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
