Learn Haskell Now!

Yann Esposito

on Yann Esposito's blog - source - txt - pdf - §permalink
A short and intense introduction to Haskell. This is an update of my old (2012) article. A lot of things have changed since then. Mostly I changed my approach about the easiest way to install a Haskell playground. I removed the not as important part, and added a short introduction about starting a new project.


In 2012, I really believed that every developer should learn Haskell. This is why I wrote my old article. This is the end of 2019 and I still strongly believe that. I think you should at least be able to understand enough Haskell to write a simple tool. There are some features in Haskell that I really miss in most programming languages and that would not appear to be difficult to provide. Typically sum types. A concept so simple yet so helpful.

Since I wrote my article the Haskell ecosystem has evolved:

  1. Project building has different existing solutions. When I wrote this article I made some web applications that I can no longer build today. I mean, if I really want to invest some time, I'm sure I could upgrade those projects to build again. But this is not worth the hassle. Now we have stack, nix, cabal new-build and I'm sure other solutions.
  2. GHC is able to do a lot more magic. This is beyond the scope of an introduction material in my opinion. While the learning curve is as steep as before, the highest point of learning just climbed higher and higher with each successive new GHC release.
  3. Still no real consencus about how to work, learn, and use Haskell. In my opinion there are three different perspectives on Haskell that could definitively change how you make decisions about different aspect of Haskell programming. I believe the main groups of ideolgies are application developers, library developers and the main compiler (GHC) developers. I find those tensions a proof of a healthy environment. There are different solutions to the same problems and that is perfectly fine. This is different when you compare to other language ecosystems where decisions are more controlled or enforced. I feel fine with both approaches. But you must understand that there is no central mindset within Haskellers unlike I can find in some other programming language communities.
  4. I think that Haskell is now perceived as a lot more serious programming language now. A lot more big projects uses Haskell. Haskell proved its utility to write succesful complex entreprise projects.

While the ecosystem evolved I believe that I myself have certainly matured. Since 2013 I'm paid to develop in Clojure. I write most of my personal side projects in Haskell or in some Haskell-inspired language.

As such I can follow two functional programming communities growth and evolution. I am kind of confident that my Haskell understanding is a lot better than before. But I still think, the ability to learn new Haskell subject is infinite.

Someday I would like to write a post about my current team philosophy about programming. Our main rule is to use as few features of a programming language as possible to achieve our goal. This is a kind of merge between minimalism and pragmatism that in the end provide a tremendous amount of benefits. This is why, even if I like to play with the latest Haskell trendy features, I generally program without those. With just a very few amount of Haskell features you will already be in enviromnent with a lot of benefits as compared to many programming languages.

So enough talk, here is my updated article. I added a section about how to create a new project template with nix.

I will try to write other articles about how to write a real program in Haskell. I tried to add those to this already long article, but, it occurs to be more work than expected. So I preferred stop at this point for now and provide separate articles in the future related to Haskell application development.


I really believe that every developer should learn Haskell. I don't think every dev needs to be a super Haskell ninja, but they should at least discover what Haskell has to offer. Learning Haskell opens your mind.

Mainstream languages share the same foundations:

Haskell is very different. The language uses a lot of concepts I had never heard about before. Many of those concepts will help you become a better programmer.

But learning Haskell can be (and will certainly be) hard. It was for me. In this article I try to provide as much help as possible to accelerate your learning.

This article will certainly be hard to follow. This is on purpose. There is no shortcut to learning Haskell. It is hard and challenging. But I believe this is a good thing. It is because it is hard that Haskell is interesting and rewarding.

Today, I could not really provide a conventional path to learn Haskell. So I think the best I can do is point you to the haskell.org documentation website. And you will see that most path involve a long learning process. By that, I mean that you should read a long book and invest a lot of hours and certainly days before having a good idea about what Haskell is all about.

In contrast, this article is a brief and dense overview of all major aspects of Haskell. I also added some information I lacked while I learned Haskell.

The article contains five parts:


Haskell logo

If you are not using either Linux nor macOS, you should look here: https://www.haskell.org/downloads/. Otherwise, you can follow my advice to use nix:

  1. Install nix (The version I used while writting this article was nix (Nix) 2.3.1, future 2.X.X versions should work with the examples in this article)

  2. create a new empty directory hsenv somewhere

  3. Put the following shell.nix file inside it

    { nixpkgs ? import (fetchTarball https://github.com/NixOS/nixpkgs/archive/19.09.tar.gz) {} }:
      inherit (nixpkgs) pkgs;
      inherit (pkgs) haskellPackages;
      haskellDeps = ps: with ps; [
      ghc = haskellPackages.ghcWithPackages haskellDeps;
      nixPackages = [
    pkgs.stdenv.mkDerivation {
      name = "env";
      buildInputs = nixPackages;
      shellHook = ''
         export PS1="\n\[[hs:\033[1;32m\]\W\[\033[0m\]]> "
  4. In the hsenv directory, in a terminal, run nix-shell --pure. You should wait a lot of time for everything to download. And you should be ready. You will have in your PATH:

    • ghc, the Haskell compiler
    • ghci that we can described as a Haskell REPL
    • runghc that will be able to interpret a Haskell file
    • cabal which is the main tool to deal with Haskell projects
    • the Haskell libraries protolude and containers.
  5. To test your env, rung ghci and type import Protolude you should see something like this:

    ~/hsenv> nix-shell
    [nix-shell:~/hsenv]$ ghci
    GHCi, version 8.6.5: http://www.haskell.org/ghc/  :? for help
    Prelude> import Protolude
    Prelude Protolude>

Congratulations you should be ready to start now.

  • There are multiple ways to install Haskell and I don't think there is a full consensus between developer about what is the best method. If you whish to use another method take a look at haskell.org.
  • This install method is only suitable for using as a playground and I think perfectly adapted to run code example from this article. I do not recommend it for serious development.
  • nix is a generic package manager and goes beyond Haskell. One great good point is that it does not only manage Haskell packages but really a lot of other kind of packages. This can be helpful if you need to depends on a Haskell package that itself depends on a system library, for example ncurses.
  • I use nix for other projects unrelated to Haskell. For example, I use the nix-shell bang pattern for shell script for which I can assume the executable I want are present.

BONUS: use direnv

~ cd hsenv
~ echo "use nix" > .envrc
~ direnv allow

Now each time you'll cd into your hsenv directory you'll get the environment set for you.

Don't be afraid

The Scream

Many books/articles about Haskell start by introducing some esoteric formula (quick sort, Fibonacci, etc…). I will do the exact opposite. At first I won't show you any Haskell super power. I will start with similarities between Haskell and other programming languages. Let's jump to the mandatory "Hello World".

main = putStrLn "Hello World!"
~ runghc hello.hs
Hello World!

Now, a program asking your name and replying "Hello" using the name you entered:

main = do
    print "What is your name?"
    name <- getLine
    print ("Hello " ++ name ++ "!")

First, let us compare this with similar programs in a few imperative languages:

# Python
print "What is your name?"
name = raw_input()
print "Hello %s!" % name
# Ruby
puts "What is your name?"
name = gets.chomp
puts "Hello #{name}!"
// In C
#include <stdio.h>
int main (int argc, char **argv) {
    char name[666]; // <- An Evil Number!
    // What if my name is more than 665 character long?
    printf("What is your name?\n");
    scanf("%s", name);
    printf("Hello %s!\n", name);
    return 0;

The structure is the same, but there are some syntax differences. The main part of this tutorial will be dedicated to explaining why.

In Haskell there is a main function and every object has a type. The type of main is IO (). This means main will cause side effects.

Just remember that Haskell can look a lot like mainstream imperative languages.

Very basic Haskell

Picasso minimal owl

Before continuing you need to be warned about some essential properties of Haskell.


Haskell is a functional language. If you have an imperative language background, you'll have to learn a lot of new things. Hopefully many of these new concepts will help you to program even in imperative languages.

Advanced Static Typing

Instead of being in your way like in C, C++ or Java, the type system is here to help you.


Generally your functions won't modify anything in the outside world. This means they can't modify the value of a variable, can't get user input, can't write on the screen, can't launch a missile. On the other hand, parallelism will be very easy to achieve. Haskell makes it clear where effects occur and where your code is pure. Also, it will be far easier to reason about your program. Most bugs will be prevented in the pure parts of your program.

Furthermore, pure functions follow a fundamental law in Haskell:

Applying a function with the same parameters always returns the same value.


Laziness by default is an uncommon language design. By default, Haskell evaluates something only when it is needed. In consequence, it provides an elegant way to manipulate infinite structures, for example.

A last warning about how you should read Haskell code. For me, it is like reading scientific papers. Some parts are clear, but when you see a formula, just focus and read slower. Also, while learning Haskell, it really doesn't matter much if you don't understand syntax details. If you meet a >>=, <$>, <- or any other weird symbol, just ignore them and follows the flow of the code.

Function declaration

You might be used to declaring functions like this:

In C:

int f(int x, int y) {
    return x*x + y*y;

In JavaScript:

function f(x,y) {
    return x*x + y*y;

in Python:

def f(x,y):
    return x*x + y*y

in Ruby:

def f(x,y)
    x*x + y*y

In Scheme:

(define (f x y)
    (+ (* x x) (* y y)))

Finally, the Haskell way is:

f x y = x*x + y*y

Very clean. No parenthesis, no def.

Don't forget, Haskell uses functions and types a lot. It is thus very easy to define them. The syntax was particularly well thought out for these objects.

A Type Example

Although it is not mandatory, type information for functions is usually made explicit. It's not mandatory because the compiler is smart enough to infer it for you. It's a good idea because it indicates intent and understanding.

Let's play a little. We declare the type using ::

f :: Int -> Int -> Int
f x y = x*x + y*y

main = print (f 2 3)
[nix-shell:~/hsenv]$ runghc basic.hs

Now try

f :: Int -> Int -> Int
f x y = x*x + y*y

main = print (f 2.3 4.2)

You should get this error:

[nix-shell:~/hsenv]$ runghc error_basic.hs

error_basic.hs:4:17: error:
    • No instance for (Fractional Int) arising from the literal ‘2.3’
    • In the first argument of ‘f’, namely ‘2.3’
      In the first argument of ‘print’, namely ‘(f 2.3 4.2)’
      In the expression: print (f 2.3 4.2)
4 | main = print (f 2.3 4.2)
  |                 ^^^

The problem: 4.2 isn't an Int.

The solution: don't declare a type for f for the moment and let Haskell infer the most general type for us:

f x y = x*x + y*y

main = print (f 2.3 4.2)
[nix-shell:~/hsenv]$ runghc float_basic.hs

It works! Luckily, we don't have to declare a new function for every single type. For example, in C, you'll have to declare a function for int, for float, for long, for double, etc…

But, what type should we declare? To discover the type Haskell has found for us, just launch ghci:

% ghci
GHCi, version 7.0.4: http://www.haskell.org/ghc/  :? for help
Loading package ghc-prim ... linking ... done.
Loading package integer-gmp ... linking ... done.
Loading package base ... linking ... done.
Loading package ffi-1.0 ... linking ... done.
Prelude> let f x y = x*x + y*y
Prelude> :type f
f :: Num a => a -> a -> a

Uh? What is this strange type?

Num a => a -> a -> a

First, let's focus on the right part a -> a -> a. To understand it, just look at a list of progressive examples:

The written typeIts meaning
Intthe type Int
Int -> Intthe type function from Int to Int
Float -> Intthe type function from Float to Int
a -> Intthe type function from any type to Int
a -> athe type function from any type a to the same type a
a -> a -> athe type function of two arguments of any type a to the same type a

In the type a -> a -> a, the letter a is a type variable. It means f is a function with two arguments and both arguments and the result have the same type. The type variable a could take many different type values. For example Int, Integer, Float

So instead of having a forced type like in C and having to declare a function for int, long, float, double, etc., we declare only one function like in a dynamically typed language.

This is sometimes called parametric polymorphism. It's also called having your cake and eating it too.

Generally a can be any type, for example a String or an Int, but also more complex types, like Trees, other functions, etc… But here our type is prefixed with Num a =>.

Num is a type class. A type class can be understood as a set of types. Num contains only types which behave like numbers. More precisely, Num is class containing types which implement a specific list of functions, and in particular (+) and (*).

Type classes are a very powerful language construct. We can do some incredibly powerful stuff with this. More on this later.

Finally, Num a => a -> a -> a means:

Let a be a type belonging to the Num type class. This is a function from type a to (a -> a).

Yes, strange. In fact, in Haskell no function really has two arguments. Instead all functions have only one argument. But we will note that taking two arguments is equivalent to taking one argument and returning a function taking the second argument as a parameter.

More precisely f 3 4 is equivalent to (f 3) 4. Note f 3 is a function:

f :: Num a => a -> a -> a

g :: Num a => a -> a
g = f 3

g y ⇔ 3*3 + y*y

Another notation exists for functions. The lambda notation allows us to create functions without assigning them a name. We call them anonymous functions. We could also have written:

g = \y -> 3*3 + y*y

The \ is used because it looks like λ and is ASCII.

If you are not used to functional programming your brain should be starting to heat up. It is time to make a real application.

But just before that, we should verify the type system works as expected:

f :: Num a => a -> a -> a
f x y = x*x + y*y

main = print (f 3 2.4)

It works, because, 3 is a valid representation both for Fractional numbers like Float and for Integer. As 2.4 is a Fractional number, 3 is then interpreted as being also a Fractional number.

If we force our function to work with different types, it will fail:

f :: Num a => a -> a -> a
f x y = x*x + y*y

x :: Int
x = 3
y :: Float
y = 2.4
-- won't work because type x ≠ type y
main = print (f x y)

The compiler complains. The two parameters must have the same type.

If you believe that this is a bad idea, and that the compiler should make the transformation from one type to another for you, you should really watch this great (and funny) video: WAT

Essential Haskell

Kandinsky Gugg

I suggest that you skim this part. Think of it as a reference. Haskell has a lot of features. A lot of information is missing here. Come back here if the notation feels strange.

I use the symbol to state that two expression are equivalent. It is a meta notation, does not exists in Haskell. I will also use to show what the return value of an expression is.



3 + 2 * 6 / 3 ⇔ 3 + ((2*6)/3)


True || False ⇒ True
True && False ⇒ False
True == False ⇒ False
True /= False ⇒ True  (/=) is the operator for different


x^n     for n an integral (understand Int or Integer)
x**y    for y any kind of number (Float for example)

Integer has no limit except the capacity of your machine:


Yeah! And also rational numbers FTW! But you need to import the module Data.Ratio:

$ ghci
Prelude> :m Data.Ratio
Data.Ratio> (11 % 15) * (5 % 3)
11 % 9


[]                      ⇔ empty list
[1,2,3]                 ⇔ List of integral
["foo","bar","baz"]     ⇔ List of String
1:[2,3]                 ⇔ [1,2,3], (:) prepend one element
1:2:[]                  ⇔ [1,2]
[1,2] ++ [3,4]          ⇔ [1,2,3,4], (++) concatenate
[1,2,3] ++ ["foo"]      ⇔ ERROR String ≠ Integral
[1..4]                  ⇔ [1,2,3,4]
[1,3..10]               ⇔ [1,3,5,7,9]
[2,3,5,7,11..100]       ⇔ ERROR! I am not so smart!
[10,9..1]               ⇔ [10,9,8,7,6,5,4,3,2,1]


In Haskell strings are list of Char.

'a' :: Char
"a" :: [Char]
""  ⇔ []
"ab" ⇔ ['a','b'] ⇔  'a':"b" ⇔ 'a':['b'] ⇔ 'a':'b':[]
"abc" ⇔ "ab"++"c"

Remark: In real code you shouldn't use list of char to represent text. You should mostly use Data.Text instead. If you want to represent a stream of ASCII char, you should use Data.ByteString.


The type of couple is (a,b). Elements in a tuple can have different types.

-- All these tuples are valid

fst (x,y)       ⇒  x
snd (x,y)       ⇒  y

fst (x,y,z)     ⇒  ERROR: fst :: (a,b) -> a
snd (x,y,z)     ⇒  ERROR: snd :: (a,b) -> b

Deal with parentheses

To remove some parentheses you can use two functions: ($) and (.).

-- By default:
f g h x         ⇔  (((f g) h) x)

-- the $ replace parenthesis from the $
-- to the end of the expression
f g $ h x       ⇔  f g (h x) ⇔ (f g) (h x)
f $ g h x       ⇔  f (g h x) ⇔ f ((g h) x)
f $ g $ h x     ⇔  f (g (h x))

-- (.) the composition function
(f . g) x       ⇔  f (g x)
(f . g . h) x   ⇔  f (g (h x))

Useful notations for functions

Just a reminder:

x :: Int            ⇔ x is of type Int
x :: a              ⇔ x can be of any type
x :: Num a => a     ⇔ x can be any type a
                      such that a belongs to Num type class
f :: a -> b         ⇔ f is a function from a to b
f :: a -> b -> c    ⇔ f is a function from a to (b→c)
f :: (a -> b) -> c  ⇔ f is a function from (a→b) to c

Remember that defining the type of a function before its declaration isn't mandatory. Haskell infers the most general type for you. But it is considered a good practice to do so.

Infix notation

square :: Num a => a -> a
square x = x^2

Note ^ uses infix notation. For each infix operator there its associated prefix notation. You just have to put it inside parenthesis.

square' x = (^) x 2

square'' x = (^2) x

We can remove x in the left and right side! It's called η-reduction.

square''' = (^2)

Note we can declare functions with ' in their name. Here:


Note for each prefix notation you can transform it to infix notation with ` like this:

foo x y ↔ x `foo` y


An implementation of the absolute function.

absolute :: (Ord a, Num a) => a -> a
absolute x = if x >= 0 then x else -x

Note: the if .. then .. else Haskell notation is more like the ¤?¤:¤ C operator. You cannot forget the else.

Another equivalent version:

absolute' x
    | x >= 0 = x
    | otherwise = -x

Notation warning: indentation is important in Haskell. Like in Python, bad indentation can break your code!

main = do
      print $ square 10
      print $ square' 10
      print $ square'' 10
      print $ square''' 10
      print $ absolute 10
      print $ absolute (-10)
      print $ absolute' 10
      print $ absolute' (-10)
~/t/hsenv> runghc functions.hs

First dive

In this part, you will be introduced to functional style, types and infinite structures manipulation.

Functional style

Biomechanical Landscape by H.R. Giger

In this section, I will give a short example of the impressive refactoring ability provided by Haskell. We will select a problem and solve it in a standard imperative way. Then I will make the code evolve. The end result will be both more elegant and easier to adapt.

Let's solve the following problem:

Given a list of integers, return the sum of the even numbers in the list.

example: [1,2,3,4,5] ⇒ 2 + 4 ⇒ 6

To show differences between functional and imperative approaches, I'll start by providing an imperative solution (in javascript):

function evenSum(list) {
    var result = 0;
    for (var i=0; i< list.length ; i++) {
        if (list[i] % 2 ==0) {
            result += list[i];
    return result;

In Haskell, by contrast, we don't have variables or a for loop. One solution to achieve the same result without loops is to use recursion.

Remark: Recursion is generally perceived as slow in imperative languages. But this is generally not the case in functional programming. Most of the time Haskell will handle recursive functions efficiently.

Here is a C version of the recursive function. Note that for simplicity I assume the int list ends with the first 0 value.

int evenSum(int *list) {
    return accumSum(0,list);

int accumSum(int n, int *list) {
    int x;
    int *xs;
    if (*list == 0) { // if the list is empty
        return n;
    } else {
        x = list[0]; // let x be the first element of the list
        xs = list+1; // let xs be the list without x
        if ( 0 == (x%2) ) { // if x is even
            return accumSum(n+x, xs);
        } else {
            return accumSum(n, xs);

Keep this code in mind. We will translate it into Haskell. First, however, I need to introduce three simple but useful functions we will use:

even :: Integral a => a -> Bool
head :: [a] -> a
tail :: [a] -> [a]

even verifies if a number is even.

even :: Integral a => a -> Bool
even 3   False
even 2   True

head returns the first element of a list:

head :: [a] -> a
head [1,2,3]  1
head []       ERROR

tail returns all elements of a list, except the first:

tail :: [a] -> [a]
tail [1,2,3]  [2,3]
tail [3]      []
tail []       ERROR

Note that for any non empty list l, l ⇔ (head l):(tail l)

The first Haskell solution. The function evenSum returns the sum of all even numbers in a list:

-- Version 1
evenSum :: [Integer] -> Integer
evenSum l = accumSum 0 l
accumSum n l = if l == []
                  then n
                  else let x = head l
                           xs = tail l
                       in if even x
                              then accumSum (n+x) xs
                              else accumSum n xs

To test a function you can use ghci:

~/t/hsenv> ghci
GHCi, version 8.6.5: http://www.haskell.org/ghc/  :? for help
Prelude> :l evenSum_v1.hs
[1 of 1] Compiling Main             ( evenSum_v1.hs, interpreted )
Ok, one module loaded.
*Main> evenSum [1..5]

Here is an example of execution2:

*Main> evenSum [1..5]
accumSum 0 [1,2,3,4,5]
1 is odd
accumSum 0 [2,3,4,5]
2 is even
accumSum (0+2) [3,4,5]
3 is odd
accumSum (0+2) [4,5]
2 is even
accumSum (0+2+4) [5]
5 is odd
accumSum (0+2+4) []
l == []

Coming from an imperative language all should seem right. In fact, many things can be improved here. First, we can generalize the type.

evenSum :: Integral a => [a] -> a

Next, we can use sub functions using where or let. This way our accumSum function will not pollute the namespace of our module.

-- Version 2
evenSum :: Integral a => [a] -> a
evenSum l = accumSum 0 l
    where accumSum n l =
            if l == []
                then n
                else let x = head l
                         xs = tail l
                     in if even x
                            then accumSum (n+x) xs
                            else accumSum n xs

Next, we can use pattern matching.

-- Version 3
evenSum l = accumSum 0 l
        accumSum n [] = n
        accumSum n (x:xs) =
             if even x
                then accumSum (n+x) xs
                else accumSum n xs

What is pattern matching? Use values instead of general parameter names3.

Instead of saying: foo l = if l = [] then <x> else <y>= you simply state:

foo [] =  <x>
foo l  =  <y>

But pattern matching goes even further. It is also able to inspect the inner data of a complex value. We can replace

foo l =  let x  = head l
             xs = tail l
         in if even x
             then foo (n+x) xs
             else foo n xs


foo (x:xs) = if even x
                 then foo (n+x) xs
                 else foo n xs

This is a very useful feature. It makes our code both terser and easier to read.

In Haskell you can simplify function definitions by η-reducing them. For example, instead of writing:

f x = (some expresion) x

you can simply write

f = (some expression)

We use this method to remove the l:

-- Version 4
evenSum :: Integral a => [a] -> a
evenSum = accumSum 0
        accumSum n [] = n
        accumSum n (x:xs) =
             if even x
                then accumSum (n+x) xs
                else accumSum n xs

Higher Order Functions


To make things even better we should use higher order functions. What are these beasts? Higher order functions are functions taking functions as parameters.

Here are some examples:

filter :: (a -> Bool) -> [a] -> [a]
map :: (a -> b) -> [a] -> [b]
foldl :: (a -> b -> a) -> a -> [b] -> a

Let's proceed by small steps.

-- Version 5
evenSum l = mysum 0 (filter even l)
      mysum n [] = n
      mysum n (x:xs) = mysum (n+x) xs


filter even [1..10] ⇔  [2,4,6,8,10]

The function filter takes a function of type (a -> Bool) and a list of type [a]. It returns a list containing only elements for which the function returned True.

Our next step is to use another technique to accomplish the same thing as a loop. We will use the foldl function to accumulate a value as we pass through the list. The function foldl captures a general coding pattern:

myfunc list = foo initialValue list
foo accumulated []     = accumulated
foo tmpValue    (x:xs) = foo (bar tmpValue x) xs

Which can be replaced by:

myfunc list = foldl bar initialValue list

If you really want to know how the magic works, here is the definition of foldl:

foldl f z [] = z
foldl f z (x:xs) = foldl f (f z x) xs
foldl f z [x1,...xn]
⇔  f (... (f (f z x1) x2) ...) xn

But as Haskell is lazy, it doesn't evaluate (f z x) and simply pushes it onto the stack. This is why we generally use foldl' instead of foldl; foldl' is a strict version of foldl. If you don't understand what lazy and strict means, don't worry, just follow the code as if foldl and foldl' were identical.

Now our new version of evenSum becomes:

-- Version 6
-- foldl' isn't accessible by default
-- we need to import it from the module Data.List
import Data.List
evenSum l = foldl' mysum 0 (filter even l)
  where mysum acc value = acc + value

We can also simplify this by using directly a lambda notation. This way we don't have to create the temporary name mysum.

-- Version 7
-- Generally it is considered a good practice
-- to import only the necessary function(s)
import Data.List (foldl')
evenSum l = foldl' (\x y -> x+y) 0 (filter even l)

And of course, we note that

(\x y -> x+y) ⇔ (+)


-- Version 8
import Data.List (foldl')
evenSum :: Integral a => [a] -> a
evenSum l = foldl' (+) 0 (filter even l)

foldl' isn't the easiest function to grasp. If you are not used to it, you should study it a bit.

To help you understand what's going on here, let's look at a step by step evaluation:

  evenSum [1,2,3,4]
 foldl' (+) 0 (filter even [1,2,3,4])
 foldl' (+) 0 [2,4]
 foldl' (+) (0+2) [4]
 foldl' (+) 2 [4]
 foldl' (+) (2+4) []
 foldl' (+) 6 []

Another useful higher order function is (.). The (.) function corresponds to mathematical composition.

(f . g . h) x ⇔  f ( g (h x))

We can take advantage of this operator to η-reduce our function:

-- Version 9
import Data.List (foldl')
evenSum :: Integral a => [a] -> a
evenSum = (foldl' (+) 0) . (filter even)

Also, we could rename some parts to make it clearer:

-- Version 10
import Data.List (foldl')
sum' :: (Num a) => [a] -> a
sum' = foldl' (+) 0
evenSum :: Integral a => [a] -> a
evenSum = sum' . (filter even)

It is time to discuss the direction our code has moved as we introduced more functional idioms. What did we gain by using higher order functions?

At first, you might think the main difference is terseness. But in fact, it has more to do with better thinking. Suppose we want to modify our function slightly, for example, to get the sum of all even squares of elements of the list.

[1,2,3,4] ▷ [1,4,9,16] ▷ [4,16] ▷ 20

Updating version 10 is extremely easy:

squareEvenSum = sum' . (filter even) . (map (^2))
squareEvenSum' = evenSum . (map (^2))

We just had to add another "transformation function".

map (^2) [1,2,3,4] ⇔ [1,4,9,16]

The map function simply applies a function to all the elements of a list.

We didn't have to modify anything inside the function definition. This makes the code more modular. But in addition you can think more mathematically about your functions. You can also use your functions interchangeably with others, as needed. That is, you can compose, map, fold, filter using your new function.

Modifying version 1 is left as an exercise to the reader ☺.

If you believe we have reached the end of generalization, then know you are very wrong. For example, there is a way to not only use this function on lists but on any recursive type. If you want to know how, I suggest you to read this quite fun article: Functional Programming with Bananas, Lenses, Envelopes and Barbed Wire by Meijer, Fokkinga and Paterson.

This example should show you how great pure functional programming is. Unfortunately, using pure functional programming isn't well suited to all usages. Or at least such a language hasn't been found yet.

One of the great powers of Haskell is the ability to create DSL (Domain Specific Language) making it easy to change the programming paradigm.

In fact, Haskell is also great when you want to write imperative style programming. Understanding this was really hard for me to grasp when first learning Haskell. A lot of effort tends to go into explaining the superiority of the functional approach. Then when you start using an imperative style with Haskell, it can be hard to understand when and how to use it.

But before talking about this Haskell super-power, we must talk about another essential aspect of Haskell: Types.


Dali, the madonna of port Lligat


  • type Name = AnotherType is just an alias and the compiler doesn't mark any difference between Name and AnotherType.
  • data Name = NameConstructor AnotherType does mark a difference.
  • data can construct structures which can be recursives.
  • deriving is magic and creates functions for you.

In Haskell, types are strong and static.

Why is this important? It will help you greatly to avoid mistakes. In Haskell, most bugs are caught during the compilation of your program. And the main reason is because of the type checking during compilation. Type checking makes it easy to detect where you used the wrong parameter at the wrong place, for example.

Type inference

Static typing is generally essential for fast execution. But most statically typed languages are bad at generalizing concepts. Haskell's saving grace is that it can infer types.

Here is a simple example, the square function in Haskell:

square x = x * x

This function can square any Numeral type. You can provide square with an Int, an Integer, a Float a Fractional and even Complex. Proof by example:

~/t/hsenv> ghci
GHCi, version 8.6.5: http://www.haskell.org/ghc/  :? for help
Prelude> let square x = x * x
Prelude> square 2
Prelude> square 2.1
Prelude> :m Data.Complex
Prelude Data.Complex> square (2 :+ 1)
3.0 :+ 4.0

x :+ y is the notation for the complex (x + iy).

Now compare with the amount of code necessary in C:

int     int_square(int x) { return x*x; }
float   float_square(float x) {return x*x; }
complex complex_square (complex z) {
    complex tmp;
    tmp.real = z.real * z.real - z.img * z.img;
    tmp.img = 2 * z.img * z.real;
complex x,y;
y = complex_square(x);

For each type, you need to write a new function. The only way to work around this problem is to use some meta-programming trick, for example using the pre-processor. In C++ there is a better way, C++ templates:

#include <iostream>
#include <complex>
using namespace std;

template<typename T>
T square(T x)
    return x*x;

int main() {
    // int
    int sqr_of_five = square(5);
    cout << sqr_of_five << endl;
    // double
    cout << (double)square(5.3) << endl;
    // complex
    cout << square( complex<double>(5,3) )
         << endl;
    return 0;

C++ does a far better job than C in this regard. But for more complex functions the syntax can be hard to follow: see this article for example.

In C++ you must declare that a function can work with different types. In Haskell, the opposite is the case. The function will be as general as possible by default.

Type inference gives Haskell the feeling of freedom that dynamically typed languages provide. But unlike dynamically typed languages, most errors are caught before run time. Generally, in Haskell:

"if it compiles it certainly does what you intended"

Type construction

You can construct your own types. First, you can use aliases or type synonyms.

type Name   = String
type Color  = String

showInfos :: Name ->  Color -> String
showInfos name color =  "Name: " ++ name
                        ++ ", Color: " ++ color
name :: Name
name = "Robin"
color :: Color
color = "Blue"
main = putStrLn $ showInfos name color

But it doesn't protect you much. Try to swap the two parameter of showInfos and run the program:

putStrLn $ showInfos color name

It will compile and execute. In fact you can replace Name, Color and String everywhere. The compiler will treat them as completely identical.

Another method is to create your own types using the keyword data.

data Name   = NameConstr String
data Color  = ColorConstr String

showInfos :: Name ->  Color -> String
showInfos (NameConstr name) (ColorConstr color) =
      "Name: " ++ name ++ ", Color: " ++ color

name  = NameConstr "Robin"
color = ColorConstr "Blue"
main = putStrLn $ showInfos name color

Now if you switch parameters of showInfos, the compiler complains! So this is a potential mistake you will never make again and the only price is to be a bit more verbose.

Also notice that constructors are functions:

NameConstr  :: String -> Name
ColorConstr :: String -> Color

The syntax of data is mainly:

data TypeName =   ConstructorName  [types]
                | ConstructorName2 [types]
                | ...

Generally the usage is to use the same name for the DataTypeName and DataTypeConstructor.


data Complex a = Num a => Complex a a

Also you can use the record syntax:

data DataTypeName = DataConstructor {
                      field1 :: [type of field1]
                    , field2 :: [type of field2]
                    , fieldn :: [type of fieldn] }

And many accessors are made for you. Furthermore you can use another order when setting values.


data Complex a = Num a => Complex { real :: a, img :: a}
c = Complex 1.0 2.0
z = Complex { real = 3, img = 4 }
real c  1.0
img z  4

Recursive type

You already encountered a recursive type: lists. You can re-create lists, but with a more verbose syntax:

data List a = Empty | Cons a (List a)

If you really want to use an easier syntax you can use an infix name for constructors.

infixr 5 :::
data List a = Nil | a ::: (List a)

The number after infixr gives the precedence.

If you want to be able to print (Show), read (Read), test equality (Eq) and compare (Ord) your new data structure you can tell Haskell to derive the appropriate functions for you.

infixr 5 :::
data List a = Nil | a ::: (List a)
              deriving (Show,Read,Eq,Ord)

When you add deriving (Show) to your data declaration, Haskell creates a show function for you. We'll see soon how you can use your own show function.

convertList [] = Nil
convertList (x:xs) = x ::: convertList xs
main = do
      print (0 ::: 1 ::: Nil)
      print (convertList [0,1])

This prints:

0 ::: (1 ::: Nil)
0 ::: (1 ::: Nil)


Magritte, l'Arbre

We'll just give another standard example: binary trees.

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

We will also create a function which turns a list into an ordered binary tree.

treeFromList :: (Ord a) => [a] -> BinTree a
treeFromList [] = Empty
treeFromList (x:xs) = Node x (treeFromList (filter (<x) xs))
                             (treeFromList (filter (>x) xs))

Look at how elegant this function is. In plain English:

main = print $ treeFromList [7,2,4,8]

You should obtain the following:

Node 7 (Node 2 Empty (Node 4 Empty Empty)) (Node 8 Empty Empty)

This is an informative but quite unpleasant representation of our tree.

I've added the containers package in the shell.nix file, it is time to use this library which contain functions to show trees and list of trees (forest) named drawTree and drawForest.

import           Data.Tree (Tree,Forest(..))
import qualified Data.Tree as Tree

data BinTree a = Empty
               | Node a (BinTree a) (BinTree a)
               deriving (Eq,Ord,Show)

treeFromList :: (Ord a) => [a] -> BinTree a
treeFromList [] = Empty
treeFromList (x:xs) = Node x (treeFromList (filter (<x) xs))
                      (treeFromList (filter (>x) xs))

-- | Function to transform our internal BinTree type to the
-- type of Tree declared in Data.Tree (from containers package)
-- so that the function Tree.drawForest can use
binTreeToForestString :: (Show a) => BinTree a -> Forest String
binTreeToForestString Empty = []
binTreeToForestString (Node x left right) =
  [Tree.Node (show x) ((binTreeToForestString left) ++ (binTreeToForestString right))]

-- | Function that given a BinTree print a representation of it in the console
prettyPrintTree :: (Show a) => BinTree a -> IO ()
prettyPrintTree = putStrLn . Tree.drawForest . binTreeToForestString

main = do
  putStrLn "Int binary tree:"
  prettyPrintTree $ treeFromList [7,2,4,8,1,3,6,21,12,23]
  putStrLn "\nNote we could also use another type\n"
  putStrLn "String binary tree:"
  prettyPrintTree $
    treeFromList ["foo","bar","baz","gor","yog"]
  putStrLn "\nAs we can test equality and order trees, we can make tree of trees!\n"
  putStrLn "\nBinary tree of Char binary trees:"
  prettyPrintTree (treeFromList
                    (map treeFromList ["foo","bar","zara","baz","foo"]))
~/t/hsenv> runghc pretty_tree.hs
Int binary tree:
+- 2
|  |
|  +- 1
|  |
|  `- 4
|     |
|     +- 3
|     |
|     `- 6
`- 8
   `- 21
      +- 12
      `- 23

Note we could also use another type

String binary tree:
+- "bar"
|  |
|  `- "baz"
`- "gor"
   `- "yog"

As we can test equality and order trees, we can make tree of trees!

Binary tree of Char binary trees:
Node 'f' Empty (Node 'o' Empty Empty)
+- Node 'b' (Node 'a' Empty Empty) (Node 'r' Empty Empty)
|  |
|  `- Node 'b' (Node 'a' Empty Empty) (Node 'z' Empty Empty)
`- Node 'z' (Node 'a' Empty (Node 'r' Empty Empty)) Empty

Notice how duplicate elements aren't inserted in trees. For exemple the Char BinTree constructed from the list foo is just f -> o. When o is inserted another time the second o is not duplicated. But more importantly it works also for our own BinTree notice how the tree for foo is inserted only once. We have this for (almost) free, because we have declared Tree to be an instance of Eq.

See how awesome this structure is: we can make trees containing not only integers, strings and chars, but also other trees. And we can even make a tree containing a tree of trees!

More Advanced Types

So far we have presented types that are close to types we can see in most typed programming languages. But the real strength of Haskell is its type system. So I will try to give you an idea about what makes the Haskell type system more advanced than in most languages.

So as comparison, classical types/schemas, etc… are about products of different sub-types:

data ProductType = P Int String
data PersonRecord = Person { age :: Int, name :: String }

Haskell has also a notion of sum types that I often lack a lot in other programming languages I use.

You can define your type as a sum:

data Point = D1 Int | D2 Int Int | D3 Int Int Int

So far so good. Sum types are already a nice thing to have, in particular within Haskell because now the compiler can warn you if you miss a case. For example if you write:

case point of
  D1 x -> ...
  D2 x y -> ...

If you compile with the -Wall flag (as you should always do for serious development) then the compiler will warn you that you are forgetting some possible value.

Those are still not really advanced types. Advanced type are higher order types. Those are the one that help with making your code more polymorphic.

We will start with example I alreday provided, lists:

data MyList a = Cons a (MyList a) | Nil

As you can see MyList takes a type parameter. So MyList is a higher order type. Generally, the intuition behind type is that a type is a data structure or a container. But in fact, Haskell types can be or can contain functions. This is for example the case for IO. And this is why it can be confusing to read the type of some functions. I will take as example sequenceA:

sequenceA :: Applicative f => t (f a) -> f (t a)

So if you read this, it can be quite difficult to grasp what is the intended use of this function. A simple technique for example, is to try to replace the higher order types (here t and f) by a type you can have some intuition about. For example consider t to be the higher order type Tree and f to be the higher order type [] (list).

Now you can see that sequenceA sill take a Tree of lists and will return a list of trees. For it to work [] need to be part of the Applicative class type (which is the case). I will not enter into the details about what Applicative type class is here. But just with this, you should start to have a better intuition about what sequenceA is about.

Infinite Structures


It is often said that Haskell is lazy.

In fact, if you are a bit pedantic, you should say that Haskell is non-strict. Laziness is just a common implementation for non-strict languages.

Then what does "not-strict" mean? From the Haskell wiki:

Reduction (the mathematical term for evaluation) proceeds from the outside in.

so if you have (a+(b*c)) then you first reduce + first, then you reduce the inner (b*c)

For example in Haskell you can do:

-- numbers = [1,2,..]
numbers :: [Integer]
numbers = 0:map (1+) numbers

take' n [] = []
take' 0 l = []
take' n (x:xs) = x:take' (n-1) xs

main = print $ take' 10 numbers

And it stops.


Instead of trying to evaluate numbers entirely, it evaluates elements only when needed.

Also, note in Haskell there is a notation for infinite lists

[1..]   ⇔ [1,2,3,4...]
[1,3..] ⇔ [1,3,5,7,9,11...]

and most functions will work with them. Also, there is a built-in function take which is equivalent to our take'.

Infinite Trees

Suppose we don't mind having an ordered binary tree. Here is an infinite binary tree:

nullTree = Node 0 nullTree nullTree

A complete binary tree where each node is equal to 0. Now I will prove you can manipulate this object using the following function:

-- take all element of a BinTree
-- up to some depth
treeTakeDepth _ Empty = Empty
treeTakeDepth 0 _     = Empty
treeTakeDepth n (Node x left right) = let
          nl = treeTakeDepth (n-1) left
          nr = treeTakeDepth (n-1) right
              Node x nl nr

See what occurs for this program:

main = prettyPrintTree (treeTakeDepth 4 nullTree)

This code compiles, runs and stops giving the following result:

[hs:hsenv]> runghc infinite_tree.hs
+- 0
|  |
|  +- 0
|  |  |
|  |  +- 0
|  |  |
|  |  `- 0
|  |
|  `- 0
|     |
|     +- 0
|     |
|     `- 0
`- 0
   +- 0
   |  |
   |  +- 0
   |  |
   |  `- 0
   `- 0
      +- 0
      `- 0

Just to heat up your neurones a bit more, let's make a slightly more interesting tree:

iTree = Node 0 (dec iTree) (inc iTree)
           dec (Node x l r) = Node (x-1) (dec l) (dec r)
           inc (Node x l r) = Node (x+1) (inc l) (inc r)

Another way to create this tree is to use a higher order function. This function should be similar to map, but should work on BinTree instead of list. Here is such a function:

-- apply a function to each node of Tree
treeMap :: (a -> b) -> BinTree a -> BinTree b
treeMap f Empty = Empty
treeMap f (Node x left right) = Node (f x)
                                     (treeMap f left)
                                     (treeMap f right)

Hint: I won't talk more about this here. If you are interested in the generalization of map to other data structures, search for functor and fmap.

Our definition is now:

infTreeTwo :: BinTree Int
infTreeTwo = Node 0 (treeMap (\x -> x-1) infTreeTwo)
                    (treeMap (\x -> x+1) infTreeTwo)

Look at the result for

main = prettyPrintTree $ treeTakeDepth 4 infTreeTwo
[hs:hsenv]> runghc infinite_tree_2.hs
+- -1
|  |
|  +- -2
|  |  |
|  |  +- -3
|  |  |
|  |  `- -1
|  |
|  `- 0
|     |
|     +- -1
|     |
|     `- 1
`- 1
   +- 0
   |  |
   |  +- -1
   |  |
   |  `- 1
   `- 2
      +- 1
      `- 3

Fibonnacci infinite list

The important things to remember. Haskell handle infinite structures naturally mostly because it is not strict.

So you can write, infinite tree, but also, you can generate infinite list like this common example:

fib :: [Integer]
fib = 1:1:zipWith (+) fib (tail fib)

main = traverse print (take 20 (drop 200 fib))

Many new details in this small code. Don't worry if you do not get all details:

This progam print all fibonnacci numbers from 201 to 221 instantaneously. Because, fib is a list that will be used as "cache" to compute each number even considering the code looks a bit like a double recursion.

[hs:0010-Haskell-Now]> time runghc fib_lazy.hs

real	0m1.000s
user	0m0.192s
sys	0m0.058s

Let's see how this work using Debug.Trace:

import Debug.Trace

-- like + but each time this is evaluated print a trace
tracedPlus x y = trace ("> " ++ show x ++ " + " ++ show y) (x + y)

fib :: [Integer]
fib = 1:1:zipWith tracedPlus fib (tail fib)

main = do
  print (fib !! 10)
  print (fib !! 12)
[hs:hsenv]> runghc fib_lazy_trace.hs
> 1 + 1
> 1 + 2
> 2 + 3
> 3 + 5
> 5 + 8
> 8 + 13
> 13 + 21
> 21 + 34
> 34 + 55
> 55 + 89
> 89 + 144

Notice how, once computed, the list is kept in memory. This is why when the second time we ask for the 12th element of fib we only perform two more additions. This is both a blessing and a curse. A blessing if you know when to use this as in this example. And a curse as if do not take care about lazyness it will come back at you with memory leaks.

After a bit of experience, most Haskellers can avoid memory leaks naturally.

Dive into the impure

Congratulations for getting so far!

You have been introduced to the functional style and how to deal with pure code. Understand code that is only evaluated without changing the state of the external world.

If you are like me, you should get the functional style. You should also understand a bit more the advantages of laziness by default. But you also don't really understand where to start in order to make a real program. And in particular:

Be prepared, the answers might be complex. But they are all very rewarding.

In this section you will first introduced about how to use IO. That should not be that hard. Then, a harder section should explain how IO works. And the last part will talk about how we can generalize why we learned so far with IO to many different types.

Deal With IO

Magritte, Carte blanche


A typical function doing IO looks a lot like an imperative program:

f :: IO a
f = do
  x <- action1
  action2 x
  y <- action3
  action4 x y
  • To set a value to an object we use <- .

  • The type of each line is IO *; in this example:

    - action1     :: IO b
    - x           :: b
    - action2 x   :: IO ()
    - action3     :: IO c
    - y           :: c
    - action4 x y :: IO a
  • Few objects have the type IO a, this should help you choose. In particular you cannot use pure functions directly here. To use pure functions you could do action2 (purefunction x) for example.

In this section, I will explain how to use IO, not how it works. You'll see how Haskell separates the pure from the impure parts of the program.

Don't stop because you're trying to understand the details of the syntax. Answers will come in the next section.

What to achieve?

Ask a user to enter a list of numbers. Print the sum of the numbers.

toList :: String -> [Integer]
toList input = read ("[" ++ input ++ "]")

main = do
  putStrLn "Enter a list of numbers (separated by comma):"
  input <- getLine
  print $ sum (toList input)

It should be straightforward to understand the behavior of this program. Let's analyze the types in more detail.

putStrLn :: String -> IO ()
getLine  :: IO String
print    :: Show a => a -> IO ()

Or more interestingly, we note that each expression in the do block has a type of IO a.

main = do
  putStrLn "Enter ... " :: IO ()
  getLine               :: IO String
  print Something       :: IO ()

We should also pay attention to the effect of the <- symbol.

  x <- something

If something :: IO a then x :: a.

Another important note about using IO: all lines in a do block must be of one of the two forms:

action1 :: IO a
        -- in this case, generally a = ()


value <- action2    -- where
                    -- action2 :: IO b
                    -- value   :: b

These two kinds of line will correspond to two different ways of sequencing actions. The meaning of this sentence should be clearer by the end of the next section.

Now let's see how this program behaves. For example, what happens if the user enters something strange? Let's try:

[hs:hsenv]> runghc io_sum.hs
Enter a list of numbers (separated by comma):
Prelude.read: no parse

Argh! An evil error message and a crash! Our first improvement will simply be to answer with a more friendly message.

In order to do this, we must detect that something went wrong. Here is one way to do this: use the type Maybe. This is a very common type in Haskell.

import Data.Maybe
import Text.Read (readMaybe)

What is this thing? Maybe is a type which takes one parameter. Its definition is:

data Maybe a = Nothing | Just a

This is a nice way to tell there was an error while trying to create/compute a value. The readMaybe function is a great example of this. This is a function similar to the function read4, but if something goes wrong the returned value is Nothing. If the value is right, it returns Just <the value>.

Now to be a bit more readable, we define a function which goes like this: If the string has the wrong format, it will return Nothing. Otherwise, for example for "1,2,3", it will return Just [1,2,3].

getListFromString :: String -> Maybe [Integer]
getListFromString str = readMaybe $ "[" ++ str ++ "]"

We simply have to test the value in our main function.

main :: IO ()
main = do
  putStrLn "Enter a list of numbers (separated by comma):"
  input <- getLine
  let maybeList = getListFromString input
  case maybeList of
    Just l  -> print (sum l)
    Nothing -> putStrLn "Bad format. Good Bye."

In case of error, we display a nice error message.

Note that the type of each expression in the main's do block remains of the form IO a.

One very important thing to note is the type of all the functions defined so far. There is only one function which contains IO in its type: main. This means main is impure. But main uses getListFromString which is pure. So it's clear just by looking at declared types which functions are pure and which are impure.

Why does purity matter? Among the many advantages, here are three:

This is why you should generally put as most code as possible inside pure functions.

Our next iteration will be to prompt the user again and again until she enters a valid answer.

We keep the first part:

import Data.Maybe
import Text.Read (readMaybe)

getListFromString :: String -> Maybe [Integer]
getListFromString str = readMaybe $ "[" ++ str ++ "]"

Now we create a function which will ask the user for an list of integers until the input is right.

askUser :: IO [Integer]
askUser = do
  putStrLn "Enter a list of numbers (separated by comma):"
  input <- getLine
  let maybeList = getListFromString input
  case maybeList of
      Just l  -> return l
      Nothing -> askUser

This function is of type IO [Integer]. Such a type means that we retrieved a value of type [Integer] through some IO actions. Some people might explain while waving their hands:

«This is an [Integer] inside an IO

If you want to understand the details behind all of this, you'll have to read the next section. But really, if you just want to use IO just practice a little and remember to think about the type.

Finally our main function is much simpler:

main :: IO ()
main = do
  list <- askUser
  print $ sum list

We have finished with our introduction to IO. This was quite fast. Here are the main things to remember:

If you practice a bit, you should be able to use IO.


  • Make a program that sums all of its arguments. Hint: use the function getArgs.

IO trick explained

Magritte, ceci n'est pas une pipe


To separate pure and impure parts, main is defined as a function which modifies the state of the world.

main :: World -> World

A function is guaranteed to have side effects only if it has this type. But look at a typical main function:

main w0 =
    let (v1,w1) = action1 w0 in
    let (v2,w2) = action2 v1 w1 in
    let (v3,w3) = action3 v2 w2 in
    action4 v3 w3

We have a lot of temporary elements (here w1, w2 and w3) which must be passed on to the next action.

We create a function bind or (>>=). With bind we don't need temporary names anymore.

main =
  action1 >>= action2 >>= action3 >>= action4

Bonus: Haskell has syntactical sugar for us:

main = do
  v1 <- action1
  v2 <- action2 v1
  v3 <- action3 v2
  action4 v3

Why did we use this strange syntax, and what exactly is this IO type? It looks a bit like magic.

For now let's just forget all about the pure parts of our program, and focus on the impure parts:

askUser :: IO [Integer]
askUser = do
  putStrLn "Enter a list of numbers (separated by commas):"
  input <- getLine
  let maybeList = getListFromString input
  case maybeList of
      Just l  -> return l
      Nothing -> askUser

main :: IO ()
main = do
  list <- askUser
  print $ sum list

First remark: this looks imperative. Haskell is powerful enough to make impure code look imperative. For example, if you wish you could create a while in Haskell. In fact, for dealing with IO, an imperative style is generally more appropriate.

But you should have noticed that the notation is a bit unusual. Here is why, in detail.

In an impure language, the state of the world can be seen as a huge hidden global variable. This hidden variable is accessible by all functions of your language. For example, you can read and write a file in any function. Whether a file exists or not is a difference in the possible states that the world can take.

In Haskell the current state of the world is not hidden. Rather, it is explicitly said that main is a function that potentially changes the state of the world. Its type is then something like:

main :: World -> World

Not all functions may access this variable. Those which have access to this variable are impure. Functions to which the world variable isn't provided are pure5.

Haskell considers the state of the world as an input variable to main. But the real type of main is closer to this one6:

main :: World -> ((),World)

The () type is the unit type. Nothing to see here.

Now let's rewrite our main function with this in mind:

main w0 =
    let (list,w1) = askUser w0 in
    let (x,w2) = print (sum list,w1) in

First, we note that all functions which have side effects must have the type:

World -> (a,World)

where a is the type of the result. For example, a getChar function should have the type World -> (Char, World).

Another thing to note is the trick to fix the order of evaluation. In Haskell, in order to evaluate f a b, you have many choices:

This is true because we're working in a pure part of the language.

Now, if you look at the main function, it is clear you must eval the first line before the second one since to evaluate the second line you have to get a parameter given by the evaluation of the first line.

This trick works like a charm. The compiler will at each step provide a pointer to a new real world id. Under the hood, print will evaluate as:

Now, if you look at the style of the main function, it is clearly awkward. Let's try to do the same to the askUser function:

askUser :: World -> ([Integer],World)


askUser :: IO [Integer]
askUser = do
  putStrLn "Enter a list of numbers:"
  input <- getLine
  let maybeList = getListFromString input in
      case maybeList of
          Just l  -> return l
          Nothing -> askUser


askUser w0 =
    let (_,w1)     = putStrLn "Enter a list of numbers:" in
    let (input,w2) = getLine w1 in
    let (l,w3)     = case getListFromString input of
                      Just l   -> (l,w2)
                      Nothing  -> askUser w2

This is similar, but awkward. Look at all these temporary w? names.

The lesson is: naive IO implementation in Pure functional languages is awkward!

Fortunately, there is a better way to handle this problem. We see a pattern. Each line is of the form:

let (y,w') = action x w in

Even if for some lines the first x argument isn't needed. The output type is a couple, (answer, newWorldValue). Each function f must have a type similar to:

f :: World -> (a,World)

Not only this, but we can also note that we always follow the same usage pattern:

let (y,w1) = action1 w0 in
let (z,w2) = action2 w1 in
let (t,w3) = action3 w2 in

Each action can take from 0 to n parameters. And in particular, each action can take a parameter from the result of a line above.

For example, we could also have:

let (_,w1) = action1 x w0   in
let (z,w2) = action2 w1     in
let (_,w3) = action3 z w2 in

With, of course: actionN w :: (World) -> (a,World).

IMPORTANT: there are only two important patterns to consider:

let (x,w1) = action1 w0 in
let (y,w2) = action2 x w1 in


let (_,w1) = action1 w0 in
let (y,w2) = action2 w1 in
Slave Market with the disappearing bust of Voltaire

Now, we will do a magic trick. We will make the temporary world symbols disappear. We will bind the two lines. Let's define the bind function. Its type is quite intimidating at first:

bind :: (World -> (a,World))
        -> (a -> (World -> (b,World)))
        -> (World -> (b,World))

But remember that (World -> (a,World)) is the type for an IO action. Now let's rename it for clarity:

type IO a = World -> (a, World)

Some examples of functions:

getLine :: IO String
print :: Show a => a -> IO ()

getLine is an IO action which takes world as a parameter and returns a couple (String, World). This can be summarized as: getLine is of type IO String, which we also see as an IO action which will return a String "embeded inside an IO".

The function print is also interesting. It takes one argument which can be shown. In fact it takes two arguments. The first is the value to print and the other is the state of world. It then returns a couple of type ((), World). This means that it changes the state of the world, but doesn't yield any more data.

This new IO a type helps us simplify the type of bind:

bind :: IO a
        -> (a -> IO b)
        -> IO b

It says that bind takes two IO actions as parameters and returns another IO action.

Now, remember the important patterns. The first was:

pattern1 w0 =
  let (x,w1) = action1 w0 in
  let (y,w2) = action2 x w1 in

Look at the types:

action1  :: IO a
action2  :: a -> IO b
pattern1 :: IO b

Doesn't it seem familiar?

(bind action1 action2) w0 =
    let (x, w1) = action1 w0
        (y, w2) = action2 x w1
    in  (y, w2)

The idea is to hide the World argument with this function. As an example imagine if we wanted to simulate:

let (line1, w1) = getLine w0 in
let ((), w2) = print line1 in
((), w2)

Now, using the bind function:

(res, w2) = (bind getLine print) w0

As print is of type Show a => a -> (World -> ((), World)), we know res = () (unit type). If you didn't see what was magic here, let's try with three lines this time.

let (line1,w1) = getLine w0 in
let (line2,w2) = getLine w1 in
let ((),w3) = print (line1 ++ line2) in

Which is equivalent to:

(res,w3) = (bind getLine (\line1 ->
             (bind getLine (\line2 ->
               print (line1 ++ line2))))) w0

Didn't you notice something? Yes, no temporary World variables are used anywhere! This is MA. GIC.

We can use a better notation. Let's use (>>=) instead of bind. (>>=) is an infix function like (+); reminder 3 + 4 ⇔ (+) 3 4

(res,w3) = (getLine >>=
           (\line1 -> getLine >>=
           (\line2 -> print (line1 ++ line2)))) w0

Merry Christmas Everyone! Haskell has made syntactical sugar for us:

  x <- action1
  y <- action2
  z <- action3

Is replaced by:

action1 >>= (\x ->
action2 >>= (\y ->
action3 >>= (\z ->

Note that you can use x in action2 and x and y in action3.

But what about the lines not using the <-? Easy, another function blindBind:

blindBind :: IO a -> IO b -> IO b
blindBind action1 action2 w0 =
    bind action (\_ -> action2) w0

I didn't simplify this definition for the purposes of clarity. Of course, we can use a better notation: we'll use the (>>) operator.



Is transformed into

action1 >>
action2 >>

Also, another function is quite useful.

putInIO :: a -> IO a
putInIO x = IO (\w -> (x,w))

This is the general way to put pure values inside the "IO context". The general name for putInIO is pure but you also see very often return. Historically pure was called return. This is quite a bad name when you learn Haskell. return is very different from what you might be used to.

To finish, let's translate our example:

askUser :: IO [Integer]
askUser = do
  putStrLn "Enter a list of numbers (separated by commas):"
  input <- getLine
  let maybeList = getListFromString input in
      case maybeList of
          Just l  -> return l
          Nothing -> askUser

main :: IO ()
main = do
  list <- askUser
  print $ sum list

Is translated into:

import Data.Maybe
import Text.Read (readMaybe)

getListFromString :: String -> Maybe [Integer]
getListFromString str = readMaybe $ "[" ++ str ++ "]"
askUser :: IO [Integer]
askUser =
    putStrLn "Enter a list of numbers (sep. by commas):" >>
    getLine >>= \input ->
    let maybeList = getListFromString input in
      case maybeList of
        Just l -> return l
        Nothing -> askUser

main :: IO ()
main = askUser >>=
  \list -> print $ sum list

You can compile this code to verify that it works.

Imagine what it would look like without the (>>) and (>>)=.


Now the secret can be revealed: IO is a monad. Being a monad means you have access to some syntactical sugar with the do notation. But mainly, you have access to a coding pattern which will ease the flow of your code.

Important remarks:

  • Monad are not necessarily about effects! There are a lot of pure monads.
  • Monad are more about sequencing

In Haskell, Monad is a type class. To be an instance of this type class, you must provide the functions (>>=) and return. The function (>>) is derived from (>>=). Here is how the type class Monad is declared (from hackage GHC.Base):

class Applicative m => Monad m where
    -- | Sequentially compose two actions, passing any value produced
    -- by the first as an argument to the second.
    (>>=)       :: forall a b. m a -> (a -> m b) -> m b

    -- | Sequentially compose two actions, discarding any value produced
    -- by the first, like sequencing operators (such as the semicolon)
    -- in imperative languages.
    (>>)        :: forall a b. m a -> m b -> m b
    m >> k = m >>= \_ -> k -- See Note [Recursive bindings for Applicative/Monad]
    {-# INLINE (>>) #-}

    -- | Inject a value into the monadic type.
    return      :: a -> m a
    return      = pure

    -- | Fail with a message.  This operation is not part of the
    -- mathematical definition of a monad, but is invoked on pattern-match
    -- failure in a @do@ expression.
    -- As part of the MonadFail proposal (MFP), this function is moved
    -- to its own class 'MonadFail' (see "Control.Monad.Fail" for more
    -- details). The definition here will be removed in a future
    -- release.
    fail        :: String -> m a
    fail s      = errorWithoutStackTrace s


  • the keyword class is not your friend. A Haskell class is not a class of the kind you will find in object-oriented programming. A Haskell class has a lot of similarities with Java interfaces. A better word would have been typeclass, since that means a set of types. For a type to belong to a class, all functions of the class must be provided for this type.

  • In this particular example of type class, the type m must be a type that takes an argument. For example IO a, but also Maybe a, [a], etc…

  • To be a useful monad, your function must obey some rules. If your construction does not obey these rules strange things might happens:

    return a >>= k  ==  k a
    m >>= return  ==  m
    m >>= (\x -> k x >>= h)  ==  (m >>= k) >>= h
  • Furthermore the Monad and Applicative operations should relate as follow:

    pure = return
    (<*>) = ap

    The above laws imply:

    fmap f xs = xs >>= return . f
    (>>) = (*>)

Monad Intuition

I explained how to use the IO Monad. In the previous chapter I explained how it works behind the scene. Notice there is a huge difference between be a client of the Monad API and be an architect of the Monad API but also have an intuition about what is really a Monad.

So to try to give you an intuition, just remember a Monad is a construction that has to do with composition into higher order type constructors (types with a parameter). So if we consider (<=<) and (>=>) (Kleisli arrow composition) which are defined (simplified for the purpose of this article) as

f >=> g = \x -> f x >>= g
g <=< f = f >=> g

Those operation constructed with the bind operator (>>=) are a generalisation of (.) and (>>>) where f >>> g = g . f. If you can look at the type this become visible, simply compare:

f :: a -> b
g :: b -> c
g . f :: a -> c
f >>> g :: a -> c


f :: a -> m b
g :: b -> m c
g <=< f :: a -> m c
f >=> g :: a -> m c

As I said, this is a generalisation of the composition operation to functions that returns types within a higher order type constructor.

To give you better example, consider:


f 2 = [2,3]
g 2 = ["2",">3"]
g 3 = ["3",">4"]

One would expect to combine f and g such that (combine f g) 0 ⇒ ["2",">3","3",">4"]. Unfortunately (.) will not work directly and this would be cumbersome to write. But thanks to the Monad abstraction we can write:

(f >=> g) 2  ["2",">3","3",">4"]
import Control.Monad ((>=>))

f :: Int -> [Int]
f n = [n, n+1]

g :: Int -> [String]
g n = [show n,">"++show (n+1)]

main = print $ (f >=> g) 2

The next chapters are simply about providing some examples of useful Monads.

Maybe is a monad

There are a lot of different types that are instances of Monad. One of the easiest to describe is Maybe. If you have a sequence of Maybe values, you can use monads to manipulate them. It is particularly useful to remove very deep if..then..else.. constructions.

Imagine a complex bank operation. You are eligible to gain about 700€ only if you can afford to follow a list of operations without your balance dipping below zero.

deposit  value account = account + value
withdraw value account = account - value

eligible :: (Num a,Ord a) => a -> Bool
eligible account =
  let account1 = deposit 100 account in
    if (account1 < 0)
    then False
      let account2 = withdraw 200 account1 in
      if (account2 < 0)
      then False
        let account3 = deposit 100 account2 in
        if (account3 < 0)
        then False
          let account4 = withdraw 300 account3 in
          if (account4 < 0)
          then False
            let account5 = deposit 1000 account4 in
            if (account5 < 0)
            then False

main = do
  print $ eligible 300 -- True
  print $ eligible 299 -- False

Now, let's make it better using Maybe and the fact that it is a Monad.

deposit :: (Num a) => a -> a -> Maybe a
deposit value account = Just (account + value)

withdraw :: (Num a,Ord a) => a -> a -> Maybe a
withdraw value account = if (account < value)
                         then Nothing
                         else Just (account - value)

eligible :: (Num a, Ord a) => a -> Maybe Bool
eligible account = do
  account1 <- deposit 100 account
  account2 <- withdraw 200 account1
  account3 <- deposit 100 account2
  account4 <- withdraw 300 account3
  account5 <- deposit 1000 account4
  Just True

main = do
  print $ eligible 300 -- Just True
  print $ eligible 299 -- Nothing

Not bad, but we can make it even better:

deposit :: (Num a) => a -> a -> Maybe a
deposit value account = Just (account + value)

withdraw :: (Num a,Ord a) => a -> a -> Maybe a
withdraw value account = if (account < value) 
                         then Nothing 
                         else Just (account - value)

eligible :: (Num a, Ord a) => a -> Maybe Bool
eligible account =
  deposit 100 account >>=
  withdraw 200 >>=
  deposit 100  >>=
  withdraw 300 >>=
  deposit 1000 >>
  return True

main = do
  print $ eligible 300 -- Just True
  print $ eligible 299 -- Nothing

We have proven that Monads are a good way to make our code more elegant. Note this idea of code organization, in particular for Maybe can be used in most imperative languages. In fact, this is the kind of construction we make naturally.

An important remark:

The first element in the sequence being evaluated to Nothing will stop the complete evaluation. This means you don't execute all lines. You get this for free, thanks to laziness.

You could also replay these example with the definition of (>>=) for Maybe in mind:

instance Monad Maybe where
    (>>=) :: Maybe a -> (a -> Maybe b) -> Maybe b
    Nothing  >>= _  = Nothing
    (Just x) >>= f  = f x

    return x = Just x

The Maybe monad proved to be useful while being a very simple example. We saw the utility of the IO monad. But now for a cooler example, lists.

The list monad

Golconde de Magritte

The list monad helps us to simulate non-deterministic computations. Here we go:

import Control.Monad (guard)

allCases = [1..10]

resolve :: [(Int,Int,Int)]
resolve = do
              x <- allCases
              y <- allCases
              z <- allCases
              guard $ 4*x + 2*y < z
              return (x,y,z)

main = do
  print resolve

MA. GIC. :


For the list monad, there is also this syntactic sugar (à la Python):

print $ [ (x,y,z) | x <- allCases,
                    y <- allCases,
                    z <- allCases,
                    4*x + 2*y < z ]

I won't list all the monads, since there are many of them. Using monads simplifies the manipulation of several notions in pure languages. In particular, monads are very useful for:

If you have followed me until here, then you've done it! You know monads7!

Start swimming

If you come this far, you can really congratulate yourself. This is already what I would personnaly call a tremendous achievement.

This chapter will focus on how to build applications with Haskell. How to use libraries inside your project.

Note application development is easier to introduce than library development. Mostly because dependency management will be a lot easier.

I first intended to provide a lot more informations about how to create a project and provide a few project examples. But it occurs this is harder than I first expected. So I will just provide the introduction about how to create a starting point with many pointers for other possible options.

Start a new project

There are multiple starting options to create a new project. The most common one is certainly to use cabal-install. Another popular option is to use stack. stack adds a layer on top of cabal-install and uses fixed set of libraries known to compile together. Another method is to nix to handle the dependencies and use cabal-install for the rest. That final choice is often considered as the most complex and difficult for beginners. Still this is the one I find the most elegant. This is the method I will use in this article.

Still, you shall not be intimidated. Look:

I will just walk you through all the steps in detail. And mostly I will tell you not to take care about most warning messages. For our end-goal, those are mostly noise. I am aware of the level of complexity that it looks like at first. But really most of the apparent complexity is due to poor naming convention and not to any fundenmental core difficulty.

Bootstrap a project template files

  1. put the shell.nix file in some directory
  2. start nix-shell --pure
  3. in the nix shell create a new directory and then
  4. cabal init -i
  5. You should use the default value for most questions except:
    1. Should I generate a simple project with sensible defaults? [default: y] n
    2. the package should build "Library AND Executable" (choice 3)
    3. Cabal specification 2.4 (choice 4)
    4. Application directory choose app (choice 3)
    5. Library directory choose lib (choice 3)
    6. Add informative comments, choose yes.

Here is a full interaction:

~/dev/hsenv> nix-shell

[hs:hsenv]> mkdir my-app

[hs:hsenv]> cd my-app/

[hs:my-app]> cabal init -i
Warning: The package list for 'hackage.haskell.org' does not exist. Run 'cabal
update' to download it.
Should I generate a simple project with sensible defaults? [default: y] n
What does the package build:
   1) Executable
   2) Library
   3) Library and Executable
Your choice? 3
What is the main module of the executable:
 * 1) Main.hs (does not yet exist, but will be created)
   2) Main.lhs (does not yet exist, but will be created)
   3) Other (specify)
Your choice? [default: Main.hs (does not yet exist, but will be created)]
Please choose version of the Cabal specification to use:
 * 1) 1.10   (legacy)
   2) 2.0    (+ support for Backpack, internal sub-libs, '^>=' operator)
   3) 2.2    (+ support for 'common', 'elif', redundant commas, SPDX)
   4) 2.4    (+ support for '**' globbing)
Your choice? [default: 1.10   (legacy)] 4
Package name? [default: my-app]
Package version? [default:]
Please choose a license:
   1) GPL-2.0-only
   2) GPL-3.0-only
   3) LGPL-2.1-only
   4) LGPL-3.0-only
   5) AGPL-3.0-only
   6) BSD-2-Clause
 * 7) BSD-3-Clause
   8) MIT
   9) ISC
  10) MPL-2.0
  11) Apache-2.0
  12) LicenseRef-PublicDomain
  13) NONE
  14) Other (specify)
Your choice? [default: BSD-3-Clause]
Author name? [default: Yann Esposito (Yogsototh)]
Maintainer email? [default: yann.esposito@gmail.com]
Project homepage URL?
Project synopsis?
Project category:
 * 1) (none)
   2) Codec
   3) Concurrency
   4) Control
   5) Data
   6) Database
   7) Development
   8) Distribution
   9) Game
  10) Graphics
  11) Language
  12) Math
  13) Network
  14) Sound
  15) System
  16) Testing
  17) Text
  18) Web
  19) Other (specify)
Your choice? [default: (none)]
Application (Main.hs) directory:
 * 1) (none)
   2) src-exe
   3) app
   4) Other (specify)
Your choice? [default: (none)] 3
Library source directory:
 * 1) (none)
   2) src
   3) lib
   4) src-lib
   5) Other (specify)
Your choice? [default: (none)] 2
Should I generate a test suite for the library? [default: y]
Test directory:
 * 1) test
   2) Other (specify)
Your choice? [default: test]
What base language is the package written in:
 * 1) Haskell2010
   2) Haskell98
   3) Other (specify)
Your choice? [default: Haskell2010]
Add informative comments to each field in the cabal file (y/n)? [default: n] y

Guessing dependencies...

Generating LICENSE...
Generating Setup.hs...
Generating CHANGELOG.md...
Generating src/MyLib.hs...
Generating app/Main.hs...
Generating test/MyLibTest.hs...
Generating my-app.cabal...

Warning: no synopsis given. You should edit the .cabal file and add one.
You may want to edit the .cabal file and add a Description field.


Please ignore the following warning:

Warning: The package list for 'hackage.haskell.org' does not exist. Run 'cabal
update' to download it.

Nix should take care of handling Haskell libraries not cabal-install. No need to run cabal update.

After this step you should end up with the following set of files:

[hs:my-app]> tree
├── Setup.hs
├── app
│   └── Main.hs
├── src
│   └── MyLib.hs
├── my-app.cabal
└── test
    └── MyLibTest.hs

3 directories, 7 files

Create a few nix files

The goal of this tutorial is not to make you learn nix because it is a bit complex, but to explain you a bit, nix use a a configuration language and not just a configuration format. So to configure your nix environment you endup writing a nix expression in this nix language. And thus you can call the content of one nix-file in another one for example, or use variables.

The first file to create is the one that will pin the versions of all your packages and libraries:

import (fetchTarball https://github.com/NixOS/nixpkgs/archive/19.09.tar.gz) {}

The second file is the default.nix file:

{ nixpkgs ? import ./nixpkgs.nix
, compiler ? "default"
, doBenchmark ? false }:
  inherit (nixpkgs) pkgs;
  name = "my-app";
  haskellPackages = pkgs.haskellPackages;
  variant = if doBenchmark
            then pkgs.haskell.lib.doBenchmark
            else pkgs.lib.id;
  drv = haskellPackages.callCabal2nix name ./. {};
  my_project = drv;
  shell = haskellPackages.shellFor {
    # generate hoogle doc
    withHoogle = true;
    packages = p: [drv];
    # packages dependencies (by default haskellPackages)
    buildInputs = with haskellPackages;
      [ hlint
        # # if you want to add some system lib like ncurses
        # # you could by writing it like:
        # pkgs.ncurses
    # nice prompt for the nix-shell
    shellHook = ''
     export PS1="\n\[[${name}:\033[1;32m\]\W\[\033[0m\]]> "

It uses the nixpkgs.nix file. But also you can configure it to enable/disable benchmarks while building your application. I do not expect you to understand what is really going on here, but a short explanation is this file take cares of:

  1. use the pinned version of nixpkgs and should provide a working set of haskell libraries.
  2. read you .cabal file and find the set of libraries you depends on so nix will be able to download them.
  3. download a few useful packages for Haskell development, in particular hlint, ghcid, cabal-install, cabal2nix and hindent. I will talk about those tools later.
  4. take care of handling the nix-shell prompt so you should see the name of your project.

The only things you should manipulate for a new fresh project should be the name and perhaps the buildInputs list to add a few more libraries that could be either Haskell libraries or any library nix know about (for example ncurses, in that case you should write it pkgs.ncurses).

The two last file simply use the default.nix file:

The shell.nix file:

(import ./. {}).shell

And release.nix:

  def = import ./. {};
 { my_project = def.my_project; }

So download those files as well as this .gitignore file:


Checking your environment

Now you should see those files in your project:

[hs:my-app]> tree
├── Setup.hs
├── app
│   └── Main.hs
├── default.nix
├── src
│   └── MyLib.hs
├── my-app.cabal
├── nixpkgs.nix
├── release.nix
├── shell.nix
└── test
    └── MyLibTest.hs

3 directories, 11 files

You shall now enter nix-shell again, but in your my-app directory this time.

[hs:my-app]> nix-shell
warning: Nix search path entry '/nix/var/nix/profiles/per-user/root/channels' does not exist, ignoring
building '/nix/store/j3hi4wm9996wfga61arc2917klfgspwr-cabal2nix-my-app.drv'...
warning: Nix search path entry '/nix/var/nix/profiles/per-user/root/channels/nixpkgs' does not exist, ignoring
warning: file 'nixpkgs' was not found in the Nix search path (add it using $NIX_PATH or -I), at (string):1:9; will use bash from your environment

[my-app:my-app]> which ghcid

[my-app:my-app]> cabal run my-app
Build profile: -w ghc-8.6.5 -O1
In order, the following will be built (use -v for more details):
 - my-app- (src) (first run)
 - my-app- (exe:my-app) (first run)
Configuring library for my-app-
Preprocessing library for my-app-
Building library for my-app-
[1 of 1] Compiling MyLib            ( src/MyLib.hs, /Users/y/hsenv/my-app/dist-newstyle/build/x86_64-osx/ghc-8.6.5/my-app- )
Configuring executable 'my-app' for my-app-
Preprocessing executable 'my-app' for my-app-
Building executable 'my-app' for my-app-
[1 of 1] Compiling Main             ( app/Main.hs, /Users/y/hsenv/my-app/dist-newstyle/build/x86_64-osx/ghc-8.6.5/my-app- )
Linking /Users/y/hs-env/my-app/dist-newstyle/build/x86_64-osx/ghc-8.6.5/my-app- ...
Hello, Haskell!

Great! It works! Try to run it again:

[my-app:my-app]> cabal run my-app
Up to date
Hello, Haskell!

This time, the compilation is not done again. cabal is smart enough not to repeat the compilation again.

You could also use nix-build to compile your app. I think this is nice to do for releases. But for development, you should use cabal.

Add a library

tl;dr: do not be afraid by the lenght of this section in fact, this is straightforward. I just take a lot of time to go through all intermediate steps.

  1. add the library in the build-depends inside your .cabal file.
  2. restart nix-shell to download the new dependencies.

If you open the my-app.cabal file in an editor you should see a library section and and executable my-app section. In particular for each section you can see a build-depends sub-section as this one:

  build-depends:       base ^>=
executable my-app
  build-depends:       base ^>=, my-app

The ^>= means that it should use the latest non breaking version of the haskell package base. The author of the base package are responsible not to break the API for minor releases. Haskell libs uses a 4 number versionning quite similar to the semantic versionning scheme with just another minor number for non visible changes. I will not argue much, but mainly, semantic versionning and Haskell versionning are just a "right to break things to your users".

I don't want to talk a lot more about this, but, it would be nice if more people would watch this talk8 related to versionning.

If you want to know more about Haskell versionning convention: https://pvp.haskell.org

Add the protolude lib in the library build-depends like this:

  build-depends:       base ^>=,
executable my-app
  build-depends:       base ^>=, my-app

I did not include a version constraint here. This is ok if you do not deploy your library publicly. This would be absolutely awful if you deploy your library publicly. So while developing a private app nobody can see except you, nothing is wrong with this. But I would encourage you to write those version bounds. It is sane to do that, but be warned that your lib might rot if you want it to be part of a working set of libs. So you might be pinged time to time to update some bounds or to adap your code to the breaking change of a lib you are using. Do not think too much about this. This is generally quite trivial work to do to maintain your lib into a working lib set.

Now that you have added protolude modify slightly the code of your app to use it. Change the code inside src/MyLib.hs:

{-# LANGUAGE NoImplicitPrelude #-}
{-# LANGUAGE OverloadedStrings #-}
module MyLib (someFunc) where

import Protolude

someFunc :: IO ()
someFunc = putText "someFunc"

Please do not try to search right now about what this change is doing. It should work mostly as before. The goal here is just to check that you can use another library easily.

So now you should get out of the nix-shell because nix dependencies changed. Generally just type ^D (Ctrl-d) then launch nix-shell --pure.

[my-app:my-app]> cabal build
Warning: The package list for 'hackage.haskell.org' does not exist. Run 'cabal
update' to download it.
Resolving dependencies...
cabal: Could not resolve dependencies:
[__0] trying: my-app- (user goal)
[__1] unknown package: protolude (dependency of my-app)
[__1] fail (backjumping, conflict set: my-app, protolude)
After searching the rest of the dependency tree exhaustively, these were the
goals I've had most trouble fulfilling: my-app, protolude

[my-app:my-app]> exit

[hs:my-app]> nix-shell
warning: Nix search path entry '/nix/var/nix/profiles/per-user/root/channels' does not exist, ignoring
building '/nix/store/sr4838rnmzn30j3qc5ray4i2n6n0p8pq-cabal2nix-my-app.drv'...

[my-app:my-app]> cabal build
Build profile: -w ghc-8.6.5 -O1
In order, the following will be built (use -v for more details):
 - my-app- (lib) (file src/MyLib.hs changed)
 - my-app- (exe:my-app) (configuration changed)
Preprocessing library for my-app-
Building library for my-app-
[1 of 1] Compiling MyLib            ( src/MyLib.hs, .../my-app/dist-newstyle/build/x86_64-osx/ghc-8.6.5/my-app- )
Configuring executable 'my-app' for my-app-
Preprocessing executable 'my-app' for my-app-
Building executable 'my-app' for my-app-
[1 of 1] Compiling Main             ( app/Main.hs, .../my-app/dist-newstyle/build/x86_64-osx/ghc-8.6.5/my-app- ) [MyLib changed]
Linking .../my-app/dist-newstyle/build/x86_64-osx/ghc-8.6.5/my-app- ...

[my-app:my-app]> cabal run my-app
Up to date
Hello, Haskell!


Better defaults

Some of the default values in the cabal file are not the best for a professional and serious application development unfortunately. First, let create a new block called common professional-properties that will help us not repeat ourselve much and show more warning during compilation.

common professional-properties
  default-language: Haskell2010
    base ^>=
    -- -Werror
    -- -O2

This should then be used with import in all other sections (library, executable and test). Also add the ghc-options to enable the use of all core by default. This might not always be a good idea. But I think this is generally a better default for most modern application.

  import: professional-properties
  build-depends: protolude

executable my-app
  import: professional-properties
    -- enable parallelism

test-suite my-app-test
  import: professional-properties

You can download the final cabal file: my-app.cabal


This was a re-written fast Haskell tutorial. I will certainly complete this with more advanced tutorial explaining how to write a few Haskell projects.

Thanks for reading it.


Thanks to /r/haskell and /r/programming. Your comment were most than welcome.

Particularly, I want to thank Emm a thousand times for the time he spent on correcting my English. Thank you man.

  1. Even if most recent languages try to hide them, they are present.↩︎

  2. I know I'm cheating. But I will talk about non-strictness later.↩︎

  3. For the brave, a more complete explanation of pattern matching can be found here.↩︎

  4. Which is itself very similar to the javascript eval function, that is applied to a string containing JSON.↩︎

  5. There are some unsafe exceptions to this rule. But you shouldn't see such use in a real application except maybe for debugging purposes.↩︎

  6. For the curious ones, the real type looks like data IO a = IO {unIO :: State# RealWorld -> (# State# RealWorld, a #)}. All the # has to do with optimisation. I swapped the fields in my example. But this is the basic idea. As of today, the definition of IO is no more visible into base. We have the following explanation in GHC.IO.hs:

    The IO Monad is just an instance of the ST monad, where the state is
    the real world.  We use the exception mechanism (in GHC.Exception) to
    implement IO exceptions.
    NOTE: The IO representation is deeply wired in to various parts of the
    system.  The following list may or may not be exhaustive:
    Compiler  - types of various primitives in PrimOp.hs
    RTS       - forceIO (StgStartup.cmm)
              - catchzh_fast, (un)?blockAsyncExceptionszh_fast, raisezh_fast
              - raiseAsync (RaiseAsync.c)
    Prelude   - GHC.IO.hs, and several other places including
    Libraries - parts of hslibs/lang.
  7. Well, you'll certainly need to practice a bit to get used to them and to understand when you can use them and create your own. But you already made a big step in this direction.↩︎

  8. Spec-ulation Keynote - Rich Hickey↩︎

Any comment? Click on my email below and I'll add it.
authorYann Esposito <yann@esposito.host>
tags#Haskell #programming #functional #tutorial
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