unit and acceptance testing, automation, productivity

Swift Optionals, Functional Programming, and You

This post is the result of a talk I have given in various forms in the past months, in particular at /dev/world and YOW! Connected.

The goal is to demystify scary terms associated with functional programming, and show a practical application of the underlying concepts when used with array and optionals.

You can follow along on the Playground I used for the YOW! talk.

Note: All the code above is written for Swift 2 and Xcode 7.

Nasty if let

Probably one of the most disruptive features of Swift compared to Objective-C is the presence of optionals. Having a type wrapped in an optional adds an extra layer of context. A constant or variable of type Something? could be nil, and consumers have to account for that.

The most common way to deal with optionals is by using an if let:

var input: String? = "foo bar"
var output: String

if let someInput = input {
    output = "🐷 " + someInput
} else {
    output = "πŸ˜”"

This construct can lead to a nasty nested indentation spiral of doom:

func fancifiedEmojiForCurrentUser() -> String? {

    // currentUser: -> User?
    if let actuallyAUser = currentUser() {
        // joinedNameForUser: User -> String
        let joinedUserName = joinedNameForUser(actuallyAUser)

        // emojiFromString: String -> Emoji?
        if let emojiForUser = emojiFromString(joinedUserName) {
            // fancifyEmoji: Emoji -> Emoji
            return fancifyEmoji(emojiForUser)

    return .None

In my opinion the code above, while being simple, is not easy to digest.

Swift 2 added the guard statement, which allows us to rewrite our example like this:

func fancifiedEmojiForCurrentUser() -> String? {

    // currentUser: -> User?
    guard let actuallyAUser = currentUser() else {
      return .None

    // joinedNameForUser: User -> String
    let joinedUserName = joinedNameForUser(actuallyAUser)

    // emojiFromString: String -> Emoji?
    guard let emojiForUser = emojiFromString(joinedUserName) {
      return .None

    // fancifyEmoji: Emoji -> Emoji
    return fancifyEmoji(emojiForUser)

This version is a bit nicer, and does good use of the early return pattern, but I still find it hard to grasp at first sight.

Let's see how we can pick some pages from the functional programming book and make that code leaner.

What Functional Programming Is All About

When I used to think about functional programming is used to associate it to the academia world, and to programs that needed to crunch big amounts of data, or to work reliably on parallel architectures.

Then cryptic words like functors and monads started to appear in my Twitter feed, and the cool kids started making jokes I couldn't understand.

Good news everybody, functional programming is not about academia, abstract programs, or monadic laws. It is all about functions. For a programming language to be functional, or at least functional friendly, it simply needs to treat functions as first class citizens.

In Swift we can define a function like this:

func plusOne(addend: Int) -> Int {
  return addend + 1

The first class citizen requirements mean that we can treat functions the same way we'd do for any other value. For example we can assign a function to a constant:

let plusTwo: Int -> Int = { $0 + 2 }

let four = plusTwo(2) // => 4

The code above defines a constant of type Int -> Int, or (Int) -> Int if you prefer, and assigns it a closure.

Functions as input

The ability of assigning functions to variables and constants means that we can also pass them as arguments to other functions. For example:

func sumTwice(addend: Int, f: Int -> Int) -> Int {
  return f(addend) + f(addend)

let x = sumTwice(addend: 1, f: { $0 + 1 })
// => (1 + 1) + (1 + 1)
// => 4

Functions as output

The same holds true for functions that return other functions:

func multiplier(base: Int) -> (Int -> Int) {
  return { x in
    return base * x

let timesThree = multiplier(3)

timesThree is now a function that multiplies the given parameter by three.

let x = timesThree(2) // => 6

Higher Order Functions

Here's the first demystification of a functional programming term. What we have seen above are example of "Higher Order Functions".

The working definition for the everyday Swift development of Higher Order Functions is simply: functions take other functions as input and/or output.

But what does this have to do with optionals? Let me introduce you to a very famous higher order function: map.


Let's say you have an array of, for example, Int, and a certain transformation function that takes Int as input and return any other type, for example String. And let's say that you need to apply the given transformation function to each element of the array, and collect the result into another array. One option you have is to use an ugly for each loop, a more concise option is to use map.

let numbers = [1, 2, 3]
let toString: Int -> String = { "\$0" }

let strings = // => ["1", "2", "3"]

Or for the one liner fans:

let strings = { "\$0" }

map is pretty cool, but also a bit picky. The example below won't compile, can you guess why?

let getLength: String -> Int = { $0.characters.count }

let lenghts = // [!] won't compile

We will come back to this in a moment.

The Array type

Something that we might forget due to the [] convenience is that an array constant or variable actually has type Array<T>, where the generic T is the type of the elements the array is allowed to contain.

We could rewrite the definition of numbers from the example above as:

let numbers: Array<Int> = [1, 2, 3]

Looking at arrays through their type definition makes it clearer to understand why doesn't compile.

Given an array Array<T> map expects a function T -> U.

In the example numbers is has type Array<Int>, and toString is Int -> String which matches the expected type signature for map. On the other hand getLenght is a String -> Int which is not compatible with map on an array of Int.

Sweet! But we haven't talked about optionals yet.

The Optional type

Like for Array it might be easy to overlook the fact that optionals variable and constants actually have type Optional<T>, where T is the type of the value wrapped by the optional.

These definitions are equivalent:

let x: String? = "an optional string"

let y: Optional<String> = "another optional string"

let z = Opional.Some("yet another optional string")

As you might have notice the definition of optional and array variables are quite similar.

let a: Array<Int> = [1, 2, 3]
let b: Optional<Int> = Optional.Some(42)

Optional is similar to Array. Array has map. Can you guess what comes next?

Optional map

Yes, you guessed right! The Optional type implements map as well.

Optional.Some(42).map { $0 / 2 } // => Optional.Some(24) { $0 / 2 } // => Optional.None

In the case of optionals, if there is a wrapped value map applies the function to the value, and returns the result wrapped in a new optional, otherwise simply returns .None.

The considerations regarding the type signatures made for Array map are valid for Optional too.

let x: Optional<Int> = 42
let f: Int -> Int = { $0 * 2 }
let q: String -> Int = { $0.characters.count  } // compiles // [!] does not compile

q has type String -> Int, but x is Optional<Int>. Their types don't match for map.


The definition of functor for the everyday Swift developer is a type that implements map.

There is more to the functors than just map, so if you want to create your own functor type be sure to learn about the functor laws from the category theory definition or functor.

Like for higher order functions, once you look into it there is nothing daunting about functor at all. It is just the name for a type that respect certain laws, with the practical result of exposing map.

Better if let

Let's look back at fancifiedEmojiForCurrentUser.

func fancifiedEmojiForCurrentUser() -> String? {

  // currentUser: -> User?
  if let actuallyAUser = currentUser() {
    // joinedNameForUser: User -> String
    let joinedUserName = joinedNameForUser(actuallyAUser)

    // emojiFromString: String -> Emoji?
    if let emojiForUser = emojiFromString(joinedUserName) {
      // fancifyEmoji: Emoji -> Emoji
      return fancifyEmoji(emojiForUser)

  return .None

The currentUser function returns a User?, as there migth not be a logged user, and joinedNameForUser gets a User as input, and returns a String. We can use map there.

emojyFromString as type signature String -> Emoji?, apparently not all the strings can be converted into emojis, and fancifyEmoji expects an input of type Emoji. We can use map on them too.

func fancifiedEmojiForCurrentUser() -> String? {

  if let joinedUserName = {
    return emojiFromString(joinedUserName).map(fancifyEmoji)

  return .None

Now, wouldn't it be nice to chain everything together using map?

Unfortunately this is not possible. Why? Let's follow the types. is a map on a User? of a User -> String function, which from what we saw above returns a String?.

emojiFromString has type signature String -> Emoji. String?, String -> Emoji?, map... The result is Emoji??, or Optional<Optional<Emoji>.

fancifyEmoji is expecting an Emoji input parameter, and it is not compatible to be mapped on an Emoji??.

And by the way, what the heck is an Optional<Optional<T>>? A nested optional like that is not very useful.

To solve this mystery let's go back to Array.

Nested arrays

What would happen if we mapped a function Int -> [Int] on an array of Int?

[1, 2, 3].map { [ $0, $0 ] } // => [ [1, 1], [2, 2], [3, 3] ]

What we get is an array of arrays, or nested array.

Sometimes nested arrays are the data structure we need in our code, other times they are not an what we need is a linear array. The operation of converting a nested array into a linear one is called flattening.

func flat<T>(array nestedArray: [ [T] ]) -> [T] {
  var linearArray: [T] = []
  for array in nestedArray {
    for element in array {

In the example above we can use flat to get a linear array:

flat([1, 2, 3].map { [ $0, $0 ] }) // => [ 1, 1, 2, 2, 3, 3 ]

flat, map... Array has a flatMap method that does exactly that.


[1, 2, 3].flatMap { [ $0, $0 ] }) // => [ 1, 1, 2, 2, 3, 3 ]

flatMap on an Array<T> expects a function T -> Array<U> and returns Array<U>. It maps then flats. Note that in our examples U is equal to T.

Before we saw that Array is similar to Optional, and that in fact they are both functors and have map. It won't surprise you to know then that Optional has a flatMap implementation itself.

flatMap on optionals

Given an Optional<T>, flatMap expects a T -> Optional<U> as input, and has output of type Optional<U>

For example, consider this function half that returns an Int? because it attempts to divide by to only if the number parameter is even:

func half(number: Int) -> Int? {
  switch number % 2 {
  case 0: return number / 2
  default: return .None

We can do:

Optional<Int>.Some(4).flatMap(half)   // => Optional.Some(2)
Optional<Int>.Some(3).flatMap(half)   // => Optional.None
Optional<Int>.None                    // => Optional.None


Here is demystified our third and final functional programming term. A Monad is a type that allows map and flatMap.

Like for functors, there is actually a very solid mathematical definition behind monads, with a set of monadic laws governing them. For the everyday Swift developer like you and me though, a monad is a type on which we can map and flatMap, like Array and Optional.

Even better if let

We left our fancifiedEmojiForCurrentUser for current user in this state:

func fancifiedEmojiForCurrentUser() -> String? {

  if let joinedUserName = {
    return emojiFromString(joinedUserName).map(fancifyEmoji)

  return .None

We tried to chain everything together with map but got stuck when we got a nested optional Emoji. Now that we know flatMap we can achieve that result, in fact returns String? and emojiFromString has type signature String -> Emoji?, this looks like a good use case for flatMap.

func fancifiedEmojiForCurrentUser() -> String? {

  return currentUser


There you go. Isn't that code nice?

To a reader familiar with map and flatMap this final example appear very clear, and is arguably easier on the eye then the version using if let or guard.

Wrapping Up

In this post we saw how higher order functions, functors, and monads, are actually simpler things that their name suggest, and found out that we had been using them everyday without knowing.

The power of functors and monads is not the fact that you can sound like a snob hipster when you mention them, but actually that you can use map and flatMap.

A good use case for map and flatMap in the context of Optional is to simplify code using if lets.

I am not advocating to start writing our iOS apps in Haskell, but I hope to have set some wheels in motion, and to have shown you that just because it might sound a bit daunting it doesn't mean that functional programming is out of your reach, and that it can actually be used together with object oriented code for the greater good ☺️

If you have any question, suggestion or fix please leave a comment below, or hit me up on Twitter @mokagio.

Happy coding, and leave the codebase better than you found it.

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