# Algebraic Datatypes

## Overview

Haskell has a system called algebraic datatypes for defining new types. This sounds fancy, but is rather simple. Let’s dive in by looking at the standard library definitions of some familiar types:

data Bool = True | False
data Ordering = LT | EQ | GT


With this syntax you too can define types:

-- definition of a type with three values
data Color = Red | Green | Blue

-- a function that uses pattern matching on our new type
rgb :: Color -> [Double]
rgb Red = [1,0,0]
rgb Green = [0,1,0]
rgb Blue = [0,0,1]

Prelude> :t Red
Red :: Color
Prelude> :t [Red,Blue,Green]
[Red,Blue,Green] :: [Color]
Prelude> rgb Red
[1.0,0.0,0.0]


### Fields

Types like Bool, Ordering and Color that just list a bunch of constants are called enumerations or enums in Haskell and other languages. Enums are useful, but you need other types as well. Here we define a type for reports containing an id number, a title, and a body:

data Report = ConstructReport Int String String


This is how you create a report:

Prelude> :t ConstructReport 1 "Title" "This is the body."
ConstructReport 1 "Title" "This is the body." :: Report


You can access the fields with pattern matching:

reportContents :: Report -> String
reportContents (ConstructReport _ _ contents) = contents
setReportContents :: String -> Report -> Report
setReportContents contents (ConstructReport id title _) =
ConstructReport id title contents


### Constructors

The things on the right hand side of a data declaration are called constructors. True, False, Red and ConstructReport are all examples of constructors. A type can have multiple constructors, and a constructor can have zero or more fields.

Here is a datatype for a standard playing card. It has five constructors, of which Joker has zero fields and the others have one field.

data Card = Joker
| Heart Int
| Club Int
| Diamond Int


Constructors with fields have function type and can be used wherever functions can:

Prelude> :t Heart
Heart :: Int -> Card
Prelude> :t Club
Club :: Int -> Card
Prelude> map Heart [1,2,3]
[Heart 1,Heart 2,Heart 3]
Prelude> (Heart . (\x -> x+1)) 3
Heart 4


### Sidenote: Deriving

By the way, there’s something missing from our Card type. Look at how it behaves compared to Ordering and Bool:

Prelude> EQ
EQ
Prelude> True
True
Prelude> Joker
<interactive>:1:0:
No instance for (Show Card)
arising from a use of print' at <interactive>:1:0-4
Possible fix: add an instance declaration for (Show Card)
In a stmt of a 'do' expression: print it


The problem is that Haskell does not know how to print the types we defined. As the error says, they are not part of the Show class. The easy solution is to just add a deriving Show after the type definition:

data Card = Joker
| Heart Int
| Club Int
| Diamond Int
deriving Show

Prelude> Joker
Joker


The deriving syntax is a way to automatically make your class a member of certain basic type classes, most notably Read, Show and Eq. We’ll talk more about what this means later.

### Algebraic?

So why are these datatypes called algebraic? This is because, theoretically speaking, each datatype can be a sum of constructors, and each constructor is a product of fields. It makes sense to think of these as sums and products for many reasons, one being that we can count the possible values of each type this way:

-- corresponds to 1+1. Has 2 possible values.
data Bool = True | False

-- corresponds to Bool*Bool, i.e. 2*2. Has 4 possible values
data TwoBools = TwoBools Bool Bool

-- corresponds to Bool*Bool+Bool+1 = 2*2+2+1 = 7
-- Has 7 possible values.
data Complex = Two Bool Bool | One Bool | None


There is a rich theory of algebraic datatypes. If you’re interested, you might find more info here or here.

## Type Parameters

We introduced type parameters and parametric polymorphism when introducing lists in a previous reading. Since then, we’ve seen other parameterized types like Maybe and Either. Now we’ll learn how we can define our own parameterized types.

### Defining Parameterized Types

The definition for Maybe is:

data Maybe a = Nothing | Just a


What’s a? We define a parameterized type by mentioning a type variable (a in this case) on the left side of the = sign. We can then use the same type variable in fields for our constructors. This is analogous to polymorphic functions. Instead of defining separate functions

headInt :: [Int] -> Int


and so on, we define one function head :: [a] -> a that works for all types a. Similarly, instead of defining multiple types

data MaybeInt = NothingInt | JustInt Int
data MaybeBool = NothingBool | JustBool Bool


we define one type Maybe a that works for all types a.

Here’s our first own parameterized type Described. The values of type Described a contain a value of type a and a String description.

data Described a = Describe a String

getValue :: Described a -> a
getValue (Describe x _) = x

getDescription :: Described a -> String
getDescription (Describe _ desc) = desc

Prelude> :t Describe
Describe :: a -> String -> Described a
Prelude> :t Describe True "This is true"
Describe True "This is true" :: Described Bool
Prelude> getValue (Describe 3 "a number")
3
Prelude> getDescription (Describe 3 "a number")
"a number"


### Syntactic Note

In the above definitions, we’ve used a as a type variable. However any word that starts with a lower case letter is fine. We could have defined Maybe like this:

data Maybe theType = Nothing | Just theType


The rules for Haskell identifiers are:

• Type variables and names for functions and values start lower case (e.g. a, map, xs)
• Type names and constructor names start with upper case (e.g. Maybe, Just, Card, Heart)

Note that a type and its constructor can have the same name. This is very common in Haskell code for types that only have one constructor. In this material we try to avoid it to avoid confusion. Here are some examples:

data Pair a = Pair a a
data Report = Report Int String String

Prelude> :t Pair
Pair :: a -> a -> Pair a


Beware of mixing up types and constructors. Luckily types and constructors can never occur in the same context, so you get a nice error:

Prelude> Maybe
<interactive>:1:1: error:
• Data constructor not in scope: Maybe

Prelude> undefined :: Nothing
<interactive>:2:14: error:
Not in scope: type constructor or class ‘Nothing’


### Sidenote: Multiple Type Parameters

Types can have multiple type parameters. The syntax is similar to defining functions with many arguments. Here’s the definition of the standard Either type:

data Either a b = Left a | Right b


## Recursive Types

So far, all of the types we’ve defined have been of constant size. We can represent one report or one colour, but how could we represent a collection of things? We could use lists of course, but could we define a list type ourselves?

Just like Haskell functions, Haskell data types can be recursive. This is no weirder than having an object in Java or Python that refers to another object of the same class. This is how you define a list of integers:

data IntList = Empty | Node Int IntList
deriving Show

ihead (Node i _) = i

itail :: IntList -> IntList
itail (Node _ t) = t

ilength :: IntList -> Int
ilength Empty = 0
ilength (Node _ t) = 1 + ilength t


We can use the functions defined above to work with lists of integers:

Prelude> ihead (Node 3 (Node 5 (Node 4 Empty)))
3
Prelude> itail (Node 3 (Node 5 (Node 4 Empty)))
Node 5 (Node 4 Empty)
Prelude> ilength (Node 3 (Node 5 (Node 4 Empty)))
3


Note that we can’t put values other than Ints inside our IntList:

Prelude> Node False Empty

<interactive>:3:6: error:
• Couldn't match expected type ‘Int’ with actual
type ‘Bool’
• In the first argument of ‘Node’, namely ‘False’
In the expression: Node False Empty
In an equation for ‘it’: it = Node False Empty


To be able to put any type of element in our list, let’s do the same thing with a type parameter. This is the same as the built in type [a], but with slightly clunkier syntax:

data List a = Empty | Node a (List a)
deriving Show


Note how we need to pass the the type parameter a onwards in the recursion. We need to write Node a (List a) instead of Node a List. The Node constructor has two arguments. The first has type a, and the second has type List a. Here are the reimplementations of some standard list functions for our List type:

lhead :: List a -> a
lhead (Node h _) = h

ltail :: List a -> List a
ltail (Node _ t) = t

lnull :: List a -> Bool
lnull Empty = True
lnull _     = False

llength :: List a -> Int
llength Empty = 0
llength (Node _ t) = 1 + llength t

Prelude> lhead (Node True Empty)
True
Prelude> ltail (Node True (Node False Empty))
Node False Empty
Prelude> lnull Empty
True


Note that just like with normal Haskell lists, we can’t have elements of different types in the same list:

Prelude> Node True (Node "foo" Empty)

<interactive>:5:12: error:
• Couldn't match type ‘[Char]’ with ‘Bool’
Expected type: List Bool
Actual type: List [Char]
• In the second argument of ‘Node’, namely
‘(Node "foo" Empty)’
In the expression: Node True (Node "foo" Empty)
In an equation for ‘it’:
it = Node True (Node "foo" Empty)


### Example: Growing a Tree

Just like a list, we can also represent a binary tree:

data Tree a = Node a (Tree a) (Tree a) | Empty


Our tree contains nodes, which contain a value of type a and two child trees, and empty trees.

In case you’re not familiar with binary trees, they’re a data structure that’s often used as the basis for other data structures (Data.Map is based on trees!). Binary trees are often drawn as (upside-down) pictures, like this: The highest node in the tree is called the root (0 in this case), and the nodes with no children are called leaves (2, 3 and 4 in this case). We can define this tree using our Tree type like this:

example :: Tree Int
example = (Node 0 (Node 1 (Node 2 Empty Empty)
(Node 3 Empty Empty))
(Node 4 Empty Empty))


The height of a binary tree is length of the longest path from the root to a leaf. In Haskell terms, it’s how many nested levels of Node constructors you need to build the tree. The height of our example tree is 3. Here’s a function that computes the height of a tree:

treeHeight :: Tree a -> Int
treeHeight Empty = 0
treeHeight (Node _ l r) =
1 + max (treeHeight l) (treeHeight r)

treeHeight Empty ==> 0
treeHeight (Node 2 Empty Empty)
==> 1 + max (treeHeight Empty)
(treeHeight Empty)
==> 1 + max 0 0
==> 1
treeHeight (Node 1 Empty (Node 2 Empty Empty))
==> 1 + max (treeHeight Empty)
(treeHeight (Node 2 Empty Empty))
==> 1 + max 0 1
==> 2
treeHeight (Node 0 (Node 1 Empty
(Node 2 Empty Empty))
Empty)
==> 1 + max (treeHeight (Node 1 Empty
(Node 2 Empty Empty)))
(treeHeight Empty)
==> 1 + max 2 0
==> 3


In case you’re familiar with binary search trees, here are the definitions of the lookup and insert opertions for a binary search tree. If you don’t know what I’m talking about, you don’t need to understand this.

lookup :: Int -> Tree Int -> Bool
lookup x Empty = False
lookup x (Node y l r)
| x < y = lookup x l
| x > y = lookup x r
| otherwise = True

insert :: Int -> Tree Int -> Tree Int
insert x Empty = Node x Empty Empty
insert x (Node y l r)
| x < y = Node y (insert x l) r
| x > y = Node y l (insert x r)
| otherwise = Node y l r


## Record Syntax

If some fields need to be accessed often, it can be convenient to have helper functions for reading those fields. For instance, the type Person might have multiple fields:

data Person = MkPerson String Int String String String
deriving Show


A list of persons might look like the following:

people :: [Person]
people = [ MkPerson "Jane Doe" 21 "Houston" "Texas" "Engineer"
, MkPerson "Maija Meikäläinen" 35 "Rovaniemi" "Finland" "Engineer"
, MkPerson "Mauno Mutikainen" 27 "Turku" "Finland" "Mathematician" ]


Suppose that we need to find all engineers from Finland:

query :: [Person] -> [Person]
query [] = []
query (MkPerson name age town state profession):xs
| state == "Finland" && profession == "Engineer" =
(MkPerson name age town state profession) : query xs
| otherwise = query xs


Thus,

query people
==> [MkPerson "Maija Meikäläinen" 35 "Rovaniemi" "Finland" "Engineer"]


Note that the types of the fields give little information on what is the intended content in those fields. We need to remember in all places in the code that town goes before state and not vice versa.

Haskell has a feature called record syntax that is helpful in these kinds of cases. The datatype Person can be defined as a record:

data Person =
MkPerson { name       :: String
, age        :: Int
, town       :: String
, state      :: String
, profession :: String }
deriving Show


We can still define values of Person normally, but the Show instance prints the field names for us:

Prelude> MkPerson "Jane Doe" 21 "Houston" "Texas" "Engineer"
MkPerson {name = "Jane Doe", age = 21, town = "Houston", state = "Texas", profession = "Engineer"}


However, we can also define values using record syntax. Note how the fields don’t need to be in any specific order now that they have names.

Prelude> MkPerson {name = "Jane Doe", town = "Houston", profession = "Engineer", state = "Texas", age = 21}
MkPerson {name = "Jane Doe", age = 21, town = "Houston", state = "Texas", profession = "Engineer"}


Prelude> :t profession
profession :: Person -> String
Prelude> profession (MkPerson "Jane Doe" 21 "Houston" "Texas" "Engineer")
"Engineer"


We can now rewrite the query function using these accessor functions:

query :: [Person] -> [Person]
query []     = []
query (x:xs)
| state x == "Finland" && profession x == "Engineer" =
x : query xs
| otherwise = query xs


You’ll probably agree that the code looks more pleasant now.

## Algebraic Datatypes: Summary

• Types are defined like this
data TypeName = ConstructorName FieldType FieldType2
| AnotherConstructor FieldType3
| OneMoreCons

• … or like this if we’re using type variables
data TypeName variable = Cons1 variable Type1
| Cons2 Type2 variable

• You can have one or more constructors
• Each constructor can have zero or more fields
• Values are handled with pattern matching:
foo (ConstructorName a b) = a+b
foo (AnotherConstructor _) = 0
foo OneMoreCons = 7

• Constructors are just functions:
ConstructorName :: FieldType -> FieldType2 -> TypeName
Cons1 :: a -> Type1 -> TypeName a

• You can also define datatypes using record syntax:
data TypeName = Constructor { field1 :: Field1Type
, field2 :: Field2Type }


This gives you accessor functions like field1 :: TypeName -> Field1Type for free.

## Sidenote: Other Ways of Defining Types

In addition to the data keyword, there are two additional ways of defining types in Haskell.

The newtype keyword works like data, but you can only have a single constructor with a single field. It’s sometimes wise to use newtype for performance reasons.

The type keyword introduces a type alias. Type aliases don’t affect type checking, they just offer a shorthand for writing types. For example the familiar String type is an alias for [Char]:

type String = [Char]


This means that whenever the compiler reads String, it just immediately replaces it with [Char]. Type aliases seem useful, but they can easily make reading type errors harder.

## How Do Algebraic Datatypes Work?

Remember how lists were represented in memory as linked lists? Let’s look in more detail at what algebraic datatypes look like in memory.

Haskell data forms directed graphs in memory. Every constructor is a node, every field is an edge. Names (of variables) are pointers into this graph. Different names can share parts of the structure. Here’s an example with lists. Note how the last two elements of x are shared with y and z.

let x = [1,2,3,4]
y = drop 2 x
z = 5:y What happens when you make a new version of a datastructure is called path copying. Since Haskell data is immutable, the changed parts of the datastructure get copied, while the unchanged parts can be shared between the old and new versions.

Consider the definition of ++:

[]     ++ ys = ys
(x:xs) ++ ys = x:(xs ++ ys)


We are making a copy of the first argument while we walk it. For every : constructor in the first input list, we are creating a new : constructor in the output list. The second argument can be shared. It is not used at all in the recursion. Visually: One more way to think about it is this: we want to change the tail pointer of the list element (3:). That means we need to make a new (3:). However the (2:) points to the (3:) so we need a new copy of the (2:) as well. Likewise for (1:).

The graphs that we get when working with lists are fairly simple. As a more involved example, here is what happens in memory when we run the binary tree insertion example from earlier in this lecture.

insert :: Int -> Tree Int -> Tree Int
insert x Empty = Node x Empty Empty
insert x (Node y l r)
| x < y = Node y (insert x l) r
| x > y = Node y l (insert x r)
| otherwise = Node y l r Note how the old and the new tree share the subtree with 3 and 4 since it wasn’t changed, but the node 7 that was “changed” and all nodes above it get copied.

## Self Checks

### Check 1

Why can’t we map Nothing?

1. Because Nothing doesn’t take arguments
2. Because Nothing returns nothing
3. Because Nothing is a constructor.

### Check 2

If we define data Boing = Frick String Boing (Int -> Bool), what is the type of Frick?

1. Boing
2. String -> Boing -> Int -> Bool -> Boing
3. String -> Boing -> (Int -> Bool) -> Boing

### Check 3

If we define data ThreeLists a b c = ThreeLists [a] [b] [c], what is the type of the constructor ThreeLists?

1. [a] -> [b] -> [c] -> ThreeLists
2. a -> b -> c -> ThreeLists a b c
3. [a] -> [b] -> [c] -> ThreeLists a b c
4. [a] -> [b] -> [c] -> ThreeLists [a] [b] [c]

### Check 4

If we define:

data TwoLists a b = TwoList { aList :: [a]
, bList :: [b] }


what is the type of the function aList?

1. aList is not a function, it is a field
2. TwoLists a b -> [a]
3. [a] -> TwoLists a b
4. [a]`