Higher Level Doesn’t Always Mean Less Code

What is your first association evoked by a mention of the Java programming language? If you said “slow”, I hope all is well back there in the 90s! But if you said “verbose” instead, you would be very much in the right. Its wordiness is almost proverbial by now, with only some small improvements – like lambdas – emerging at the distant horizon.

Thankfully, more modern and higher level languages are much better in this regard. The likes of Python, Ruby or JavaScript, that is. They are more expressive and less bureaucratic, therefore requiring much less code to accomplish the same thing that takes pages upon pages in Java, C# or C++. The amount of “boilerplate” – tedious, repetitive code – is also said to be significantly lower, almost to the point of disappearing completely.

Sounds good? Sure it does. The only problem here is that most of those optimistic claims are patently false. Good real-world code written in high level, dynamic language does not necessarily end up being much shorter. Quite often, it is either on par or even longer than the equivalent source in Java et al.
It happens for several reasons, most of which are not immediately obvious looking only at a Hello World-like samples.

You need copious amount of documentation

It is said Python is pretty much pseudocode that happens to be syntactically strict enough to parse and run. While usually meant as a compliment, this observation has an uglier counterbalance. Being a pseudocode, the raw Python source is woefully incomplete when it comes to providing necessary information for future maintainers. As a result, it gets out of hand rather quickly.

To rein it, we need to put that information back somehow. Here’s where the documentation and commenting part steps in. In case of Python, there is even a syntactical distinction on the language level between both. The former takes the form of docstrings attached to function and class definitions. They are meant to fill in the gaps those definitions always leave open, including such “trivialities” as what kind of arguments the function actually takes, what it returns, and what exceptions it may raise.

Even when you don’t write expansive prose with frequent usage examples and such, an adequate amount of docstrings will still take noticeable space. The reward you’ll get for your efforts won’t be impressive, too: you’ll just add the information you’d include anyway if you were writing the code in a static language.
The catch here is that you won’t even get the automatic assurance that you’ve added the information correctly… which brings us immediately to the next point.

You need a really good test suite

There are two types of programmers: those who write tests, and those who will be writing tests. Undoubtedly, the best way to have someone join the first group is to make them write serious code in any interpreted, dynamic language.

In those languages, a comprehensive set of tests is probably the only automated and unambiguous way to ensure your code is satisfying even some basic invariants. Whole classes of errors that elsewhere would be eliminated by the compiler can slip completely undetected if the particular execution path is not exercised regularly. This includes trying to invoke a non-existent method; to pass an unexpected argument to a function; call a “function” which is not callable (or conversely, not call a function when it should have been); and many others. To my knowledge, none of these are normally detected by the various tools for static analysis (linting).

So, you write tests. You write so many tests, in fact, that they easily outmatch the very code they’re testing – if not necessarily in effort, then very likely in quantity. There’s no middle ground here: either you blanket your code with good tests coverage, or you can expect it to break in all kinds of silly ways.

You need to keep abstractions in check

Documentation, comments and tests take time and space. But at least the code in high level language can be short and sweet. Beautiful, elegant, crisp and concise, without any kind of unnecessary cruft!
Just why are you staring at me like that when I say I used a metaclass here?…

See, the problem with powerful and highly expressive languages is that they are dangerous. The old adage of power and responsibility does very much apply here. Without a proper harness, you will one day find out that:

• the clever trick you’ve used half a year ago is not nearly as obvious as it was back then
• the programing style which feels natural for one member of your team is nearly incomprehensible to some of the others
• new people have serious trouble grasping all the neat abstractions you’ve used in your project so liberally

Unless you can guarantee you’ll always have only real Perl/Python/Ruby rockstars on board, it’s necessary to tame that wild creativity at least a little bit. The inevitable side effect is that your code will sometimes have to be longer, at least compared to what that smart but mystifying technique would yield.

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