{-# LANGUAGE Safe #-} {-# LANGUAGE FlexibleInstances #-} {-# LANGUAGE Arrows #-} {-# LANGUAGE RankNTypes #-} {-# LANGUAGE TypeSynonymInstances #-} {-# LANGUAGE MultiParamTypeClasses #-} {-# LANGUAGE GADTs #-} {-| Module: Control.Arrow.Machine Description: Contains the main documentation and module imports. -} module Control.Arrow.Machine ( -- * Quick introduction -- $introduction -- * Note -- $note -- * Modules -- | "Control.Arrow.Machine" is good to import qualified, because no operators are exported. -- -- Alternatively, you can import libraries below individually, -- with only "Control.Arrow.Machine.Utils" qualified or identifier specified. -- -- Control.Arrow.Machine.Misc.* are not included by default. -- They are all designed to import qualified. module Control.Arrow.Machine.ArrowUtil, module Control.Arrow.Machine.Types, module Control.Arrow.Machine.Utils ) where import Control.Arrow.Machine.ArrowUtil import Control.Arrow.Machine.Types import Control.Arrow.Machine.Utils -- $introduction -- As other iteratee or pipe libraries, machinecell abstracts general iteration processes. -- -- Here is an example that is a simple iteration over a list. -- -- >>> run (evMap (+1)) [1, 2, 3] -- [2, 3, 4] -- -- In above statement, "`evMap` (+1)" has a type "ProcessA (-\>) (Event Int) (Event Int)", -- which denotes "A stream transducer that takes a series of Int as input, -- gives a series of Int as output, run on base arrow (-\>)." -- -- `ProcessA` is the transducer type of machinecell library. -- -- = Side effects -- -- In general, `Arrow` types other than (-\>) may have side effects. -- For example any monadic side effects can be performed by wrapping the monad with `Kleisli`. -- -- ProcessA can run the effects as following. -- -- >>> runKleisli (run_ $ anytime (Kleisli print)) [1, 2, 3] -- 1 -- 2 -- 3 -- -- Where `anytime` makes a transducer that executes side effects for each input. -- `run_` is almost same as `run` but discards transducer's output. -- -- That is useful in the case rather side effects are main concern. -- -- = ProcessA as pipes -- -- "ProcessA a (Event b) (Event c)" transducers are actually one-directional composable pipes. -- -- They can be constructed from the `Plan` monad. -- In `Plan` monad context, `await` and `yield` can be used to get and emit values. -- And actions of base monads can be `lift`ed to the context. -- -- @ -- source :: ProcessA (Kleisli IO) (Event ()) (Event String) -- source = repeatedlyT kleisli0 $ -- do -- _ \<- await -- x \<- lift getLine -- yield x -- -- pipe :: ArrowApply a =\> ProcessA a (Event String) (Event String) -- pipe = construct $ -- do -- s1 \<- await -- s2 \<- await -- yield (s1 ++ s2) -- -- sink :: ProcessA (Kleisli IO) (Event String) (Event Void) -- sink = repeatedlyT kleisli0 -- do -- x \<- await -- lift $ putStrLn x -- @ -- -- Then, resulting processes are composed as `Category` using `(\>\>\>)` operator. -- -- > runKleisli (run_ $ source >>> pipe >>> sink) (repeat ()) -- -- This reads two lines from stdin, puts a concatenated line to stdout and finishes. -- -- Unlike other pipe libraries, even the source calls `await`. -- The source awaits dummy input, namely "(repeat ())", and discard input values. -- -- Even the input is an infinite list, this program stops when the "pipe" transducer stops. -- -- == More details on finalizing -- -- Finalizing behavior of transducers obey the following scenario. -- -- 1. Signals of type `Event` can carry /end signs/. -- 2. Most transducers stop when they get an end sign. -- (Some exceptions can be made by `onEnd` or `catchP`) -- 3. If `run` function detects an end sign as an output of a running transducer, -- it stops feeding input values and alternatively feeds end signs. -- 4. Continue iteration until no more events can be occurred. -- -- So "await \`catchP\` some_cleanup" can handle any stop of both upstream and downstream. -- -- On the other hand, a plan never gets end sign without calling await. -- So it is better that even a source calls await. -- -- A source that calls await periodically is an "interleaved source". -- Interleaved sources have a number of advantages. -- They can be controled their output timings by their upstream, or can be stopped any time. -- -- There is another kind of source that doesn't call await, namely "blocking source". -- -- see "sources" section of "Control.Arrow.Machine.Utils" documentation. -- -- = Arrow composition -- -- One of the most attractive feature of machinecell is the /arrow composition/. -- -- In addition to `Category`, ProcessA has `Arrow` instance declaration, -- which allows parallel compositions. -- -- If a type has an `Arrow` instance, it can be wrote by ghc extended proc-do notation as following. -- -- @ -- f :: ProcessA (Kleisli IO) (Event Int) (Event ()) -- f = proc x -\> -- do -- -- Process odd integers. -- odds \<- filter $ arr odd -\< x -- anytime $ Kleisli (putStrLn . ("Odd: " ++)) -\< show \<$\> odds -- -- -- Process even integers. -- evens \<- filter $ arr even -\< x -- anytime $ Kleisli (putStrLn . ("Even: " ++)) -\< show \<$\> evens -- @ -- -- >>> P.runKleisli (run f) [1..10] -- Odd: 1 -- Even: 2 -- Odd: 3 -- Even: 4 -- ... -- -- The result implies that two statements that inputs x and their downstreams are -- executed in parallel. -- -- = Behaviours -- -- The transducers we have already seen are all have input and output type wrapped by `Event`. -- We have not taken care of them so far because all of them are cancelled each other. -- -- But several built-in transducers provide non-event values like below. -- -- @ -- hold :: ArrowApply a =\> b -\> ProcessA a (Event b) b -- accum :: ArrowApply a =\> b -\> ProcessA a (Event (b-\>b)) b -- @ -- -- `hold` keeps the last input until a new value is provided. -- -- `accum` updates its outputting by applying every input function. -- -- According to a knowledge from arrowized FRP(functional reactive programming), -- values that appear naked in arrow notations are /behaviour/, -- that means /coutinuous/ time-varying values, -- whereas /event/ values are /discrete/. -- -- Note that all values that can be input, output, or taken effects must be discrete. -- -- To use continuous values anyhow interacting the real world, -- they must be encoded to discrete values. -- -- That's done by functor calculations between any existing events. -- -- An example is below. -- -- @ -- f :: ArrowApply a =\> ProcessA a (Event Int) (Event Int) -- f = proc x -\> -- do -- y \<- accum 0 -\< (+) \<$\> x -- returnA -\< y \<$ x -- @ -- -- >>> run f [1, 2, 3] -- [1, 3, 6] -- -- `(\<$)` operator discards the value of rhs and only uses that's container structure -- e.g. 1 \<$ Just "a" =\> Just 1, 1 \<$ Nothing =\> Nothing, -- 1 \<$ [True, False, undefined] =\> [1, 1, 1]. -- -- In this case, the value of y are outputed according to the timing of x. -- -- $note -- = Purity of `ProcessA (-\>)` -- Since the 1st type parameter of `ProcessA` represents base monad(ArrowApply), -- "ProcessA (-\>)" is expected to be pure. -- -- In other words, the following arrow results the same result for arbitrary f. -- -- @ -- proc x -\> -- do -- _ \<- `fit` arr f -\< x -- g -\< x -- @ -- -- Which is desugared to "fit arr f &&& g \>\>\> arr snd". At least if `Event` constructor is exported, -- someone can make a counter example. -- When f is "arr (replicate k) \>\>\> fork" for some integer k and g is "arr (const $ Event ())", -- g yields ()s for k times. That is because, the result value of arrow "f &&& g" is -- nothing but "(Event x, Event ())" and its number of yields is k because "Event x" must -- be yielded k times. -- -- This is the reason why the `Event` constructor is hidden. -- Using exported primitives, it works almost correctly. -- Event number is conserved by inserting an appropriate number of `NoEvent`s. -- But there is still a loophole. -- -- Under the current implementation, the arrow below behaves like "arr (const $ Event x)". -- -- @ -- proc x -\> hold noEvent -\< ev \<$ ev -- @ -- -- I have an idea to correct this, such that the above arrow always be `NoEvent`. -- But in the result `Event` is no longer a functor in the meaning of haskell type class. -- -- For now, if you never make value of nested event type like "ev \<$ ev", -- the problem will be avoided. -- -- = Looping -- -- Although `ProcessA` is an instance of `ArrowLoop`, -- there is a large limitation. -- -- The limitation is, Events mustn't be looped back to upstream. -- -- In example below, result is [0, 0, 0, 0], not [1, 2, 3, 4]. -- -- @ -- f = proc x -\> -- do -- rec -- b \<- hold 0 -\< y -- y \<- fork -\< (\xx -\> [xx, xx+1, xx+2, xx+3]) \<$\> x -- returnA -\< b \<$ y -- -- dHold i = proc x -\> drSwitch (pure i) -\< ((), pure \<$\> x) -- @ -- -- >>> run f [1] -- [0, 0, 0, 0] -- -- In general, `Event` values refered at upstream in rec statements are -- almost always `NoEvent`s. -- -- A better way to send events to upstream is, to encode them to behaviours using `dHold`, -- `dAccum` and so on, then send to upstream in rec statement. --