Recently I've been making an effort to write JavaScript in a more functional manner. It requires a change of mind in how to approach problems, but I'd like to share some of the basics that I've learnt so far.

I'll also take a look at how lodash/fp makes functional code a pleasant experience.

Why write functionally?

Before going any further let's have a look at some examples of why we might even want to entertain this whole functional idea. The first and sometimes most revealing benefit is switching from explicit to implicit code.

Explicit

Here is how you could square all the members of an array explicitly:

function squareAll ( numbers ) { var squared = [ ] ; for ( var i = 0 ; i < numbers . length ; i ++ ) { squared . push ( numbers [ i ] * numbers [ i ] ) ; } return squared ; } squareAll ( [ 1 , 2 , 3 , 4 ] ) ;

At every step of the way we have to tell the JS engine exactly what to do and whilst it's nice to be thorough it leaves more room for bugs and unoptimised code.

It's also just plain ugly to read.

Implicit

A more implicit approach is to use Array.map :

function squareAll ( numbers ) { return numbers . map ( num => num * num ) ; } squareAll ( [ 1 , 2 , 3 , 4 ] ) ;

Here we're leaving the details of looping and creating a new array to the map array method, which is easier to read and less error prone. This is much better, but we still need to call it on the numbers array manually. Could we do better?

const map = require ( 'lodash/fp/map' ) ; const squareAll = map ( num => num * num ) ; squareAll ( [ 1 , 2 , 3 , 4 ] ) ;

Okay, now we're talking!

Using lodash/fp means the functions are curried for us by default, and the argument order is swapped around so it goes from the more familiar version of map(array, function) to map(function, array) . We also no longer deal with the numbers argument which is a concept known as point-free programming.

Another nice side effect is little code to read, test and maintain.

But, a lot changed from the explicit for loop we had earlier, including the introduction of terms like 'curried' and 'point-free' so now would be an ideal time to clarify some terminology.

A delicious curry

Currying is where a function expects a certain amount of arguments and if provided with less, it returns another function that is awaiting the remaining arguments.

Only once it receives all expected arguments does a result get returned.

If provided with the expected amount of arguments all at once it works as normal and returns a result.

const curry = require ( 'lodash/fp/curry' ) ; const greet = curry ( ( greeting , name ) => ` ${ greeting } , ${ name } !` ) ; greet ( 'Hello' , 'Simon' ) ; const sayBye = greet ( 'See ya' ) ; sayBye ( 'John' ) ;

Here is how the lodash/fp documentation describes itself:

The lodash/fp module promotes a more functional programming (FP) friendly style by exporting an instance of lodash with its methods wrapped to produce immutable auto-curried iteratee-first data-last methods.

With that in mind, we can now see why the last squareAll example allowed us to pass the logic to map first, and then call it with an array later. We could also have done it one step like so:

map ( num => num * num , [ 1 , 2 , 3 , 4 ] ) ;

We can start to appreciate the use of currying when we look at the next section, composition.

Compose yourself

The idea of composing functions (or flow in lodash) is to build a larger function out of many smaller ones. The data goes in one end and flows (ah ha!) through each function until it comes out the other side. Each function in the chain passes its return value to the next.

Let's see an example using lodash/fp:

const flow = require ( 'lodash/fp/flow' ) ; const escape = require ( 'lodash/fp/escape' ) ; const trim = require ( 'lodash/fp/trim' ) ; const sanitise = flow ( escape , trim ) ; sanitise ( ' <html> ' ) ;

You can see that we've created a sanitise function from escape and trim and when the HTML string is passed in it flows through these two functions before being returned as expected. Again, we're just being implicit and declaring what we want to happen, not how.

How does currying help?

lodash/fp functions are auto-curried, so when given fewer arguments than expected they give back a function. This works really well with flow :

const flow = require ( 'lodash/fp/flow' ) ; const get = require ( 'lodash/fp/get' ) ; const isEqual = require ( 'lodash/fp/isEqual' ) ; const data = { items : 45 } ; const hasAllItems = flow ( get ( 'items' ) , isEqual ( 45 ) ) ; hasAllItems ( data )

Here we're configuring the get and isEqual functions with the arguments needed to get the result, and now they're waiting for their final argument which is the data. Thanks to flow we can pass that in at one end and let it pass through each curried function until our expected value comes out at the end.

For composition to work each function should be unary (accept one argument) and return a single value for the next function to consume. It's fine for the first function to be polyadic (takes multiple arguments) as long it returns a single value.

One more example

What about iterating over a set of items and filtering them?

const flow = require ( 'lodash/fp/flow' ) ; const get = require ( 'lodash/fp/get' ) ; const filter = require ( 'lodash/fp/filter' ) ; const isEqual = require ( 'lodash/fp/isEqual' ) ; const items = [ { name : 'baz' } , { name : 'foo' } , { name : 'bar' } , { name : 'bar' } , { name : 'foo' } , ] ; const getBars = filter ( flow ( get ( 'name' ) , isEqual ( 'bar' ) ) ) ; getBars ( items ) ;

The function created by flow is what is used by filter to apply to each member of the array. Each item is passed through the get and isEqual and if it satisfies the condition it ends up in the new array.

Hopefully you're getting the hang of this!

A note on point-free

You may have noticed that in the last two examples you can't see any mention of data or items apart from when it is passed in as an argument. From the Wikipedia page:

Tacit programming, also called point-free style, is a programming paradigm in which function definitions do not identify the arguments (or "points") on which they operate. Instead the definitions merely compose other functions, among which are combinators that manipulate the arguments.

Without trying we've written some point-free code!

It's not something to worry about too much, but keeping it in mind has helped me transform code like this:

function isSuccess ( response ) { if ( response . status === 200 ) { return true ; } } isSuccess ( response ) ;

Into something more concise:

const isSuccess = flow ( get ( 'status' ) , isEqual ( 200 ) ) ; isSuccess ( response ) ;

It's a useful guideline to follow.

Pure functions

The last topic to look at is the concept of function purity. This is a function that doesn't depend on state outside of its scope, and doesn't modify it either. Its only jurisdiction is that of the arguments passed in, and even then it should never mutate this data, but return new versions.

Not only does this make testing simpler (you can just pass different arguments and test the results without needing to mock global objects) but it makes code more predictable.

Here's an example where a function mutates its input:

const data = { foo : 'bar' } ; function sendData ( data ) { data . baz = 'test' ; API . send ( data ) ; } function renderData ( data ) { } sendData ( data ) ; renderData ( data ) ;

sendData needs to add an additional property before sending the payload to an endpoint. This causes problems for renderData as objects are passed by reference so now when it comes to render the payload it has an additional baz property that should not be there.

The correct approach would be to create a copy and leave the input untouched:

function sendData ( data ) { const newData = assign ( { } , data , { baz : 'test' } ) ; API . send ( newData ) ; }

Functions in lodash like pick , omit , map etc will always return new copies of the data.

It won't be possible to always write pure functions, especially if you're interacting with things like document or window but it's another thing to keep in mind.

Practical examples

Well done for shunning the TL:DR crowd and making it this far!

After wading through all the same topics I found it hard to apply them to my code as I wasn't often squaring numbers, or greeting users.

Thankfully it's quite easy to start writing JS in a functional way, even if it's just in small doses. So now I'll go through some small examples that will hopefully inspire you to carry on.

Extracting props in a React component

{ "user" : { "profile" : { "username" : "simonsmith" , "age" : "31" , "img" : "http://image.com" , "gender" : "male" } } }

const getUserProps = flow ( getOr ( { } , 'user.profile' ) , pick ( [ 'username' , 'img' , 'age' ] ) ) ; const User = props => { const { username , age , img } = getUserProps ( props ) ; return ( < div className = "User" > { username } < / div > ) ; } ; module . exports = User ;

This is a pattern I find myself using often in React, grabbing the data you need from some props. The use of getOr here allows us to set a default value if user.profile is undefined.

Without JSX

If you're not using JSX you can take this a step further and flow the props directly into a factory function. Here's an example with one from React.DOM :

const flow = require ( 'lodash/fp/flow' ) ; const pick = require ( 'lodash/fp/pick' ) ; const React = require ( 'react' ) ; const { img } = React . DOM ; const imgWithProps = flow ( pick ( [ 'src' , 'alt' , 'className' ] ) , img ) ; const Component = props => imgWithProps ( props ) ;

I've become quite fond of this pattern.

Turning an object into query string parameters

const map = require ( 'lodash/fp/map' ) . convert ( { 'cap' : false } ) ; const join = require ( 'lodash/fp/join' ) ; const flow = require ( 'lodash/fp/flow' ) ; const toQueryString = flow ( map ( ( value , key ) => { return encodeURIComponent ( key ) + '=' + encodeURIComponent ( value ) ; } ) , join ( '&' ) ) ; toQueryString ( { foo : 'bar' , baz : 'moo' } )

One thing that may cause some confusion when coming to lodash/fp from regular lodash is how the arguments are capped for certain functions. That means that whilst you may be used to accessing the value and key in map it will only provide you with value by default in lodash/fp .

In the above code I'm using .convert to change the behaviour and allowing toQueryString to work as expected.

Read more about convert and capped arguments in the documentation.

Handling data from an API

The last example is a simplified version of some code from a real project. An API returned a payload with a meta object about the response and the body contained a stringified version of the main payload:

const response = { data : { meta : { responseCode : '200' , statusMessage : 'OK' } , body : '{"html":{"head":"<head></head>","foot":"<footer></footer>"}}' } } ;

The goal is to extract the HTML from the body if the response is successful, otherwise log the error status code and message.

const flow = require ( 'lodash/fp/flow' ) ; const get = require ( 'lodash/fp/get' ) ; const negate = require ( 'lodash/fp/negate' ) ; const toNumber = require ( 'lodash/fp/toNumber' ) ; const isEqual = require ( 'lodash/fp/isEqual' ) ; const logger = require ( './logger' ) ; const getRoot = get ( 'data' ) ; const getMeta = flow ( getRoot , get ( 'meta' ) ) ; const getResponseCode = flow ( getMeta , get ( 'responseCode' ) , toNumber ) ; const getStatusMessage = flow ( getMeta , get ( 'statusMessage' ) ) ; const isApiFailure = flow ( getResponseCode , negate ( isEqual ( 200 ) ) ) ; const getHtml = flow ( getRoot , get ( 'body' ) , JSON . parse , get ( 'html' ) ) ; function handleResponse ( response ) { if ( isApiFailure ( response ) ) { return logger ( getResponseCode ( response ) , getStatusMessage ( response ) ) ; } return { html : getHtml ( response ) } ; }

The focus here is to prefer many small functions that do one thing. Code written this way is simple to unit test, and in this example we pass a lot of the work to lodash and gain extra confidence knowing that it is already well tested and performant.

A note on Ramda

The other well known alternative to lodash/fp is Ramda. It works in a similar way with auto-curried, data last functions. Why not advocate that as well? I've tried using it, and it's great but here are the reasons I stuck with lodash:

It's very easy to switch to lodash/fp gradually. The benefit of being able to switch from lodash/assign to lodash/fp/assign is enormous. It means you can start write functionally in areas of your code base without refactoring every module.

lodash/fp comes with mappings to Ramda functions, so there is no need to relearn the API immediately if you're a Ramda user.

Performance is a big concern for lodash, which gives confidence that you can use its functions quite liberally to achieve point-free code.

Wrapping up

Hopefully this has shed some light on how you can start implementing functional programming into your own projects. This post by no means covers everything, so I've compiled a list of excellent resources from very smart people to help you go further on your functional journey.

Resources