>> My use of python is somewhat recent. But the two languages that I have used a lot of - Java and JS - have interpreters that were heavily optimized over time. I wonder why that never happened with python and, instead, everyone continues to write their critical code in C/Rust.
Improving Python performance has been a topic as far back as 2008 when I attended my first PyCon. A quick detour on Python 3 because there is some historical revisionism because many online people weren't around in the earlier days.
Back then the big migration to Python 3 was in front of the community. The timeline concerns that popped up when Python really got steam in the industry between 2012 and 2015 weren't as huge a concern. You can refer to Guido's talks from PyCon 2008 and 2009 if they are available somewhere to get the vibe on the urgency. Python is impactful because it changes the language and platform while requiring a massive amount of effort.
Back to perf. Around 2008, there was a feeling that an alternative to CPython might be the future. Candidates included IronPython, Jython, and PyPy. Others like Unladen Swallow wanted to make major changes to CPython (https://peps.python.org/pep-3146/).
Removing the GIL was another direction people wanted to take because it seemed simpler in a way. This is a well researched area with David Beazley having many talks like this oldie (https://www.youtube.com/watch?v=ph374fJqFPE). The idea is much older (https://dabeaz.blogspot.com/2011/08/inside-look-at-gil-remov...).
All of these alternative implementations of Python from this time period have basically failed at the goal of replacing CPython. IronPython was a Python 2 implmentation and updating to Python 3 while trying grow to challenge CPython was impossible. Eventually, Microsoft lost interest and that was that. Similar things happened for the others.
GIL removal was a constant topic from 2008 until recently. Compatibility of extensions was a major concern causing inertia and the popularity meant even more C/C++/Rust code relying on a GIL. The option to disable (https://peps.python.org/pep-0703/) only happened because the groundwork was eventually done properly to help the community move.
The JVM has very clearly defined interfaces and specs similar to the CLR which make optimization viable. JS doesn't have the compatibility concerns.
That was just a rough overview but many of the stories of Python woes miss a lot of this context. Many discussions about perf over the years have descended into a GIL discussion without any data to show the GIL would change performance. People love to talk about it but turn out to be IO-bound when you profile code.
