I have taken a liking to Python over the last several months. I used to be more of a snob. Python seemed to be a grab bag of reasonable ideas that were better expressed elsewhere. The thing about Python though is it seems to work well in practice.

Gordon is tantalized by the prospect of some way cool lispy way of doing this. I think that all the components are there for that. And you'd get decent perf to boot by compiling lisp to native code.

Here's a series of thought provoking zingers from his post

Give a 500MHz P3 to one professional graphics designer and a 3GHz P4 to another and compare their productivity: you will see a productivity difference, because this is a task / profession which has managed to leverage the computer itself. Give the same disparate hardware to two comparably talented programmers and what productivity difference will you see? None, or so little difference as to be immeasurable. Similarly, give two designers the current feature set of a preferred professional tool (let's say, Photoshop) and the feature set of that tool 5 years ago, and you'll see a difference. In programming? Doubtful (with the notable exception of a refactoring IDE such as IDEA).

Pattern matching is absolutely fundamental to human problem-solving, but where's the computer-support for pattern matching in the task of software development? That is, why can't a programming language leverage the fact that the vast majority of computer programs are built from examples?

What's wrong with today's languages? Everything.

This kata is a thought experiment. What are the top three advantages and top three disadvantages of the two approaches? If you're been using classes to hold data in your business applications, what would the impact be if you were to switch to hashes, and vice versa? Is this issue related to the static/dynamic typing debate?