Using optional type annotations is a really promising strategy and may eventually be added to Pyston, but our primary target right now is unmodified and untyped Python code. I think there's room for both approaches -- I think the "using type annotations to achieve near-native performance" can be very useful ex. in a numerical computing context, but might not apply as well to a "large web application" case.
On Thu, Apr 3, 2014 at 3:42 PM, Sturla Molden <sturla.mol...@gmail.com>wrote: > Kevin Modzelewski <k...@dropbox.com> wrote: > > > Since it's the question that I think most people will inevitably (and > > rightly) ask, why do we think there's a place for Pyston when there's > PyPy > > and (previously) Unladen Swallow? > > Have you seen Numba, the Python JIT that integrates with NumPy? > > http://numba.pydata.org > > It uses LLVM to compile Python bytecode. When I have tried it I tend to get > speed comparable to -O2 in C for numerical and algorithmic code. > > Here is an example, giving a 150 times speed boost to Python: > > > http://stackoverflow.com/questions/21811381/how-to-shove-this-loop-into-numpy/21818591#21818591 > > > Sturla > > _______________________________________________ > Python-Dev mailing list > Python-Dev@python.org > https://mail.python.org/mailman/listinfo/python-dev > Unsubscribe: > https://mail.python.org/mailman/options/python-dev/kmod%40dropbox.com >
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