Imperative curlies 3: for comprehensions and powder skiing

Continuation of Previous Bashing of Curlies
Over the many year of my involvement in Java I have seen very little code reuse around loops. For loops (and other loops) in Java are yet another category of hard to test, hard to maintain code. By now we know they are no good: they are surrounded by the curlies ; ).

Functional programmers have for loops too, only they call them comprehensions! Functional programming often deals with collections of data so loops are unavoidable. So what is the difference?

The difference is really in the attitude. It is like powder skiing. I am a developer and a ski bum. I am very much into safe (inbounds) powder skiing. Like many other skiers I had hard time to learn how to ski powder at first. Frustrated, I decided that what I need to do is to start pretending. So I started pretending that I am really good: with posture and everything else making sure it appears to look like I know what I am doing. (Side note: this technique is very effective in a very deep powder because no one will see what I am doing anyway ; ) Obviously I sucked big time, I only appeared to be a good powder skier. (Think of this as writing a for loop which looks very pretty.) After some years of pretending I learned that my skiing consists of simple reusable elements such as tipping, retracting, pulling back my feet, etc . So for typical everyday tasks on the snow I now can stop pretending and just do these elemental tasks and ski! (Think of this as not using for loops any more: code reuse). When I need to do something new on skis (like trying teles), I will go back to pretending (or to writing a for loop).

The first step is the acknowledgement that what my for loop is doing should have a single purpose: comprehending a collection. (I also think of this step as admittance of being guilty of using the curlies.) The second step is the code reuse for the tasks we perform often, what kind of comprehensions will we be typically doing?: how about: joining, reducing, folding, mapping, finding (any), finding all, etc.

Assume that we need to produce a custom version of toString().  Let’s look at some old Java first:

1:  public class PackRat { 
2:    private List<String> stuff = new ArrayList<String>(); 

3:    public void addToStuff() { ... }
 
4:    public String toString() { 
5:     StringBuffer res = new StringBuffer(); 
6:     res.append("PackRat: "); 
7:     for(int i=0; i<stuff.size(); i++) { 
8:       res.append(stuff.get(i); 
9:       if(i<stuff.size() -1) { 
10:        res.append(";"); 
11:       }  
12:     } 
13:     return res.toString(); 
14:    } 
15:  } 

Same thing done in Groovy, which adds some reusable methods to avoid writing explicit for loops:

1:  class ParckRat { 
2:    List stuff = [] 
3:    def addToStuff … 
4:    String toString() { 
5:     "PackRat "+ stuff.join(";") 
6:    } 
7:  } 

Note: Libraries like Guava or Apache Commons provide you with join() method as external utility, sadly Java List interface does not have a join method.

The Groovy code looks much better . But still 2 curlies we should be able to get rid of. Unfortunately, we are trying to override a Java method in Groovy so we are stuck with the limitations the methods have (methods are not closures). So what could we do if method where closures? Let’s look as SCALA where functions are functions, not methods or closures: I want to my code to simply state that my toString function is really the same as a prefixed stuff.join(“;”). I should be able to declare it, not implement it!

So here is the more declarative and curlyless version done in SCALA:

1:  class PackRat {  
2:    private var stuff: List[String] = List[String]() 
3:    def addToStuff = … 
4:    override def toString = "PackRat: " + stuff.mkString(";") 
5:  } 

(SCALA glossary: var makes stuff a mutable instance variable, def keyword indicates function definition. List[String] is somewhat different than java List, for example, it is immutable: Note that Java/Groovy code above is not thread safe, SCALAs version does not have such problem.)

Here is yet another proof of the curly count being a good measure of code quality. On one end of the spectrum there is the imperative code with loop spelled out in Java (please count curlies in that code), on the other end there is SCALAs beautiful code where a particular kind of comprehension logic is simply declared!

Many developers think of the fact that SCALA allows you to drop curly brackets from one-liner functions as just a syntactic sugar and find the syntax iffy. My view is the opposite. The curlyless functions support the declarative style of coding and allows developer to define functions using expressions supported by SCALA language (contrast this with implementing all the methods in Java).

Obviously, there are other kinds of reusable comprehensions. For example reducing is far more general than joining. Here is SCALAs version of the above toString function using reduce:

override def toString = "PackRat: " + stuff.reduceLeft(_ + ";" + _)

Might look like compiler sugar (and again conceptually a deep stuff not iffy stuff), here is a spelled out version which is still purely declarative with no curlies:

def myConcatenateStrings(s1: String, s2: String):  String = s1 + ";" + s2
override def toString = "PackRat: " + stuff.reduceLeft(myConcatenateStrings)

Groovy code can be designed with more closures and fewer methods. This could facilitate much more declarative type of coding than methods allow. We have seen some of it in our previous post (Post on Curlies and GORM). The same declarative approach can be used to get rid of many for loops and make Groovy code closer to SCALA.

So what is the point of all of this? First, the obvious, code reuse and testability should be a good thing no matter what is the language; using reusable for loop logic can be done in Java too. It will look like someone is trying hard to be functional in Java (you can always say you are doing fluent coding and no one will know ;) Second, the idea of one-liners being closer to declarative programming warrants more thought and is more that a coding style no matter what is your language.

I hope to write more about it in the future.

Side Note: To all Java programmers (that would include me) I want to point out the obvious big difference between imperative for loops and functional comprehensions:  Imperative for loop is really a sequence of side-effects executed in order,  pure functional programming cannot have side-effects so comprehensions always return a new collection. 

Next Bashing of Curlies.