alt Hacker News> I would also say there’s generally less impetus to optimize CPython
Nonetheless, Microsoft employed a whole "Faster CPython" team for 4 years - they targeted a 5x speedup but could only achieve ~1.5x. Why couldn't they make a significantly faster Python implementation, especially given that PyPy exists and proves it's possible?
Pypy has much slower C interop than CPython, which I believe is part of the tradeoff. Eg data analysis pipelines are probably still faster in numpy on CPython than pypy.
Not an expert here, but my understanding is that Python is dynamic to the point that optimizing is hard. Like allowing one namespace to modify another; last I used it, the Stackdriver logging adapter for Python would overwrite the stdlib logging library. You import stackdriver, and it changes logging to send logs to stackdriver.
All package level names (functions and variables) are effectively global, mutable variables.
I suspect a dramatically faster Python would involve disabling some of the more unhinged mutability. Eg package functions and variables cannot be mutated, only wrapped into a new variable.