Monads in Haskell can be thought of as composable computation descriptions. The essence of monad is thus separation of composition timeline from the composed computation's execution timeline, as well as the ability of computation to implicitly carry extra data, as pertaining to the computation itself, in addition to its one (hence the name) output, that it will produce when run (or queried, or called upon). This lends monads to supplementing pure calculations with features like I/O, common environment or state, etc.
Each monad, or computation type, provides means, subject to Monad Laws, to (a) create a description of computation action that will produce (a.k.a. "return") a given Haskell value, (b) somehow run a computation action description (possibly getting its output back into Haskell should the monad choose to allow it, if computations described by the monad are pure, or causing the prescribed side effects if it's not), and (c) combine (a.k.a. "bind") a computation action description with a reaction to it – a regular Haskell function of one argument (that will receive computation-produced value) returning another action description (using or dependent on that value, if need be) – thus creating a combined computation action description that will feed the original action's output through the reaction while automatically taking care of the particulars of the computational process itself. A monad might also define additional primitives to provide access to and/or enable manipulation of data it implicitly carries, specific to its nature.
Thus in Haskell, though it is a purely-functional language, side effects that will be performed by a computation can be dealt with and combined purely at the monad's composition time. Monads thus resemble programs in a particular DSL. While programs may describe impure effects and actions outside Haskell, they can still be combined and processed ("assembled") purely, inside Haskell, creating a pure Haskell value - a computation action description that describes an impure calculation. That is how Monads in Haskell separate between the pure and the impure.
The computation doesn't have to be impure and can be pure itself as well. Then monads serve to provide the benefits of separation of concerns, and automatic creation of a computational "pipeline". Because they are very useful in practice but rather mind-twisting for the beginners, numerous tutorials that deal exclusively with monads were created (see monad tutorials).
Most common applications of monads include:
- Representing failure using
- Nondeterminism using
Listmonad to represent carrying multiple values
- State using
- Read-only environment using
- I/O using
Monads can be viewed as a standard programming interface to various data or control structures, which is captured by the
Monad class. All common monads are members of it:
class Monad m where (>>=) :: m a -> ( a -> m b) -> m b (>>) :: m a -> m b -> m b return :: a -> m a fail :: String -> m a
In addition to implementing the class functions, all instances of Monad should obey the following equations, or Monad Laws:
return a >>= k = k a m >>= return = m m >>= (\x -> k x >>= h) = (m >>= k) >>= h
See this intuitive explanation of why they should obey the Monad laws. It basically says that monad's reactions should be associative under Kleisli composition, defined as
(f >=> g) x = f x >>= g, with
return its left and right identity element.
As of GHC 7.10, the Applicative typeclass is a superclass of Monad, and the Functor typeclass is a superclass of Applicative. This means that all monads are applicatives, all applicatives are functors, and, therefore, all monads are also functors. See Functor hierarchy proposal.
In order to improve the look of code that uses monads Haskell provides a special syntactic sugar called
do-notation. For example, the following expression:
thing1 >>= (\x -> func1 x >>= (\y -> thing2 >>= (\_ -> func2 y >>= (\z -> return z))))
which can be written more clearly by breaking it into several lines and omitting parentheses:
thing1 >>= \x -> func1 x >>= \y -> thing2 >>= \_ -> func2 y >>= \z -> return z
This can also be written using the
do-notation as follows:
do x <- thing1 y <- func1 x thing2 z <- func2 y return z
Code written using
do-notation is transformed by the compiler to ordinary expressions that use the functions from the
do-notation and a monad like
IO programs look very much like programs written in an imperative language as each line contains a statement that can change the simulated global state of the program and optionally binds a (local) variable that can be used by the statements later in the code block.
It is possible to intermix the
do-notation with regular notation.
Commutative monads are monads for which the order of actions makes no difference (they commute), that is when following code:
do a <- actA b <- actB m a b
is the same as:
do b <- actB a <- actA m a b
Examples of commutative include:
Monads are known for being deeply confusing to lots of people, so there are plenty of tutorials specifically related to monads. Each takes a different approach to Monads, and hopefully everyone will find something useful.
See the Monad tutorials timeline for a comprehensive list of monad tutorials.
Monad reference guides
An explanation of the basic Monad functions, with examples, can be found in the reference guide A tour of the Haskell Monad functions, by Henk-Jan van Tuyl.
A collection of research papers about monads.
Monads in other languages
Implementations of monads in other languages.
- CML.event ?
- Clean State monad
- Perl6 ?
- The Unix Shell
- More monads by Oleg
- CLL: a concurrent language based on a first-order intuitionistic linear logic where all right synchronous connectives are restricted to a monad.
And possibly there exist:
- Standard ML (via modules?)
Please add them if you know of other implementations.
A list of monads for various evaluation strategies and games:
- Identity monad - the trivial monad.
- Optional results from computations - error checking without null.
- Random values - run code in an environment with access to a stream of random numbers.
- Read only variables - guarantee read-only access to values.
- Writable state - i.e. log to a state buffer
- A supply of unique values - useful for e.g. guids or unique variable names
- ST - memory-only, locally-encapsulated mutable variables. Safely embed mutable state inside pure functions.
- Global state - a scoped, mutable state.
- Undoable state effects - roll back state changes
- Function application - chains of function application.
- Functions which may error - track location and causes of errors.
- Atomic memory transactions - software transactional memory
- Continuations - computations which can be interrupted and resumed.
- IO - unrestricted side effects on the world
- Search monad - bfs and dfs search environments.
- non-determinism - interleave computations with suspension.
- stepwise computation - encode non-deterministic choices as stepwise deterministic ones
- Backtracking computations
- Region allocation effects
- LogicT - backtracking monad transformer with fair operations and pruning
- concurrent events and threads - refactor event and callback heavy programs into straight-line code via co-routines
- QIO - The Quantum computing monad
- Pi calculus - a monad for Pi-calculus style concurrent programming
- Commutable monads for parallel programming
- Simple, Fair and Terminating Backtracking Monad
- Typed exceptions with call traces as a monad
- Breadth first list monad
- Continuation-based queues as monads
- Typed network protocol monad
- Non-Determinism Monad for Level-Wise Search
- Transactional state monad
- A constraint programming monad
- A probability distribution monad
- Sets - Set computations
- HTTP - http connections as a monadic environment
- Memoization - add memoization to code
There are many more interesting instance of the monad abstraction out there. Please add them as you come across each species.
- If you are tired of monads, you can easily get rid of them.