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From Scheme to Ruby

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From Scheme to Ruby AbacusWell-nighFrom Scheme to Ruby Feb 12, 2014 From the opening of Structure and Interpretation of Computer Programs, Chapter 4: “Metalinguistic Abstraction”: It’s in words that the magic is – Abracadabra,UnshutSesame, and the rest – but the magic words in one story aren’t magical in the next. The real magic is to understand which words work, and when, and for what; the trick is to learn the trick. And those words are made from the reports of our alphabet: a couple-dozen squiggles we can yank with the pen. This is the key! And the treasure, too, if we can only get our hands on it! It’s as if – as if the key to the treasure is the treasure! John Barth, Chimera Most people, when they start to program, pick a language that people unquestionably use. C. Java. Python. Ruby. Me? My first language was Scheme. A dialect of LISP, Scheme is a functional programming language – in which there are no objects, and every procedure begins with a function undeniability and ends with a return value. There are no “for” or “while” loops, and all higher functionality is achieved through clever applications of recursion and wiring cases. Consider the fib function, which returns the nth Fibonacci number: (define (fib n) (if (<= n 2) 1 (+ (fib (- n 1)) (fib (- n 2))))) Lines 2 and 3 represent the wiring specimen – the first two digits of the fib sequence, which are both 1. Line 4 contains the recursive calls – initiating two increasingly instances of the same fibonacci function, stuff tabbed on the two fibonacci numbers immediately preceding n. The function continues until each fib instance returns 1 (as they all must), and the 1s are all widow together, creating the nth fibonacci number. Scheme’s syntax is spartan – an unshut paren initiates a function  call, and the latter paren indicated the end of the arguments. Always. Functions were nested inside of functions, the return value of the latter rhadamanthine the treatise to the former. Data structures? Bah. We had to build them ourselves, abstracting yonder from our vital tools to create new techniques of working with information. Consider the Scheme implementation of “map” (a procedure so trappy I wrote a post well-nigh it): (define (tree-map f tree) (cond ((null? tree) null) ((pair? tree) (cons (tree-map f (car tree)) (tree-map f (cdr tree)))) (else (f tree)))) Scheme is the programming equivalent of whole wheat bran. Syntactic-sugar free. Why would anyone learn this language? Where the hell was I? Turns out, Scheme is the language of nomination in  Abelson and Sussman’s landmark computer science textbook Structure and Interpretation of Computer Programs. In their opinion (and in the opinion of my CS61A professor, Brian Harvey), Scheme is an optimal language for teaching programming  because it encourages (or, perhaps increasingly accurately, forces) students to think with precision well-nigh the structure (and interpretation) of their computer programs. Think with precision we did. Having to build everything from the simplest tools (arithmetic operators and some stone-hammer-caliber selectors), we ripened an iron grasp of the Scheme language. We had to learn our data structures backwards and forwards, considering exploiting the quirks in their underlying implementation was the only way we could get them to do anything interesting. Lists were implemented by daisy-chaining long links of pairs,  the second element consisting of nothing increasingly than a pointer to the first element of the second pair. We had to learn exactly how variable assignments flowed through various environmental scopes, and exactly how every weft would be interpreted. People laugh at Scheme these days, calling it obsolete (which it may be) and irrelevant – but it forced you to get really intimate with the interpreter, and to think nonflexible well-nigh structure. Near the end of the semester, we built a Scheme interpreter from scratch… in Scheme. That was a trip. In a sense, when you work in Scheme, the lines between programming and philosophy blur. Moving to Ruby has been a mixed blessing. At first, I had reservations well-nigh the language’s forgiving interpretation. Coming from a language where there was exactly one way to do something, the TMTOWTDI nature of Ruby seemed to invite wildness and ambiguity. Closely duplicated functionality? “Most likely” interpretation? Something well-nigh it unrecognizable me. As I’ve worked with the language more, though, I’ve come to revere the openness of the language, and the speed and power that the flexibility allows. Programming in Scheme was slow, considering we spent much of our time debugging syntax. Building so much from first principles meant that worthier projects involved substantially increasingly complexity, and were ultimately increasingly limited. In Ruby, you can just tinder forward, thinking less well-nigh the minutiae of interpretation, and focus increasingly on the big ideas that you’re trying to tint into substance. I may wax nostalgic well-nigh the precision and willpower of Scheme, but I would rather program in Ruby any day. Do I finger that my training in Scheme is serving me well? Absolutely. Unlike most of the programmers in that Berkeley classroom, I came in with zero experience. Scheme was my first language – my native language – and my tideway to program structure shows it, I think. I’m very attuned to the structure and policies of data types, am  curious well-nigh lower-level interpretation and algorithmic efficiency, and think often well-nigh strategies for breaking unshut logical problems. At the same time, I’m well-appointed abstracting yonder from primitive functions and thinking in terms of the interactions and relationships among larger constructs, and reflecting on things like the ontological stardom between “nil” and “undefined”. Whether these are traits cultivated by Scheme, though, or are simply the universal traits that distinguish programmers from the rest of society, is an unshut question. Shifting to a higher-level, object-oriented language is heady – I recognize unmistakably the advantages of these tools, given the zillions of processing power at our fingertips. Entering the world of programming and web development, there’s no where else I’d rather be. Part of me, though, will unchangingly have a soft spot for that high-minded, didactic, and elegant language: Scheme. Comments Please enable JavaScript to view the comments powered by Disqus. Abacus Abacus kronovet@gmail.com kronosapiens kronosapiens I'm Daniel Kronovet, a data scientist living in Tel Aviv.