A Technically Inaccurate Explanation of Monads

I’ve come across a multitude of technically inaccurate explanations of monads on the web, all intending to explain them in simple terms to FP newbies, most revolving around their use in Haskell. They all suck. This is mine. It also sucks, but I hope it sucks less.

[NOTE: I have no intent here to explain the mathematical concept of monads, the semantic gap between the way the term is used in set theory and in some flavors of functional programming, or any of that high-minded magic. My purpose is to explain what a monad is in terms of a computing utility to a functional programmer. This is a discussion about the sort of tool it is, not the theory behind that tool.]

Imagine using a purely functional language where side effects are verboten and we can’t do IO or anything else useful because of this. The host environment can clearly do IO just fine, otherwise our environment couldn’t do things like read memory locations (or our code) and our program would be useless. So it is obvious the host environment can do things externally that our program itself cannot do directly. This does not prevent us from describing what we wish it would do on behalf of our program, however.

In this way the host environment is sort of like a pantheon of gods and our programs are mere mortal blips of disembodied consciousness — capable of thought, desire and expression but powerless to touch the physical world in any way. All we can do is express our desires as regard the results of our thoughts and appeal to the gods to pity us and take action in accordance with our desires. Whether they take actions on our behalf is entirely up to them.*

With this in mind…
Imagine a function written in SomeLanguage:

int f(x): return x

It takes an integer and returns an integer. So what? The system doesn’t do anything with it so it is practically useless.

Now imagine a wrapper function:

tuple w(int x):
    tuple t = (f(x), "Please put this in STDOUT")
    return t

So w() has taken the output of f() and wrapped it in a tuple that contains the value returned by f() and a prayer to the system gods to “Please put this in STDOUT”. Pretty straight forward. Now the system gods can do whatever they want with it, but our language itself can’t — because talking to STDOUT would be a side effect and that’s strictly forbidden on Planet Functon. What we can do, however, is pray that the gods take mercy on us and act according to our wishes as regard the value that accompanies the prayer.

If this is the best model of a monad you can muster at the moment, then just stop here. This model is sufficient to make the concept of monads useful to you as you write programs that do useful work. (Which is the whole point. Unless you’re an academic, in which case your point is to write a lengthy article in a peer reviewed journal in which your explanation of monads is prefaced with a demonstration of your deep knowledge of set theory and type theory and esoteric discussion of things like monoids and thus make it appear that unfamiliarity with these subjects precludes the ability to use monads in a useful way in functional programs.)

But there are a few unresolved issues above, most of which I won’t address below, but the glaring issue of typing is relevant… (The other glaring issue of the undefined and imaginary syntax of SomeLanguage won’t be addressed at all.)

The type tuple is pretty ambiguous for this use (we could be talking about coordinates or relational values or immutable strings or whatever). How are the gods to know that we have a prayer for them? Should they inspect every tuple, or even every value we dream up, just checking for a “prayer” type? Of course not, they are busy doing immaculate things. We need a more clear signal.

One way to clear this up is to make a function that takes a function, its arguments and a request specification and returns a type prayer whose existence is itself a magical signal to get the attention of the gods. So ultimately a prayer is a type whose definition is a combined value composed of a thingy plus a prayer request regarding that thingy:

prayer p(function z, list l, request r):
    return (z(*l), r())

And then define an action of type request and rewrite w() in a way that returns a prayer:

request q = "Print to STDOUT"

prayer w(int x):
    return p(f, x, q)

Here we have defined a request for the system to perform, passed a reference/pointer/label to the function f() along with its arguments to the prayer maker function p(), which has executed f() along with its argument and returned a bundle of type prayer that contains the original integer return value along with a request to the system gods to do something regarding the bundled value.

Note that in Haskell it is common to define the underlying function (represented here by f()) and its monadic version (represented here as w()) separately. I suppose this isn’t strictly necessary — one could define monads in terms of lambdas — but this is the way things are done.

So we have specified a side effect, but we are only praying that the system takes an action based on our specification. Nothing more. Obviously I’m glossing over the details of how a request object itself is actually defined, but this is the general idea behind how monads are used to write programs in purely functional languages that have side effects.

An interesting consequence of this idea of a program specifying actions instead of actually taking them is that it is now trivial to write a host environment that deliberately ignores all prayers. In this way writing a host environment purely for the purpose of examining the behavior is also trivial. Its the ultimate sandboxing tool. It is equally easy to write a host environment that selectively observes requests, taking only some and ignoring all others, or ignoring some and taking all others.

I believe the abundance of confusing monad explanations to be a side effect of the Haskell community being disproportionately populated with mathematicians, type theorists and set theorists (“for real” or self-educated) and their explanations assume a knowledge base and vocabulary that is foreign and intimidating to most newcomers. The Clojure community doesn’t seem to have this problem, at least not as deeply.

[*It is easy to reverse this metaphor, of course, and imagine that we are uncorporeal gods, capable of thought and expression of our command to the slavish host to do whatever we specify. But I like the “program as mortals, host as gods” way better, because it extends to include the very real case of writing a test host that takes no action and merely observes (or even checks for the correctness of) the program’s behavior.]

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