Hardcore Functional Programming in JavaScrpt

There are notes taken from Frontend Masters course "Hardcore Functional Programming in JavaScrpt"


  1. Frontend Masters course
  2. Course Slides
  3. RamdaJS
  4. BaconJS
  5. Fantasy IO
  6. Pointfree Fantasy - for mjoin, chain etc
  7. Folktale - Either monad


"Separation and recognition" - the soul of functional programming.

The symptoms:

  1. Custom names
  2. Looping patterns
  3. Glue code
  4. Side effects

Omit Needless Names

Variable declarations from within a function - is it needed? If not, omit and add as an argument.

Separating Mutation From Calculation

Ask "where is the mutation happening?" For example, the teaser function in the example to chop down text in the call map(teaser(50), all('p')) is where the mutation is happening. It is important to understand where and how this mutation works for simplification.

In the above example, the teaser also ran setText from within the function with the mutated text, which is unnecessary for that function and can be abstracted out.

Recognize Pure Functions

Functions that don't change anything are called "pure".

Their purity makes them:

  1. Testable
  2. Portable
  3. Memoizable
  4. Parallelizable

Separate Functions From Rules

Functions are nouns. Each input (in the domain) should map to a specific output (in the range).

Separate arity from functions:

function get(property, object) { return object[property]; } var people = [{ name: 'example' }]; // args up front function getPersonName(person) { return get('name', person); } var names = people.map(getPersonName); // more args later // - magic happens here - var names = people.map(get('name')); // the magic in detail function curry(fn) { return function() { if (fn.length > argument.length) { var slice = Array.prototype.slice; var args = slice.apply(arguments); return function() { return fn.apply(null, args.concat(slice.apply(arguments))); }; } return fn.apply(null, arguments); }; } var get = curry(function(property, object) { return object[property]; });

Arity is the idea of separating functions and making them only give one thing at a time (currying).

The examples then used in this application where using Ramda.


Function can "meld" aka compose. Compose is right-to-left, the opposite of Unix pipe which is left-to-right.

When you can understand the relationship between map and compose you can start to see the relationship between the two.

Point Free

Points in this case mean arguments.

The Voyage

Category Theory

Here is a simply example: add(1, 1) // => 2

Mathematically, we know this:

// associative add(add(1, 1), 4) === add(1, add(1, 4)); // communitive add(1, 4) === add(4, 1); // identity add(n, 0) === n; // distributive multiply(2, add(3, 4)) === add(multiply(2, 3), multiply(2, 4));

These theorems and formulas make the basis of our work.

compose :: (b -> c) -> (a -> b) -> (a -> c) id :: a -> a

You need both a composition AND an identity to form a category.

Note: The identity function is if you give it a value it will give it right back.

So we can get some category laws:

// left identity compose( id, f, ) === f; // right identity compose( f, id, ) === f; // associativity compose( compose( f, g, ), h, ) === compose( f, compose( g, h, ), );


How do we deal with errors, side effects etc? We use objects. Think of them like:

  1. Container/Wrappers for values (also known as Identity)
  2. No methods
  3. Not nouns
  4. Probably won't be making your own often

The container:

var _Container = function(val) { this.val = val; }; // helper for during compose use var Container = function(x) { return new _Container(x); }; Container(3); // => _Container { val: 3}

In order to map over our container, we can add the following:

var _Container.prototype.map = function(f) { // this is the important part - it is running // the function on the value in the container return Container(f(this.val)) } Container("flamethrower").map(function(s) { return capitalize(s)}) Container("flamethrower").map(capitalize) // => Container("Flamethrower")

The general idea is that we go within the object and run a function on the object.

These themselves are what we know as a functor.

More example of this in action with the ramda.map function:

map(match(/cat/g), Container('catsup')); //=> Container(["cat"]) map( compose( first, reverse, ), Container('dog'), ); //=> Container("g")

Maybe Functor

"An object or data structure you can map over" - a functor

Let's take an example that runs in null issues:

var getElement = document.querySelector; var getNameParts = compose( split(''), get('value'), getElement, ); getNameParts('#full_name'); //=> ['Jonathan', 'Gregory', 'Brandis']

So, meeting our first Functor: Maybe.

  1. Captures a null check
  2. The value inside may not be there
  3. Sometimes has two subclasses Just / Nothing
  4. Sometimes called Option with subclassess Some / None

The idea is that you may or may not have a value in your container.

var _Maybe.prototype.map = function(f) { return this.val ? Maybe(f(this.val)) : Maybe(null) } map(capitalize, Maybe("flame")) //=> Maybe("Flame") map(capitalize, Maybe(null)) //=> Maybe(null)

This in application:

var firstMatch = compose( map(first), Maybe, match(/cat/g), ); firstMatch('dogsup'); //=> Maybe(null)

Worthy inclusions from the course questions:

const _ = require('ramda'); const inc = _.add(1); map(inc, [4]); // [5] map(inc, Identity(4)); // Identity(5) map(map(inc), Identity([4])); // Identity([5])

This can also trip people up:

var xs = Identity(['do', 'ray', 'me', 'fa', 'so', 'la', 'ti', 'do']); var ex2 = map(_.head); assertEqual(Identity('do'), ex2(xs)); // Note the identity gets passed in here!

Either w/ subclasses Left or Right

Typically used for pure error handling. Like Maybe, but with an error message embedded. Has two subclasses: Left/Right. Mays the function over a Right, ignores the Left.

map(function(x) { return x + 1; }, Right(2)); //=> Right(3) map(function(x) { return x + 1; }, Left('some message')); //=> Left('some message') for error handling

A more practical application:

var determineAge = function(user) { return user.age ? Right(user.age) : Left('could not get age'); }; var yearOlder = compose( map(add(1)), determineAge, ); yearOlder({ age: 22 }); //=> Right(23) yearOlder({ age: null }); //=> Left("couldn't get age")


IO is a functor that puts a function inside it (not a string, number etc).

Facets of IO:

  1. A lazy computation "builder"
  2. Typically used to contain side effects
  3. You must runIO to perform the operation
  4. Map appends the function to a list of things to run with the effectful value


var email_io = IO(function() { return $('#email').val(); }); var msg_io = map(concat('welcome'), email_io); runIO(msg_io); //=> "welcome steve@foodie.net"

An example of building up an IO:

var getBgColor = compose( get('background-color'), JSON.parse, ); var bgPref = compose( map(getBgColor), Store.get('preferences'), ); var app = bgPref(); //=> IO() runIO(app); //=> #efefef

Other Functors

  1. EventStream: Infinite list of results, dual of array, map is sometimes lazy, calls the mapped function each time an event happens. Similar-ish to RxJS. They used Bacon in this example.
  2. Future: Has an eventual value, similar to a promise but "lazy", you must "fork" it to kick it off, it takes a function as its value, calls the function with it's result once it's there.

Functor Law Properties

// identity map(id) === id; // composition compose( map(f), map(g), ) === map( compose( f, g, ), );

An example functor:

// reverse :: String -> String // toArray :: a -> Array a var toArray = function(x) { return [x]; }; compose( toArray, reverse, )('bingo'); //=> [ognib] compose( map(reverse), toArray, )('bingo'); //=> [ognib]

Natural Transformations is when you take one functor to another without knowing anything about the values.

An example is Maybe:

maybeToArray(Maybe(2)); maybeToArray(Maybe(null));


Monads = Pointed Functors of :: a -> F a aka: pure, return, unit, point.

Anything with an of is a Pointed Functor:

Container.of(split); // Container(split) Future.of(split); // Future(split) Maybe.of(split); // Maybe(split) EventStream.of(split); // EventStream(split)

"Nest computations" - just a pointed functor with one the following functions: mjoin, chain.

mjoin :: M M a -> M a chain :: (a -> M b) -> M a -> M b


mjoin(Container(Container(2))); //=> Container(2) // in the given example var getTrackingId = compose( Maybe, get('tracking_id'), ); var findOrder = compose( Maybe, Api.findOrder, ); var getOrderTracking = compose( mjoin, map(getTrackingId), findOrder, ); var renderPage = compose( map(renderTemplate), getOrderTracking, ); renderPage(379); //=> Maybe(Html)

Converting deep nested maps:

// safeGet returns a Maybe functor var ex1 = compose( map(map(safeGet('name'))), map(safeGet('street')), safeGet('address'), ); // with a mjoin, you could do... var ex1 = compose( mjoin map(safeGet('name')), mjoin, map(safeGet('street')), safeGet('address'), ); // but given we know chain is just "monad", // then mjoin, we could... var ex1 = compose( chain(safeGet('name')), chain(safeGet('street')), safeGet('address'), );

There is also such thing as mcompose which will remove the need for the child chain function.