. The only reason the past couple major versions were released was due to a few small companies or individuals directly implementing the updates themselves. That's my understanding at least. It's disheartening because I've been primarily using PyPy for 5 years, advocated for it, and was looking into contributing more to it before finding out about its state.
Perhaps if the money which was spent on the built-in JIT had been spent on PyPy we'd be somewhere.
PyPy wasn't great for me because its startup time interfered with the main usecase I wanted it for in one instance and in another there bugs that made it not quite compatible enough. Money could solve the bug issue.
On the other hand I did get pygame working with it at one point and that seemed like a nice scenario.
>There are already many way of addressing Python performance (leaving aside whether Python is a good choice if performance matters) such as Cython, Numba, Pypy and C extensions.
And all of them are lacking in different ways, we ALSO, want faster pure Python.
They all have drawbacks, but they also reduce the case for needing to speed up CPython.
Pypy does provide faster pure Python. Its a compatible implementation with JIT.
The newest version of python that PyPy supports is 3.12. CPython is on 3.15.
And from what I understand there are limitations with using libraries that use the CPython API to interface with native code.
Onlything is a lot of cextensions are super slow there. that is only bottleneck left which could be solved with resources that those guys spent on experimental jit.