Error handling resources for Haskell


I’m very interesting in error handling. It is such an important topic in programming. It’s complicated, difficult, but the only way to go for writing correct software.

This subject is still not solved in the Haskell world. There are a lot of different ways to handle errors and it is also very controversial.

This post is a collection of the different approaches I stubbled upon.

Pure code

On the most basic level, let’s say in pure code to be simple (i.e. non monadic code), the subject is not controversial. People usually agree on not to throw any Exception and use Maybe as the return type when the function has only one way to fail or Either when it has more than one.

Monadic code

This is a complete different story in monadic code. There are basically two camps here:

  • the one in favour of exceptions
  • the other in favour of errors appearing in the function signature, sometimes called “checked exceptions” because the compiler checks that the exceptions are handled by the developer

I won’t go into the details of the two camps here, arguments of both sides are pretty well explained in the following posts.

Let’s first have a look at what is an Exception in Haskell. The following post contains the most comprehensive description of the different types of exceptions that I have read so far. So it is an interesting read:

The three kinds of Haskell exceptions and how to use them

The authoritative

When I started getting interested in Haskell, the learning material produced by FP Complete was hugely valuable. Honestly, I’m not sure I would have been able to make my way into the functional programming world without it. So I’ll be always very grateful to them for producing such good documentation.

Among the material they produced, there are posts about exceptions and error handling:

When I discovered that what I recognized to be the most authoritative source of Haskell good practices were advocating for the use of exceptions for error handling instead of trying to track errors in the type system, I have to say that this was a huge disappointment for me.

I have some experience about this approach in C++ and Python and I know how easy it is to forget about handling exceptions. It’s not too bad to do it right when you work alone and on the first code iteration. In this case, it’s easy to keep track of the control flow defined by exceptions in your head. But when the code needs evolutions or refactoring, there is chance close to 100% that you forget to handle correctly the errors that needs to be handled.

But anyway, I wanted to learn Haskell so bad and if it was the way to go I would give it a try. Later I learned that there are alternative ways to handle errors in Haskell.

I have followed this approach in my main project hscalendar. My feedback is: yes it is easy to write and yes it is easy to forget about it. I wasn’t very surprised by the developer experience here. So if you decide to go that way I would recommend to write down somewhere the different exceptions that you can think about during the development and for each of them write tests to make sure they are properly handled.

Purity with ExceptT

Other people do want to track errors on the type level, this is the case for the author of this post:

What do you mean ExceptT doesn’t Compose?

In his example, he makes use of the package errors. Another package called transformers-except also offers pretty good combinators to handle errors in ExceptT.

Going through the related reddit discussion and you can see how controversial this subject is.

I did use this approach for error handling in a small project of mine: bigball. I can say that it feels good to be reminded by the compiler to do something with errors. Of course not all the errors are handled in this code. But at least, all the obvious ones are and this is good enough for me.

Doing so, I kind of understood the statement “it doesn’t compose”. It’s not that it doesn’t but it is actually true that “it doesn’t easily compose”. But in a sense it is not surprising either because it adds another layer of thinking when you develop. You have to think about what needs to be done in case of an error and this is usually pretty complex.

Other posts of people following this approach:

Making it easy to compose

The fact that this approach does not easily compose is viewed by some people as an ergonomic problem. Some special syntax needs to be defined to compose functions that might returns errors. That is what is done in Rust with great success so it should be possible to do it in Haskell as well.

Matt Parson and Chris Done, two well known members of the Haskell community are following this way. These guys are trying really hard to find an ergonomic way to handle errors on the type level.

Matt Parson

Matt Parson has written numerous posts about this subject:

The library that came out of this idea: plucky

He also made a pretty complete and well explained video about this subject at lambda conf 2018.

I greatly appreciate his honesty in the part about the so called “good practices” that he presented as “some guy opinion”.

Other libraries based on open variants:

Chris Done

When QualifiedDo was introduced in GHC 9.0.1, Chris Done saw it as an opportunity to address this ergonomic issue.

This list of posts is pretty well summarized by Gabriel Gonzales in this tweet:

The great people of Kowainik are also trying to follow the QualifiedDo path with this library:

IO with Exceptions tracked on the type-level

Other resources

Here are some other links related to the subject:


That story doesn’t end up here and I’m sure there will be in the future a lot of work done in this area. I’ll keep this page up to date as new ideas pops out and I hope that a consensus will be found in the near future so a lot more people will start using the same idiom for error handling. As a result it will bring consistency to the ecosystem and raise approachability for new comers.

As for me, I’m currently sold to the camp of checked exceptions. That doesn’t mean I’ll never change my mind. I’d like to use some of these approaches to confront them to real world problems and see how they scale.

April 11, 2021