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.
PyPy on numpy heavy code is often a lot slower than CPython
Sorry can you explain more the connection between PyPy and CFFI (which generates compiled extension modules to wrap an existing C library)? I have never used PyPy, but I use CFFI all the time (to wrap C libraries unrelated to Python so that I can use them from Python)