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.
Thoughts on Functional Programming Podcast
An off-the-cuff stream of Functional Programming ideas, skills, patterns, and news from Functional Programming expert Eric Normand.
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.
Continuations are a cool feature you often find in functional languages. In this episode, we look at what they are, why you’re probably already using them, and the cool things you can do with them.
Functional programming cannot be suited for everything, right? Well, let’s not be so sure. Functional programming, like imperative programming and object-oriented programming, is a paradigm. It is a fundamental way to approach software. There are many languages that fall within the umbrella of FP. It is quite possible that everything we know how to do in software, we know how to do well with FP, the same way we know how to do it with imperative and with OOP.
Monads are real, y’all. They are all around us. In this metaphor-free episode, I’ll share two real-world monads you interact with all the time. No burritos or space suits, I promise! Plus, we’ll see why monads are useful in Haskell.
My new book, Grokking Simplicity, all about functional programming, is now available in early access. The first three chapters are ready to read. Go to https://lispcast.com/gs, add the book to the cart, and use discount code MLNORMAND for 50% off.
My favorite definitions of parallelism and concurrency come from Brian Goetz. They are not the traditional ones, which focus mostly on # of cores. In modern computing, we are sharing so many resources, parallelism and concurrency need to account for that. In this episode, we go over those definitions.
A few people have asked me how to develop Level 3 thinking. I’m not sure. But I’ve got some directions to try. In this episode, I go over 3 and a half ways to develop algebraic thinking.