Part 1: Functors

Welcome to our series on monads and other abstract structures in Haskell! Monads are one of those concepts that seems to cause of lot of fear and anguish among people trying to learn Haskell. The aim of this series is to show that they aren’t a scary or difficult concept, but can be easily understood by taking the proper steps.

In this first part of the series, we’ll start by learning about functors, a simpler abstract structure. If you already know about functors, feel free to move onto part 2, where we discuss applicative functors. If you know about both these concepts and want to dive straight into monads, head to part 3!

As a word of advice, this series will be a lot more beneficial if you can follow along with the code examples. If you’ve never installed Haskell or written a line of code, download our Beginners Checklist to find out how you can get started.

A Simple Example

Here’s a simple example to start us on our way. This code converts an input string like “John Doe 24” into a tuple. We want to consider all inputs though, so the resulting type is a Maybe.

tupleFromInputString :: String -> Maybe (String, String, Int)
tupleFromInputString input = if length stringComponents /= 3
  then Nothing
  else Just (stringComponents !! 0, stringComponents !! 1, age)
  where 
    stringComponents = words input
    age = (read (stringComponents !! 2) :: Int)

This simple function simply takes a string and converts it into parameters for first name, last name, and age. Suppose we have another part of our program using a data type to represent a person instead of a tuple. We might write a conversion function between these two different types. We want to account for the possibility of failure. So we’ll have another function handling that case.

data Person = Person {
  firstName :: String,
  lastName :: String,
  age :: Int
}

personFromTuple :: (String, String, Int) -> Person
personFromTuple (fName, lName, age) = Person fName lName age

convertTuple :: Maybe (String, String, Int) -> Maybe Person
convertTuple Nothing = Nothing
convertTuple (Just t) = Just (personFromTuple t)

A Change of Format

But imagine our original program changes to read in a whole list of names:

listFromInputString :: String -> [(String, String, Int)]
listFromInputString contents = mapMaybe tupleFromInputString (lines contents)

tupleFromInputString :: String -> Maybe (String, String, Int)
...

Now if we passed this result to the code using Person, we would have to change the type of the convertTuple function. It would have a parallel structure though. Maybe and List can both act as containers for other values. Sometimes, we don’t care how values are wrapped. We just want to transform whatever underlying value exists, and then return the new value in the same wrapper.

Introduction to Functors

With this idea in mind, we can start understanding functors. First and foremost, Functor is a typeclass in Haskell. In order for a data type to be an instance of the Functor typeclass, it must implement a single function: fmap.

fmap :: (a -> b) -> f a -> f b

The fmap function takes two inputs. First, it demands a function between two data types. The second parameter is some container of the first type. The output then is a container of the second type. Now let’s look at a few different Functor instances for some familiar types. For lists, fmap is simply defined as the basic map function:

instance Functor [] where
  fmap = map

In fact, fmap is a generalization of mapping. For example, the Map data type is also a functor. It uses its own map function for fmap. Functors simply take this idea of transforming all underlying values and apply it to other types. With this in mind, let’s observe how Maybe is a functor:

instance Functor Maybe where
  fmap _ Nothing = Nothing
  fmap f (Just a) = Just (f a)

This looks a lot like our original convertTuple function! If we have no value in the first place, then the result is Nothing. If we do have a value, simply apply the function to the value, and rewrap it in Just. The Either data type can be seen as a Maybe type with more information about how it failed. It has similar behavior:

instance Functor (Either a) where
    fmap _ (Left x) = Left x
    fmap f (Right y) = Right (f y)

Note the first type parameter of this instance is fixed. Only the second parameter of an Either value is changed by fmap. Based on these examples, we can see how to rewrite convertTuple to be more generic:

convertTuple :: Functor f => f (String, String, Int) -> f Person
convertTuple = fmap personFromTuple

Making Our Own Functors

We can also take our own data type and define an instance of Functor. Suppose we have the following data type representing a directory of local government officials. It is parameterized by the type a. This means we allow different directories using different representations of a person:

data GovDirectory a = GovDirectory {
  mayor :: a,
  interimMayor :: Maybe a,
  cabinet :: Map String a,
  councilMembers :: [a]
}

One part of our application might represent people with tuples. Its type would be GovDirectory (String, String, Int). However, another part could use the type GovDirectory Person. We can define the following Functor instance for GovDirectory by defining fmap. Since our underlying types are mostly functors themselves, this just involves calling fmap on the fields!

instance Functor GovDirectory where
  fmap f oldDirectory = GovDirectory {
    mayor = f (mayor oldDirectory),
    interimMayor = f <$> interimMayor oldDirectory,
    cabinet = f <$> cabinet oldDirectory,
    councilMembers = f <$> councilMembers oldDirectory
  }

Note <$> is simply a synonym for fmap. Now we have our own functor instance, sp transforming the underlying data type of our directory class is easy! We can just use:

convertTuple <$> oldDirectory

Conclusion

Now that you know about functors, it's time to deepen your understanding of these kinds of structures. So move onto part 2 where we'll discuss applicative functors. If you’re dying to try out some of these examples but have never tried Haskell before, download our Beginners Checklist to learn how!