Writing Game of Life in Elm

Introduction

In this article, we will walk through the steps for writing an implementation of Conway's Game of Life in the Elm programming language.

In doing so, we will learn about the basic principles involved with writing programs in Elm, while grounding them in a concrete problem. We will be building a single program in steps, so much of the source will be repeated between the examples, but it will be more clear to present each step in its entirety.

I first became interested in Elm after seeing Evan Czaplicki's talk from mloc.js 2013, where he presented an overview of Elm and the compelling example of how one would write a simple side-scroller in an extremely straight forward fashion as a consequence of the core concept in Elm: signals.

Elm is a functional reactive programming language, a paradigm concerned with using an explicit model of time. Elm uses signals as its abstraction of time-varying values, including various time functions (e.g. every second ), constants (e.g. constant True ), which are invariant over time, and user input (e.g. Mouse.clicks ). These, and other, signals can be combined and manipulated in various ways to achieve vastly complex results, clearly and concisely. It is this expressive power of Elm that I find especially interesting. The overview of FRP on the Elm site is excellent resource for these core concepts.

For this reason, I chose Elm to explore Conway's Game of Life. Having seen that Life can be written concisely, to an almost absurd degree, in APL , it seems to me to be a very interesting problem by which to compare different languages. I have only dabbled with Elm in the past, writing a toy for LD 28 , but have always wanted to spend some more time getting to know the language.

Without further ado, let us begin writing Conway's Game of Life.

First Steps

We will begin by writing a very simple static grid, the foundation for our game. I often begin writing Elm programs with all my signals planned out, interacting in complex ways, since that seems the more interesting part of the problem, as compared with some boringly simple display components. The fact of the matter is, however, that, lacking in experience with static typing and the concepts of signals, I often find myself in a mess and have to back out.

I, in fact, did that with this program. Several times. I believe I come to understand the core concepts much more, but the fact remains: start with a solid base and build on top of it. This first example will simply a grid of a predetermined size. It has support for cells being turned on and off, but they are all on to begin with.

static_grid.elm Source import List import Color ( rgb ) import Graphics.Element ( Element , flow , right , down , container , topLeft , spacer , color ) cellSize = 5 ( columns , rows ) = ( 35 , 35 ) main : Element main = renderGrid generateGrid generateGrid : List ( List Bool ) generateGrid = List . repeat rows ( List . repeat columns True ) renderGrid : List ( List Bool ) -> Element renderGrid grid = grid |> List . map renderRow |> List . map ( flow right ) |> flow down |> container ( cellSize * columns ) ( cellSize * rows ) topLeft renderRow : List Bool -> List Element renderRow row = List . map renderCell row renderCell : Bool -> Element renderCell on = spacer cellSize cellSize |> color ( if on then ( rgb 0 0 0 ) else ( rgb 255 255 255 )) View Result

The crux of this program is that we want to turn a nested list of boolean values ( List (List Bool) ) into an Element , one of two possible types for the main function in an Elm program. We use the Element API to achieve this in a few steps.

This first example is, beyond those points, only really interesting syntactically. It should feel somewhat familiar to anyone who has worked with other functional languages. One point worth mentioning is the forward function application helper ( |> ). This helps clarify the program (at least to my eye), when a value passes through a number of functions sequentially. The following are equivalent: (c (b a)) and a |> b |> c .

Seeding the Grid

The next step is to take the grid we created in the first example and seed it with randomly generated examples. In Elm, the Random component has three functions, all of which are a Signal . This means that, we can no longer be concerned with simply taking one value and mutating it into another, but instead, with taking a signal and converting it into another signal. The main function can also be of the type Signal Element , which, in a sense, becomes the goal of our program - we have an input of type Signal (List Int) we will be taking from Random.list , and we want to convert it into a Signal Element that Elm can consume.

Herein lies a core concept - that of map ing a signal. The map function has the type (a -> b) -> Signal a -> Signal b ; it takes a function from type a to type b and a signal of type a and returns a signal of type b . This function is the primary means by which signals are converted from one type to another.

As a consequence of the way lift works, by taking a function to convert a signal, rewriting our static example to one that is randomly generated involves very few steps. These are as follows:

Change the type of main from Element to Signal Element . Write an initialSeed function of type Signal Random.Seed Write a seededGrid function of type Random.Seed -> List (List Bool) Change generateGrid from List (List Bool) to List Int -> List (List Bool) map our seededGrid function through our existing renderGrid function.

random_grid.elm Source import Signal ( (<~) , Signal ) import Signal import List ( (::) ) import List import Time import Random import Color ( rgb ) import Graphics.Element ( Element , flow , right , down , container , topLeft , spacer , color ) cellSize = 5 ( columns , rows ) = ( 35 , 35 ) main : Signal Element main = renderGrid <~ ( seededGrid <~ initialSeed ) initialSeed : Signal Random . Seed initialSeed = ( \ ( time , _ ) -> Random . initialSeed ( round time )) <~ Time . timestamp ( Signal . constant ()) seededGrid : Random . Seed -> List ( List Bool ) seededGrid seed = let ( lst , _ ) = Random . generate ( Random . list ( columns * rows ) ( Random . int 0 1 )) seed in generateGrid lst generateGrid : List Int -> List ( List Bool ) generateGrid seeds = List . map generateRow ( groupInto rows seeds ) generateRow : List Int -> List Bool generateRow seeds = List . map ( \ n -> n == 1 ) seeds renderGrid : List ( List Bool ) -> Element renderGrid grid = grid |> List . map renderRow |> List . map ( flow right ) |> flow down |> container ( cellSize * columns ) ( cellSize * rows ) topLeft renderRow : List Bool -> List Element renderRow row = List . map renderCell row renderCell : Bool -> Element renderCell on = spacer cellSize cellSize |> color ( if on then ( rgb 0 0 0 ) else ( rgb 255 255 255 )) groupInto : Int -> List a -> List ( List a ) groupInto groups initial = let len = List . length initial n = len // groups in List . repeat groups [] |> List . indexedMap ( \ i _ -> List . take n ( List . drop ( n * i ) initial )) View Result

We do write two other helper functions, generateRow and groupInto , but neither change is essential for the example. In fact, the rendering we wrote before, the helpers, and now the basic seeding never needs to change again.

These core input and output signals will remain constant, but we will have to add some additional transitions in order to make life evolve.

Adding Generations

This final piece of the puzzle is to make the grid evolve from one generation to the next. Elm makes this exceptionally easy with its concept of past dependent signals. The function foldp , of type (a -> b -> b) -> b -> Signal a -> Signal b takes a function of two values, a default value for the output signal, and an input signal. The function takes two arguments: the current value of the input signal, and the past value (or the default on the first event).

We can use this construct to take our initialSeed of Signal (List (List Bool)) and step it from generation to generation. This is, again, a comparatively simple process, consisting primarily of the following steps:

Update the main function to make use of foldp . Create a step function of type List (List Bool) -> List (List Bool) -> List (List Bool) . Create an evolve function of type List (List Bool) -> List (List Bool) .

game_of_life.elm Source import Signal ( (<~) , Signal ) import Signal import List ( (::) ) import List import Time import Random import Color ( rgb ) import Graphics.Element ( Element , flow , right , down , container , topLeft , spacer , color ) cellSize = 5 ( columns , rows ) = ( 35 , 35 ) main : Signal Element main = Signal . sampleOn ( Time . every Time . second ) ( seededGrid <~ initialSeed ) |> Signal . foldp ( step ) [[]] |> Signal . map renderGrid step : List ( List Bool ) -> List ( List Bool ) -> List ( List Bool ) step current past = if ( List . isEmpty ( List . head past )) then current else ( evolve past ) initialSeed : Signal Random . Seed initialSeed = ( \ ( time , _ ) -> Random . initialSeed ( round time )) <~ Time . timestamp ( Signal . constant ()) seededGrid : Random . Seed -> List ( List Bool ) seededGrid seed = let ( lst , _ ) = Random . generate ( Random . list ( columns * rows ) ( Random . int 0 1 )) seed in generateGrid lst generateGrid : List Int -> List ( List Bool ) generateGrid seeds = List . map generateRow ( groupInto rows seeds ) generateRow : List Int -> List Bool generateRow seeds = List . map ( \ n -> n == 1 ) seeds evolve : List ( List Bool ) -> List ( List Bool ) evolve generation = List . indexedMap ( \ y row -> List . indexedMap ( \ x _ -> descend generation x y ) row ) generation descend : List ( List Bool ) -> Int -> Int -> Bool descend grid x y = List . concatMap ( \ n -> List . map ( \ m -> ( x + n , y + m )) [ - 1 , 0 , 1 ]) [ - 1 , 0 , 1 ] |> List . filter ( \ p -> ( fst p ) > - 1 && ( fst p ) < columns && ( snd p ) > - 1 && ( snd p ) < rows && ( not (( fst p ) == x && ( snd p ) == y ))) |> List . filter ( \ p -> ( itemAt ( fst p ) ( itemAt ( snd p ) grid )) == True ) |> List . length |> ( \ l -> (( itemAt x ( itemAt y grid )) && l > 1 && l < 4 ) || l == 3 ) renderGrid : List ( List Bool ) -> Element renderGrid grid = grid |> List . map renderRow |> List . map ( flow right ) |> flow down |> container ( cellSize * columns ) ( cellSize * rows ) topLeft renderRow : List Bool -> List Element renderRow row = List . map renderCell row renderCell : Bool -> Element renderCell on = spacer cellSize cellSize |> color ( if on then ( rgb 0 0 0 ) else ( rgb 255 255 255 )) itemAt : Int -> List a -> a itemAt i lst = List . head ( List . drop i lst ) groupInto : Int -> List a -> List ( List a ) groupInto groups initial = let len = List . length initial n = len // groups in List . repeat groups [] |> List . indexedMap ( \ i _ -> List . take n ( List . drop ( n * i ) initial )) View Result

The only real nuance here is that we must sampleOn seed (every second) , which updates the signal with the constant initial value. We use an empty default to determine whether we should return the value from the seed, or whether we should evolve the past value.

We use an indexedMap for the evolve function, because we will need to have the index of the cell available when calling the descend function. Aside from these points, it is simply gathering all the neighboring cells, filtering invalid ones, counting live neighbors, and mapping to a new boolean value.

Conclusion and Further Steps

Elm is a wonderful and extremely expressive language, and my experiences with it have been overwhelmingly positive. I think it is excellent for these types of applications, and its core concepts are very solid. While neophytes may struggle with the type system - I know I have had my share of problems - this can be solved through experience. The community, moreover, is both knowledgeable and willing to help. When I had a question, Evan responded almost immediately and Jeff Smits elucidated my misconceptions.

In terms of this example, I think it is clear so long as the core concepts are in place. It may be longer than the APL example, but I did also err on the side of clarity over brevity. I have a feeling this could be condensed considerably were that the goal of the exercise.

As such, the most interesting way to proceed with this start would be to add interactive elements. Allowing a user to control things like cell size and count, duration of a generation, to flip individuals cells, to pause the game. The list could probably go on and on, and combining signals from many different inputs is one of the strengths of Elm. I intend on revisiting this example and improving upon it in the near future, so watch out for that update.

(This post was updated for Elm 0.14 on 13 Dec 2014)