Like Lisp, there seems to be about 10% of the programmer population who think "ah this is obviously the clearest way to do it" and the remaining 90% who go "huh?", and the 10% are really bad at explaining it in a way the others can grasp.
The two monad explainers that really resonated with me were:
- How do you deal with state in a language that would prefer to be stateless? Answer: wrap the entire external universe and all its messy state up into an object, then pass that down a chain of functions which can return "universe, but with some bytes written to the network" (IO monad)
- If you have a set of objects with the same mutually pluggable connectors on both ends, you can daisy-chain them in any order like extension cables or toy train tracks.
(It's a joke, but people need to recognise why "A monad is just a monoid in the category of endofunctors" is a bad explanation 99% of the time and understand how to produce better explanations)
Grokking monads really requires the adoption of the mathematical mindset of finding commonalities in things that at a first glance appear completely different. Tell an average OO programmer that lists, exceptions, dependency injection, and asynchronous execution all share a common structure, and they will probably give you a blank stare.
Of course, just the fact that abstracting over those things is possible doesn’t mean it is useful. In a pure FP language it might be necessary, but why should I bother with weird mathy things in my imperative language that has side effects and global state? You really have to start by explaining why composability is such a nice thing to have, and that gives the motivation for various FP patterns that are, fundamentally, all about composability.
But then you start running into the nasty issue that when you need to compose multiple monads, you find out that monad transformers don't always commute!
There are good reasons, like encapsulation, etc. But the real reason is, it just dosn't feel right and there is this urge to fix it.
Once you have this feeling of obviousness, how do you transmit it to the next person? Many things can be explained, but in math it was figured out long ago that at any given time there are many things we don't know how to explain, and aren't sure we ever will be able to explain in a way that transmits understanding faster than experience can instill it. The best thing you can do for someone is give them the definitions and some problems to work on. We can't rule out that someone may eventually come up with a brilliant explanation that provides a shortcut to understanding, but we know from experience that some things persistently defy our efforts to explain them. If hundreds of people's earnest attempts to explain something have failed, then perhaps teachers should keep trying, but learners should not waste their time with these experiments; they should skip the explanations and seek active engagement with the idea through problem solving.
That's how I feel about monads. I can't absolutely rule out the possibility that someday an effective way to explain them will be found, but I think we can agree at this point that there is ample evidence that people who want to understand monads should not waste their time waiting for the right analogy to be blogged and posted on HN. They should just start programming, and soon enough they too will feel like a great explanation is on the tip of their tongue.
I have had this experience, that I've moved much faster learning to use math tools when a friend much more advanced than me suggested that I can use a tool even if I don't know how it works. It's like if I stopped building a house because I want to see if I can build a hammer myself !
(Well, this is also my experience programming, implementing the low level stuff myself is a much more attractive exercise than actually assembling off-the-shelf parts into something people would actually use!)
What I've observed is that a lot of learning programming is about becoming comfortable with thinking of more and more concepts as first-class entities. Turning larger pieces of code, procedure, and patterns into object/values you can pass around, hold, create, etc.
1. small-scale one I see a lot is that many programmers don't realize boolean expressions produce values. Instead, they think they are syntax that can only be used inside control flow statements. It is a mental leap to realize that you can go from:
if (thing == otherThing) { doStuff(); }
moreStuff();
if (thing == otherThing) { doLastStuff(); }
var sameThings = thing == otherThing;
if (sameThings) { doStuff(); }
moreStuff();
if (sameThings) { doLastStuff(); }
3. Closures are another big one where you take a piece of code and turn it into a value that you can delay executing, pass to other procedures, etc.
- They're explained badly.
- Once they're explained well, many (including me) think it's a bad idea (not the monad, the motivation behind its use in pure-FP).
You start with a pure functional formalism, because you like to be stateless. Then you realize that avoiding statefulness is impossible in computing. So you try to shoehorn state into your stateless state of affairs (no pun), while at the same time refusing to admit that you're not stateless anymore.
The larger issue: some folks appear to think that imperativity is a subset of declarativity.
What that really means is that, they're saying that, computing is a proper subset of math.
And by that, what they're really saying, is that actions are a subset of words.
In other words, if you write something on a piece of paper that describes some action in the real world, (roughly speaking) that action happens or is supposed to happen automatically.
That's now how the world works. That's not how computers work. And I'm sorry to say that's not how programming works.
Computing is not a subset of mathematics. And Mathematics is not a subset of Computing. Same goes with Physics (Physics is not a subset of Mathematics, despite there being way more math used in Physics than CS).
Physics, Computing, and Mathematics are the holy trinity of the reality that we live in. You have to give each of the three the respect they deserve, and only try to make connections between the three, and NOT try to make any of them a subset of the other.
if i understand you correctly, are you saying that mathematics in the classical sense is not “computing” (von neumann machines?), just as math is not physics, but math is used to model physics
then the proper way to think about the problem is: can there be a math that models actual computing (does that include physics?) as it is today, and is that what we already have in our programming languages today?
and finally, maybe your main point is, with purely functional languages, there is a math invented (lambda calculus?) to describe a stateless ideal that is shoehorned into a reality that it doesn’t describe?
apologies for the random thoughts, just trying to grok everything ^_^
When trying to map (or bind :) a monad to OOP/imperative programming, it strikes me as more straightforward to think that, e.g., the IO monad is an object that encapsulates the result of a network operation, together with some utility functions for dealing with the result and not having to deal with the unwrapping of the result. Kind of like Futures or Promises.
(Now, here the real FPers will say that the comparison is flawed because of certain FP desiderata like referential transparency, but that's beyond the extent to which I've internalized monads.)
But for many people, they will be used to IO returning nothing, or error values they can ignore. So the case has to be made as to why you need a monad there at all.
(I've just had the slightly disturbing realisation that C++ streams are also monads .. the documentation never uses this term.)
I think this also. You need to pick a language that fits your problem area, but also one that fits your brain.
Encapsulation? No one gets direct access to the state. Instead, there are methods or functions for dealing with the state indirectly, crafted to protect those outside.
Answer: wrap the entire external universe and all its messy state up into an object, then pass that down a chain of functions which can return "universe, but with some bytes written to the network" (IO monad)
Sounds like "Outside the Asylum" from the Hitchhiker's Guide to the Galaxy universe. Basically, someone decided the world had gone mad, so he constructed an inside-out house to be an asylum for it.
http://outside-the-asylum.net/
"A monad is a type that wraps an object of another type. There is no direct way to get that ‘inside’ object. Instead you ask the monad to act on it for you." How is a Monad anything different than a particular kind of object wrapper?
2) "A monad is a type that wraps an object of another type. There is no direct way to get that ‘inside’ object. Instead you ask the monad to act on it for you." Your objection to this quote is right, because the quote is wrong.
It _is_ a particular type of wrapper object. That's where the whole "in the category of endofunctors" comes in. An endofunctor being a functor from something to itself.
You have IEnumberable<SomeObject> and that lets you do SelectMany to flatmap some internal nested set of objects down to IEnumerable<SomeOtherObject>.
The shape of what you get back doesn't change. You get back an IEnumerable of something. That has a specific contract on which you can do specific operations regardless of the object it is wrapping.
The other piece of the puzzle is that it is monoidal. A monoid is just a collection of objects + a way of combining them + a 'no-op'. This is usually worded something like "a set of objects with an associative binary operator and an identity".
The classic definition "a monad is just a monoid in the category of endofunctors" is worth picking apart piece by piece. But it's also utterly useless because you have to spend quite awhile picking it apart and then looking at concretions of every one of the individual abstractions to understand what the hell each part individually looks like and then put it back together in your mind.
That definition is classically used as a joke because it's so terse you have no hope of understanding it without a lot of study, yet at the same time it's so precise it's all the information you need!
An object wrapper has to have the object somewhere in memory, you just can't touch it. With a monad, the object might not even exist yet (example: Promise) or there might be more than one (example: Collections).
So, the Adapter Pattern, but for types?
I think part of it is that lots of languages don't have sufficient abstraction ability to encapsulate the monad pattern in their type system, and those that do tend to be academic focused. That doesn't mean you can't (and do) use monads in the other languages, it's just that you can't describe the whole pattern in their type systems.
I was pretty sad that the discussion around javascript promises sidelined the monad pattern.
Off-putting to some working programmers. I am a mathematically-minded working programmer who prefers mathematical and type theoretical explanations quite strongly since they just click for me.
There is a cliche that no-one can write a good introduction to monads. I don't think that is true. My opinion is more that monads were so far from the average programmer's experience they could not grok them. I think as more people experience particular instances of monads (mostly Futures / Promises) the mystique will wear off and eventually they will be a widely known part of the programmer's toolkit. I've seen this happen already with other language constructs such as first-class functions. ("The future is here just not evenly distributed.")
Indeed, that is a big part of a problem.
I find "Functional Programming Jargon" [1] extremely approachable (if you already know modern JS) even though it has been pointed out that their definitions might not be "pure"/correct enough.
[1] https://github.com/hemanth/functional-programming-jargon#mon...
I think because languages like Java are evolving towards a world where those things are common, the average programmer is 'forced' to learn those concepts.
It’s important to emphasize that algebraic structures are abstractions or “interfaces” that let you reason with a small set of axioms, like proving stuff about all groups and writing functions polymorphic for all monads.
With monads in particular I think the pure/map/join presentation is great. First explain taking “a” to “m a” and “a -> b” to “m a -> m b” and then “m (m a)” to “m a”. The examples of IO, Maybe, and [a] are great.
You can also mention how JavaScript promises don’t work as monads because they have an implicit join semantics as a practical compromise.
The average programmer is much more likely to encounter monads (e.g. error handling, promises), than they are to encounter groups in an abstract context. Unnecessary maths will drive people away. Making a big deal of axioms, reasoning, and all this stuff that functional programmers love (including myself) is the approach that has been tried for the last 20 years, and it has failed to reach the mainstream. If you want to reach the average programmer you need to solve problems they care about in a language (both programming and natural) they understand.
Why not go all the way and teach functors and applicatives before monads? Then the student can see that monads are just a small addition built on top of the other two. Functors, in particular, are very easy to grasp despite their intimidating name. They just generalize map over arbitrary data structures:
l_double : List Int -> List Int
l_double xs = map (* 2) xs
f_double : Functor f => f Int -> f Int
f_double xs = map (* 2) xs
m_add : Maybe Int -> Maybe Int -> Maybe Int
m_add x y = case x of
Nothing => Nothing
Just x' => case y of
Nothing => Nothing
Just y' => Just (x' + y')
m_add' : Maybe Int -> Maybe Int -> Maybe Int
m_add' x y = [| x + y |]
[1] http://docs.idris-lang.org/en/latest/tutorial/interfaces.htm...
The Haskell formulation of applicatives doesn't make much sense outside of languages where currying is idiomatic---which is most languages. In these languages you tend to see the product / semigroupal formulation, and here applicatives become a bit trickier to explain as you need more machinery.
I think it’d be best to include examples in a number of languages with a lanugage selector, actually. That way, people who are fluent in functional languages can read that version, and others can read the one they are more fluent in.
The point is, functional languages are designed to express these concepts with much, much less cruft with extra features like currying, immutability-by-default, and type classes. Yes, use your current language to get oriented, but if you're going to really learn it, pick up a proper syntax to express it.
"A monad is a type that wraps an object of another type. There is no direct way to get that ‘inside’ object. Instead you ask the monad to act on it for you."
that you want to add some emphasis that the monad interface itself provides no way to reach in and get the innards out, but that does not prevent specific implementations of the monad interface from providing ways of getting the insides. Obviously, Maybe X lets you get the value out if there is one, for instance. This can at least be inferred from the rest of the content in the post, since it uses types that can clearly be extracted from. It is not a requirement of implementing the monad interface on a particular type/class/whatever that there be no way to reach inside and manipulate the contents.
But otherwise pretty good.
(I think this was commonly screwed up in Haskell discussions because the IO monad looms so large, and does have that characteristic where you can never simply extract the inside, give or take unsafe calls. People who end up coming away from these discussions with the impression that the monads literally never let you extract the values come away with the question "What's the use of such a thing then?", to which the correct answer is indeed, yes, that's pretty useless. However, specific implementations always have some way of getting values out, be it via IO in the case of IO, direct querying in the case of List/Maybe/Option/Either, or other fancy things in the fancier implementations like STM. Controlling the extraction is generally how they implement their guarantees, if any, like for IO and STM.)
Here's a recent talk I gave on the subject: https://youtu.be/r6P0_FDr53Q
Monads let you break the functional programming paradigm that a function should have the same value each time it is called. e.g.
do {
x <- getInput
y <- getInput
return x+y }
The heureka moment came when I learned about the flatMap in scala which is nothing else but the bind function in haskell ("just flatmap that sXXt") and voila thats how to use monads.
See the following explanation:
https://medium.com/free-code-camp/demystifying-the-monad-in-...
I still have a rudimentary understanding of functional programming (apart from the canonical "it's just an implementation of lambda calculus"). And I have to say that without exercise and training one grabs at wisps and mist. In mathematics it's also like this, you often have your favorite prototypical monad, adjunction, group, set, etc. (e.g.: The adjunction Set->Set^op by powerset is a strong contender.) And I view axiomatic systems in essence as sort of list of computational rules (e.g.: transitive closure).
I haven't found some idiosyncratic project to code in Haskell yet though...
However an optional is really just a list constrained to size 0 or 1. And a future is often called "not truly a monad."
So I question the value of explaining this abstraction in great detail over so many articles when people struggle to come up with more than 1 concrete example of it (Lists), an example that engineers have already understood since our first month coding.
Maybe somebody can speak to this more.
One monad that I occasionally use is something I'll call "Tracked". For "return" (when we make a new instance of the monad) we store a pair (initialValue, initialValue). For "bind" (when we act on what's in the monad) we only ever touch the second value in the pair, returning (initialValue, transformedValue).
That way, you can know where this piece of data came from. I've gotten a lot of mileage out of Tracked<Result<T>>: when one of your Results is an exception, then you can check what piece of data ended up triggering that exception. Yes, you could do this without the Tracked monad, but doing it monadically means that most of your functions don't need to know or care about tracking the initial data; you can just Apply those simpler functions and the Tracked instance will do it for you.
I think you've misunderstood this observation. It is possible to write a future library that gives a monad (I use such a library regularly). But the most common ones do not, because it happens to be a decent design decision in dynamically-typed languages to not quite obey the monad equations.
The next interesting monad is probably Haskell's Either (or OCaml's Result, if you're into that). It is only a slight twist on the optional monad. Where optional's None case contains no data, Either's Left case can contain data.
After the collections (list and optional), either, and future monads, the difficulty to understand useful monads without first understanding the category of monads jumps considerably. If you're interested, the next ones to look at would be the reader, writer, state, and continuation monads. There's also the classic example from Haskell, the IO monad.
If you've learned from the assembly end of programming upwards, it can be very hard to see the need for them at all.
True, but you've only written about them as data types, which misses the monadic part. What makes them monads is that you can join any Optional<Optional<T>> into an Optional<T>. Likewise you can join a List<List<T>> into a List<T>. It is that principled 'smooshing down' of the data types that makes them monads.
What?
More concretely, "an optional" is something that either 'has a value' or 'does NOT have a value'. So it "is really just a list constrained to size 0 or 1" in the sense that an optional that 'does NOT have a value' is equivalent to a list of size 0, i.e. a list with no contents/members, and an optional that DOES 'have a value' is equivalent to a list of size 1, i.e. it's 'value' is the single/unique member of the list.
Think of statements like 'is really just' in the sense that an integer between 0 and 255 'is really just' 8 ordered bits – they're 'equivalent' in the sense that you can map all possible values of those integers to all possible values of 8 ordered bits, and vice versa, and (importantly in a mathematical sense) in a way such that every integer is mapped to a single set of 8 ordered bit values and every set of 8 ordered bit values is mapped to a single integer. In mathematics that's often described as an 'isomorphism' which is, in working programmer terminology, just a way to convert back and forth between two sets of values 'perfectly and losslessly'.
And of course the list is constrained to not contain more than a single entry.
http://adit.io/posts/2013-04-17-functors,_applicatives,_and_...
It's somewhat more than a monad explanation -- it covers functors and applicatives, and is somewhat haskell specific, but it was one of the guides that really clicked for me when I was trying to grok monads
[0]: http://james-iry.blogspot.com/2009/05/brief-incomplete-and-m..., 1990 Haskell entry