Note: This post was edited for clarity. This JAPH uses a Turing machine. The machine accepts any string that ends in '\n' and allows side effects. This lets us print the value of the tape as it encounters each character. While the idea of using lambda functions as side effects in a Turing machine is a little bizarre on many levels, we work with what we have. And Python is multi-paradigmatic, so what the heck....

Note: This post was edited for clarity. At this point, tricking python into printing strings via indirect means got a little boring. So I switched to obfuscating fundamental computer science algorithms. Here’s a JAPH that takes in a Huffman coded version of 'just another python hacker', decodes, and prints it. # Build coding tree def build_tree(scheme): if scheme.startswith('*'): left, scheme = build_tree(scheme[1:]) right, scheme = build_tree(scheme) return (left, right), scheme else: return scheme[0], scheme[1:] def decode(tree, encoded): ret = '' node = tree for direction in encoded: if direction == '0': node = node[0] else: node = node[1] if isinstance(node, str): ret += node node = tree return ret tree = build_tree('*****ju*sp*er***yct* h**ka*no')[0] print( decode(tree, bin(10627344201836243859174935587)....

Note: This post was updated to work with Python 3.12. It may not work with different versions. Here’s a JAPH composed solely for effect. For each letter in 'just another python hacker' it loops over each the characters ' abcdefghijklmnopqrstuvwxyz', printing each. Between characters it pauses for 0.05 seconds, backing up and moving on to the next if it hasn’t reached the desired one yet. This achieves a sort of rolling effect by which the final string appears on our screen over time....

Note: This post was updated to work with Python 3.12. It may not work with different versions. No series of JAPHs would be complete without ROT13. This is the example through which aspiring Perl programmers learn to use tr and its synonym y. In Perl the basic ROT13 JAPH starts as: $foo = 'whfg nabgure crey unpxre'; $foo =~ y/a-z/n-za-m/; print $foo; Python has nothing quite so elegant in its default namespace....

Here’s the second in my reformed JAPH series. It takes an anagram of 'just another python hacker' and converts it prior to printing. It sorts the anagram by the indices of another string, in order of their associated characters. This is sort of like a pre-digested Schwartzian transform. x = 'upjohn tehran hectors katy' y = '1D0HG6JFO9P5ICKAM87B24NL3E' print(''.join(x[i] for i in sorted(range(len(x)), key=lambda p: y[p]))) Obfuscation consists mostly of using silly machinations to construct the string we use to sort the anagram....

Note: This post was edited for clarity. Many years ago, I was a Perl programmer. Then one day I became disillusioned at the progress of Perl 6 and decided to import this. This seems to be a fairly common story for Perl to Python converts. While I haven’t looked back much, there are a number of things I really miss about perl (lower case intentional). I miss having value types in a dynamic language, magical and ill-advised use of cryptocontext, and sometimes even pseudohashes because they were inexcusably weird....

I hope you saw “China’s way to the top” on the Post’s website recently. It’s a very clear presentation of their statement and is certainly worth a look. So say you’re an economist and you actually do need to produce a realistic estimate of when China’s GDP surpasses that of the USA. Can you use such an approach? Not really. There are several simplifying assumptions the Post made that are perfectly reasonable....

Note: This post was updated to include an example data file. I thought it might be useful to follow up the last post with another one showing the same examples in R. R provides a function called lm, which is similar in spirit to NumPy’s linalg.lstsq. As you’ll see, lm’s interface is a bit more tuned to the concepts of modeling. We begin by reading in the example CSV into a data frame:...

This post is based on a memo I sent to some former colleagues at the Post. I’ve edited it for use here since it fits well as the second in a series on simple data fitting techniques. If you’re among the many enlightened individuals already using regression analysis, then this post is probably not for you. If you aren’t, then hopefully this provides everything you need to develop rudimentary predictive models that yield surprising levels of accuracy....

Consider this scenario: You run a contest that accepts votes from the general Internet population. In order to encourage user engagement, you record any and all votes into a database over several days, storing nothing more than the competitor voted for, when each vote is cast, and a cookie set on the voter’s computer along with their apparent IP addresses. If a voter already has a recorded cookie set they are denied subsequent votes....