JIT compilers for Python, what is the latest news?

[Ian Kelly]

On Fri, Apr 5, 2013 at 2:39 AM, John Ladasky <john_ladasky at sbcglobal.net> wrote:
>> 2) Rewrite some key portions in C, possibly using Cython (as MRAB suggested).
>
> And as I replied to MRAB, my limiting code is within Numpy.  I've taken care to look for ways that I might have been using Numpy itself inefficiently (and I did find a problem once: fixing it tripled my execution speed).  But I would like to think that Numpy itself, since it is already a C extension, should be optimal.

That doesn't seem to follow from your original post.  Because Numpy is
a C extension, its performance would not be improved by psyco at all.
The 20% performance increase that you reported must have been a result
of the JIT compiling of some Python code, and if you can identify that
and rewrite it in C, then you may be able to see the same sort of
boost you had from psyco.