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Probably the most indicative part of Norvig's code beauty is the requirements file[0]. With python developers being infamous for importing obscure/questionable libraries for even a simple task, I love how Norvig solved all these with just native libraries and the staples numpy/plt.
[0]: https://github.com/norvig/pytudes/blob/master/requirements.t...
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I'd recommend taking a look at his book Paradigms of AI Programming [0]. It really shows his thought process in developing solutions to problems. The only other way is practice, and in particular practice with languages that offer functional features. Notice his use of lambdas, assignment of existing functions/constructors to more accurate names (Passport instead of dict, day 4), and higher order functions (quantify).
Those are things that really help in algorithmic code by increasing accuracy of the names of things to the application (almost creating a domain specific language).
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If you like this, you will love https://github.com/mebeim/aoc/tree/master/2020
The guy created very clean python solutions, and very insigthful walkthrough (although a bit wordy some times). It was my go to repo after validating my solutions on AoC (he managed to publish daily during the whole challenge !).