Set, similarly to [] has a perfectly defined monadic operations. The problem is that they require that the values satisfy Ord constraint, and so it's impossible to define return and >>= without any constraints. The same problem applies to many other data structures that require some kind of constraints on possible values.
The standard trick (suggested to me in a haskell-cafe post) is to wrap Set into the continuation monad. ContT doesn't care if the underlying type functor has any constraints. The constraints become only needed when wrapping/unwrapping Sets into/from continuations:
import Control.Monad.Cont
import Data.Foldable (foldrM)
import Data.Set
setReturn :: a -> Set a
setReturn = singleton
setBind :: (Ord b) => Set a -> (a -> Set b) -> Set b
setBind set f = foldl' (\s -> union s . f) empty set
type SetM r a = ContT r Set a
fromSet :: (Ord r) => Set a -> SetM r a
fromSet = ContT . setBind
toSet :: SetM r r -> Set r
toSet c = runContT c setReturn
This works as needed. For example, we can simulate a non-deterministic function that either increases its argument by 1 or leaves it intact:
step :: (Ord r) => Int -> SetM r Int
step i = fromSet $ fromList [i, i + 1]
-- repeated application of step:
stepN :: Int -> Int -> Set Int
stepN times start = toSet $ foldrM ($) start (replicate times step)
Indeed, stepN 5 0 yields fromList [0,1,2,3,4,5]. If we used [] monad instead, we would get
[0,1,1,2,1,2,2,3,1,2,2,3,2,3,3,4,1,2,2,3,2,3,3,4,2,3,3,4,3,4,4,5]
instead.
The problem is efficiency. If we call stepN 20 0 the output takes a few seconds and stepN 30 0 doesn't finish within a reasonable amount of time. It turns out that all Set.union operations are performed at the end, instead of performing them after each monadic computation. The result is that exponentially many Sets are constructed and unioned only at the end, which is unacceptable for most tasks.
Is there any way around it, to make this construction efficient? I tried but without success.
(I even suspect that there could be some kinds of theoretical limits following from Curry-Howard isomorphism and Glivenko's theorem. Glivenko's theorem says that for any propositional tautology φ the formula ¬¬φ can be proved in intuitionistic logic. However, I suspect that the length of the proof (in normal form) can be exponentially long. So, perhaps, there could be cases when wrapping a computation into the continuation monad will make it exponentially longer?)
Monads are one particular way of structuring and sequencing computations. The bind of a monad cannot magically restructure your computation so as to happen in a more efficient way. There are two problems with the way you structure your computation.
When evaluating stepN 20 0, the result of step 0 will be computed 20 times. This is because each step of the computation produces 0 as one alternative, which is then fed to the next step, which also produces 0 as alternative, and so on...
Perhaps a bit of memoization here can help.
A much bigger problem is the effect of ContT on the structure of your computation. With a bit of equational reasoning, expanding out the result of replicate 20 step, the definition of foldrM and simplifying as many times as necessary, we can see that stepN 20 0 is equivalent to:
(...(return 0 >>= step) >>= step) >>= step) >>= ...)
All parentheses of this expression associate to the left. That's great, because it means that the RHS of each occurrence of (>>=) is an elementary computation, namely step, rather than a composed one. However, zooming in on the definition of (>>=) for ContT,
m >>= k = ContT $ \c -> runContT m (\a -> runContT (k a) c)
we see that when evaluating a chain of (>>=) associating to the left, each bind will push a new computation onto the current continuation c. To illustrate what is going on, we can use again a bit of equational reasoning, expanding out this definition for (>>=) and the definition for runContT, and simplifying, yielding:
setReturn 0 `setBind`
(\x1 -> step x1 `setBind`
(\x2 -> step x2 `setBind` (\x3 -> ...)...)
Now, for each occurrence of setBind, let's ask ourselves what the RHS argument is. For the leftmost occurrence, the RHS argument is the whole rest of the computation after setReturn 0. For the second occurrence, it's everything after step x1, etc. Let's zoom in to the definition of setBind:
setBind set f = foldl' (\s -> union s . f) empty set
Here f represents all the rest of the computation, everything on the right hand side of an occurrence of setBind. That means that at each step, we are capturing the rest of the computation as f, and applying f as many times as there are elements in set. The computations are not elementary as before, but rather composed, and these computations will be duplicated many times.
The crux of the problem is that the ContT monad transformer is transforming the initial structure of the computation, which you meant as a left associative chain of setBind's, into a computation with a different structure, ie a right associative chain. This is after all perfectly fine, because one of the monad laws says that, for every m, f and g we have
(m >>= f) >>= g = m >>= (\x -> f x >>= g)
However, the monad laws do not impose that the complexity remain the same on each side of the equations of each law. And indeed, in this case, the left associative way of structuring this computation is a lot more efficient. The left associative chain of setBind's evaluates in no time, because only elementary subcomputations are duplicated.
It turns out that other solutions shoehorning Set into a monad also suffer from the same problem. In particular, the set-monad package, yields similar runtimes. The reason being, that it too, rewrites left associative expressions into right associative ones.
I think you have put the finger on a very important yet rather subtle problem with insisting that Set obeys a Monad interface. And I don't think it can be solved. The problem is that the type of the bind of a monad needs to be
(>>=) :: m a -> (a -> m b) -> m b
ie no class constraint allowed on either a or b. That means that we cannot nest binds on the left, without first invoking the monad laws to rewrite into a right associative chain. Here's why: given (m >>= f) >>= g, the type of the computation (m >>= f) is of the form m b. A value of the computation (m >>= f) is of type b. But because we can't hang any class constraint onto the type variable b, we can't know that the value we got satisfies an Ord constraint, and therefore cannot use this value as the element of a set on which we want to be able to compute union's.