Monads in Haskell Explained: Maybe Monad & Effects

[00:00:00]So, monads are a concept that was invented in mathematics in the 1960s, and then it was rediscovered in computer science in the 1990s. And what it gives you, is a new way of thinking about programming with effects. And for me, this is one of the most important new ideas in programming languages in the last 25 years. So that's what we're going to be looking at today - programming with monads.

[00:00:23]We're going to come at this using a simple example, and the example that we're going to look at is the idea of writing a function that evaluates simple expressions. And I'm going to use Haskell for this, but it doesn't matter if you don't know anything about Haskell, because we're going to use it in a very simple way, and I'm going to explain everything as we're going along. So, what we're going to start with, is by defining a simple datatype for the kind of expressions that we're going to be evaluating. So, we'll use the data keyword in Haskell, which introduces a new data type, and then we're going to define a new data type for expressions. And then there's two things that an expression can be. It can either be an integer value, so we'll write that down - we have Val of an Int.

[00:01:08]Or, it can be the division of two sub-expressions. So we've got two constructors here in our data type - we've got Val, which builds expressions from integers, and we've got Div, which builds expressions from two sub-expressions. So, just to reiterate what what's actually going on here, we're declaring a new data type called Expr, and it's got two new constructors - one called Val, which takes an integer parameter, and one called Div, which takes two sub-expressions as parameters as well.

[00:01:36]So basically what we're working with is expressions that are built up from integer values using a simple division operator. So, many of you may not be familiar of this kind of syntax, so let's have a couple of examples of values of this data type, so that we make sure everyone's on the same page. So, what I'm going to do here, is draw a little table. So, on one side, on the left-hand side, I'm going to have what we would normally write down in mathematics. And then on the right-hand side, we'll think how would you translate this into a value in this Haskell data type? So, let's have three simple examples here - we'll have one, and we'll have six divided by two, and let's do one more example, we'll have six divided by three divided by one. So, these are simple expressions built up from integers using a division operator. But, we're writing Haskell programs today, so let's think how do these things actually get represented as values of our expression data type? So, the first one is very simple - if we want to represent the value one, we just need to use the Val tag, so we write Val of one. If we want to have an expression like six divided by two, well it's a division, so we have a Div at the top level, and then we have two values - we have Val six, and Val two. And actually, I'll leave the last one is a little exercise for you here, so you can try this one for yourself - how do you represent this as a value in Haskell? Well, you're gonna need two divisions, you're going to need three Val constructors, and then a bunch of brackets. So, this is the basic idea - we've got simple expressions built up from integers using division, and we want to think about how do we write a program to evaluate these expressions? Let's write a program to do that. So, we're going to write an evaluator, and it's going to be a program, or a function in this case, that takes an expression as input, and what it's going to give back is the integer value of that expression.

[00:03:26]And there's going to be two cases here, because we have two kinds of expressions.

[00:03:30]We have a case for values, and we need to figure out what to do with that, which we'll do in a moment. And then we have a case for division, and we need to think what to do with that. So, we've got the skeleton here of a program, and then we just need to fill in the details. So, how do you evaluate an integer value? Well, that's very simple, you just give back the number - so if I had Val of one, it's value is just one. And then how do I evaluate a division? Well, these two expressions here, x and y, these could be as complicated as you wish. So, we need to evaluate these recursively. So what we would do, is evaluate the first one, x, and that will give us an integer. And then we'll evaluate the second one, y, and that will give us another integer. And then, all we need to do is divide one by the other. So, this is a nice simple program that evaluates these kind of expressions built up from integers using division - we just have a simple recursive program, two cases, and everything looks fine. But there's a problem with this program, and the problem is that it may crash - because if you divide a number by zero, then that's undefined, so this program will just crash. So, in particular, if the value of the expression y here was zero, then this division operator would crash, and you get some kind of runtime error. So we don't want our programs to crash, so we think, what do we do to fix this problem?

[00:04:49]First of all, what we're going to do is we're going to define a safe version of the division operator, which doesn't crash anymore. Because that's basically the root of the problem here - division by zero gives an undefined result, and the program is going to crash. So, let's define a safe version of the division operator. We're going to define a function called safediv, and it's going to take a couple of integers, and it's going to give back Maybe an integer. And Maybe is the way that we deal with things that can possibly fail in Haskell.

[00:05:18]So, the type here is not Int to Int to Int, it's Int to Int to Maybe Int, because division may fail. And we'll see how this Maybe type works in a moment. So, how do we actually define safediv? We take two integers, n and m, and then what we'll do is check - is the second of these zero? Because that's the case when things would go wrong. So, if m happened to be zero, then we will give back the result Nothing. Okay, so Nothing is one of the constructors in the Maybe type. If m is not zero, what we're going to do is Just give back the result of dividing. So, Just is another constructor in the Maybe type - Maybe only has two constructors, Nothing, which represents things that have gone wrong, or in our case division by zero, and Just, which represent things that have gone fine. In this case, we actually just get back the result of dividing one number by the other. So, what we have here now is a safe version of the division operator, which is explicitly checking for the case when the program would have crashed. So this doesn't crash anymore, it returns one of two values - either Nothing if things go wrong, or Just of the division if things have gone fine. So, what we can do then, with this safe division operator, is rewrite our little evaluator program to make sure that it doesn't crash. So, our new evaluator is going to have a slightly different type than before. So before, the original program just took an expression as input, and then it gave back an integer. But that program could crash. The new evaluator takes an expression as input as before, but now it Maybe gives you an integer, because it could fail, it could have division by zero. So, how do we rewrite this evaluator? So, we'll do the two cases again - write down the skeleton, and then we'll fill in the details. So, in the base case, we can't just return n this time, because we've got to return a Maybe value. And there's only two things we could return, either Nothing or Just, and in this case the right thing to do is to return Just of n, because if you evaluate a value that's always going to succeed, so we use a success tag, which is Just, and then we have the integer value sitting in here. If we have a division, now we need to do a bit more work, because when we evaluate x that may fail, when we evaluate y that may fail, and then when we do the division that may fail. So, we're going to need to do a little bit of checking and management of failure. So, what we're going to do, is when we evaluate a division, first of all, we'll do a case analysis on the result of evaluating x. And that could be one of two things - it could either be Nothing, in which case we're going to do something, or we could get Just of some number, in which case we're going to do something. So, there's two cases to consider - when we evaluate the first parameter x, either it succeeds or it fails. So in the failure case, if we get back Nothing, the only sensible thing to do is just to say, well if evaluation of x fails, the evaluation of the whole division fails. So we'll just return Nothing as well. In the Just case, then we need to evaluate the second parameter y. So, what we're going to do is do another case analysis, we'll do a case eval of y, and then again there's two possible outcomes which we could have here - either we could have Nothing, which means it failed, or we could have Just of m, some other number, in which case we've succeeded. Then again, we need to think what do we do in each of these two cases. So, in the first case, if the evaluation of y fails, the only sensible thing to do is say, well, we fail as well. In the second case, we've now got to successfully evaluated expressions - x has given the result n, y has given the result m, and now we can do the safe division. So, in this case we just do safediv. Now we have a working evaluator.

[00:08:52]We started off with a two-line program, which kind of did the essence of evaluation, but it didn't check for things going wrong - it didn't check for a division by zero. Now we've fixed the problem completely, we have a program which works, this program will never crash, it will always give a well-defined result, either Nothing or Just, but there's a bit of a problem with this program, in that it's a bit too long. It's a bit too verbose, there's quite a lot of noise in here, I can hardly see what's going on anymore, because it's all of this management of failure. So, we can look at this program, and think - how can we make this program better? And how can we make it more like the original program, that didn't work, but still maintain the fact that this actually does the right thing? And the idea here, is we're going to observe a common pattern. So, when you look at this program, you can see quite clearly we're doing the same thing twice - we're doing two case analyses. What we're doing, is doing a case analysis on the result of evaluating x, and if it's Nothing we give back Nothing, and if it's Just, we do something with the result. And then we do exactly the same thing with eval of y - we're doing a case analysis on the result of evaluating y, if that gives Nothing we give back Nothing, and if it's a Just, we do something with it. So, a very common idea in computing is when you see the same things multiple times, you abstract them out, and have them as a definition. And that's what we're going to do here. So, let's draw a little picture first, to capture the pattern which we've seen twice. So, the pattern we have here, is we're doing a case analysis on something, so let me just draw as a little box - we don't know what's in there, we're doing a case analysis on something. And, there's two cases - if it's Nothing, we give back Nothing, and if we get Just of some value x, then what we're going to do is we're going to process it in some way, we're going to apply some other function to x.

[00:10:37]So, this is the pattern which we've seen twice. In the first case, we had eval of x sitting here, and in the second case, we had eval of y sitting here, but this is the same pattern that we see two times in the new evaluator which we've just written. So, what we can do now, is abstract this out as a definition. And the idea here, is that we're going to give names to these boxes.

[00:10:57]So, this box is a Maybe value - it's going to be either Nothing or a Just, so we'll call it m. And this box is going to be a function, it's going process the result in the case we're successful, so we'll call this f. So, we can turn this picture here into a definition now, and then we can use it to make our program simpler. So, the definition we're going to have is, if we have some Maybe value, feeding into, or in sequence with, some function f. So, the operator we're defining here is this funny sequencing symbol, and we'll back to that in a second. What we're going to do, is a case analysis - we're going to look at what the Maybe value is - if it's Nothing, we'll give back Nothing, and if it's Just of x, we'll apply the function to it. Okay, so we'll just captured the pattern, which we've seen twice, by a definition now. So, we have some Maybe value, then, or in sequence with, some function f, and all we're going to do is look at what the value of the Maybe is - if it's failed, we'll fail, if it succeeds, we pass the result to the function f. It's just the idea of abstracting out a common pattern as a definition. So, now we can use this definition to make our program simpler. So, let's rewrite our evaluator once again. The type will remain the same - it takes in an expression as input, and it's going to give back a Maybe value, as before. But the definition is going to be a bit simpler this time. So, let's write down the skeleton. So, if we evaluate a value, we're going to do something. If we evaluate a division, we're going to do something. So, what do we write in the base case? Well, I could write Just of n here, but actually I'm going to abstract that as well - rather than writing Just of n, I'm going to write return of n, so really what I'm making is a little kind of side definition, that says return of x is the same as Just of x. And then, what are we doing in the division case? Well, we're going to do an evaluation first - we're going to evaluate x, and then if that's successful, using our little sequencing operator, we're going to feed the result into a function. So that function is going to take the result, n, that comes from evaluating that, and then it's going to evaluate y. So, if we do eval of y, if that's successful, we're going to feed that result into a function. And here again, I'm using the lambda notation, which we did a video about previously, you can have a look back at that. So, if these two things are both successful, we'll have two values, n and m, and then all we do is call safediv with them, then close the brackets. So, this program here is equivalent to the program which we wrote, which had all the nested case analyses. But, that's all been abstracted away now - it's all been kind of abstracted into return, and the sequencing, and safediv. So, this is a nicer program now, but still I'm not entirely happy with this. There's still some complexity in there - we're still using the funny lambda notation, we're still using this funny symbol, which we've introduced. Maybe I can make it even simpler? So, what a language like Haskell gives you, is a special notation for writing programs which have this kind of form. And this is called the do notation. So let me write this in do notation, and then we'll come back to what this has all got to do with monads.

[00:14:07]So, let's write this program in an even more simple form, and this will be our final program. We take an expression as input, and it's going to Maybe deliver us an integer. And the base case will not change, so we'll get return of n. But the recursive case is going to become a bit simpler, because we use the do notation as a shorthand for using the sequencing operator which we've introduced. So, I can say, if I evaluate a division, what I'm going to do, and this is the keyword, which just gives you a shorthand for exactly what we've just written, it's not anything special, it's just shorthand, just syntactic sugar. What we're going to do, is take the result n, from the result of evaluating x, if it's successful. Then, we'll take the result m, from the result of evaluating y, if that's successful. And then, we will call safediv. And this is our final program, and I'm much happier with this one. I mean, it looks kind of similar to the original program, a similar level of complexity, but all the failure management is now handled for us automatically. The failure is happening behind the scenes with the do notation, and with safediv, but we don't need to see that when we're reading this program. This is a much nicer program than the last one, because we've kind of abstracted away from a lot of the detail. So, you can look at a program like this, and I've hardly mentioned the word monads in the last ten minutes, you can say what's this actually got to do with monads? Well, what we've actually done, is we've rediscovered what's known as the Maybe monad. The Maybe monad is three things - it's the Maybe type, or really the Maybe type constructor, because it takes a parameter. So you can have Maybe of an integer, or maybe of a Boolean, or maybe of whatever you like. And then it's two functions - it's the function called return, and it's the sequencing operator which we introduced. And we can think about what are the types of these things? So what return does, is it takes a thing of any old type, a - could be an integer, could be a Boolean, could be whatever you like. And it converts it into a Maybe value. So, in our case, this just took an integer like five, and we return Just of five. Okay, so that's all the return was doing, it's basically just applying Just. And what it gives you, is a bridge between the pure world of values here, and the impure world of things that could go wrong - so it's a bridge from pure to impure, if you like. And what sequencing does, is it gives you a way of sequencing things - so you give it something which can fail, a Maybe a, and then you give it a function that tells you what to do with that a, if you succeed - so an a to Maybe b. And then, finally, what you're going to get back is a Maybe b. Okay, and this is all that a monad is essentially - a monad is some kind of type constructor, like Maybe, or List, or something else, as there's many other examples, together with two functions that have these types here. So, what we've essentially done is rediscovered what's called the Maybe monad. What's the point of all of this? I mean, what's the point?

[00:17:00]We seem to have gone through quite a lot of steps, to write in the end quite a simple program. What was the actual point here? So there's four points which I would like to emphasize here. So, the first point, is that the same idea we've seen works for other effects as well - it's not specific to Maybe, which captures failure. The same idea captures other kinds, or you can use with, other kinds of effects like input/output, like mutable state, like reading from environments, like writing to log files, non-determinism. All sorts of other things which you think of as being effects in programming languages fit exactly the same pattern. So, monads kind of give you a uniform framework for thinking about programming with effects. Another important point is that it supports pure programming with effects. I mean, Haskell is a pure language - functions just take inputs, and produce outputs, they don't have any kind of side effects at all. But you need to have side effects to write real programs. So, what monads give you is a way of doing impure things, like proper side effects, like input/output, in a pure programming language like Haskell. Another important point here, is that the use of the effects is explicit in the types.

[00:18:10]When I wrote the evaluator which didn't fail, it took an expression as input, and it delivered Maybe of an integer. So, the Maybe in the type is telling me that this program may fail. So, this is the idea of being explicit about what kind of effects, or side effects, that your programs can have in the types. And this is a very, very powerful idea. And the last thing is, it's a little bit strange, but it's particularly interesting, it's the idea of writing functions that work for any effect - we might call this kind of effect polymorphism. So, a simple example of this would be maybe you have a sequence of things, which can have some effects, and you want to run them all one after the other. You could write a generic function, in a language like Haskell which supports monads, which would take a sequence of effects of any kind, any monadic type, and it would run them for you. So this is a very, very powerful idea, and languages like Haskell have libraries of kind of generic effect functions, which are very useful. So, that's basically all I want to say. Just going back to the start, I think the idea of programming with monads is one of the most important developments in programming languages in the last 25 years - I find this particularly fascinating. We've only really touched on the surface here, and if you want to know a little bit more, I can do a bit of a plug - I have a new book which came out fairly recently, Programming in Haskell, and this has got a chapter specifically about this, which goes into much more detail. I've only really touched on the surface, there's lots of things I didn't say, which maybe you need to know to write real programs using this stuff. So, you could have a look in the book to find out more about that. This is an interesting point, it causes quite quite some problems for people learning languages like Haskell, because Haskell people tend to use the proper mathematical terms for things, and those terms are often quite foreign to programmers. And it does cause quite a lot of difficulty - so there's some people have the view that we shouldn't actually have used the term monad, maybe we should have called them effects, or something like that. So, just use the more kind of human, or a familiar term. But it is an issue. But I'm actually of the point of view that, if we know the proper term for something, we should call it that something, and the people who are using it should just learn that term.

[00:20:20]I mean, it's what it is, it's a monad, and we should kind of pay homage to the mathematicians for discovering this idea first, and not kind of reappropriate it as if it was discovered independently - the mathematicians discovered this, they should get credit for that, and so I'm quite happy with the word monad. But, it does cause some problems when people are learning programming languages, because it does sound a bit scary, and there's lots more scary terms like this in programming as well. This is all built into languages like Haskell. So, there's lots of libraries for programming with monadic things - you don't need to define a lot of the infrastructure, like Maybe, and return, and the sequencing, for yourself - this is kind of built in as libraries. You can define your own ones if you want to, but there's maybe kind of fifteen or twenty monads which are just lying around waiting for people to use. And if you want to use multiple different monads in your programs, maybe you need two different kinds of effects, maybe you need things that can fail, and you need some state, there's ways of coping with that kind of stuff as well. So, you don't need to do all yourself, it's mostly built in for you.