Easier Asynchronous State Modelling in React Redux or Hooks

Introduction

Modelling state for asynchronous actions in React using Redux via thunks or sagas is verbose. It requires a lot of code. It also is easy to accidentally miss flipping one of the values and result in a wrong state that your UI then shows the wrong thing. Thankfully there are ways to use Algebraic Data Types to model this state that results in less code in your reducers, whether in Redux or Hooks’ useReducer, as well as in your components. Below we’ll show the 3 problems modelling using Objects can cause and how to solve them using ADT’s.

All code shown below is on Github. The masterbranch has the Object way of modelling, and the types branch has the ADT solutions.

Most of the post below is based on prior art from Making Impossible States Impossible by Richard Feldman, and Solving the Boolean Identity Crisis by Jeremy Fairbank. Like Redux, stolen from Elm.

Continue reading “Easier Asynchronous State Modelling in React Redux or Hooks”

Advent of Code 2018 in Elm Review

Introduction

I participated briefly in the Advent of Code 2018. Every year, they post 31 coding puzzles, 2 per day. You have to solve them before you can proceed to next one. I wanted to post about what I learned. I’ve never participated before, and wanted to use it an excuse to force myself to use a Functional Programming language. I use Functional Programming concepts in my day job, but never had the opportunity to immerse myself, and force myself, to accomplish harder challenges in a pure FP language. It was doubly hard because the exercises are NOT what I do at my day job at all and are challenging. They were very hard in a fun way, though. Below I’ll cover the 6 exercises I did (I threw in the towel on Day 7), and explain some of the interesting nuances I found either with the exercise and thinking in FP… and thinking in Elm.

Continue reading “Advent of Code 2018 in Elm Review”

Four Ways to Compose Synchronous Functions in JavaScript: Nest, Promise, Compose, & Pipeline

Introduction

Functional Programming is built around composing pure functions. Composing functions means taking all those useful functions you wrote and using them together to build more powerful functions, and even applications. This article will cover the 4 main ways to do that with synchronous code which includes the new pipeline operator. A future article will handle asynchronous options as well as dealing with partial applications and curried functions. If you’d like to play with the examples yourself, I have a Code Sandbox setup with basic and advanced examples.

Read more