On-topic: alternate Python implementations

Stefan Behnel stefan_ml at behnel.de
Sat Aug 4 08:40:16 CEST 2012


Steven D'Aprano, 04.08.2012 08:15:
> Most people are aware, if only vaguely, of the big Four Python 
> implementations:
> 
> CPython, or just Python, the reference implementation written in C.
> IronPython, written in .NET.
> Jython, written in Java.
> PyPy, the optimizing implementation written in Python (actually, it's 
> written in a subset of Python, RPython).
> 
> But the Python ecosystem is a lot bigger than just those four. Here are 
> just a few other implementations that you might be interested in:
> 
> 
> Stackless - the "forgetten Python", Stackless is, I believe, the oldest 
> implementation behind only CPython itself. It's a fork of CPython with 
> the calling stack removed and fast and lightweight microthreads, and is 
> used extensively in EVE Online.
> 
> http://www.stackless.com/
> 
> 
> Nuitka - optimising Python compiler written in C++, supports Python 2.6 
> and 2.7, claims to be up to twice as fast as CPython.
> 
> http://nuitka.net/pages/overview.html
> 
> 
> WPython - another optimizing version of Python with wordcodes instead of 
> bytecodes.
> 
> http://code.google.com/p/wpython/
> 
> 
> CLPython, an implementation of Python written in Common Lisp.
> 
> http://common-lisp.net/project/clpython/
> 
> 
> CapPython is an experimental restricted version of Python with 
> capabilities.
> 
> http://plash.beasts.org/wiki/CapPython
> http://en.wikipedia.org/wiki/Object-capability_model
> 
> 
> Berp - a compiler which works by translating Python to Haskell and 
> compiling that.
> 
> https://github.com/bjpop/berp/wiki

And not to forget Cython, which is the only static Python compiler that is
widely used. Compiles and optimises Python to C code that uses the CPython
runtime and allows for easy manual optimisations to get C-like performance
out of it.

http://cython.org/

Stefan




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