PyPy is a fantastic achievement and deserves far more support than it gets. Microsoft’s “Faster CPython” team tried to make Python 5x faster but only achieved ~1.5x in four years - meanwhile PyPy has been running at over 5x faster for decades.

On the other hand, I always got the impression that the main goal of PyPy is to be a research project (on meta-tracing, STM etc) rather than a replacement for CPython in production.

Maybe that, plus the core Python team’s indifference towards non-CPython implementations, is why it doesn’t get the recognition it deserves.

▲

mattip 2 hours ago | parent [-]

Third party libraries like SciPy scikit-learn, pandas, tensorflow and pytorch have been critical to python’s success. Since CPython is written in C and exposes a nice C API, those libraries can leverage it to quickly move from (slow) python to (fast) C/C++, hitting an optimum between speed of development and speed of runtime.

PyPy’s alternative, CFFI, was not attractive enough for the big players to adopt. And HPy, another alternative that would have played better with Cython and friends came too late in the game, by that time PyPy development had lost momentum.

▲

toxik 2 hours ago | parent [-]

PyPy on numpy heavy code is often a lot slower than CPython

	▲	mattip 14 minutes ago \| parent [-]
		Yes. The C API those libraries use is a good fit to CPython, a bad fit to PyPy. Hence CFFI and HPy. Actually, many if the lessons from HPy are making their way into CPython since their JIT and speedups face the same problems as PyPy. See https://github.com/py-ni