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1.2.1 • Public • Published


Provides a powerful API for native ES6 iterables and async iterables.


yarn add iternal

API Documentation

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import iter from 'iternal'
  iter.of(1, 3, 5)
    .map(v => v * 2)
> result[2, 6, 10, 2, 6, 10]
  'The min and max value: ',
  iter([8, 3, 6, 7], [4, 10, 6]).collect(iter.ops.range)
> resultThe min and max value:  [ 3, 10 ]
  'Average word length:',
  iter(['This', 'is', 'a', 'test'])
      iter.ops.average.mapInput(word => word.length)
> resultAverage word length2.75


import iter from 'iternal'
// rangeBy returns the values for which the function gives the minimum and maximum value
const shortestAndLongestStringCollector = iter.ops.rangeBy<string>(w => w.length)
// mapInput converts some input type into a type the collector understands
const averageStringLengthCollector = iter.ops.average.mapInput<string>(w => w.length)
// We construct a string from the combination of the above two collectors
const verySpecificCollector = iter.collector.combineWith(
  ([shortest, longest], avgLen) =>
    `Shortest word: ${shortest}, longest word: ${longest}, average length: ${avgLen}`,
// We create an Iter iterable from a string split
const words = iter('This is a very normal sentence'.split(' '))
// Get the final result at once
> resultShortest worda, longest wordsentence, average length4.166666666666666
// Get the results for each new word
words.collectIter(verySpecificCollector).forEach(v => console.log(v))
> result:
Shortest wordThis, longest wordThis, average length4
Shortest wordis, longest wordThis, average length3
Shortest worda, longest wordThis, average length2.3333333333333335
Shortest worda, longest wordThis, average length2.75
Shortest worda, longest wordnormal, average length3.4
Shortest worda, longest wordsentence, average length4.166666666666666


ES6 Iterables are awesome, but miss some basic functionality that e.g. Arrays have, like .map and .filter.

At the same time, Iterables in some ways are more powerful than Arrays, in that they can represent infinite data because by nature they are lazy. This means that each next element is evaluated only when requested. The drawback compared to Arrays is that Iterables are not indexed, so getting the nth element requires iterating over all n elements.

Why then are Iterables so great?

  1. Iterables can be combined lazily, without needing to create intermediate structures. Imagine that you have 2 or more large arrays of data, and you want to perform some calculation over all of them. Normally you can choose either to copy all data into one large array and perform the calculation over this array, or you can write a function that takes an array and returns an intermediate value, and then combine the results of all the arrays. Using Iterables, you can concatenate the arrays, creating a 'virtual' large array without actually copying data. Then, you can define a Collector that calculates over all the arrays at once without needing to combine intermediate results.

  2. Iterables can be edited without actually creating an in-memory copied data structure. This means you can arbitrarily insert or remove elements at certain positions, you can map and filter the elements without doing anything in memory. You are basically creating imaginary structures that only materialize once you start iterating over the structure.

  3. As mentioned before, Iterables can represent infinite data. For example, iter.nats represents all natural integers starting for 0. As long as you are not evaluating (e.g. collecting, or performing .forEach()) an infinite Iterable, you can safely use them in your code. They are very convenient for use cases like zipping or taking a limited amout.

Iterables vs Iterators

iternal does its best to stick to only the (Async)Iterable interfaces, and keep the (Async)Iterators under the surface.


Iterables are predictable and should in principle result in the same values every time an iterable is iterated over. On the contrast, Iterators have a hidden state, meaning that they can be partially consumed. This can have undesired effects, since using the same Iterator multiple times can give different results. Except for Iterables that depend on impure inputs (like e.g. iter.randomInt()), Iterables should always return the same values. This keeps code functional, pure, and thus predictable.

The result is that Iter and AsyncIter provide a predicable and pure functional API on top of Iterables.

Collect your results

A Collector is a very powerful concept, present in languages like Java. It is related to Reducers, which since React have become more popular.

A Collector specifies a start state, and a combination function taking some element, and producing a new state. This makes a Collector very similar to a for loop. Most for loops start with some initial values, then loop over something iterable, while modifying the initial values, and, once the iterable is done, return some results based on the final state of the variables.

However, because, in contrast to a for loop, a Collector is just an object, it can be re-used and composed. This means that, once you have written a Collector, you can use it on any iterable object, and you can compose it with other Collectors that will run in 'parallel'. This is impossible using basic for loops. That's a major boost to re-usable components.

Let's take some examples:

function getSum(array) {
  let sum = 0
  for (const value of array) sum += value
  return sum
function getProduct(array) {
  let product = 1
  for (const value of array) product *= value
  return product

Here we have written 2 functions that can get the sum and product of an array of integers. But what if we want both? We can write something like const [sum, product] = [getSum(someArray), getProduct(someArray)] but this will process the array twice. That should not be necessary. The only way to do it in the above way is to write a new function that loops over the array once and calculates both results at once.

Now, using Collectors:

// already defined as iter.ops.sum
const sumCollector = iter.collector.create({ init: 0, next: (state, value) => state + value })
// already defined as iter.ops.product
const productCollector = iter.collector.create({ init: 1, next: (state, value) => state * value })
const [sum, product] = iter(someArray).collect(
  iter.collector.combine(sumCollector, productCollector)

Now that we have written these Collectors, we can also reuse the logic in many different ways. Imagine that we want to calculate the sum of all lengths of words in an array. We cannot directly use the sumCollector defined above, since it doesn't handle strings as input. Instead of converting our array of strings to an array with the lengths of the words, we can modify the our Collect to do this input conversion 'on the fly':

const wordLengthSum = sumCollector.mapInput<string>(word => word.length)
const totalLength = iter(arrayOfStrings, someOtherArrayOfStrings).collect(wordLengthSum)

And again, we can use Collector.combine if we want to get multiple results for the array:

const wordLengthAverage = iter.ops.average.mapInput<string>(word => word.length)
const [totalLength, averageLength] = iter(arrayOfStrings).collect(
  iter.collector.combine(wordLengthSum, wordLengthAverage)

iternal even defines many input modifiers for Collectors that help modifying the input, for exampe:

const aCollector = iter.ops.average
  .mapInput<string>(word => word.length)
  .appendInput('test', 'foo')
  .filterInput(word => word.length > 2)

This collector will take the average word lengths of the input words, where the input is modified as follows:

  • mapInput indicates that strings are taken as input, but the length is taken for the average collector
  • filterInput removes all words with length less than 3
  • appendInput adds the words 'test' and 'foo' to the end of the input
  • dropInput skips the first input word
  • sampleInput takes every 2nd word of the input

It is interesting to note here that, as the list indicates, most of these operations should be read in backward order, since we are transforming a given input stream towards our desired input stream.

Hopefully you see that you now probably never have to write a for loop over some Iterable again.

Advanced topic: More powerful and efficient Collectors

A collector is very similar to a function called fold or reduce in functional programming. However, it solves some of the issues that the functional fold method has. Issues of the fold method compared to a for loop are:

  1. A functional fold's state type is also the result type, meaning that the state cannot be some intermediate value from which a result is derived.
  2. A functional fold always has to process all values of the iterable, even if its result can never change regardless of future inputs. This can be inefficient, but also makes it impossible to fold infinite iterables.
  3. A functional fold cannot use mutable objects in its state, since the object would be reused for every future fold and thus cause unwanted side-effects.

Let's see how the iternal library solves these three drawbacks.

Intermediate state

In iternal, you can define a function that maps the collector's state to a result of a different type. Imagine the following for loop:

function sumIsPrime(someArray) {
  let value = 0
  for (const elem of someArray) value += elem
  return isPrime(value)

As a Collector:

const sumIsPrime: Collector<number, boolean> = iter.collector.createState({
  init: 0,
  next: (state, elem) => state + elem,
  stateToResult: isPrime

You can actually also do this after the fact with an existing Collector:

const sumIsPrime2 = sumCollector.mapResult(isPrime)

Intermediate return

In iternal you can define an 'escape' condition, indicating that the state will never change, and thus iteration can be interrupted. Let's look at the following for loop:

function getEfficientProduct(array) {
  let product = 1
  for (const value of array) {
    // if any value equals 0 the result will always be 0
    if (value === 0) return 0
    product *= value

We can express the return condition in iternal by supplying an escape predicate as follows:

const efficientProduct = iter.collector.create({
  init: 0,
  next: (state, value) => state * value,
  escape: state => state === 0

Now, we can run this collector on infinite streams (but only if they somewhere meet the escape condition):

>> returns 0
// We use the 'inefficient' productCollector we defined earlier
>> never returns, since it has no escape

Using mutable state

Imagine that you need to create some Object from an iterable like the following for loop:

function createObject(array) {
  let object = {}
  for (const key of array) {
    object[key] = 'init'
  return object

Everytime you call this createObject function, you will receive a new object, which is what you expect.

However, let's see what happens using a naive Collector:

const createObject = iter.collector.create({
  init: {},
  next: (state, key) => {
    state[key] = 'init'
    return state
const result1 = iter(['a', 'b']).collect(createObject)
> result1 = { a: 'init', b: 'init' }
const result2 = iter(['c']).collect(createObject)
> result2 = { a: 'init', b: 'init', c: 'init' }

Ouch, what went wrong here?

Well, since we specified our Collector as a constant that has some object as its initial state, this object will be used across all collect requests, meaning the object will keep collecting new values in this one only object.

Obviously, that is not desirable.

To fix such cases, you can optionally provide a constructor function as the initial state. iternal will recognize this constructor function, and then create a new object every time the Collector is used:

const fixedCreateObject = iter.collector.create({
  init: () => ({}),  // <-- this line has changed
  next: (state, key) => {
    state[key] = 'init'
    return state
const result1 = iter(['a', 'b']).collect(fixedCreateObject)
> result1 = { a: 'init', b: 'init' }
const result2 = iter(['c']).collect(fixedCreateObject)
> result2 = { c: 'init' }


I hope to have shown you how powerful and efficient iternal can be as a library, and that it should not be needed to ever write a for loop again.

This quick tutorial only scratches the surface of what is possible, since there is also the AsyncIter interface that provides almost the same API as Iter but then for asynchronous iterables. The possibilities are literally endless :)


Arvid Nicolaas

Have fun!

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