The Sieve results I got weren't using Psyco; using it, the difference
in performance is about what the shootout lists, proportionally.
However, it requires source-level changes to the files, and the source
code on the shootout site doesn't included those changes. It's also
not mentioned in the language information page for Python, or listed
as a seperate implementation.

Psyco does some great things for the performance of certain
algorithms, but it's not part of the core Python distribution for any
number of reasons: only works on x86, breaks several standard
introspection and debugging libraries, and perhaps most importantly,
prevents redefinition of methods at runtime on optimized objects.

In short, it's almost more like a specialized reimplementation of
Python (ala Stackless) than an add-on library. I don't think it's
significantly more appropriate to use for this kind of benchmarking
than, say, Ruby or Perl scripts rewritten to use one of the Inline
libraries to do the heavy listing in C...especially when it's not
explicitly mentioned on the benchmark site.

Lennon