Perl

Perl is cool, much more so than Python. But I prefer writing Python.

Perl is fun to read about. It has an endless stream of features to discover. Python by comparison is kinda dull. But the aspects of a language that make it fun to read about do not necessarily make it pleasant to use.

I wrote Perl off and on for several years before trying Python. People would tell me I should try Python and every six months or so I’d skim through a Python book. My impression was that Python was prosaic. It didn’t seem to offer any advantage over Perl, so I stuck with Perl. (Not that I was ever very good at Perl.)

Then I read an article by Bruce Eckel saying that he liked Python because he could remember the syntax. He said that despite teaching Java and writing books on Java, he could never remember the syntax for opening a file in Java, for example. But he could remember the corresponding Python syntax. I would never have picked up on that by skimming books. You’ve got to actually use a language a while to know how memorable the syntax is. But  I had used Perl enough to know that I could not remember its syntax without frequent use. Memorable syntax increases productivity. You don’t have to break your train of thought as often to reach for a reference book.

I stand by my initial impression that Python is plain, but I now think that’s a strength. It just gets out of my way and lets me get my work done. I’m sure  Perl gurus can be extremely productive in Perl. I tried being a Perl guru, and I never made it. I wouldn’t say I’m a Python guru, but I also don’t feel the need to be a guru to use Python.

Python code is not cool in a line-by-line sense, not in the way that an awesomely powerful Perl one-liner is cool. Python is cool in more subtle ways.

Related posts:

Languages that are easy to pick back up
API symmetry
Periodic table of Perl operators
Three-hour-a-week language

Symmetric APIs are easier to use. I was reminded of this when doing some regular expression programming in Python and comparing it to Perl. Perl’s regular expression operators for search and replace are symmetric in a way that their Python counterparts are not.

Perl uses m/pattern/ for matching and s/pattern/replacement/ for substitution. Both apply to the first instance of a pattern in a string by default. The g option following a match or substitute operator causes the command to apply to all instances of the pattern. The i option after either a match or substitute command causes the pattern to apply in a case-insensitive manner. Matching and substitution are symmetric.

Python uses re.search() for matching and re.sub() for substitution. The search function can only apply to the first instance of a pattern; to match all instances of a pattern, use re.findall(). The function re.sub() applies to all instances by default, but it has a max parameter that can be set to limit the number of instances it applies to. To make a search pattern case-insensitive, pass in re.IGNORECASE flag. To make a substitution case-insensitive, modify the regular expression itself by adding (?i).

In general, I find Python syntax much cleaner than Perl, but regular expressions are implemented more elegantly in Perl.

Some programming languages are much easier to come back to than others. In my previous post I mentioned that Mathematica is easy to come back to, put Perl is not.

I found it easy to come back LaTeX after not using it for a while. It has a few quirks, but it’s basically consistent. The LaTeX commands for Greek letters are their names, lower case names for lower case letters, upper case names for upper case letters. The command mathematical symbols is usually the name a mathematician would give the symbol. Modes always begin with \begin and end with \end.

Python also has a consistent syntax that make it easier to come back to the language after a break. Someone has said that Python is similar to Perl, except that the word “except” does not appear nearly so often in the Python documentation.

It’s more important that a language be internally consistent than conventional. Each of the languages I mentioned have their peculiarities. Mathematica uses square brackets for function argument arguments. LaTeX uses percent signs for comments. Python uses indention to denote blocks. Each of these take a little getting used to, but each makes sense in its own context.

A special case of consistency is using full names for keywords. Mathematica always spells out words in full. For example, the gamma distribution object is named GammaDistribution. I don’t mind a little extra typing. I’d rather optimize for recall and readability than minimize keystrokes since I spend more time recalling and reading than typing. (One flaw in LaTeX is that it occasionally uses unnecessary abbreviations. For example, \infty for infinity. The corresponding Mathematica keyword is Infinity.)

I just found out that Douglas Crockford has written a book JavaScript: The Good Parts. I haven’t read the book, but I imagine it’s quite good based on having seen the author’s JavaScript videos.

Crockford says JavaScript is an elegant and powerful language at its core, but it suffers from numerous egregious flaws that have been impossible to correct due to its rapid adoption and standardization.

I like the idea of carving out a subset of a language, the good parts, but several difficulties come to mind.

1. Although you may limit yourself to a certain language subset, your colleagues may choose a different subset. This is particularly a problem with an enormous language such as Perl. Coworkers may carve out nearly disjoint subsets for their own use.
2. Features outside your intended subset may be just a typo away. You have to have at least some familiarity with the whole language because every feature is a feature you might accidentally use.
3. The parts of the language you don’t want to use still take up space in your reference material and make it harder to find what you’re looking for.

One of the design principles of C++ is “you only pay for what you use.” I believe the primary intention was that you shouldn’t pay a performance penalty for language features you don’t use, and C++ delivers on that promise. But there’s a mental price to pay for language features you don’t use. As I’d commented about Perl before, you have to use the language several hours a week just to keep it loaded in your memory.

There’s an old saying that when you marry a girl you marry her family. A similar principle applies to programming languages. You may have a subset you love, but you’re going to have to live with the rest of the language.

Mark Lentczner has posted a periodic table of Perl operators. The table shows Perl 6 in all its Byzantine glory. If you work in the language constantly and enjoy the terse syntax optimized for experts, you’ll love Perl 6. But if you’re already having difficulty holding Perl in your head, this periodic table might be the straw that breaks the camel’s back.

I listened to an interview last night with Perl guru Randal Schwartz. He said that Perl is meant for people who use the language at least two or three hours per week. If you’re not going to use it that often, you’re probably better off using something else. But if you use it full time, you can see huge productivity increases.

That matches my experience, at least the first part. I was attracted to Perl because I could imagine being very productive with it. At first I used the language infrequently. Every time I sat down to write Perl I had to work hard to reload the language into my brain. Then for a while I used it frequently enough to achieve some fluency. Then as I wrote Perl less often I could almost feel the language slipping away.

Of course you have to use any language, human or computer, to achieve and maintain fluency. But my sense is that Perl requires more frequent use than other programming languages in order to remain minimally competent, and it repays frequent use more than other languages. I imagine this is a consequence of the natural language principles baked into the language.

One of the things I prefer about Python is that you do not have to use it three hours a week to remain competent.

I no longer write Perl, but I still enjoy listening to thought-provoking Perl speakers like Randal Schwartz.