Perl Ate My Brain!

Looking back at my earlier posts here I see a lot of optimism about rebooting (an irresistible pun) my ability to write software; a year or so ago, I had a plan to learn some new languages, notably Java, and refresh my knowledge of existing ones, notably C++, by embarking on a few different programming projects. It seems I’ve taken a slightly different route. I’ve done a lot of programming over the past year, but it’s almost all been in Perl. Hardcore Perl fans would say this was inevitable—that the language is so powerful and flexible that, once you start using it, there’s no need to use any other. People with a lower opinion of Perl would be more likely to call it a sickness.

What’s so seductive about Perl? A few things, to start, off the top of my head:

• The astonishing variety of freely available modules (Perl-speak for libraries) for highly specialized tasks: more than a few times I’ve girt my loins for a difficult bit of coding, only to check CPAN and find that someone else has already done it for me.


• Flexible built-in data structures and the ability to easily create more elaborate ones when the built-ins won’t do. Perl’s built-in lists, hashes, and references seem to capture the best features of the C++ Standard Template Library, Lisp lists, and hand-built C data structures, with performance (thanks to a highly evolved and optimized interpreter) fast enough for most purposes.


• Syntax that, once a slight learning curve is overcome, feels natural and is (surprise!) easy to read. Perl’s reputation for looking like line noise comes from two things: the idiomatic use of regular expressions as the most effective way to parse string (and often numeric as well) data, and the way that non-alphanumeric characters are used to mark variable types. The former did encourage “write-only” code in Perl 4, but in the current implementation of the language, you can interpolate comments in regexps to make them as readable as you want. The latter becomes more rational once you realize that the dollar, percent, and at symbols are used to identify a variable’s type not just at declaration, but at use, in context; they aren’t just an uglier cousin of Hungarian notation but a concise expression of an extremely elegant kind of dynamic casting. There are a few rough edges—for example, the backslash and curly braces are overloaded for references (sort of like C pointers) in a way that makes me uncomfortable—but on the other hand, there are only so many non-alphanumeric characters in ASCII. Perhaps Perl 6 should move on to use some interesting Unicode symbols, or (I’m only mostly joking here) something like APL… (In the meantime, the plethora of dollar signs in Perl code gives me a bit of a warm fuzzy feeling, as it reminds me of my childhood programming in 8-bit home computer BASIC, where the dollar sign indicated a string variable.)
  

I still fully intend to learn Python. Even though he was contrasting immature versions of both languages, open-source guru Eric Scott Raymond’s classic essay on the elegance and ease of Python compared to Perl still makes as big an impression on me now as it did when I read it ten years ago. Perl’s become more elegant since then, and its suitability for large software projects has been greatly enhanced by the Moose project, which transforms Perl’s OOP features to such a degree that it almost creates a separate dialect of the language. On the other hand, Python has loud cheerleaders in the scientific community: my impression is that the NumPy libraries have in just a few years supplanted Fortran as the development environment of choice for numerical analysis of large data sets, something that is a critical programming task for me. And somewhere near the top of my to-do list is to learn one of the new platform-independent Web 2.0 programming frameworks; Ruby on Rails seems to be the most popular, although I privately suspect that’s partly because of its oddly catchy name—but Python-based systems are close behind.