Alice is a very exciting new language from the ML family. It offers many interesting approaches to well-known problems and extends ML with meaningful features such as a functional model for multithreading. What particularly fascinates me is the discussion of lazy evaluation, futures and promises in the Alice tour - that hit exactly the nerve, as I had just finished building my own package for Python (lazypy). I immediately extended it with futures. An OS X version of Alice is also planned - I'm really curious, as the screenshots of the environment suggest quite a lot of promise. Previous ML implementations have tended to be rather austere in their user interface.
Here you can find the original article.
Codewalker for Python - A code walker that can make various modifications to code from lambda expressions (specifically early binding etc.)
Phillip J. Eby is thinking about how to implement a forward-chaining factbase (a fundamental mechanism of AI systems that enable rule- and fact-based programming) in Python. Very fascinating to read - he actually comes from the OO corner of Python (as one of the PEAK programmers - PEAK is basically the J2EE of the Python world) and here has his first hard encounters with functional programming. The whole thing also has practical implications: in PyProtocols (another project by Phillip), there is now already quite an advanced extension of Python's OO system towards a more CLOS-like environment with generic functions and multi-parameter dispatch for methods. Very interesting, as it opens up completely new possibilities. Here's the original article.
Wow, the Wikipedia page on the Indian Ocean earthquake is really impressive. Lots of information and well-presented too.
I found the original article at Wortfeld.
Xoltar Python Page - diverse functional extensions to Python - curry, lazy expressions, partial evaluation etc.