Constructs a tagged union data structure.

This feature is experimental!

This API is still experimental, so it may change or be removed in future versions. You should not rely on it for production applications.


union(typeId, patterns)
(String, Object (Array String)) => Union


Constructs a tagged union data structure.

Using the adt/union module:

const union = require('folktale/adt/union/union');

var List = union('List', {
  Nil(){ },
  Cons(value, rest) {
    return { value, rest };

var { Nil, Cons } = List;

Cons('a', Cons('b', Cons('c', Nil())));
// ==> { value: 'a', rest: { value: 'b', ..._ }}

Why use tagged unions?

Data modelling is a very important part of programming, directly affecting things like correctness and performance. Folktale is in general mostly interested in correctness, and providing tools for achieving that.

When modelling data in a program, there are several different choices that one must make in an attempt to capture the rules of how that data is manipulated and what they represent. Data modeling tends to come in three different concepts:

  • Scalars represent concepts that have only one atomic value at a time. This value makes sense on its own, and can't be divided into further concepts. Examples of this are numers, strings, etc.

  • Product represent bigger concepts that are made out of possibly several smaller concepts, each of which is independent of each other, and always present. An object that contains a person's name and age is an example of a product, arrays are another example.

  • Unions represent one of out of many concepts, at any given time. JS doesn't have many data structures that capture the idea of a union, but there are many cases where this happens in a codebase:

    • Reading a file may either give you the data in that file or an error object;

    • Accessing a property in an object may either give you the value or undefined;

    • Querying a database may give you a connection error (maybe we weren't able to contact the database), a query error (maybe the query wasn't well formed), a "this value isn't here" response, or the value you want.

Out of these, you're probably already familiar with products and scalars, because they're used everywhere in JavaScript, but maybe you're not familiar with unions, since JavaScript doesn't have many of them built-in.

For example, when reading a file in Node, you have this:

fs.readFile(filename, (error, value) => {
  if (error != null) {
  } else {

The callback function receives two arguments, error and value, but only one of them may ever be present at any given time. If you have a value, then error must be null, and if you have an error, then value must be null. Nothing in the representation of this data tells you that, or forces you to deal with it like that.

If you compare it with an API like fetch, where you get a Promise instead, many of these problems are solved:

  (response) => handleSuccess(response),
  (error)    => handleError(error)

Here the result of fetch can be either a response or an error, like in the readFile example, but the only way of getting to that value is through the then function, which requires you to define separate branches for handling each case. This way it's not possible to forget to deal with one of the cases, or make mistakes in the branching condition, such as if (error == null) { handleError(...) } — which the first version of this documentation had, in fact.

Modelling data with adt/union

So, properly modelling your data helps making sure that a series of errors can't ever occurr in your program, which is great as you have to deal with less problems, but how does adt/union help you in that?

A simple failure case

To answer this question let's consider a very simple, everyday problem: you have a function that can return any value, but it can also fail. How do you differentiate failure from regular values?

const find = (predicate, items) => {
  for (let i = 0; i < items.length; ++i) {
    const item = items[i];
    if (predicate(item))  return item;
  return null;

The example above returns the item if the predicate matches anything, or null if it doesn't. But null is also a valid JavaScript value:

find(x => true, [1, 2, 3]);    // ==> 1
find(x => false, [1, 2, 3]);   // ==> null
find(x => true, [null, 1, 2]); // ==> null

Now, there isn't a way of differentiating failure from success if your arrays have a null value. One could say "this function works for arrays without nulls", but there isn't a separate type that can enforce those guarantees either. This confusing behaviour opens the door for bugs that are very difficult to find, since they're created way before they hit the find function.

A more practical approach is to return something that can't be in the array. For example, if we return an object like: { found: Bool, value: Any }, then we don't run into this issue:

const find2 = (predicate, items) => {
  for (let i = 0; i < items.length; ++i) {
    const item = items[i];
    if (predicate(item))  return { found: true, value: item };
  return { found: false };

find2(x => true, [1, 2, 3]);    // ==> { found: true, value: 1 }
find2(x => false, [1, 2, 3]);   // ==> { found: false }
find2(x => true, [null, 1, 2]); // ==> { found: true, value: null }

We can differentiate between successes and failures now, but in order to use the value we need to unpack it. Now we have two problems: found and value aren't entirely related, and we have to create this ad-hoc relationship through an if statement. That's very easy to get wrong. Another problem is that nothing forces people to check found before looking at value.

So, a better solution for this is to use tagged unions and pattern matching:

const union = require('folktale/adt/union/union');

const Maybe = union('Maybe', {
  None() { return {} },
  Some(value) { return { value } }

const find3 = (predicate, items) => {
  for (let i = 0; i < items.length; ++i) {
    const item = items[i];
    if (predicate(item))  return Maybe.Some(item);
  return Maybe.None();

find3(x => true, [1, 2, 3]);    // ==> Maybe.Some(1)
find3(x => false, [1, 2, 3]);   // ==> Maybe.None()
find3(x => true, [null, 1, 2]); // ==> Maybe.Some(null)

find3(x => true, [1, 2, 3]).matchWith({
  None: ()          => "Not found",
  Some: ({ value }) => "Found " + value
}); // ==> "Found 1"

Modelling complex cases

Let's consider a more complex case. Imagine you're writing a function to handle communicating with some HTTP API. Like in the case presented in the previous section, a call to the API may succeed or fail. Unlike the previous example, here a failure has more information associated with it, and we can have different kinds of failures:

  • The operation may succeed, and return a value;
  • The operation may fail:
    • Because it wasn't possible to reach the API (due to a network error, for example);
    • Because the return value of the API wasn't in the expected format (unable to parse);
    • Because the API itself returned an error (e.g.: if the request had bad data in it).

A common way of writing this in Node would be like this:

api.method((error, response) => {
  if (error != null) {
    if (error.code === "http") {
      // handle network failures here
    if (error.code === "service") {
      // handle service failures here
  } else {
    try {
      var data = normalise(response);
      // handle success here 
    } catch(e) { 
      // handle invalid responses here

But again, in this style of programming it's easier to make mistakes that are hard to catch, since we're assigning meaning through control flow in an ad-hoc manner, and there's nothing to tell us if we've got it wrong. It's also harder to abstract, because we can't capture these rules as data, so we have to add even more special control flow structures to handle the abstractions.

Let's model it as a tagged union instead. We could make a single data structure that captures all 4 possible results, and that would be a reasonable way of modelling this. But on the other hand, we wouldn't be able to talk about failures in general, because this forces us to handle each failure case independently. Instead we'll have two tagged unions:

const union = require('folktale/adt/union/union');

const Result = union('Result', {
  Ok(value) {
    return { value }; 
  Error(reason) {
    return { reason };

const APIError = union('APIError', {
    return { error };
  ServiceError(code, message) {
    return { code, message };
  ParsingError(error, data) {
    return { error, data };

Then we can construct these values in the API, and make sure people will handle all cases when using it:

function handleError(error) {
    NetworkError: ({ error }) => { ... },
    ServiceError: ({ code, message }) => { ... },
    ParsingError: ({ error, data }) => { ... }

api.method(response => {
    Error: ({ reason }) => handleError(reason),
    Ok:    ({ value })  => { ... }

Providing common functionality

When you're modelling data with unions it's tempting to create a lot of very specific objects to capture correctly all of the choices that may exist in a particular domain, but adt/union only gives you construction and pattern matching, so what if you want your types to have a notion of equality?

That's where the concept of derivation comes in. A derivation is a function that provides a set of common functionality for an union and its variants. For example, if one wanted to add the notion of equality to an union, they could derive Equality as follows:

const union = require('folktale/adt/union/union');
const Equality = require('folktale/adt/union/derivations/equality');

const Either = union('Either', {
  Left(value) { return { value } },
  Right(value){ return { value } }

Note the .derive(Equality) invocation. derive is a method that can be called at any time on the union to provide new common functionality to it. In this case, the Equality derivation gives all variants an equals() method:

Either.Left(1).equals(Either.Left(1));   // ==> true
Either.Left(1).equals(Either.Right(1));  // ==> false
Either.Right(1).equals(Either.Right(2)); // ==> false
Either.Right(2).equals(Either.Right(2)); // ==> true

While adt/union provides a set of common derivations (categorised Derivation in the documentation), one may create their own derivation functions to use with Folktale's unions. See the Extending unions section for details.


The adt/union module approaches this problem in a structural-type-ish way, which happens to be very similar to how OCaml's polymorphic variants work, and how different values are handled in untyped languages.

In essence, calling union with a set of patterns results in the creation of N constructors, each with a distinct tag.

Revisiting the previous List union example, when one writes:

const union = require('folktale/adt/union/union');

var List = union('List', {
  Nil:  () => {},
  Cons: (value, rest) => ({ value, rest })

That's roughly equivalent to the idiomatic:

var List = {};

function Nil() { }
Nil.prototype = Object.create(List);

function Cons(value, rest) {
  this.value = value;
  this.rest  = rest;
Cons.prototype = Object.create(List);

The union function takes as arguments a type identifier (which can be any object, if you want it to be unique), and an object with the variants. Each property in this object is expected to be a function that returns the properties that'll be provided for the instance of that variant.

The given variants are not returned directly. Instead, we return a wrapper that will construct a proper value of this type, and augment it with the properties provided by that variant initialiser.


The adt/union module relies on JavaScript's built-in reflective features first, and adds a couple of additional fields to this.

Types and Tags

The provided type for the union, and the tag provided for the variant are both reified in the union structure and the constructed values. These allow checking the compatibility of different values structurally, which sidesteps the problems with realms.

The type of the union is provided by the global symbol @@folktale:adt:type:

const union = require('folktale/adt/union/union');

var Id = union('Identity', { Id: () => {} });
// ==> 'Identity'

The tag of the value is provided by the global symbol @@folktale:adt:tag:

var List = union('List', {
  Nil: () => {},
  Cons: (h, t) => ({ h, t })
// ==> 'Nil'

These symbols are also exported as properties of the union function itself, so you can use union.typeSymbol and union.tagSymbol instead of retrieving a symbol instance with the Symbol.for function.

is-a tests

Sometimes it's desirable to test if a value belongs to an union or to a variant. Out of the box the structures constructed by union provide a hasInstance check that verify if a value is structurally part of an union structure, by checking the Type and Tag of that value.

checking if a value belongs to an union:
const union = require('folktale/adt/union/union');

var IdA = union('IdA', { Id: (x) => ({ x }) });
var IdB = union('IdB', { Id: (x) => ({ x }) });

IdA.hasInstance(IdA.Id(1))  // ==> true
IdA.hasInstance(IdB.Id(1))  // ==> false
checking if a value belongs to a variant:
const union = require('folktale/adt/union/union');

var Either = union('Either', {
  Left:  value => ({ value }),
  Right: value => ({ value })
var { Left, Right } = Either;

Left.hasInstance(Left(1));  // ==> true
Left.hasInstance(Right(1)); // ==> false

Note that if two unions have the same type ID, they'll be considered equivalent by hasInstance. You may pass an object (like Symbol('type name')) to data to avoid this, however reference equality does not work across realms in JavaScript.

Since all instances inherit from the union and the variant's prototype it's also possible to use proto.isPrototypeOf(instance) to check if an instance belongs to an union by reference equality, rather than structural equality.

Extending unions

Because all variants inherit from the union namespace, it's possible to provide new functionality to all variants by simply adding new properties to the union:

const union = require('folktale/adt/union/union');

var List = union('List', {
  Nil:  () => {},
  Cons: (value, rest) => ({ value, rest })

var { Nil, Cons } = List;

List.sum = function() {
  return this.matchWith({
    Nil:  () => 0,
    Cons: ({ value, rest }) => value + rest.sum()

Cons(1, Cons(2, Nil())).sum();
// ==> 3

A better approach, however, may be to use the derive function from the union to provide new functionality to every variant. derive accepts many derivation functions, which are just functions taking a variant and union, and providing new functionality for that variant.

If one wanted to define a JSON serialisation for each variant, for example, they could do so by using the derive functionality:

function ToJSON(variant, union) {
  var { tag, type } = variant;
  variant.prototype.toJSON = function() {
    var json = { tag: `${type}:${tag}` };
    Object.keys(this).forEach(key => {
      var value = this[key];
      if (value && typeof value.toJSON === "function") {
        json[key] = value.toJSON();
      } else {
        json[key] = value;
    return json;

var List = union('List', {
  Nil:  () => {},
  Cons: (value, rest) => ({ value, rest })

var { Nil, Cons } = List;

// ==> { tag: "List:Nil" }

Cons(1, Nil()).toJSON()
// ==> { tag: "List:Cons", value: 1, rest: { "tag": "List:Nil" }}


Supporting objects


The basis of all union data types.



A Symbol.


A Symbol.


Source Code

Defined in source/adt/union/union.js at line 157, column 0
(typeId, patterns) => {
  const UnionNamespace = Object.create(Union);
  const variants       = defineVariants(typeId, patterns, UnionNamespace);

  extend(UnionNamespace, variants, {
    // This is internal, and we don't really document it to the user
    [TYPE]: typeId,

     * type: Array Variant
     * module: null
     * ~belongsTo: UnionNamespace
    variants: values(variants),

     * ~belongsTo: UnionNamespace
     * module: null
     * type: |
     *   Union.(Variant) -> Boolean
    hasInstance(value) {
      return Boolean(value)
      &&     value[TYPE] === this[TYPE];

  return UnionNamespace;
(c) 2013-2017 Quildreen Motta, and CONTRIBUTORS
  • Quildreen Motta
  • Quildreen Motta <queen@robotlolita.me> (http://robotlolita.me/)