Coding in Haskell: a new adventure

, 1716 words

I was reading Gregory Gunderson’s blog post “Why I keep a research blog”1 while, at the same time, writing an exciting new project in Haskell which made me think it would be quite fun to document the process of learning to make something real-ish in a completely new language.

I have not programmed in a pure, functional language like Haskell since we were forced to learn Standard ML in my first year at Cambridge, but I have toyed with the idea of writing in Haskell for some time, attracted by the mathematical style of expression, the strong type system, and a general love of applying many of the principles of functional programming in languages that are not purely functional like Javascript (which makes it fairly easy).

I first tried my hand at this when I was playing with the Advent of Code 2019 challenge. Unfortunately, I did not really have much time for it, and I was not particularly inspired by doing the challenges while also learning a new language, and entire paradigm of programming.

When it came to this new project (about which I will write separately), however, I was fairly settled in my mind that I would at least attempt it in Haskell rather than Python or Javascript (which would have been my go-to languages for toys like this).

Growing up.

I have been programming for most of my life, but when I was younger I was somewhat enamoured of object oriented programming. I liked structure, and I found the ability to create endlessly complex frameworks and hierarchies of objects gave me a sense of power and allowed me to show how “clever” I was. At the time, I had not really been exposed to any functional programming, but had certainly spent a lot of time building things. When we were made to use Standard ML at University, I found this new way of doing things quite painful and frustrating. I wanted to build systems, but ML restricted the sorts of functions I could write, and I could not see a way out of this restriction, even while I appreciated the mathematical style of the language.

Fast forward a few years, and I found myself increasingly preferring “simple” solutions to problems, and appreciating a more functional approach to programming. This drove a brief foray into clojure which I enjoyed but never ended up taking very far.

This post is a collection of my first impressions of Haskell, what I have liked, and what I have not.

Some of the annoyances

Stack, Cabal, and the toolchain

Working out how to get going with Haskell took me some time. It was not really clear what the best way of starting a project was, how I could install dependencies, etc.. By contract, the Rust project is very opinionated on this, officially, and points you in the direction of Cargo. Cargo seems to have learnt all the lessons of npm and is exceptionally easy to use.

I have still have been unable to get the Haskell IDE Engine to work properly with COC and NeoVim despite following instructions. As a result, and form of intelligent autocompletion, etc., have gone out the window.

Once I settled on using stack to manage my Haskell projects, a lot of this became easier, but it was not obvious to a beginner that stack was the way to go.

Cryptic compiler errors

The amazing thing about learning Rust is that the compiler is very helpful, and often makes it obvious exactly how to go about fixing your problems. It references help articles and gives suggestions. When one starts out learning a language, one has not yet developed the instinct for the sorts of things for which one should be looking out, and so even very simple errors can be extremely difficult to debug.

Haskell’s compiler gives terrible errors, and most often I am just left with parse error and not much more to work out. It is true that sometimes the type errors can be very helpful as they make it clear where things have gone wrong, but I have spent an inordinate amount of time trying to work out how to make a cryptic parse error go away.

Sometimes this is an indentation problem (it would be nice to have a separate class of error for this), and sometimes I have misunderstood some syntax or the proper way to achieve something. The cryptic errors just make it harder to find one’s way.

Accessing the properties of records

This is something that just feels inexcusably wrong in Haskell. If I were to have a data record defined and initialised as follows:

data Person = Person { name :: String
                     , age :: Integer
me :: Person
me = Person { name="Gideon", age=29 }

In most languages one would access those properties using something like the dot operator (or some other infix to denote the hierarchy of class → property). For example in Javascript or Python, one would write In Haskell, however, the property accessors become functions at the module level, which means they have to be explicitly imported and exported. Therefore in my example above, name actually becomes a function with the signature name :: Person -> String, and is accessed by writing name me.

As several people have noted, this creates problems with namespacing, and is just generally somewhat irritating as one often has to remember to explicitly import and export these property accessor functions.

What I have loved so far

The type system

Haskell’s type system is great. There is no doubt that I have barely scratched the surface of what it unlocks, but so far I have really enjoyed working with it.

One of the ways it stands out is the way in which one declares how certain classes work with new types. In many languages, if you wanted to declare an interface for dealing with equality (==, /=, etc.), you would have to do this in the equality interface itself. Not so for Haskell, for example my Agent record type should consider equality only on the name property, so I do the following:

type AgentID = Integer
data Agent = Agent { name :: AgentID
                   , generosity :: Double
                   , selfishness :: Double
                   , score :: Double
                   } deriving Show

instance Eq Agent where
  (==) a b = name a == name b
  (/=) a b = name a /= name b

Now, anywhere a function has a constraint on a type that requires Eq a, my Agent type is suddenly compatible. Comparing this to the verbosity I found in Rust for doing something similar I much prefer the Haskell way.

Cognitive load up front

The thing I like best about writing in Haskell is that it forces me to break down problems, and makes it quite difficult to write big, sprawling functions. Single-purpose functions, separation of concerns, and pure functions with immutable data structures are all principles to which I adhere (and which I have instilled in my engineering team), but when writing a new project it is often easy to be a little lazy to try to get it done “quickly”. In reality, this approach is much slower, as the functions and structures quickly sprawl and become confusing. In Haskell, one is nearly forced to create small functions which have clearly defined purposes, often obvious from their signatures.

For example, the following code took me a long time to work out how to write, but the writing itself was very fast. Haskell is forcing me to do the cognitive work up front, and to work at a higher level of abstraction. One of the most notable results of this is that, most of the time, I find that my tests just work with the first version of my implementation that compiles.

-- Given a Reactor function, this acts on a list of InteractionHistories
-- and interacts each agent with each other agent, providing the next
-- iteration of the InteractionHistories.
interactAll :: Reactor -> [InteractionHistory] -> IO [InteractionHistory]
interactAll react histories = interactAll' histories
  where interactAll' :: [InteractionHistory] -> IO [InteractionHistory]
        interactAll' []           = return []
        interactAll' ((me, _):hs) = do
          new_histories  <- sequence [ interactionFactory react me x
                                     | x <- histories, fst x /= me
          tail_histories <- interactAll' hs
          return ((me, new_histories) : tail_histories)

My working method has started to become:

  1. Work out what the function signature should be.
  2. Write a dummy implementation so it compiles.
  3. Write tests.
  4. Work out the implementation.
  5. Tests pass, move on.

Which is basically TDD, but the nice part is that Haskell is just naturally forcing this way of working. It makes you think about the contracts your functions fulfil before you write the implementation, partly because the way such a purely functional language works makes it hard to make those functions sprawl.

Hspec and testing

The Javascript testing landscape is probably nonpareil. There is a large number of options, with very flexible test runners (like mocha and jest), expressive assertion libraries (like chai), and lots of smaller libraries for making it easy to write assertions for whatever libraries and frameworks you are using to write applications. As such, I think the Javascript ecosystem is probably impossible to beat in this regard (although I do not have experience with the ruby ecosystem, the python ecosystem is not nearly as replete).

Hspec feels, by contrast, to be a fairly basic framework for writing tests in Haskell, but I was surprised at how easy I found it to get started, and I was writing tests from the beginning of my project. I did not have to fight with it at all, and the syntax was fairly similar to the unit-testing frameworks I was used to (describe, it, shouldBe).

Monads: IO and Maybe

One of the things I have really loved about Haskell was the use of Monads to encapsulate things like uncertainty and side-effects. This means that I can encapsulate things in the type system that I could not otherwise encapsulate except by using a lot of guards and checks in the codebase itself.

The Maybe monad is a very powerful way of encapsulating something that may or may not have a value. For example, I have the following function which finds interactions between agents. The problem is that there is no guarantee that these agents have previously interacted. In some languages we would cope with this by returning null, or None, but in these loosely typed languages (Javascript and Python respectively) we always have to remember to check the value of the result. With the Maybe monad, we can make these checks explicit in the type signature, and therefore avoid some silly errors.

findMyInteractions :: AgentID -> [Interaction] -> [Interaction]
findMyInteractions me = filter (\ (Interaction a b _ _) -> (a==me) || (b==me))

findInteraction :: AgentID -> AgentID -> [Interaction] -> Maybe Interaction
findInteraction a b interactions =
  let found = findMyInteractions a . findMyInteractions b $ interactions
  in case length found of 0 -> Nothing
                          _ -> Just (head found)

Similarly, the IO monad is a great way of encapsulating side effects. My programme deals a lot with random numbers as a way of generating probabilistic responses. Randomness, however, is not a pure operation as you can obtain different results with the same input. The IO monad ensures that anything which is affected by this impurity is explicitly acknowledged as such, making it much clearer when one is dealing with pure functions and when one is not.

  1. Gundersen, G., “Why I keep a research blog” (retrieved 2020-02-02)↩︎