https://peps.python.org/pep-3000/ - PEP 3000 says it will be a derived from the Python 2 codebase and not a complete rewrite (referencing Joel Spolsky's views on complete rewrites and Netscape Navigator).
https://peps.python.org/pep-3099/ - PEP 3099 is changes Guido van Rossum rejected from Python 3 (including := as a binding operator), parallel iteration, programmable syntax, parser going beyond LL(1), changing the for/else construct.
https://peps.python.org/pep-3100/ - PEP 3100 is things he set as goals for it, things like all strings are Unicode and byte arrays are a separate type, optional type annotations, 'exec' and 'print' change from statements to functions, None/True/False become keywords, old-style classes are gone, changing inequality comparison from <> to != , require C99, drop BeOS support, drop old standard library modules, and more.
actually, more changes than I remember.
Probably also during the 2 to 3 migration, but that goal appears to have now been abandoned.
I wonder how the authors of other implementations like pypy will be able to keep up as the reference implementation becomes more and more complex.
Last release on Oct 14. Beta support for 3.12. It's not that bad really and 1/10 of the people who complain about it did something then the situation would be better.
The problem was he exposed too much of the implementation into the language itself, destroying its ability to be a simple reference implementation that others could re-implement.
The python documentation has historically also not been especially clear at distinguishing between what the language guarantees, vs what is just implementation details of the cPython implementation. So even if libraries wanted to try to avoid depending on implementation specifics, it isn't always clear what those are.
The net result is that for the end user python the language is effectively: whatever cpython does. This really, really discourages creating alternate implementations, as the only way to be an alternative implementation with good compatibility is to be a living fork of cpython, constantly merging in all the changes from it, while also maintaining your improvements.
Today there are far more people using it, and everyone has a different perspective on what it is. No longer is it a niche glue language, now it's a backbone of AI technology at major tech firms, so it's understandable they'd like it to be faster on its own.