Thoughts on Functional Programming Podcast

Nil punning does give power to Lispers. But where does the power come from? Is it that nil really is a great value? Or is it more about the design choices made? In this episode, we explore this question.

Nil punning is a feature of Lisp. It began when nil was both the empty list and the false value. Two meanings for the same thing led to the idea of punning. Lispers liked it. And now, Clojure carries the tradition forward. In Clojure, nil has different meanings in different contexts. Is it good? Is it bad? We explore it in this episode.

What happens when your language is so powerful that small, independent teams can solve their problems without libraries? Does everyone flock to it? Or do you just get a lack of libraries?

Structure and Interpretation of Computer Programs talked about abstraction barriers as a way to hide the intricacies of data structures made out of cons cells. Is this concept still useful in a world of literal hashmaps with string keys? I say, yes, but in a much more limited way than before. In this episode, we go into what abstraction barriers are, why (and why not) to use them, and the limits of their usefulness.

I’ve gotten several questions about how to do X or Y in the Onion Architecture. It seems like giving the architecture a name has miscommunicated how simple it is. It’s just function calls that at some point are all calculations. In this episode, I try to deconstruct what makes the onion architecture work. Spoiler: it’s just function calls.

Are types compatible with data orientation? The short answer is ‘yes’. Types trade freedom of movement for clarity.

Data orientation allows freedom of movement between layers of meaning. Each interpretation adds a layer of meaning. If the data were hidden, we would not be able to freely interpret it how we want. In this episode, we explore an example of what it means to move up and down the layers of meaning.

We often talk about data orientation in functional programming circles. It basically means programming with data, without hiding your data. Our software is information systems, so why not treat the data in the raw? In this episode, we dive into what is data, what data orientation is all about, and how you program with it.

Total functions are functions that give you a valid return value for every combination of valid arguments. They never throw errors and they don’t require checks of the return value. Total functions help you write more robust code and simpler code, free from defensive checks and errors.