Notes from “Thinking Functionally with Haskell”

I’m always curious about how people think, and these days I’m most interested in how functional programmers think about programming problems. Along those lines I found a good blog post (tutorial) titled, “Thinking Functionally with Haskell”, and these are my notes from that post:

  • FP is all about data. Put data first.
  • “Most of it is about deciding which data structures you need, then coding up various transformations”
  • The Unix pipes example shows how we think in data, and massage that data with small, good, tools. Data in, massage the data, data out.
  • Regarding zip, think of zippers in clothes; the zipper merges the two elements/streams.
  • Creating data types is important. (Like OOP developers build classes.)
  • In Haskell, “it’s very quick and easy to add the data type that fits your problem domain well.”
  • With pattern matching you don’t need if statements so much.
  • When we have a collection of things to process, most of the transformations fall into two main patterns: mapping and folding.
  • Mapping is about applying the same operation to everything in a collection, but keeping the shape the same.
  • Folding: “Another way to think of folding is to replace the ’nodes’ of some data structure with functions (or constants)”; “collapsing or folding the data into a different type”,
  • “The dot deserves special mention. It is functional composition in Haskell, and basically means joining the output of one function to the input of another, so forming a bigger function.” (Sounds like a Unix pipe, or method chaining.)
  • “deforestation” - FP compilers optimize away some of the intermediate data structures in a chain of functions and so save on memory and time.

The Haskell notation for the types looks like this:

A -> B

indicating a conversion from some type A to some other type B. Tests on color values will have type:

RGB -> Bool

or determining the max of two colours will look like this:

RGB -> RGB -> RGB

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