Hamming (coding challenge) Part II

Hamming coding challenge Part I

This article is the second part of Exercism's Hamming coding challenge. Initially I had explained my first solution and the lesson learnt as hinted by Exrecism. This second part focuses more on how I refactored my initial solution as seen in part I.

The refactored code goes like this:

class UnequalStrandError < ArgumentError def initialize(error_message = 'Strands must be of equal length') super end end class Hamming def self.compute(first_strand, second_strand) new(first_strand, second_strand).distance end attr_reader :distance, :first_strand, :second_strand private def initialize(first_strand, second_strand) @first_strand = first_strand @second_strand = second_strand validate @distance = nucleotides.count { |n1, n2| n1 != n2 } end def nucleotides(first_strand, second_strand) first_strand.chars.zip(second_strand.chars) end public def validate raise UnequalStrandError unless first_strand.length == second_strand.length end end 

From this second iteration you can observed that it is now leaner and readable. However, what did do to make it leaner and readable?
As usual I will start with the UnequalStrandError class. In the new code I created a function called validate. This will take care of raising errors whenever any error is encountered in the code. Note that I now have a one line code:

 raise UnequalStrandError unless first_strand.length == second_strand.length 

compared to what I had earlier to help handle raising errors:

 raise UnequalStrandError if first_strand.empty? && second_strand.size.positive? raise UnequalStrandError if first_strand.size.positive? && second_strand.empty? raise UnequalStrandError if first_strand.size > second_strand.size raise UnequalStrandError if first_strand.size < second_strand.size 

Secondly I refactored compute as :

 def self.compute(first_strand, second_strand) new(first_strand, second_strand).distance end 

The compute method in the above is a class method as indicated with the self prefix and also in compute body, I instatiated Hamming class and called distance on it.
The distance method is defined in initialize method:

 def initialize(first_strand, second_strand) @first_strand = first_strand @second_strand = second_strand validate **@distance = nucleotides.count { |n1, n2| n1 != n2 }** end 

and it is defined as an instance variable which is then exposed using attr_reader method.

 attr_reader :distance, :first_strand, :second_strand 

Note that @distance is a variable holding the result derived from nucleotides.count { |n1, n2| n1 != n2 }. Also the nucleotides method defined in the body of Hamming class handles the separation and zipping of first_strand and second_strand
In the initial code I had used the split() method to get an array from the string supplied but I found chars() to be effective as well. After creating the array I zipped both first_strand and second_strand array together. While using the zip() method this is what it does:

 first_strand = [G,A,G,C] second_strand = [C,A,T,C] first_strand.zip(second_strand) result = [[G,C],[A,A],[G,T],[C,C]] 

After zipping I called the count() method on the zipped array and this method was able to get a count of items in the sub array that are not the same.

With this refactoring for readability, I learnt about self, and what self means in the context of this challenge. I understood that when self is used in a code, it refers to the class and in this case it is reffering to the class Hamming.
I also learnt a new trick: instantiating a class in a class method and calling a defined method in the class on it.

 def self.compute(first_strand, second_strand) new(first_strand, second_strand).distance end 

When Hamming.compute is called, the new class instantiation will also call the method involved. This is a quick way of getting results instead of having to create new objects of class Hamming.
I also learned that, I can raise Errors in the initialize method to catch the errors thrown as quick as possible.

These are what I learned while solving the hamming coding challenge on Exercism. I will be solving more challenges on Exercism and do watch out for more articles on how I solved and refactored the challenges.