Thoughts on Functional Programming Podcast

Referential transparency is a term you’ll hear a lot in functional programming. It means that an expression can be replaced by its result. That is, 5+4 can be replaced by 9, without changing the behavior of the program. You can extend the definition also to functions. So you can say + is referentially transparent, because if you call it with the same values, it will give you the same answer.

In OOP, we wrap our data in an interface, which is called implementation-hiding or data-hiding. In functional programming, we don’t do that. We use our data in the nude. We pass the data around and allow the context to interpret the data as it seens fit. In this episode, we look at this significant difference between OOP and FP and how to do it.

Higher-order functions are functions that take a function as an argument and/or return a function. We use them a lot in functional programming. They are a way to define reusable functionality, as we do with map, filter, and reduce.

Function composition is taking the return value of one function and passing it as an argument to another function. It’s common enough that functional programmers have turned it into its own operation. In this episode, we go deep into why it’s important and how you can use it and write it yourself.

Some functions have a special value that will stop computation. For instance, multiplication will stop if you multiply zero by anything. We can use this property to our advantage.

Some functions have identities, which are values that tell you where to start calculating. In this episode, we look at what identities are, some examples of them, and how you can use them in your own code.

Promises are more popular than ever. They make our code better than callbacks. But why? In this episode, I dive deep into why promises are better than callbacks, and it’s not just about indentation.

First-class functions are functions that can be treated like any other value. You can pass them to functions as arguments, return them from functions, and save them in variables. In this episode, we talk about why they are important for functional programming and what features we require of them.

It can be really hard to find time to learn a new language or new paradigm. How can you find the time you need? In this episode, I share 5 tips for setting yourself for success when you’re learning functional programming.