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In this article we discuss the journey of Hoppinger, an innovative web development company, across the perilous lands of modern client-side web-application development with React and modern JavaScript variants such as TypeScript.

By boldly committing to the strictest software engineering disciplines of static typing, referential transparency, and functional programming, we are observing a significant increase in the quality and reliability of our deployed products, not to mention developer efficiency (when taking into account the dramatic reduction of bugs and defects).

The wonders of React and TypeScript

About a year ago, at Hoppinger, we made a serious switch to React and TypeScript. The goal was to stop with writing spaghetti-jQuery, and to embrace single page applications (SPA’s).

The big improvement of React over jQuery is simply lack of mutable shared state. When components can only communicate via callbacks, they effectively become referentially transparent: each component will always behave the same as long as it receives the same starting properties.

As a contrived example of why this is important, consider the following code:

let x1 = f(1)
let x2 = f(2)
let x3 = f(1)

What do we expect from such a simple piece of code? The first, naïve interpretation would expect x1 and x3 to be equal: after all, they both come from f(1). Whenever this does not happen, it means we are sharing mutable state across computations: this very often leads to unpredictable units of code that can only be used in some (poorly understood, but very specific) context.

React does not suffer from this issue. This fundamental reliability makes React components simpler to reuse and to compose with each other.

Enter TypeScript

Of course, as more and more code was written in React, we found ourselves confronted with the issue of correctly composing components with complex interfaces. The question “what properties does this component expect?” becomes so recurring, that you begin to wonder if a better experience is possible.

<PersonForm value={this.state.person}
            setValue={p => this.setState({...this.state, person:p})}

Code like the above can grow to dozens of properties, and it simply becomes possible to forget that the property editable actually was called edit, or that the PersonForm also expects a title property. Indeed, just by looking at the code above, it is impossible to tell if it correctly sets up all the needed properties, even though most of the code looks reasonable.

Shortly after our dive into React, we realized that TypeScript was the answer to this secondary problem: by using static typing and an alert compiler, we can get contextual help (and often also beautiful visual help in our editor) whenever we pass the wrong parameters to functions and components. If the title property is missing, then the compiler will alert us.

The Bliss

At this point, we had reached a temporary state of nirvana: we could build beautiful reusable components, and using and combining them together was happening effortlessly thanks to the helping hand of TypeScript.

The pains of React and TypeScript

Of course, the honeymoon phase was soon over. We quickly realized that the toolchain we had set up introduced new issues, just at a higher level of abstraction. One of the most evident new issue was the large amount of ceremony needed around the definition and invocation of a React component. Lots of components with just some basic local state will look like:

type Props = { ... }
type State = { ... }
class Comp extends React.Component<Props, State> {
  constructor(p:Props, context:any) {
    super(p, context)

    this.state = { ... }
  componentWillMount() {
  componentWillUnmount() {
  componentWillReceiveProps(p:Props) {
  render() {

Notice that we have not even gotten the chance yet to specify what the component even does: this is all just surrounding noise.

Moreover, it becomes quickly evident that without some very serious complexity, building truly generic abstract libraries of components requires a veritable mountain of glue code. Dispatching containers will quickly pop out all over the place when building wizards or any sort of state machine, looking roughly like:

type Props = { ... }
type State = { step:"A"|"B"|"C"|..., ... }
class Comp extends React.Component<Props, State> {
  constructor(p:Props, context:any) {
    super(p, context)

    this.state = { step:"A", ... }
  componentWillMount() {
  componentWillUnmount() {
  componentWillReceiveProps(p:Props) {
  render() {
    return step == "A" ?
        <AComponent data={this.state...} callback={x => this.setState(...)} />
      : step == "B" ?
        <BComponent data={this.state...} callback={y => this.setState(...)} />
      : ...

The mere creation of a form or a wizard, which is conceptually very simple, becomes unwieldy and verbose. Even though this does not offset the great power of this combination of React and TypeScript (the result is good enough more often than not!), it left us to wonder whether or not it would be possible to define better libraries and abstractions.

Enter Monads

Fortunately, this sort of problem has already been encountered, and conquered, in other domains within informatica. The functional programming community, in their quest to translate the elegance of mathematical and logical constructs into programming languages, stumbled decades ago across the concept of “monads”. Monads are a very abstract construction which is, surpisingly, proving to be very flexible, and capable of fixing issues related to:

  • concurrency management (async/await in ES6, TypeScript, and C#);
  • query management (flatMap in Immutablejs, Stream in Java, LINQ in C#);
  • collection management (generators in Python and JavaScript, yield return in C#);
  • and much more…

The impact of monads has been so profound and has led to some languages standing at the forefront of innovation (Haskell, F# and Scala among others) to acquire an extension to their syntax to make using generic monads visually more pleasant (the do notation in Haskell and computation expressions in F# are two interesting examples).

From monads to React

Sometimes we get lost in the more operative aspects of a given technology, thereby losing sight of the bigger picture, or abstracting away details which were actually relevant (and thus must not be abstracted away!).

Consider an HTML control, such as <input type=”text” … />. What are its inputs and outputs? A naïve answer would point out that the input control has:

  • the user-written text as input;
  • the input box in the page as output.

This user centric approach is certainly fundamental when building interactive systems, but does not help during the engineering phase. During the engineering phase, we should rather switch to a new perspective. After all, we are assembling a network of interconnected elements on a page.

This means, that, with respect to this interconnected network of elements on a page, the <input type=”text” … /> seen before should be now reformulated as having:

  • the initial text as input;
  • text as output (whenever the user types something).

Notice how the input and the output have been turned around with respect to the naïve definition, and even better, how we are now ignoring all the details that are not relevant for the composition of elements.

The idea that components should be classified according to their output (with respect to our network of components) is worth further investigation, as it alluringly implies that components can be linked when one of them produces values that the other component can consume!

We can continue along this thought process and give a general definition of our monadic react components, capturing the fact that a component which produces an output of type A is a react renderable (JSX.Element) which encapsulates a continuation (cont) which is called back whenever the JSX.Element is capable of yielding yet another output:

type C<A> = (cont:(_:A)=>void) => JSX.Element

Adding useful monadic operations (the well-known unit and bind/resolve and then/…) gives rise to a new library: monadic react.

We can now easily bind different components together. Suppose we had a component select_number:C<number>, we could print only the even numbers by saying:

.filter(n => n % 2 == 0)
.map(n => `The last even number you typed is ${n}`)
.then(s => string("view")(s))

(Note: this is actual monadic react code!)

Scaling this approach up to forms, wizards, menus, and much more is, so far, holding up. For example, here is the actual code from a form:

let course_form_sample : C<void> =
  simple_form_with_save_button("edit", c => `course_${c.Id}`,
    { kind:"string", field_name:"Name",
      in:c => c.Name || "", out:c => (n:string) => ({...c, Name:n}),
      get_errors:c=>c.Name.length < 3 ? ["The name cannot be shorter than three characters."] : [] },
    { kind:"number", field_name:"Points",
      in:c => c.Points || 0, out:c => (p:number) => ({...c, Points:p}),
      get_errors:c=>c.Points < 1 ? ["The course must be worth at least one point."] : [] },
    { kind:"date", field_name:"Begin",
      in:c => c.StartDate, out:c => (p:Moment.Moment) => ({...c, StartDate:p}),
      get_errors:c=>[] },
  download_course(1), upload_course)

The definition of the form has essentially become declarative and is now very hard to get wrong.

Moreover, since the type of the object is now C<void>, the form itself can be composed again, for example to build a larger form or a larger page with multiple smaller components working in unison. As they say, it’s turtles all the way down.

The rest of the React world?

monadic react supports, of course, the integration of its structures within existing React applications, thereby allowing developers to introduce it on a very small scale, in the context of easily replaceable peripheral functionality, and use it more and more if desired and/or convenient.

At the same time, existing React components can be wrapped inside a thin adapter in order to be used inside a monadic react application. This makes it possible to reuse existing React code without having to refactor it. Moreover, the wrapping requires no more than passing a continuation (callback) that notifies the rest of monadic react of the fact that the external component has produced some data that needs to be processed.

The benefits

The main benefits that we have noticed are:

  • we write less code: this reduces the attack surface where potential bugs may hide;
  • we write less boring code: this allows us to focus on functionality, not plumbing;
  • we can define templates: this allows us to create a DSL per application;
  • we still have code and regular old functions everywhere: we can do plenty of regular coding between components;
  • we can easily compose and recompose components in a type safe fashion: this allows us to experiment and refactor SPA applications quickly.

Useful links

All sources are shared, of course, under an open source license (MIT). The project also has an npm package.

To see the library in action, you can jump to:


The world of web development is changing, fast. Innovation is happening at a break-neck pace, and large companies educate users every day to the marvelous possibilities that web sites and web applications offer. This makes life exciting, but also less than easy, for web developers: the technology to support this change is rapidly increasing in complexity, as the applications that customers consider to be the norm are more and more interactive and rich.

Staying ahead of the wave requires thinking in dynamic terms, and embracing, rather than fighting, the adoption of more reliable engineering practices.

Monads, and in general higher principles from informatica provide the toolbox. Teams that dare dive in will thrive in this beautifully evolving world.

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Wij zijn Hoppinger

Met een team van 75 specialisten vertalen we complexe en uitdagende vraagstukken naar web en native oplossingen die onze opdrachtgevers succesvoller en het leven van hun publiek gemakkelijker maken. Zo maken we als strategisch partner digitale ambities waar.

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