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Personally, I'm not too excited about PyPy, because it has little promise of speeding up the two typical use cases for Python in the kind of scientific code I care about:

1. Python is used to setup/glue together code that is written in a compiled langugage.

2. Someone writes a code by starting out writing everything in Python, then profiling and identifying the slow parts, and then writing these in a compiled language.

Edit: example of 1): HOOMD-blue, example of 2): PyClaw.



If you're using pypy, the slow parts might not be slow anymore. It might even run faster than C, because JITs are better at some things than static compilers. http://morepypy.blogspot.com/2011/02/pypy-faster-than-c-on-c...




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