[wyldfire]

> My biggest issue with PyPy is library/modules incompatibility.

Addressing this has been a big focus for PyPy lately. You should consider re-evaluating PyPy. numpy (arguably one of the heaviest users of C extensions) works on pypy at very nearly 100% of its tests passing.

[dr_zoidberg]

We tested last week, distorm3 and yara bindings for python are the big things that just didn't work (yet again) with our test case (the volatility memory forensics framework). We got them installed with pip, but they just didn work. Volatility still runs without them, it just complains a bit.

Also, startup time of volatility exploded for no apparent reason (4 seconds CPython vs 12 seconds PyPy, latest 2.7 branch). Real analysis time was indeed faster (~30 seconds CPython vs ~15 seconds PyPy), but half the plugins won't work.

Plus, in the end (startup+analysis), both CPython and PyPy got close results (though arguably PyPy was some about 15% faster).

[wyldfire]

Might be worth reporting since you have a reproducible failure and a use case for which the performance is not satisfactory. You can tune some of the JIT behavior with command line options -- that might make it kick in sooner and you might see a net benefit.

[sho_hn]

Original numpy? Or their private reimplementation started because the original won't run ...?

[wyldfire]

The former.

See http://pypy.org/download.html#numpy-via-cpyext