A Deep Dive Into Iterators And Generators In Javascript

This article’s a journey: The goal is to build to an understanding of generators from the ground up, detailing the intuitions behind why generators, and JavaScript generators in particular, work the way they do. Surprises along the way include iterables, symbols, coroutines, and async/await. Let’s dive into square one!

Intro to Iteration

The Google dictionary result for iteration is “the repetition of a process.”

for and while loops are both examples of iteration. Programming languages can additionally offer declarative shorthands for constructing “looped” passes through larger entities. The act of repeating an operation on an entity in a subset by subset manner can be referred to as “iterating over” that entity.

Here’s an example of iteration in JavaScript using the spread operator:

// ['w', 'o', 'r', 'd']

The spread operator passes over the string 'word' character by character, performing the same operation on each. Each character is pulled from its context in the larger string and pushed onto the array on its own.

Here’s another example of iteration in JavaScript:

for (const char of 'word') {
// w o r d

Rather than commenting on what’s going on above specifically, let’s consider the general trened illustrated by this last example:

for (const variable of iterable) {
  // do something

In general, iteration can be performed on what is known as an iterable; i.e., an object implementing the “iterable protocol.”

Iteration Protocols

Iterable protocol

According to MDN, “The iterable protocol allows JavaScript objects to define or customize their iteration behavior.”

If you were a JavaScript object, how would you define your iteration behavior?

MDN continues: “In order to be iterable, an object…(or one of the objects up its prototype chain) must have a property with a @@iterator key which is available via [the] constant Symbol.iterator.”

Let’s back up there–Symbol, Symbol.iterator, @@iterator, iterables–and tackle these one by one.


In JavaScript, a Symbol is a primitive data type representing a unique ID token. Symbols perform a whole grab bag’s worth of functionality.

One thing Symbols can do is expose built-in object capabilities, including the only sometimes realized ability for objects to perform iteration. That its collection of data can be iterated over is, by default, an unrealized possibility for an object literal. Symbols thus expose the way in which JS objects may conform to the iterator protocol.


One can expose certain JavaScript types’ iteration behavior via accessing these types’ Symbol.iterator property. Strings and Arrays both have built-in iterators (StringIterator and Array Iterator, respectively); one need only invoke a string or array’s Symbol.iterator built-in function to access such an iterator directly. Object literals’ iteration behavior must be manually defined.

In defining a Symbol.iterator property on an object literal, we can take a thing without default iteration behavior, set iteration behavior, and then iterate over that thing.


const myIterable = {}
myIterable[Symbol.iterator] = ??
for (const val of myIterable) {
  // do something with val


“@@ describes what’s called a well-known symbol” (Stack Overflow). @@iterator is just shorthand for Symbol.iterator.


The Symbol.iterator invocation discussed can be summed up as a process of turning objects into iterables, where an iterable is an object from which you can get an iterator.

Iterables are thus objects that can be iterated over, according to the iterator protocol. The iterator protocol details how iterables work under the hood.

Iterator protocol

In the context of the iterator protocol, MDN defines iteration as “a standard way to produce a sequence of values (either finite or infinite).” An object thus accords with the iterator protocol when

  1. it knows how to access items from a collection one at a time, while
  2. keeping track of its current position within that sequence. An iterable is furthermore supposed to meet both these criteria in a particular way: An iterable must implement a next() method.


next() is a function not requiring any arguments and returning an object with two properties, done and value.

A great analogy for how next() works with regard to iterables is a Pez dispenser. You can consume the “next” candy from a Pez dispenser in a one-at-a-time fashion. When there are no more candies left, the dispenser is (at least temporarily) “done.”

Let’s observe next() in action.

First, let’s set an iterable:

const iterable = 'hi'[Symbol.iterator]()

Because the String data type contains the built-in StringIterator property, one need only invoke a string’s Symbol.iterator built-in function to effectively set an iterable from that string. iterable is such a StringIterator object.

We can now invoke the next() on our iterable:

iterable.next() // 1st call
// { value: "h", done: false }

We get back an object with the value prop set to "h"–the first character of "hi", our original thing-to-be-iterated-over–and the done prop set to false.

Note that calling our iterable again, this time yielding a value of "i", still keeps that done prop false.

iterable.next() // 2nd call
// { value: "i", done: false }

It is only after we attempt to call the iterable an “n + 1th” time, where n is the number of items our iterable consumes, that we get back an object with a value of undefined and done set to true.

iterable.next() // 3rd call
// { value: undefined, done: true }

Subsequent calls to the same iterable now yield the same result:

iterable.next() // 4th call
// { value: undefined, done: true }
iterable.next() // 5th call
// { value: undefined, done: true }
iterable.next() // nth call
// { value: undefined, done: true }

Note that if we are, say, streaming in data, n may be very large or even infinite. It is thus conceivable for an iterable not to terminate.

Intro to Generators

We’ve glossed how to take a thing without default iteration behavior, set iteration behavior via [Symbol.iterator], and then iterate over that thing:

const iterableObj = {}
iterableObj[Symbol.iterator] = ?????
for (const val of iterableObj) {
  // something with val

But what actually happens on that second line? What should you set an iterable-to-be’s Symbol.iterator property to?

A generator, of course!

iterableObj[Symbol.iterator] = INSERT GENERATOR HERE

We now have our requirements for a generator function: A generator function must return an iterable object, of a kind with you would get from invoking Symbol.iterator; and this iterable “generator object” must conform to iterator protocol, supporting a next() method that returns an object with value and done props.

Our work’s cut out for us!

Generator Syntax

Let’s make a generator:

const myIterable = {}

myIterable[Symbol.iterator] = function*() {
  let i = 3
  while (i > 0) yield i--
  yield 'liftoff!'

for (const val of myIterable) console.log(val)
/* logs the following:

What’s going on above? We’re able to use myIterable as an iterable by defining its Symbol.iterator property to be a generator. myIterable then communicates (somehow) with the generator available at myIterable[Symbol.iterator] to yield the results we expect.

Meanwhile, we employ two significant bits of syntax in our generator:


The “*” in the function signature signifies a generator function.


The yield keyword functions as a “play/pause” button for generators. Generator execution can be paused and resumed at yield statements.

Generators thus supports the iterable protocol in addition to the iteration protocol by allowing for the creation of a pausable, resumable–“yieldable”–function. Iteration is performed in the for...of loop via the yielding of next values.

We can condense the code block above to the following:

const myGenerator = function*() {
  let i = 3
  while (i > 0) yield i--
  yield 'liftoff!'
for (const val of myGenerator()) console.log(val)
/* logs the same:

Invoking a Generator

Let’s dispel some magic. What happens when we invoke the myGenerator function?

  1. A new iterable “generator object” is created: const generatorObj = {}. (You cannot use the “new” keyword to construct an iterable generator object. Instead, you must create a generator function and invoke it.)
  2. A Symbol.iterator property is instantiated on the new iterable generator object, and set to the myGenerator function: generatorObj[Symbol.iterator] = myGenerator.
  3. The iterable generator object is returned.

Altogether, it works out like this:

const myIterable = myGenerator()
const generatorObj = {}
generatorObj[Symbol.iterator] = myGenerator
return generatorObj
const myIterable = generatorObj

We can now iterate through the generator through use of the iterator protocol’s next() method. The for...of loop does this implicitly.

Usage of Generators

Generators can be used for a variety of problems, including but not limited to executing asynchronous operations (think fetch and database calls) and lazily-loading data.

If you’re familiar with async/await syntax, consider that generators can be used for any operations for which you’d use async/await. As noted here–L, “Generators, Coroutines, Async/Await” (highly recommended)–Babel will actually transpile async/await syntax to generator syntax. As the just-cited article notes, this is because “async functions are just syntactic sugar on top of generators. They use the exact same concept as coroutines.”

Which, of course, leads to the question of what a coroutine actually is.

Generators and Coroutines

As defined in the above article, “Coroutines are a programming concept that allows functions to pause themselves and give control to another function. The functions pass control back and forth.” We need some way to manage generators, and coroutines constitute this level of management.

Control flow goes something like this:

Coroutine                           Generator
---------                           ---------
Example: Let’s Seed a Database

Let’s say we’re seeding a DB. We’ve got some dummy data and want to call a single seed() method to perform operations including adding the single user and all the moves to our DB, as well as, say, instantiating a one-many relation between user and moves. (For the sake of this example, I’ll be using the ORM syntax of Sequelize for instance creation.)

const hedgehogUser = {
  id: 1, name: Mittens, age: 5
const hedgehogMoves = [
  { id: 1, description: ball up },
  { id: 2, description: roll },
  { id: 3, description: go to work },
  { id: 4, description: charlie brown },
  { id: 5, description: cha cha real smooth }


We could, and probably should, write seed() using async/await syntax…

async function seed() {
  const [ user, moves ] = await Promise.all([
  await user.setMoves(moves)

…or, we could write seed() as a coroutine managing a generator in the following way:

function* seedGenerator() {
  const [ user, moves ] = yield Promise.all([
  yield user.setMoves(moves)

function seedCoroutine(generator) {
  const iterable = generator()
  function doNext(data) {
    const { value, done } = iterable.next(data)
    if (!done) value.then(doNext)

function seed() {
  return seedCoroutine(seedGenerator)
A Note on next(args)

Before we dive into the control flow, let’s address the next(data) call above. next() can take in an argument. In this way, our generator can access the argument passed through next(). When we thus resume the generator, we resume right where we left off, and whatever we pass to next() gets passed into the generator as the value of the yield statement where we left off. This way, if we’ve assigned some variable to this yield statement, this variable can hold the value of whatever we passed into whatever next() statement got us back to the yield.

Control Flow Walkthrough

The generator/coroutine combo makes for the following sequence of events when calling seed(). (I’d encourage you to read over the following list primarily to get a sense of the general pattern, and only secondarily to try and understand how every line of code is working in each and every context.)

  1. The first thing that happens when we call seed() is that seedCoroutine is called with our seedGenerator passed in as an argument.
  2. seedGenerator is invoked, giving us an iterable object, iterable, whose Symbol.iterator property has been set to seedGenerator.
  3. Still within seedCoroutine, the doNext function gets invoked with no arguments.
  4. Within doNext, data === undefined. So when we call next(data) off iterable, we’re effectively calling next(undefined).
  5. seedCoroutine “pauses” at next() and hands off control to seedGenerator.
  6. seedGenerator runs, yielding an array of promises for a hedgehogUser instance and hedgehogMoves instances, respectively.
  7. seedGenerator “pauses” at yield and hands off control to seedCoroutine.
  8. seedCoroutine resumes right where it left off, at next(). iterable.next(data) becomes { value: Promise, done: false }. We destructure the value and done properties off of this object.
  9. done === false, so we wait until value settles. (We might also synchronously return a promise at this point to any outer scope requiring knowledge of what our coroutine is up to. This is how async/await works: an async function returns a promise that can eventually resolve to the async function’s eventual return value.)
  10. When value settles, we call doNext, passing in the resolved data as an argument: doNext(resolvedData). In this case, the resolved data is an array of a hedgehogUser object and an array of hedgehogMoves objects.
  11. We then call iterable.next(resolvedData).
  12. seedCoroutine “pauses” at next() and hands off control to seedGenerator.
  13. seedGenerator resumes right where it left off, at yield. The entire yield statement (yield Promise.all ...) becomes resolvedData. We destructure [ users, moves ] from the resolvedData array.
  14. seedGenerator continues execution. We reach the next yield statement, yielding a promise for the user on whom we want to set some moves.
  15. seedGenerator “pauses” at yield and hands off control to seedCoroutine.
  16. seedCoroutine resumes at next(). iterable.next(previouslyResolvedData) becomes { value: Promise, done: false }. We destructure the value and done properties off of this object.
  17. done === false, so we wait until value settles.
  18. When value settles, we call doNext, passing in the resolved data as an argument: doNext(newlyResolvedData). In this case, the resolved data is a single hedgehogUser instance.
  19. We then call iterable.next(newlyResolvedData).
  20. seedCoroutine “pauses” at next() and hands off control to seedGenerator.
  21. seedGenerator resumes at the same yield statement at which it left off. The entire yield statement (yield user.setMoves(moves)) becomes newlyResolvedData.
  22. We hit the end of the seedGenerator function. By default, seedGenerator hands off control to seedCoroutine, passing back an object with value: undefined and done: true.
  23. seedCoroutine resumes at next(). iterable.next(data) becomes { value: undefined, done: true }. We destructure the value and done properties off of this object.
  24. done !== false, so we don’t have to wait until value settles. We’re done!

We have just seen how coroutines can manage generators to support custom iteration behavior. As the author of the by-now-clearly-inspiration-article-for-this-article, “Generators, Coroutines, Async/Await” notes of this use case:

As long as the generator only yields promises, next.value will always be a promise. The coroutine calls then on the promise to run doNext again when the promise finishes. When doNext runs again, it unpauses the generator and gets the next promise. This repeats until there’s no more yields in the generator. Each time coroutine calls next, control passes to the generator. Each time the generator calls yield, control returns to coroutine. This concept of passing control back and forth asynchronously is known as coroutine. You can use synchronous control flow with coroutines.


At this point you’ve hopefully gained some familiarity with the generator interface. There are several key uses for generators besides seeding a database. Generators can be used to compose middleware, coordinate fetch requests, implement streaming (lazy loading, infinite scrolloing) behavior–basically any operations for which you’d use async/await. As L, author of “Generators, Coroutines, Async/Await” notes, “Async functions are just syntactic sugar on top of generators. They use the exact same concept as coroutines.” In fact, Babel will actually transpile async functions to generators-plus-coroutines. As L concludes, “Even though async functions and coroutines are essentially the same thing, async/await is a lot more intuitive.” Go forth and use async/await! You can now hopefully better reason about what’s going on under the hood.

Written on July 1, 2018