Library for the rapid development of dynamic software solutions for board games

I want to use Python to evaluate different approaches to dynamic programming for two-player board games without ambiguity (like chess, etc.). I am interested in both exact and heuristic solutions. My “assessment” is to try every approach and see how well it works in the test cases that I generate.

I am looking for a very flexible library or framework that helps me quickly and easily coordinate, evaluate (and debug ...) different approaches.

I'm only interested in asymptotic characteristics (e.g. O(n log n)vs O(n^2), etc.). Therefore, I need efficient data structures, but I do not mind performance with a constant coefficient.

I do not mind if it takes some time to study the library.

I do not need an external interface; I use only the command line interface.

I also do not need support for parallel / distributed programming (although I would not refuse if it was available).

I need a library to support Python 3 either now or very soon.

Are there libraries providing such support?

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, . , memoization , memoization , Python 3.2, lru_cache().

functools, , .

http://docs.python.org/dev/library/functools.html

@functools.lru_cache(maxsize=100, typed=False)

Python, .

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