A survival guide to the Either monad in Scala

I started to work with Scala few months ago. One of the concepts that I had the most difficulties to understand is the Either monad. So, I decided to play around with it and better understand its power.

In this story I share what I’ve learned, hoping to help coders approaching this beautiful language.

The Either monad

Either is one of the most useful monads in Scala. If you are wondering what a monad is, well… I cannot go into the details here, maybe in a future story!

Imagine Either like a box containing a computation. You work inside this box, until you decide to get the result out of it.

In this specific case, our Either box can have two “forms”. It can be ( Either ) a Left or a Right , depending on the result of the computation inside it.

I can hear you asking: “OK, and what is it useful for?”

The usual answer is: error handling.

We can put a computation in the Either , and make it a Left in case of errors, or a Right containing a result in case of success. The use of Left for errors, and Right for success is a convention. Let’s understand this with some code!

In this snippet we are only defining an Either variable.

We can define it as a Right containing a valid value, or as Left containing an error. We also have a computation that return an Either , meaning it can be a Left or a Right . Simple, isn’t it?

Right and Left projection

Once we have the computation in the box, we may want to get the value out of it. I’m sure you expect to call a .get on the Either and extract your result.

That’s not so simple.

Think about it: you put your computation in the Either , but you don’t know if it resulted in a Left or a Right . So what should a .get call return? The error, or the value?

This is why to get the result you should make an assumption about the outcome of the computation.

Here is where the projection comes into play.

Starting from an Either , you can get a RightProjection or a LeftProjection . The former means that you assume the computation resulted in a Right , the latter in a Left .

I know, I know… this may be a little confusing. It’s better to understand it with some code. After all, code always tells the truth.

That’s it. Note that when you try to get the result from a RightProjection , but it is a Left , you get an exception. The same goes for a LeftProjection and you have a Right .

The cool thing is that you can map on projections. This means you can say: “assume it is a Right : do this with it”, leaving the Left unchanged (and the other way around).

From Option to Either

Option is another common way to deal with invalid values.

An Option can have a value or be empty (it’s value is Nothing ). I bet you noticed a similarity with Either … It’s even better, because we can actually transform an Option into an Either ! Code time!

It is possible to transform an Option to a Left or a Right . The resulting side of the Either will contain the value of the Option if it is defined. Cool. Wait a minute… What if the Option is empty? We get the other side, but we need to specify what we expect to find in it.

Inside out

Either is magic, we all agree on that. So we decide to use it for our uncertain computations. A typical scenario when doing functional programming is the mapping a function on a List of elements, or on a Map . Let’s do it with our fresh new Either -powered computation…

Huston, we have a “problem” (ok, it’s not a BIG problem, but it is a bit uncomfortable). It would be better to have the collection inside the Either than lots of Either inside the collection. We can work on that.

List

Let’s start with List . First we reason about it, then we can play with code.

We have to extract the value from the Either , put it in the List , and put the list inside an Either . Good, I like it.

The point is that we can have a Left or a Right , so we need to handle both cases. Until we find a Right , we can put its value inside a new List . We proceed this way accumulating every value in the new List .

Eventually we will reach the end of the List of Either , meaning we have a new List containing all the values. We can pack it in a Right and we are done. This was the case where our computation didn’t return an Error inside a Left .

If this happens, it means that something went wrong in our computation, so we can return the Left with the Error . We have the logic, now we need the code.

Map

The work on Map is quite simple once we have done the homework for the List (despite needing to make it generic):

Step one: transform the Map in a List of Either containing the tuple (key, value) .

in a of containing the tuple . Step two: pass the result to the function we defined on List .

. Step three: transform the List of tuples inside the Either in a Map .

Easy Peasy.

Let’s get classy: a useful implicit converter

We introduced Either and understood it is useful for error handling. We played a bit with projections. We saw how to pass from an Option to an Either . We also implemented some useful functions to “extract” Either from List and Map . So far so good.

I would like to conclude our journey in the Either monad going a little bit further. The utility functions we defined do their jobs, but I feel like something is missing…

It would be amazing to do our conversion directly on the collection. We would have something like myList.toEitherList or myMap.toEitherMap . More or less like what we do with Option.toRight or Option.toLeft .

Good news: we can do it using implicit classes!

Using implicit classes in Scala lets us extend the capabilities of another class.

In our case, we extend the capability of List and Map to automagically “extract” the Either . The implementation of the conversion is the same we defined before. The only difference is that now we make it generic. Isn’t Scala awesome?

Since this can be a useful utility class, I prepared for you a gist you can copy and paste with ease.

object EitherConverter { implicit class EitherList[E, A](le: List[Either[E, A]]){ def toEitherList: Either[E, List[A]] = { def helper(list: List[Either[E, A]], acc: List[A]): Either[E, List[A]] = list match { case Nil => Right(acc) case x::xs => x match { case Left(e) => Left(e) case Right(v) => helper(xs, acc :+ v) } } helper(le, Nil) } } implicit class EitherMap[K, V, E](me: Map[K, Either[E, V]]) { def toEitherMap: Either[E, Map[K, V]] = me.map{ case (k, Right(v)) => Right(k, v) case (_, e) => e }.toList.toEitherList.map(l => l.asInstanceOf[List[(K, V)]].toMap) } }

Conclusion

That’s all folks. I hope this short story may help you to better understand the Either monad.

Please note that my implementation is quite simple. I bet there are more complex and elegant ways to do the same thing. I’m a newbie in Scala and I like to KISS, so I prefer readability over (elegant) complexity.

If you have a better solution, especially for the utility class, I will be happy to see it and learn something new! :-)