Safe Haskell | None |
---|---|

Language | Haskell98 |

- data Event a
- data Behavior a
- interpret :: (Event a -> Moment (Event b)) -> [Maybe a] -> IO [Maybe b]
- module Control.Applicative
- module Data.Monoid
- never :: Event a
- unionWith :: (a -> a -> a) -> Event a -> Event a -> Event a
- filterE :: (a -> Bool) -> Event a -> Event a
- apply :: Behavior (a -> b) -> Event a -> Event b
- data Moment a
- class Monad m => MonadMoment m where
- liftMoment :: Moment a -> m a

- accumE :: MonadMoment m => a -> Event (a -> a) -> m (Event a)
- stepper :: MonadMoment m => a -> Event a -> m (Behavior a)
- valueB :: MonadMoment m => Behavior a -> m a
- valueBLater :: MonadMoment m => Behavior a -> m a
- observeE :: Event (Moment a) -> Event a
- switchE :: MonadMoment m => Event (Event a) -> m (Event a)
- switchB :: MonadMoment m => Behavior a -> Event (Behavior a) -> m (Behavior a)
- (<@>) :: Behavior (a -> b) -> Event a -> Event b
- (<@) :: Behavior b -> Event a -> Event b
- filterJust :: Event (Maybe a) -> Event a
- filterApply :: Behavior (a -> Bool) -> Event a -> Event a
- whenE :: Behavior Bool -> Event a -> Event a
- split :: Event (Either a b) -> (Event a, Event b)
- unions :: [Event (a -> a)] -> Event (a -> a)
- accumB :: MonadMoment m => a -> Event (a -> a) -> m (Behavior a)
- mapAccum :: MonadMoment m => acc -> Event (acc -> (x, acc)) -> m (Event x, Behavior acc)

# Synopsis

The main types and combinators of Functional Reactive Programming (FRP).

At its core, FRP is about two data types `Event`

and `Behavior`

and the various ways to combine them.
There is also a third type `Moment`

,
which is necessary for the higher-order combinators.

# Core Combinators

## Event and Behavior

`Event a`

represents a stream of events as they occur in time.
Semantically, you can think of `Event a`

as an infinite list of values
that are tagged with their corresponding time of occurrence,

type Event a = [(Time,a)]

Each pair is called an *event occurrence*.
Note that within a single event stream,
no two event occurrences may happen at the same time.

`Behavior a`

represents a value that varies in time.
Semantically, you can think of it as a function

type Behavior a = Time -> a

Functor Behavior Source | The function fmap :: (a -> b) -> Behavior a -> Behavior b fmap f b = \time -> f (b time) |

Applicative Behavior Source | The function pure :: a -> Behavior a pure x = \time -> x The combinator (<*>) :: Behavior (a -> b) -> Behavior a -> Behavior b fx <*> bx = \time -> fx time $ bx time |

interpret :: (Event a -> Moment (Event b)) -> [Maybe a] -> IO [Maybe b] Source

Interpret an event processing function. Useful for testing.

Note: You can safely assume that this function is pure,
even though the type seems to suggest otherwise.
I'm really sorry about the extra `IO`

, but it can't be helped.
See source code for the sordid details.

## First-order

This subsections lists the primitive first-order combinators for FRP.
The `Functor`

and `Applicative`

instances are also part of this,
but they are documented at the types `Event`

and `Behavior`

.

module Control.Applicative

module Data.Monoid

unionWith :: (a -> a -> a) -> Event a -> Event a -> Event a Source

Merge two event streams of the same type. The function argument specifies how event values are to be combined in case of a simultaneous occurrence. The semantics are

unionWith f ((timex,x):xs) ((timey,y):ys) | timex < timey = (timex,x) : unionWith f xs ((timey,y):ys) | timex > timey = (timey,y) : unionWith f ((timex,x):xs) ys | timex == timey = (timex,f x y) : unionWith f xs ys

filterE :: (a -> Bool) -> Event a -> Event a Source

Allow all events that fulfill the predicate, discard the rest. Semantically,

filterE p es = [(time,a) | (time,a) <- es, p a]

apply :: Behavior (a -> b) -> Event a -> Event b Source

Apply a time-varying function to a stream of events. Semantically,

apply bf ex = [(time, bf time x) | (time, x) <- ex]

This function is generally used in its infix variant `<@>`

.

## Moment and accumulation

The `Moment`

monad denotes a *pure* computation that happens
at one particular moment in time. Semantically, it is a reader monad

type Moment a = Time -> a

When run, the argument tells the time at which this computation happens.

Note that in this context, *time* really means to *logical time*.
Of course, every calculation on a computer takes some
amount of wall-clock time to complete.
Instead, what is meant here is the time as it relates to
`Event`

s and `Behavior`

s.
We use the fiction that every calculation within the `Moment`

monad takes zero *logical time* to perform.

class Monad m => MonadMoment m where Source

An instance of the `MonadMoment`

class denotes a computation
that happens at one particular moment in time.
Unlike the `Moment`

monad, it need not be pure anymore.

liftMoment :: Moment a -> m a Source

accumE :: MonadMoment m => a -> Event (a -> a) -> m (Event a) Source

The `accumE`

function accumulates a stream of event values,
similar to a *strict* left scan, `scanl'`

.
It starts with an initial value and emits a new value
whenever an event occurrence happens.
The new value is calculated by applying the function in the event
to the old value.

Example:

accumE "x" [(time1,(++"y")),(time2,(++"z"))] = trimE [(time1,"xy"),(time2,"xyz")] where trimE e start = [(time,x) | (time,x) <- e, start <= time]

stepper :: MonadMoment m => a -> Event a -> m (Behavior a) Source

Construct a time-varying function from an initial value and a stream of new values. The result will be a step function. Semantically,

stepper x0 ex = \time1 -> \time2 -> last (x0 : [x | (timex,x) <- ex, time1 <= timex, timex < time2])

Here is an illustration of the result Behavior at a particular time:

Note: The smaller-than-sign in the comparison `timex < time2`

means
that at time `time2 == timex`

, the value of the Behavior will
still be the previous value.
In the illustration, this is indicated by the dots at the end
of each step.
This allows for recursive definitions.
See the discussion below for more on recursion.

## Recursion

*Recursion* is a very important technique in FRP that is not apparent
from the type signatures.

Here is a prototypical example. It shows how the `accumE`

can be expressed
in terms of the `stepper`

and `apply`

functions by using recursion:

accumE a e1 = mdo let e2 = (\a f -> f a) <$> b <@> e1 b <- stepper a e2 return e2

(The `mdo`

notation refers to *value recursion* in a monad.
The `MonadFix`

instance for the `Moment`

class enables this kind of recursive code.)
(Strictly speaking, this also means that `accumE`

is not a primitive,
because it can be expressed in terms of other combinators.)

This general pattern appears very often in practice:
A Behavior (here `b`

) controls what value is put into an Event (here `e2`

),
but at the same time, the Event contributes to changes in this Behavior.
Modeling this situation requires recursion.

For another example, consider a vending machine that sells banana juice.
The amount that the customer still has to pay for a juice
is modeled by a Behavior `bAmount`

.
Whenever the customer inserts a coin into the machine,
an Event `eCoin`

occurs, and the amount will be reduced.
Whenver the amount goes below zero, an Event `eSold`

will occur,
indicating the release of a bottle of fresh banana juice,
and the amount to be paid will be reset to the original price.
The model requires recursion, and can be expressed in code as follows:

mdo let price = 50 :: Int bAmount <- accumB price $ unions [ subtract 10 <$ eCoin , const price <$ eSold ] let eSold = whenE ((<= 0) <$> bAmount) eCoin

On one hand, the Behavior `bAmount`

controls whether the Event `eSold`

occcurs at all; the bottle of banana juice is unavailable to penniless customers.
But at the same time, the Event `eSold`

will cause a reset
of the Behavior `bAmount`

, so both depend on each other.

Recursive code like this examples works thanks to the semantics of `stepper`

.
In general, *mutual recursion* between several `Event`

s and `Behavior`

s
is always well-defined,
as long as an Event depends on itself only *via* a Behavior,
and vice versa.

## Higher-order

valueB :: MonadMoment m => Behavior a -> m a Source

Obtain the value of the `Behavior`

at a given moment in time.
Semantically, it corresponds to

valueB b = \time -> b time

Note: The value is immediately available for pattern matching.
Unfortunately, this means that `valueB`

is unsuitable for use
with value recursion in the `Moment`

monad.
If you need recursion, please use `valueBLater`

instead.

valueBLater :: MonadMoment m => Behavior a -> m a Source

Obtain the value of the `Behavior`

at a given moment in time.
Semantically, it corresponds to

valueBLater b = \time -> b time

Note: To allow for more recursion, the value is returned *lazily*
and not available for pattern matching immediately.
It can be used safely with most combinators like `stepper`

.
If that doesn't work for you, please use `valueB`

instead.

observeE :: Event (Moment a) -> Event a Source

Observe a value at those moments in time where event occurrences happen. Semantically,

observeE e = [(time, m time) | (time, m) <- e]

switchE :: MonadMoment m => Event (Event a) -> m (Event a) Source

Dynamically switch between `Event`

.
Semantically,

switchE ee = \time0 -> concat [trim t1 t2 e | (t1,t2,e) <- intervals ee, time0 <= t1] where intervals e = [(time1, time2, x) | ((time1,x),(time2,_)) <- zip e (tail e)] trim time1 time2 e = [x | (timex,x) <- e, time1 < timex, timex <= time2]

switchB :: MonadMoment m => Behavior a -> Event (Behavior a) -> m (Behavior a) Source

Dynamically switch between `Behavior`

.
Semantically,

switchB b0 eb = \time0 -> \time1 -> last (b0 : [b | (timeb,b) <- eb, time0 <= timeb, timeb < time1]) time1

# Derived Combinators

## Infix operators

(<@) :: Behavior b -> Event a -> Event b infixl 4 Source

Tag all event occurrences with a time-varying value. Similar to `<*`

.

infixl 4 <@

## Filtering

filterJust :: Event (Maybe a) -> Event a Source

filterApply :: Behavior (a -> Bool) -> Event a -> Event a Source

Allow all events that fulfill the time-varying predicate, discard the rest.
Generalization of `filterE`

.

whenE :: Behavior Bool -> Event a -> Event a Source

Allow events only when the behavior is `True`

.
Variant of `filterApply`

.

## Accumulation

Note: All accumulation functions are strict in the accumulated value!

Note: The order of arguments is `acc -> (x,acc)`

which is also the convention used by `unfoldr`

and `State`

.

unions :: [Event (a -> a)] -> Event (a -> a) Source

Merge event streams whose values are functions.
In case of simultaneous occurrences, the functions at the beginning
of the list are applied *after* the functions at the end.

unions [] = never unions xs = foldr1 (unionWith (.)) xs

Very useful in conjunction with accumulation functions like `accumB`

and `accumE`

.

accumB :: MonadMoment m => a -> Event (a -> a) -> m (Behavior a) Source

The `accumB`

function accumulates event occurrences into a `Behavior`

.

The value is accumulated using `accumE`

and converted
into a time-varying value using `stepper`

.

Example:

accumB "x" [(time1,(++"y")),(time2,(++"z"))] = stepper "x" [(time1,"xy"),(time2,"xyz")]

Note: As with `stepper`

, the value of the behavior changes "slightly after"
the events occur. This allows for recursive definitions.