Type Classes

Chapter Goals

This chapter will introduce a powerful form of abstraction which is enabled by PureScript's type system - type classes.

This motivating example for this chapter will be a library for hashing data structures. We will see how the machinery of type classes allow us to hash complex data structures without having to think directly about the structure of the data itself.

We will also see a collection of standard type classes from PureScript's Prelude and standard libraries. PureScript code leans heavily on the power of type classes to express ideas concisely, so it will be beneficial to familiarize yourself with these classes.

If you come from an Object Oriented background, please note that the word "class" means something very different in this context than what you're used to. A type class serves a purpose more similar to an OO interface.

Project Setup

The source code for this chapter is defined in the file src/Data/Hashable.purs.

The project has the following dependencies:

  • maybe, which defines the Maybe data type, which represents optional values.
  • tuples, which defines the Tuple data type, which represents pairs of values.
  • either, which defines the Either data type, which represents disjoint unions.
  • strings, which defines functions which operate on strings.
  • functions, which defines some helper functions for defining PureScript functions.

The module Data.Hashable imports several modules provided by these packages.

Show Me!

Our first simple example of a type class is provided by a function we've seen several times already: the show function, which takes a value and displays it as a string.

show is defined by a type class in the Prelude module called Show, which is defined as follows:

class Show a where
  show :: a -> String

This code declares a new type class called Show, which is parameterized by the type variable a.

A type class instance contains implementations of the functions defined in a type class, specialized to a particular type.

For example, here is the definition of the Show type class instance for Boolean values, taken from the Prelude:

instance showBoolean :: Show Boolean where
  show true = "true"
  show false = "false"

This code declares a type class instance called showBoolean - in PureScript, type class instances can be named to aid the readability of the generated JavaScript. We say that the Boolean type belongs to the Show type class.

We can try out the Show type class in PSCi, by showing a few values with different types:

> import Prelude

> show true

> show 1.0

> show "Hello World"
"\"Hello World\""

These examples demonstrate how to show values of various primitive types, but we can also show values with more complicated types:

> import Data.Tuple

> show (Tuple 1 true)
"(Tuple 1 true)"

> import Data.Maybe

> show (Just "testing")
"(Just \"testing\")"

The output of show should be a string that you can paste back into the repl (or .purs file) to recreate the item being shown. Here we'll use logShow, which just calls show then log, to render the string without quotes. Ignore the unit print - that will covered in Chapter 8 when we examine Effects, like log.

> import Effect.Console

> logShow (Tuple 1 true)
(Tuple 1 true)

> logShow (Just "testing")
(Just "testing")

If we try to show a value of type Data.Either, we get an interesting error message:

> import Data.Either
> show (Left 10)

The inferred type

    forall a. Show a => String

has type variables which are not mentioned in the body of the type. Consider adding a type annotation.

The problem here is not that there is no Show instance for the type we intended to show, but rather that PSCi was unable to infer the type. This is indicated by the unknown type a in the inferred type.

We can annotate the expression with a type, using the :: operator, so that PSCi can choose the correct type class instance:

> show (Left 10 :: Either Int String)
"(Left 10)"

Some types do not have a Show instance defined at all. One example of this is the function type ->. If we try to show a function from Int to Int, we get an appropriate error message from the type checker:

> import Prelude
> show $ \n -> n + 1

No type class instance was found for

  Data.Show.Show (Int -> Int)

Type class instances can be defined in one of two places: in the same module that the type class is defined, or in the same module that the type "belonging to" the type class is defined. An instance defined in any other spot is called an "orphan instance" and is not allowed by the PureScript compiler. Some of the exercises in this chapter will require you to copy the definition of a type into your MySolutions module so that you can define type class instances for that type.


  1. (Easy) Define a Show instance for Point. Match the same output as the showPoint function from the previous chapter. Note: Point is now a newtype (instead of a type synonym), which allows us to customize how to show it. Otherwise, we'd be stuck with the default Show instance for records.

    newtype Point
      = Point
      { x :: Number
      , y :: Number

Common Type Classes

In this section, we'll look at some standard type classes defined in the Prelude and standard libraries. These type classes form the basis of many common patterns of abstraction in idiomatic PureScript code, so a basic understanding of their functions is highly recommended.


The Eq type class defines the eq function, which tests two values for equality. The == operator is actually just an alias for eq.

class Eq a where
  eq :: a -> a -> Boolean

Note that in either case, the two arguments must have the same type: it does not make sense to compare two values of different types for equality.

Try out the Eq type class in PSCi:

> 1 == 2

> "Test" == "Test"


The Ord type class defines the compare function, which can be used to compare two values, for types which support ordering. The comparison operators < and > along with their non-strict companions <= and >=, can be defined in terms of compare.

data Ordering = LT | EQ | GT

class Eq a <= Ord a where
  compare :: a -> a -> Ordering

The compare function compares two values, and returns an Ordering, which has three alternatives:

  • LT - if the first argument is less than the second.
  • EQ - if the first argument is equal to the second.
  • GT - if the first argument is greater than the second.

Again, we can try out the compare function in PSCi:

> compare 1 2

> compare "A" "Z"


The Field type class identifies those types which support numeric operators such as addition, subtraction, multiplication and division. It is provided to abstract over those operators, so that they can be reused where appropriate.

Note: Just like the Eq and Ord type classes, the Field type class has special support in the PureScript compiler, so that simple expressions such as 1 + 2 * 3 get translated into simple JavaScript, as opposed to function calls which dispatch based on a type class implementation.

class EuclideanRing a <= Field a

The Field type class is composed from several more general superclasses. This allows us to talk abstractly about types which support some but not all of the Field operations. For example, a type of natural numbers would be closed under addition and multiplication, but not necessarily under subtraction, so that type might have an instance of the Semiring class (which is a superclass of Num), but not an instance of Ring or Field.

Superclasses will be explained later in this chapter, but the full numeric type class hierarchy (cheatsheet) is beyond the scope of this chapter. The interested reader is encouraged to read the documentation for the superclasses of Field in prelude.

Semigroups and Monoids

The Semigroup type class identifies those types which support an append operation to combine two values:

class Semigroup a where
  append :: a -> a -> a

Strings form a semigroup under regular string concatenation, and so do arrays. Several other standard instances are provided by the prelude package.

The <> concatenation operator, which we have already seen, is provided as an alias for append.

The Monoid type class (provided by the prelude package) extends the Semigroup type class with the concept of an empty value, called mempty:

class Semigroup m <= Monoid m where
  mempty :: m

Again, strings and arrays are simple examples of monoids.

A Monoid type class instance for a type describes how to accumulate a result with that type, by starting with an "empty" value, and combining new results. For example, we can write a function which concatenates an array of values in some monoid by using a fold. In PSCi:

> import Prelude
> import Data.Monoid
> import Data.Foldable

> foldl append mempty ["Hello", " ", "World"]
"Hello World"

> foldl append mempty [[1, 2, 3], [4, 5], [6]]

The prelude package provides many examples of monoids and semigroups, which we will use in the rest of the book.


If the Monoid type class identifies those types which act as the result of a fold, then the Foldable type class identifies those type constructors which can be used as the source of a fold.

The Foldable type class is provided in the foldable-traversable package, which also contains instances for some standard containers such as arrays and Maybe.

The type signatures for the functions belonging to the Foldable class are a little more complicated than the ones we've seen so far:

class Foldable f where
  foldr :: forall a b. (a -> b -> b) -> b -> f a -> b
  foldl :: forall a b. (b -> a -> b) -> b -> f a -> b
  foldMap :: forall a m. Monoid m => (a -> m) -> f a -> m

It is instructive to specialize to the case where f is the array type constructor. In this case, we can replace f a with Array a for any a, and we notice that the types of foldl and foldr become the types that we saw when we first encountered folds over arrays.

What about foldMap? Well, that becomes forall a m. Monoid m => (a -> m) -> Array a -> m. This type signature says that we can choose any type m for our result type, as long as that type is an instance of the Monoid type class. If we can provide a function which turns our array elements into values in that monoid, then we can accumulate over our array using the structure of the monoid, and return a single value.

Let's try out foldMap in PSCi:

> import Data.Foldable

> foldMap show [1, 2, 3, 4, 5]

Here, we choose the monoid for strings, which concatenates strings together, and the show function which renders an Int as a String. Then, passing in an array of integers, we see that the results of showing each integer have been concatenated into a single String.

But arrays are not the only types which are foldable. foldable-traversable also defines Foldable instances for types like Maybe and Tuple, and other libraries like lists define Foldable instances for their own data types. Foldable captures the notion of an ordered container.

Functor, and Type Class Laws

The Prelude also defines a collection of type classes which enable a functional style of programming with side-effects in PureScript: Functor, Applicative and Monad. We will cover these abstractions later in the book, but for now, let's look at the definition of the Functor type class, which we have seen already in the form of the map function:

class Functor f where
  map :: forall a b. (a -> b) -> f a -> f b

The map function (and its alias <$>) allows a function to be "lifted" over a data structure. The precise definition of the word "lifted" here depends on the data structure in question, but we have already seen its behavior for some simple types:

> import Prelude

> map (\n -> n < 3) [1, 2, 3, 4, 5]
[true, true, false, false, false]

> import Data.Maybe
> import Data.String (length)

> map length (Just "testing")
(Just 7)

How can we understand the meaning of the map function, when it acts on many different structures, each in a different way?

Well, we can build an intuition that the map function applies the function it is given to each element of a container, and builds a new container from the results, with the same shape as the original. But how do we make this concept precise?

Type class instances for Functor are expected to adhere to a set of laws, called the functor laws:

  • map identity xs = xs
  • map g (map f xs) = map (g <<< f) xs

The first law is the identity law. It states that lifting the identity function (the function which returns its argument unchanged) over a structure just returns the original structure. This makes sense since the identity function does not modify its input.

The second law is the composition law. It states that mapping one function over a structure, and then mapping a second, is the same thing as mapping the composition of the two functions over the structure.

Whatever "lifting" means in the general sense, it should be true that any reasonable definition of lifting a function over a data structure should obey these rules.

Many standard type classes come with their own set of similar laws. The laws given to a type class give structure to the functions of that type class and allow us to study its instances in generality. The interested reader can research the laws ascribed to the standard type classes that we have seen already.

Deriving Instances

Rather than writing instances manually, you can let the compiler do most of the work for you. Take a look at this Type Class Deriving guide. That information will help you solve the following exercises.


The following newtype represents a complex number:

newtype Complex
  = Complex
  { real :: Number
  , imaginary :: Number
  1. (Easy) Define a Show instance for Complex. Match the output format expected by the tests (e.g. 1.2+3.4i, 5.6-7.8i, etc.).

  2. (Easy) Derive an Eq instance for Complex. Note: You may instead write this instance manually, but why do more work if you don't have to?

  3. (Medium) Define a Semiring instance for Complex. Note: You can use wrap and over2 from Data.Newtype to create a more concise solution. If you do so, you will also need to import class Newtype from Data.Newtype and derive a Newtype instance for Complex.

  4. (Easy) Derive (via newtype) a Ring instance for Complex. Note: You may instead write this instance manually, but that's not as convenient.

    Here's the Shape ADT from the previous chapter:

    data Shape
      = Circle Point Number
      | Rectangle Point Number Number
      | Line Point Point
      | Text Point String
  5. (Medium) Derive (via Generic) a Show instance for Shape. How does the amount of code written and String output compare to showShape from the previous chapter? Hint: See the Deriving from Generic section of the Type Class Deriving guide.

Type Class Constraints

Types of functions can be constrained by using type classes. Here is an example: suppose we want to write a function which tests if three values are equal, by using equality defined using an Eq type class instance.

threeAreEqual :: forall a. Eq a => a -> a -> a -> Boolean
threeAreEqual a1 a2 a3 = a1 == a2 && a2 == a3

The type declaration looks like an ordinary polymorphic type defined using forall. However, there is a type class constraint Eq a, separated from the rest of the type by a double arrow =>.

This type says that we can call threeAreEqual with any choice of type a, as long as there is an Eq instance available for a in one of the imported modules.

Constrained types can contain several type class instances, and the types of the instances are not restricted to simple type variables. Here is another example which uses Ord and Show instances to compare two values:

showCompare :: forall a. Ord a => Show a => a -> a -> String
showCompare a1 a2 | a1 < a2 =
  show a1 <> " is less than " <> show a2
showCompare a1 a2 | a1 > a2 =
  show a1 <> " is greater than " <> show a2
showCompare a1 a2 =
  show a1 <> " is equal to " <> show a2

Note that multiple constraints can be specified by using the => symbol multiple times, just like we specify curried functions of multiple arguments. But remember not to confuse the two symbols:

  • a -> b denotes the type of functions from type a to type b, whereas
  • a => b applies the constraint a to the type b.

The PureScript compiler will try to infer constrained types when a type annotation is not provided. This can be useful if we want to use the most general type possible for a function.

To see this, try using one of the standard type classes like Semiring in PSCi:

> import Prelude

> :type \x -> x + x
forall a. Semiring a => a -> a

Here, we might have annotated this function as Int -> Int, or Number -> Number, but PSCi shows us that the most general type works for any Semiring, allowing us to use our function with both Ints and Numbers.

Instance Dependencies

Just as the implementation of functions can depend on type class instances using constrained types, so can the implementation of type class instances depend on other type class instances. This provides a powerful form of program inference, in which the implementation of a program can be inferred using its types.

For example, consider the Show type class. We can write a type class instance to show arrays of elements, as long as we have a way to show the elements themselves:

instance showArray :: Show a => Show (Array a) where

If a type class instance depends on multiple other instances, those instances should be grouped in parentheses and separated by commas on the left hand side of the => symbol:

instance showEither :: (Show a, Show b) => Show (Either a b) where

These two type class instances are provided in the prelude library.

When the program is compiled, the correct type class instance for Show is chosen based on the inferred type of the argument to show. The selected instance might depend on many such instance relationships, but this complexity is not exposed to the developer.


  1. (Easy) The following declaration defines a type of non-empty arrays of elements of type a:

    data NonEmpty a = NonEmpty a (Array a)

    Write an Eq instance for the type NonEmpty a which reuses the instances for Eq a and Eq (Array a). Note: you may instead derive the Eq instance.

  2. (Medium) Write a Semigroup instance for NonEmpty a by reusing the Semigroup instance for Array.

  3. (Medium) Write a Functor instance for NonEmpty.

  4. (Medium) Given any type a with an instance of Ord, we can add a new "infinite" value which is greater than any other value:

    data Extended a = Infinite | Finite a 

    Write an Ord instance for Extended a which reuses the Ord instance for a.

  5. (Difficult) Write a Foldable instance for NonEmpty. Hint: reuse the Foldable instance for arrays.

  6. (Difficult) Given a type constructor f which defines an ordered container (and so has a Foldable instance), we can create a new container type which includes an extra element at the front:

    data OneMore f a = OneMore a (f a)

    The container OneMore f also has an ordering, where the new element comes before any element of f. Write a Foldable instance for OneMore f:

    instance foldableOneMore :: Foldable f => Foldable (OneMore f) where
  7. (Medium) Write a dedupShapes :: Array Shape -> Array Shape function which removes duplicate Shapes from an array using the nubEq function.

  8. (Medium) Write a dedupShapesFast function which is the same as dedupShapes, but uses the more efficient nub function.

Multi Parameter Type Classes

It's not the case that a type class can only take a single type as an argument. This is the most common case, but in fact, a type class can be parameterized by zero or more type arguments.

Let's see an example of a type class with two type arguments.

module Stream where

import Data.Array as Array
import Data.Maybe (Maybe)
import Data.String.CodeUnits as String

class Stream stream element where
  uncons :: stream -> Maybe { head :: element, tail :: stream }

instance streamArray :: Stream (Array a) a where
  uncons = Array.uncons

instance streamString :: Stream String Char where
  uncons = String.uncons

The Stream module defines a class Stream which identifies types which look like streams of elements, where elements can be pulled from the front of the stream using the uncons function.

Note that the Stream type class is parameterized not only by the type of the stream itself, but also by its elements. This allows us to define type class instances for the same stream type but different element types.

The module defines two type class instances: an instance for arrays, where uncons removes the head element of the array using pattern matching, and an instance for String, which removes the first character from a String.

We can write functions which work over arbitrary streams. For example, here is a function which accumulates a result in some Monoid based on the elements of a stream:

import Prelude
import Data.Monoid (class Monoid, mempty)

foldStream :: forall l e m. Stream l e => Monoid m => (e -> m) -> l -> m
foldStream f list =
  case uncons list of
    Nothing -> mempty
    Just cons -> f cons.head <> foldStream f cons.tail

Try using foldStream in PSCi for different types of Stream and different types of Monoid.

Functional Dependencies

Multi-parameter type classes can be very useful, but can easily lead to confusing types and even issues with type inference. As a simple example, consider writing a generic tail function on streams using the Stream class given above:

genericTail xs = map _.tail (uncons xs)

This gives a somewhat confusing error message:

The inferred type

  forall stream a. Stream stream a => stream -> Maybe stream

has type variables which are not mentioned in the body of the type. Consider adding a type annotation.

The problem is that the genericTail function does not use the element type mentioned in the definition of the Stream type class, so that type is left unsolved.

Worse still, we cannot even use genericTail by applying it to a specific type of stream:

> map _.tail (uncons "testing")

The inferred type

  forall a. Stream String a => Maybe String

has type variables which are not mentioned in the body of the type. Consider adding a type annotation.

Here, we might expect the compiler to choose the streamString instance. After all, a String is a stream of Chars, and cannot be a stream of any other type of elements.

The compiler is unable to make that deduction automatically, and cannot commit to the streamString instance. However, we can help the compiler by adding a hint to the type class definition:

class Stream stream element | stream -> element where
  uncons :: stream -> Maybe { head :: element, tail :: stream }

Here, stream -> element is called a functional dependency. A functional dependency asserts a functional relationship between the type arguments of a multi-parameter type class. This functional dependency tells the compiler that there is a function from stream types to (unique) element types, so if the compiler knows the stream type, then it can commit to the element type.

This hint is enough for the compiler to infer the correct type for our generic tail function above:

> :type genericTail
forall stream element. Stream stream element => stream -> Maybe stream

> genericTail "testing"
(Just "esting")

Functional dependencies can be quite useful when using multi-parameter type classes to design certain APIs.

Nullary Type Classes

We can even define type classes with zero type arguments! These correspond to compile-time assertions about our functions, allowing us to track global properties of our code in the type system.

An important example is the Partial class which we saw earlier when discussing partial functions. Take for example the functions head and tail defined in Data.Array.Partial that allow us to get the head or tail of an array without wrapping them in a Maybe, so they can fail if the array is empty:

head :: forall a. Partial => Array a -> a

tail :: forall a. Partial => Array a -> Array a

Note that there is no instance defined for the Partial type class! Doing so would defeat its purpose: attempting to use the head function directly will result in a type error:

> head [1, 2, 3]

No type class instance was found for


Instead, we can republish the Partial constraint for any functions making use of partial functions:

secondElement :: forall a. Partial => Array a -> a
secondElement xs = head (tail xs)

We've already seen the unsafePartial function, which allows us to treat a partial function as a regular function (unsafely). This function is defined in the Partial.Unsafe module:

unsafePartial :: forall a. (Partial => a) -> a

Note that the Partial constraint appears inside the parentheses on the left of the function arrow, but not in the outer forall. That is, unsafePartial is a function from partial values to regular values:

> unsafePartial head [1, 2, 3]

> unsafePartial secondElement [1, 2, 3]


Just as we can express relationships between type class instances by making an instance dependent on another instance, we can express relationships between type classes themselves using so-called superclasses.

We say that one type class is a superclass of another if every instance of the second class is required to be an instance of the first, and we indicate a superclass relationship in the class definition by using a backwards facing double arrow.

We've already seen some examples of superclass relationships: the Eq class is a superclass of Ord, and the Semigroup class is a superclass of Monoid. For every type class instance of the Ord class, there must be a corresponding Eq instance for the same type. This makes sense, since in many cases, when the compare function reports that two values are incomparable, we often want to use the Eq class to determine if they are in fact equal.

In general, it makes sense to define a superclass relationship when the laws for the subclass mention the members of the superclass. For example, it is reasonable to assume, for any pair of Ord and Eq instances, that if two values are equal under the Eq instance, then the compare function should return EQ. In other words, a == b should be true exactly when compare a b evaluates to EQ. This relationship on the level of laws justifies the superclass relationship between Eq and Ord.

Another reason to define a superclass relationship is in the case where there is a clear "is-a" relationship between the two classes. That is, every member of the subclass is a member of the superclass as well.


  1. (Medium) Define a partial function unsafeMaximum :: Partial => Array Int -> Int which finds the maximum of a non-empty array of integers. Test out your function in PSCi using unsafePartial. Hint: Use the maximum function from Data.Foldable.

  2. (Medium) The Action class is a multi-parameter type class which defines an action of one type on another:

    class Monoid m <= Action m a where
      act :: m -> a -> a

    An action is a function which describes how monoidal values are used to determine how to modify a value of another type. There are two laws for the Action type class:

    • act mempty a = a
    • act (m1 <> m2) a = act m1 (act m2 a)

    Applying an empty action is a no-op. And applying two actions in sequence is the same as applying the actions combined. That is, actions respect the operations defined by the Monoid class.

    For example, the natural numbers form a monoid under multiplication:

    newtype Multiply = Multiply Int
    instance semigroupMultiply :: Semigroup Multiply where
      append (Multiply n) (Multiply m) = Multiply (n * m)
    instance monoidMultiply :: Monoid Multiply where
      mempty = Multiply 1

    Write an instance which implements this action:

    instance actionMultiplyInt :: Action Multiply Int where

    Remember, your instance must satisfy the laws listed above.

  3. (Difficult) There are actually multiple ways to implement an instance of Action Multiply Int. How many can you think of? Purescript does not allow multiple implementations of a same instance, so you will have to replace your original implementation. Note: the tests cover 4 implementations.

  4. (Medium) Write an Action instance which repeats an input string some number of times:

    instance actionMultiplyString :: Action Multiply String where

    Hint: Search Pursuit for a helper-function with the signature String -> Int -> String. Note that String might appear as a more generic type (such as Monoid).

    Does this instance satisfy the laws listed above?

  5. (Medium) Write an instance Action m a => Action m (Array a), where the action on arrays is defined by acting on each array element independently.

  6. (Difficult) Given the following newtype, write an instance for Action m (Self m), where the monoid m acts on itself using append:

    newtype Self m = Self m

    Note: The testing framework requires Show and Eq instances for the Self and Multiply types. You may either write these instances manually, or let the compiler handle this for you with derive newtype instance shorthand.

  7. (Difficult) Should the arguments of the multi-parameter type class Action be related by some functional dependency? Why or why not? Note: There is no test for this exercise.

A Type Class for Hashes

In the last section of this chapter, we will use the lessons from the rest of the chapter to create a library for hashing data structures.

Note that this library is for demonstration purposes only, and is not intended to provide a robust hashing mechanism.

What properties might we expect of a hash function?

  • A hash function should be deterministic, and map equal values to equal hash codes.
  • A hash function should distribute its results approximately uniformly over some set of hash codes.

The first property looks a lot like a law for a type class, whereas the second property is more along the lines of an informal contract, and certainly would not be enforceable by PureScript's type system. However, this should provide the intuition for the following type class:

newtype HashCode = HashCode Int

instance hashCodeEq :: Eq HashCode where
  eq (HashCode a) (HashCode b) = a == b

hashCode :: Int -> HashCode
hashCode h = HashCode (h `mod` 65535)

class Eq a <= Hashable a where
  hash :: a -> HashCode

with the associated law that a == b implies hash a == hash b.

We'll spend the rest of this section building a library of instances and functions associated with the Hashable type class.

We will need a way to combine hash codes in a deterministic way:

combineHashes :: HashCode -> HashCode -> HashCode
combineHashes (HashCode h1) (HashCode h2) = hashCode (73 * h1 + 51 * h2)

The combineHashes function will mix two hash codes and redistribute the result over the interval 0-65535.

Let's write a function which uses the Hashable constraint to restrict the types of its inputs. One common task which requires a hashing function is to determine if two values hash to the same hash code. The hashEqual relation provides such a capability:

hashEqual :: forall a. Hashable a => a -> a -> Boolean
hashEqual = eq `on` hash

This function uses the on function from Data.Function to define hash-equality in terms of equality of hash codes, and should read like a declarative definition of hash-equality: two values are "hash-equal" if they are equal after each value has been passed through the hash function.

Let's write some Hashable instances for some primitive types. Let's start with an instance for integers. Since a HashCode is really just a wrapped integer, this is simple - we can use the hashCode helper function:

instance hashInt :: Hashable Int where
  hash = hashCode

We can also define a simple instance for Boolean values using pattern matching:

instance hashBoolean :: Hashable Boolean where
  hash false = hashCode 0
  hash true  = hashCode 1

With an instance for hashing integers, we can create an instance for hashing Chars by using the toCharCode function from Data.Char:

instance hashChar :: Hashable Char where
  hash = hash <<< toCharCode

To define an instance for arrays, we can map the hash function over the elements of the array (if the element type is also an instance of Hashable) and then perform a left fold over the resulting hashes using the combineHashes function:

instance hashArray :: Hashable a => Hashable (Array a) where
  hash = foldl combineHashes (hashCode 0) <<< map hash

Notice how we build up instances using the simpler instances we have already written. Let's use our new Array instance to define an instance for Strings, by turning a String into an array of Chars:

instance hashString :: Hashable String where
  hash = hash <<< toCharArray

How can we prove that these Hashable instances satisfy the type class law that we stated above? We need to make sure that equal values have equal hash codes. In cases like Int, Char, String and Boolean, this is simple because there are no values of those types which are equal in the sense of Eq but not equal identically.

What about some more interesting types? To prove the type class law for the Array instance, we can use induction on the length of the array. The only array with length zero is []. Any two non-empty arrays are equal only if they have equal head elements and equal tails, by the definition of Eq on arrays. By the inductive hypothesis, the tails have equal hashes, and we know that the head elements have equal hashes if the Hashable a instance must satisfy the law. Therefore, the two arrays have equal hashes, and so the Hashable (Array a) obeys the type class law as well.

The source code for this chapter includes several other examples of Hashable instances, such as instances for the Maybe and Tuple type.


  1. (Easy) Use PSCi to test the hash functions for each of the defined instances. Note: There is no provided unit test for this exercise.

  2. (Medium) Write a function arrayHasDuplicates which tests if an array has any duplicate elements based on both hash and value equality. First check for hash equality with the hashEqual function, then check for value equality with == if a duplicate pair of hashes is found. Hint: the nubByEq function in Data.Array should make this task much simpler.

  3. (Medium) Write a Hashable instance for the following newtype which satisfies the type class law:

    newtype Hour = Hour Int
    instance eqHour :: Eq Hour where
      eq (Hour n) (Hour m) = mod n 12 == mod m 12

    The newtype Hour and its Eq instance represent the type of integers modulo 12, so that 1 and 13 are identified as equal, for example. Prove that the type class law holds for your instance.

  4. (Difficult) Prove the type class laws for the Hashable instances for Maybe, Either and Tuple. Note: There is no test for this exercise.


In this chapter, we've been introduced to type classes, a type-oriented form of abstraction which enables powerful forms of code reuse. We've seen a collection of standard type classes from the PureScript standard libraries, and defined our own library based on a type class for computing hash codes.

This chapter also gave an introduction to the notion of type class laws, a technique for proving properties about code which uses type classes for abstraction. Type class laws are part of a larger subject called equational reasoning, in which the properties of a programming language and its type system are used to enable logical reasoning about its programs. This is an important idea, and will be a theme which we will return to throughout the rest of the book.