Understanding Monads With JavaScript

Nice people have translated this article into Portuguese and Russian.

For the past weeks I’ve been working hard studying monads. I’m still learning Haskell, and to be honest I thought I knew what monads are all about, but when I wanted to write a little Haskell library, just to sharpen up my skills, I realized that while I understood the way monadic bind ( >>= ) and return work, I had no understanding of where that state comes from. So, most likely I had no understanding at all. As a result of this I thought I rediscover monads myself using JavaScript. The plan was basically the same as that used when I derived the Y Combinator: start from the initial problem (dealing with explicit immutable state in this case), and work my way up to the solution by applying simple code transformations.

Also, I chose JavaScript because it forces you to write some code that Haskell readily hides for you thanks to its terse syntax or different semantics (lambda expressions, operators, and built-in function currying). Lastly, I learn best by comparison, which is why I tried it in CoffeeScript and Scheme too. Here are the GitHub gists for the latter two:

Constraints

In this article I’ll limit my problem to the state monad. Understanding the state monad is good enough to have an idea what monads are all about. So here are the solution constraints.

no mutable state — Haskell makes use of the state monad because it does not allow mutable state.

— Haskell makes use of the state monad because it does not allow mutable state. no explicit state — When you don’t have mutable state, you have to thread residual state around. Typing and reading all those intermediate states is not pleasant. Monads try to hide all this plumbing. You’ll see what I mean in a moment.

— When you don’t have mutable state, you have to thread residual state around. Typing and reading all those intermediate states is not pleasant. Monads try to hide all this plumbing. You’ll see what I mean in a moment. no code duplication — This goes hand in hand with the previous point, but I still put it here because in my experience removal of code duplication is a powerful tool to explore new grounds.

Too Long; Won’t Read

This article is a pretty dense one, so I thought I should add some additional material to it. That’s why I recorded a little video with all the steps that are described below. It’s sort of a tl;dr version, and it should help visualize the transitions more easily, but most likely the video won’t make too much sense if you won’t read the whole article.

I advise you watch it directly on Vimeo, where it’s available in HD.

Derivation Vehicle

I’ll use a stack as my derivation vehicle because it’s an easy to understand data structure, and its usual implementation is done using mutable state. First, here’s how you’d normally use a stack in JavaScript.

var stack = []; stack . push ( 4 ); stack . push ( 5 ); stack . pop (); // 5 stack . pop (); // 4

JavaScript array objects have the usual methods one would expect from a stack, push and pop . What I don’t like about it is that it mutates state. Well, I don’t it like for the sake of this article, at least.

Each step I’ll describe is a working step. Just open your browser’s console and reload this page. You should see several console groups with the string 5 : 4 logged inside. However, in the body of the article I’ll only present those parts that differ from the previous steps.

A Stack With Explicit Handling of State

The obvious solution to avoid mutable state is to construct a new state container every time we need mutation. Here’s how it can look like in JavaScript (note that concat and slice are two Array methods that do not mutate the object they’re called on, instead they create new Array objects):

var push = function ( element , stack ) { var newStack = [ element ]. concat ( stack ); return newStack ; }; var pop = function ( stack ) { var value = stack [ 0 ]; var newStack = stack . slice ( 1 ); return { value : value , stack : newStack }; }; var stack0 = []; var stack1 = push ( 4 , stack0 ); var stack2 = push ( 5 , stack1 ); var result0 = pop ( stack2 ); // {value: 5, stack: [4]} var result1 = pop ( result0 . stack ); // {value: 4, stack: []}

As you can see, both push and pop return a residual stack, the resulted state. pop additionally returns the popped value. Each subsequent stack operation uses the previous stack, but this may not be easily observable because of differences in representation of return values. However, code duplication can be emphasized by normalizing return values. We’ll have push return a dummy undefined value.

var push = function ( element , stack ) { var value = undefined ; var newStack = [ element ]. concat ( stack ); return { value : value , stack : newStack }; }; var pop = function ( stack ) { var value = stack [ 0 ]; var newStack = stack . slice ( 1 ); return { value : value , stack : newStack }; }; var stack0 = []; var result0 = push ( 4 , stack0 ); var result1 = push ( 5 , result0 . stack ); var result2 = pop ( result1 . stack ); // {value: 5, stack: [4]} var result3 = pop ( result2 . stack ); // {value: 4, stack: []}

That’s the kind of duplication I was talking earlier. Duplication that also means explicit handling of state.

Transforming to Continuation-Passing Style

Now, I’ll replace those intermediate result variables with functions and parameters. I want this because I find it easier to abstract over functions and parameters than over simple variables. To do this, I’ll create a small helper function, called bind , which does nothing more than just apply a continuation callback to the stack operation result. In other works, it binds a continuation to a stack operation.

var bind = function ( value , continuation ) { return continuation ( value ); }; var stack0 = []; var finalResult = bind ( push ( 4 , stack0 ), function ( result0 ) { return bind ( push ( 5 , result0 . stack ), function ( result1 ) { return bind ( pop ( result1 . stack ), function ( result2 ) { return bind ( pop ( result2 . stack ), function ( result3 ) { var value = result2 . value + " : " + result3 . value ; return { value : value , stack : result3 . stack }; }); }); }); });

The return value of the whole expression, stored in finalResult , has the same type as the return value of a single push or pop operation. We want to have consistent interfaces.

Currying push and pop

Next, we want to be able to detach the stack arguments from push and pop . We want this because the intention is to have bind thread them behind the scenes.

For this we’ll apply another lambda calculus trick called function currying. An alternative name could be function application procrastination.

Now, instead of calling push(4, stack0) , we’ll call push(4)(stack0) . In Haskell we wouldn’t even need this step, because its functions are curried by default.

var push = function ( element ) { return function ( stack ) { var value = undefined ; var newStack = [ element ]. concat ( stack ); return { value : value , stack : newStack }; }; }; var pop = function () { return function ( stack ) { var value = stack [ 0 ]; var newStack = stack . slice ( 1 ); return { value : value , stack : newStack }; }; }; var stack0 = []; var finalResult = bind ( push ( 4 )( stack0 ), function ( result0 ) { return bind ( push ( 5 )( result0 . stack ), function ( result1 ) { return bind ( pop ()( result1 . stack ), function ( result2 ) { return bind ( pop ()( result2 . stack ), function ( result3 ) { var value = result2 . value + " : " + result3 . value ; return { value : value , stack : result3 . stack }; }); }); }); });

Preparing bind to Handle Intermediate Stacks

As I said in the previous section, I’d like bind to handle the passing of the explicit stack arguments. First, let’s have bind accept a stack as its last parameter, but in a curried way, i.e. bind now returns a function which takes a stack. Also, push and pop are now partially applied, i.e. we longer pass them the stack manually. bind will handle this instead.

var bind = function ( stackOperation , continuation ) { return function ( stack ) { return continuation ( stackOperation ( stack )); }; }; var stack0 = []; var finalResult = bind ( push ( 4 ), function ( result0 ) { return bind ( push ( 5 ), function ( result1 ) { return bind ( pop (), function ( result2 ) { return bind ( pop (), function ( result3 ) { var value = result2 . value + " : " + result3 . value ; return { value : value , stack : result3 . stack }; })( result2 . stack ); })( result1 . stack ); })( result0 . stack ); })( stack0 );

Removing Trailing Stacks

We’re now able to hide the intermediary stacks by modifying bind to inspect the return value of a stackOperation , extract the stack and use it as an argument to the return value of the continuation callback, which must be a function that receives a stack. That’s why we also have to wrap the final result ( return result2.value + " : " + result3.value ) inside an anonymous function that will receive a stack.

var bind = function ( stackOperation , continuation ) { return function ( stack ) { var result = stackOperation ( stack ); var newStack = result . stack ; return continuation ( result )( newStack ); }; }; var computation = bind ( push ( 4 ), function ( result0 ) { return bind ( push ( 5 ), function ( result1 ) { return bind ( pop (), function ( result2 ) { return bind ( pop (), function ( result3 ) { var value = result2 . value + " : " + result3 . value ; // We need this anonymous function because we changed the protocol // of the continuation. Now, each continuation must return a // function which accepts a stack. return function ( stack ) { return { value : value , stack : stack }; }; }); }); }); }); var stack0 = []; var finalResult = computation ( stack0 );

Hiding the Final Residual Stack

In the previous step, we hid away several intermediate stacks, but exposed a new one in the function that wraps the final result value. We can hide this trace of a stack by writing another helper function that I’ll call result . Additionally, this will also hide the internal representation of the state we’re keeping, i.e. a struct with two fields, value and stack .

var result = function ( value ) { return function ( stack ) { return { value : value , stack : stack }; }; }; var computation = bind ( push ( 4 ), function ( result0 ) { return bind ( push ( 5 ), function ( result1 ) { return bind ( pop (), function ( result2 ) { return bind ( pop (), function ( result3 ) { return result ( result2 . value + " : " + result3 . value ); }); }); }); }); var stack0 = []; var finalResult = computation ( stack0 );

This is exactly what the return functions does in Haskell. It wraps the computation result inside a monad. In our case it wraps the result in a closure which accepts a stack. But that’s basically what the state monad is, a function that accepts its state. Another way to view result / return is like a factory function that creates a new stateful context around the value we provide it with.

Keeping State Internal

We don’t want our continuation callbacks to have to traverse or even know about the struct returned by push or pop , which actually represents the internals of the monad. So, we’ll modify bind to pass just the minimum required data to the callback.

var bind = function ( stackOperation , continuation ) { return function ( stack ) { var result = stackOperation ( stack ); return continuation ( result . value )( result . stack ); }; }; var computation = bind ( push ( 4 ), function () { return bind ( push ( 5 ), function () { return bind ( pop (), function ( result1 ) { return bind ( pop (), function ( result2 ) { return result ( result1 + " : " + result2 ); }); }); }); }); var stack0 = []; var finalResult = computation ( stack0 );

Evaluating The Stack Computation

Once we’re able to compose stack operations this way, we’ll also want to run these computations and do something with the result. This is generally called evaluation of the monad. In Haskell, the state monad provides three functions for evaluating the state monad: runState , evalState , and execState .

For the purpose of this article though, I’ll replace the “State” suffix with “Stack”.

// Returns both the result and the final state. var runStack = function ( stackOperation , initialStack ) { return stackOperation ( initialStack ); }; // Returns only the computed result. var evalStack = function ( stackOperation , initialStack ) { return stackOperation ( initialStack ). value ; }; // Returns only the final state. var execStack = function ( stackOperation , initialStack ) { return stackOperation ( initialStack ). stack ; }; var stack0 = []; console . log ( runStack ( computation , stack0 )); // { value="5 : 4", stack=[]} console . log ( evalStack ( computation , stack0 )); // 5 : 4 console . log ( execStack ( computation , stack0 )); // []

If all we’re interested in is the final computed value, then evalStack is what we need. It will trigger the whole monadic computation, drop the final resulted state and return the computed value. Using this function we can extract a value out of its monadic context.

If you’ve ever heard that you can’t escape a monad, then let me tell that this is true just in a small number of cases, like the IO monad for example. But that’s another story. The point is that you can get out of the state monad.

Done

If you’re still with me, then let me tell you that this is how the state monad could look like in JavaScript. It probably doesn’t look that readable, compared to a similar Haskell version, but it’s the most I can get out of JavaScript today.

A monad is a pretty abstract concept because it specifies little about what you have to write. Mainly, it says that you need to design a function which will take some arguments (the state in the case of the state monad), and two additional functions: result and bind . The former will act as a factory for the function you just designed. The latter will be responsible for exposing just enough details about your monad to the outside world, and also perform some boring stuff like passing state around. Exposing is done by means of a continuation function that will take the value that the monad computes. Everything that is internal to the monad will be kept internal. Just like in object-oriented programming. And it’s even possible to have monadic getters/setters for the those internals.

Just for the record, here’s how the computation function would look like in Haskell.

computation = do push 4 push 5 a <- pop b <- pop return $ ( show a ) ++ " : " ++ ( show b )

The main reason the Haskell version looks better is because Haskell has built-in syntactic support for monads in the form of the do notation. do notation is just sugar for the following version, which still looks better than the JavaScript one. Haskell, having support for operator definitions and terse lambda expressions allows for a more readable, in my opinion, implementation of monads.

computation = push 4 >>= \ _ -> push 5 >>= \ _ -> pop >>= \ a -> pop >>= \ b -> return $ ( show a ) ++ " : " ++ ( show b )

What I called bind in JavaScript is >>= in Haskell, and what I called result in JavaScript is return in Haskell. Yes, return in Haskell is a function, not a keyword. Other times, return is named unit . Brian Marick called >>= a decider in his videos about monads in Clojure. The patcher was of course return .

Some JavaScript Sugar

It turns out there’s a better way to do monadic computations in JavaScript using a little utility function called sequence . Thanks to JavaScript’s dynamic nature, sequence can take a variable number of arguments that represent the monadic actions it must perform in sequence, save for the final argument which is a callback that contains the computation over the result of the monadic actions. The callback is called with all the non- undefined results of the monadic actions.

var sequence = function ( /* monadicActions..., continuation */ ) { var args = []. slice . call ( arguments ); var monadicActions = args . slice ( 0 , - 1 ); var continuation = args . slice ( - 1 )[ 0 ]; return function ( stack ) { var initialState = { values : [], stack : stack }; var state = monadicActions . reduce ( function ( state , action ) { var result = action ( state . stack ); var values = state . values . concat ( result . value ); var stack = result . stack ; return { values : values , stack : stack }; }, initialState ); var values = state . values . filter ( function ( value ) { return value !== undefined ; }); return continuation . apply ( this , values )( state . stack ); }; }; var computation = sequence ( push ( 4 ), // <- programmable commas :) push ( 5 ), pop (), pop (), function ( pop1 , pop2 ) { return result ( pop1 + " : " + pop2 ); } ); var initialStack = []; var result = computation ( initialStack ); // "5 : 4"

The authors of Real World Haskell compared monads to a programmable semicolon. In this case, I can say we have programmable commas, because that’s what I used when calling sequence to separate monadic actions.

Monads As Suspended Computations

You’ll often see monads being called computations. In the beginning I didn’t understand why. You might say because they compute stuff, but… nobody says “monads compute something”, they actually say “monads are computations”. I finally understood (or I think I did) what that means after I finished an early draft of this article. All that chaining of monadic actions and values does not actually compute anything until you tell it to. It’s all a big chain of partially applied functions, which represent a suspended computation that will finally be triggered by calling it with the initial state. Again, here’s this snippet.

var computation = sequence ( push ( 4 ), push ( 5 ), pop (), pop (), function ( pop1 , pop2 ) { return result ( pop1 + " : " + pop2 ); } );

Does it compute anything when it is evaluated? No. You have to trigger the computation with runStack , evalStack , or execStack .

var initialStack = []; evalStack ( computation , initialStack );

It looks like the push and pop functions act on some global value, whereas they in fact are always awaiting for that value to come. It’s almost like in OOP where this is the context of the computation. In our case though, this is implemented by means of currying and partial application, it also points to a new context in each expression. And, if in OO context is said to be implicit, then by using monads you make it even more implicit (if there even is such a thing).

The advantage of monads (and functional programming in general) is that you get highly composable building blocks. And it’s all because of function currying. Each time two monadic actions are chained, a new function is created which awaits to be run.

var computation1 = sequence ( push ( 4 ), push ( 5 ), pop (), pop (), function ( pop1 , pop2 ) { return result ( pop1 + " : " + pop2 ); } ); var computation2 = sequence ( push ( 2 ), push ( 3 ), pop (), pop (), function ( pop1 , pop2 ) { return result ( pop1 + " : " + pop2 ); } ); var composed = sequence ( computation1 , computation2 , function ( a , b ) { return result ( a + " : " + b ); } ); console . log ( evalStack ( composed , []) ); // "5 : 4 : 3 : 2"

This may seem useless for performing stack operations, but when designing a library of monadic parser combinators for example, this gets very handy. It allows the author of the library to provide just a handful of “primitive” functions on his Parser monad, and then, the user of the library is able to mix and match those primitives as he sees fit, ultimately ending up with an embedded domain specific language ( EDSL ).

The End

Well, I hope you found this article useful. Writing it definitely helped me having a better understanding of monads.

References