In Python, p.x * 2 means dynamic lookup, possible descriptors, big-int overflow checks, etc. A compiler can drop that only if it proves they don’t matter or speculates and adds guards—which is still overhead. That’s why Python is slower on scalar hot loops: not because it’s interpreted, but because its dynamic contract must be honored.
Somehow Smalltalk JIT compilers handle it without major issues.
You get real speed in Python by narrowing the semantics (e.g. via NumPy, Numba, or Cython) not by hoping the compiler outsmarts the language.
There is to say everything dynamic that can be used as Python excuse, Smalltalk and Self, have it, and double up.
Second, at most this describes WHY it is slow, not that it isn't, which is my point. Python is slow. Very slow (esp. for computation heavy workloads). And that is okay, because it does what it needs to do.