Introduction to Haskell

This post assumes that the reader has at least an intermediate knowledge of an imperative programming language, but does not assume knowledge of functional programming.

You’ll need the Glasgow Haskell Compiler installed (you can get it as part of Haskell Platform). Then, you’ll be able to evaluate stuff and see what you get.


Before we cover the more interesting stuff, we’ll need to cover the basics of Haskell.

Interactive Haskell

We can use Haskell as a calculator. Let’s start up ghci first:

$ ghci

and we can now type stuff into the prompt:

Prelude> 3 + 7
Prelude> 20 - 10
Prelude> 9 / 0

Or check out the types of expressions:

Prelude> :type 2 + 2 == 5
2 + 2 == 5 :: Bool

What goes after the double colon is our type. As you can see here, 2 + 2 == 5 yields a boolean. We’ll see the double colon notation being used later on.

Protip: :t is an alias for :type.


Comments can start with --, which lasts till the end of a line, or enclosed within {- and -}. The latter can span multiple lines.


Functions are the building block of Haskell. Everything we do in Haskell relies on stringing together functions.

Every function is comprised of 2 parts:

  1. Type signature
  2. Equations

Type Signature

The type signature tells us what type the function has. Let’s look at an example:

addByThree :: Integer -> Integer

The first line is a type signature. In this case, we take in a single Integer and return an Integer.

Let’s look at a function to add two integers:

add :: Integer -> Integer -> Integer

This time round, we take in 2 integers and return a single integer.

In Haskell, we usually go by type signatures to describe what our function does.


Let’s take a look at what the whole of addByThree looks like.

addByThree :: Integer -> Integer
addByThree x = x + 3

In Haskell, we write functions similar to equations. The left hand side is addByThree x, which is our function name and the integer x. The right hand side is x + 3 which adds 3 to our integer x.

Hence, by calling addByThree 10 we’ll get back 13.

Likewise, our add function is the following:

add :: Integer -> Integer -> Integer
add x y = x + y

You can give these functions a try by pasting this into main.hs:

addByThree :: Integer -> Integer
addByThree x = x + 3

add :: Integer -> Integer -> Integer
add x y = x + y

and then running GHCi:

$ ghci

Then, typing into the prompt:

Prelude> :load main.hs
[1 of 1] Compiling Main             ( main.hs, interpreted )
Ok, modules loaded: Main.
*Main> addByThree 10
*Main> add 10 20

Protip: You can also run the command ghci main.hs on your shell. Another nifty thing is that you can reload a file by :reload main.hs.

Protip 2: :l is :load and :r is :reload.

Infix functions

Operators like + and * are infix functions. We can use it as a “normal” function by enclosing it in brackets. For example, we can rewrite 3 + 7 as (+) 3 7 (give this a try in GHCi!).


Lists in Haskell are linked lists.

We define lists this way:

Prelude> [1, 2, 3]
[1, 2, 3]
Prelude> :type "abc"
"abc" :: [Char]

Lists in Haskell are implemented as a series of “cons” operations, which join up elements of the list. We use the : operator to do this (otherwise known as the cons operator). It prepends an element to a list of the same type.

Prelude> 3 : [1, 2]
[3, 1, 2]

The interesting part about the : operator is that it is right-associative. This means that everything on the right is evaluated first.

Prelude> 3 : (2 : (1 : []))
[3, 2, 1]
Prelude> 3 : 2 : 1 : []
[3, 2, 1]

Polymorphic types

This sounds complex but it’s actually quite a simple concept.

Polymorphic types allow for any type. Let’s take a look at a function, id.

id :: a -> a
id x = x

The function id can take in any type.

As you can see from the use of a as both input and output, the two types have to be the same (note that polymorphic types are lowercase while “normal” types are uppercase).

In our equations, we specified that id x = x. This function just returns the value it was passed into, hence the reason why it’s called the identity function.

Higher Order functions

Higher order functions are functions that can take in or return other functions.

A function which takes in one parameter and returns something of the same type is denoted by a -> a. Likewise, a function that takes in a function and returns something of the same type is (a -> a) -> a.

A very commonly used function is map. It applies a function to every value in a list. Let’s look at the type:

map :: (a -> b) -> [a] -> [b]

map takes in a function that changes the type of an element from a to b. It then takes in a list of type a and returns a list of type b.

We can test this out with map addByThree [1, 2, 3, 4, 5] etc.

That’s it for the basics. Let’s get down to some interesting code.

Powers of a number

Haskell lets us do quite a lot of elegant stuff. Here’s one that I find particularly elegant (there’re many other ways to write this function too, but I believe that this is one of the clearest).

pows :: Integer -> [Integer]
pows base = iterate (* base) 1

In here, we define a function that takes in an integer and returns a list of integers.

Our equation then defines pows base as iterate (* base) 1. What does that do?

(* base)?

There appears to be a typo in * base. This is not the case. Haskell allows the use of partially applied functions which is going to be explained soon.

Let’s first look at the difference between multiplying 2 integers and multiplying an integer by 3:

multiply :: Integer -> Integer -> Integer
multiply x y = x * y
multiplyByThree :: Integer -> Integer
multiplyByThree x = x * 3

We notice that the two functions appear similar. Both take in x and multiply it by a value.

Now, what if we had a way to specify not all arguments to (*) such that we’d get another function?

This is where the interesting part comes in. We can rewrite the above functions as:

multiply :: Integer -> Integer -> Integer
multiply x y = (x *) y
multiplyByThree :: Integer -> Integer
multiplyByThree x = (x *) 3

We provide the left value, x, to (*). (x *) gives us a function that takes in a single number and multiples that by x. Finally, we get a value.

Haskell allows us to supply only a few parameters required, so as to get back a function that takes in the rest of the parameters. This is known as partial application.

How does that help us? This is where higher order functions come in.

The iterate function

Here’s the definition of iterate:

iterate :: (a -> a) -> a -> [a]
iterate f x = x : iterate f (f x)

By now, you should be familiar with looking at type signatures.

What iterate does is that it prepends a value to a list, applies a function to the value and pass the new value into iterate again. This is what we call a recursive function – a function that calls itself.

Trace of the pows function

It’s hard to see what this function does if you’re not familiar with recursion, so let’s look at a trace.

  pows 3
= iterate (3 *) 1
= 1 : iterate (3 *) 3           -- 3 * 1
= 1 : 3 : iterate (3 *) 9       -- 3 * 3
= 1 : 3 : 9 : iterate (3 *) 27  -- 3 * 9
= ...

We can see that we’ll get a list of powers of 3. How this comes about is that we go through the following steps:

  1. Prepend the current value to the list
  2. Apply (3 *) to the current value to get a new value.
  3. Apply iterate (3 *) to the new value.

Partially applied functions allow us to write this very elegantly, without having to define a new function multiplyByThree. This is one of the lovely things about functional programming; we get to reuse all sorts of functions.

Running that will give us a list of the powers of 3.

But wait! Wouldn’t that go on for infinity? In Haskell, executing pows 3 would have given us an infinite list of the powers of 3 (try it and see what happens!). Notice that the list will keep on growing. That looks like a horrible thing.

But we can still do stuff with an infinite list, thanks to laziness. We need not evaluate the whole list. We only need to evaluate the items that we need to. That is the crux of laziness.

That means that from our infinite list:

[1, 3, 9, 27, 81, 243, 729, 2187, 6561, 19683, ...]

We can do stuff like get the first 5 powers of 3:

take 5 (pows 3)

and get:

[1, 3, 9, 27, 81]

or maybe get all powers of 2 below 100:

takeWhile (< 100) (pows 2)

and get:

[1, 2, 4, 8, 16, 32, 64]

The elegance of this solution lies in the fact that we easily did this with recursion, in a rather terse, clear and “mathematical” way.

The ability to reuse functions like this grants us a lot of power in Haskell and allows us to reason about code in a very powerful way.

Fibonacci Numbers

Fibonacci numbers start with 0 and 1. Each number is the sum of the previous two numbers. In this example, we’ll handle only natural numbers.

Here’s how the sequence looks like:

0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597 2584 4181 ...

As you can see, the third number, 1, is the sum of 0 and 1. The fourth number, 2 is the sum of 1 and 1. This sequence goes on forever.

On to the code:

fibs :: [Integer]
fibs = 0 : 1 : zipWith (+) fibs (tail fibs)

This time round, we define fibs as a list of integers. We then prepend 0 and 1 to zipWith (+) fibs (tail fibs).

What does zipWith do? Before we cover it, we need to take a look at some list terminology and pattern matching.


Take a look at this graphical representation:

[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

The top line denotes the elements that make up the tail while the bottom carat denotes the head. To put it in words, the head is the first element of the list, while the tail is everything after the head.

Here’s another graphical representation:

[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

This time round, the top line denotes the init and the carat denotes the last.

All these 4 terminology are functions. You can try them out in GHCi.

> head [1, 2, 3]
> tail [1, 2, 3]
[2, 3]
> init [1, 2, 3]
[1, 2]
> last [1, 2, 3]


Now that we’ve conquered list terminology, let’s look at zipWith.

zipWith :: (a -> b -> c) -> [a] -> [b] -> [c]
zipWith f (a : as) (b : bs) = f a b : zipWith f as bs
zipWith _ _ _ = []

Hmm. We have 2 equations, with some weird looking stuff. How does this work?

Haskell allows for pattern matching. In our case, (a : as) seperates a list of values into a (the head) and as (the tail). We do the same with (b : bs).

Afterwards, we apply f to a and b, then prepend our value to zipWith f as bs.

However, there’s still a second equation. Underscores are a way for us to dispose unneeded values. The last clause catches everything that doesn’t fit the first equation and returns an empty list.

But why do we need a catchall? As it turns out, the head of an empty list is undefined. Hence, (a : as) will only match lists with at least one element. Our catchall ensures that the function doesn’t error out when we exhaust both lists. Instead, it returns an empty list.

This is what we call the base case of a recursive function, as all other calls to the recursive function gets reduced to this. It’s also the reason why zipWith terminates while iterate doesn’t.

While we now know what the function is doing, we still have no idea how it works. Looking at the trace should gain some inspiration as to how this works:

zipWith (+) [1, 2, 3] [4, 5, 6]   -- 1 + 4
= 5 : zipWith (+) [2, 3] [5, 6]   -- 2 + 5
= 5 : 7 : zipWith (+) [3] [6]     -- 3 + 6
= 5 : 7 : 9 : zipwith (+) [] []   -- returns []
= 5 : 7 : 9 : []
= [5, 7, 9]

The comment shows how the (+) function is being applied to the values of the list and how the values turn into a list.

Back to the fibs function.

zipWith (+) fibs (tail fibs) is still a mystery to us. What could it possibly mean? Let’s look at fibs and tail fibs first (with the values that we already know):

  0 1 ...
+ 1 ...

The first line is fibs and the second line is tail fibs. Adding up the numbers on the first column, 0 and 1, gives us 1, our third number. We append this to the list.

When we evaluate the fourth number, here’s what our list looks like:

  0 1 1 ...
+ 1 1 ...
  1 2

We get the fourth number, 2, and it’s appended to the list. Now, for the fifth number:

  0 1 1 2 ...
+ 1 1 2 ...
  1 2 3

We get 3. This continues, eventually building up a list of Fibonacci numbers.

This algorithm, while a bit hard to comprehend, is inherently elegant and simple.


I hope this has showed you how elegant Haskell could be and why many programmers like working in it.

There’s a lot more to Haskell than this (such as functors, monads, etc.) which make solving other real-life problems quite elegant as well.

You can take a look at the following readings:

You may also wish to follow Chris Allen’s guide to learn more Haskell. (As of 4th Oct 2015, Chris Allen is midway through writing a book on Haskell and is offering early access to sections of the book.)

If you have any comments or suggestions, go to this post’s Reddit post. Thanks for reading!

You can view the history of changes made to this post at this website's GitHub repository.