That makes sense if you're comparing with Java or C#, but not Ruby, which is way more dynamic than Python.

The more likely reason is that there simply hasn't been that big a push for it. Ruby was dog slow before the JIT and Rails was very popular, so there was a lot of demand and room for improvement. PHP was the primary language used by Facebook for a long time, and they had deep pockets. JS powers the web, so there's a huge incentive for companies like Google to make it faster. Python never really had that same level of investment, at least from a performance standpoint.

To your point, though, the C API has made certain types of optimizations extremely difficult, as the PyPy team has figured out.

Google, Dropbox, and Microsoft from what I can recall all tried to make Python fast so I don’t buy the “hasn’t seen a huge amount of investment”. For a long time Guido was opposed to any changes and that ossified the ecosystem.

But the main problem was actually that pypy was never adopted as “the JIT” mechanism. That would have made a huge difference a long time ago and made sure they evolved in lock step.

> Python never really had that same level of investment, at least from a performance standpoint.

Or lack of incentive?

Alot of big python projects that does machine learning and data processing offloads the heavy data processing from pure python code to libraries like numpy and pandas that take advantage of C api binding to do native execution.