In the first part of this blog post, I wrote about why FP is mandatory for programmers that work on modern software projects. Summing it up, it was like this – modern hardware scales up by adding cores, therefore, if software wants to scale up and well, then it has to do it by going concurrent, and FP is a good choice to deal with concurrent programming issues.
In this post, I’ll write about some differences between traditional and FP programming and I’ll present one more reason about why FP is a good match with parallel programming.
You can write bad code in any language. That’s a fact. So there’s no magic in functional programming to turn a lame programmer in a brilliant one. On the other hand, you can write pretty good code in the functional paradigm by sticking with the tools provided by functional languages.
So, let’s have a look at this FP thing… First, it is evident that this is not your parent’s FP – map, filter, fold… Just a few of the most recurring spells you’d see in a Scala source and none of them was in the notes I jotted down during my University courses. Even looking at my LISP textbook I couldn’t find any reference to the map operation. (Just to help those with no FP background – map (transform in C++) is an operation that applies a transformation to each item in a collection. In other words, if you have a function that turns apples into pears, then – using map – you can turn your array of apples into an array of pears.)