Fair! I guess I didn't mean language as such, but as used.

But a lot of the monkey-patching kind of things and dynamism of python also means a lot of those sorts of things have to be re-checked often for correctness, so it does take a ton of optimizations off the table. (Of course, those are rare corner cases, so compilers like pypy have been able to optimize for the "happy case" and have a slow fall-back path - but pypy had a ton of incompatibility issues and now seems to be dying).

Python has a JIT compiling version in GraalPy. If you have pure Python it works well. The problem is, a lot of Python code is just callouts to C++ ML libs these days and the Python/C interop boundary just assumes you're using CPython and requires other runtimes to emulate it.

You don't even need to go all V8, you could just build something like LuaJIT and get most of the way there. LuaJIT is like 10k LOCs and V8 is 3M LOC.

The real reason is that it is a deliberate choice by the CPython project to prefer extensibility and maintainability to performance. The result is that python is a much more hackable language, with much better C interop than V8 or JVM.