In a sense it is, because in those communities the approach has been, "it is hard but we will solve it sooner or later", whereas in the Python world, PyPy seems to be the only approach that has embraced this culture, whereas everyone else takes the path "it is hard, Python cannot be made fast because it is dynamic".
That’s not been my impression. On the contrary - there have been very many unsuccessful attempts (Unladen swallow, Pyston, Nuitka, cython-for-plain-python, a few more I can’t recall right now); they all tried to maintain compatibility (complete language and binary api), and all delivered very meager speedups.
Those that focused on a subset (numba, shedskin, rpython) were actually able to deliver significant speedups. Even PyPy dropped binary compatibility.
The odd one out is Psyco, the precursor to PyPy. Perfect compatibility with non trivial speedup - but was considered a dead end by its authors, and that’s why they started PyPy
And the fact that there are languages as dynamic as Python is not as important as how it is implemented through the language; Lua is about as dynamic as Python, but with effects that are much more local in general. IIRC Mike Pall (of LuaJIT fame) said that Lua was almost optimal for JITting, JS is sort-of-ok if you ignore some things, but Python is beyond hope -- and I tend to think he knows what he's talking about, given that his hobby, one-man-show LuaJIT handily beat all well-funded-with-tens-of-employees JS engines for a very long time (maybe still does).
I wonder how good the SmallTalk JITs really are by today's standards, in the presence of e.g. "become:". The fact that's it is there, and supported, doesn't mean it's in common use, or supported efficiently -- just like JavaScript's "with".