# Changes between Version 1 and Version 2 of Architecture

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Timestamp:
01/14/10 00:46:24 (8 years ago)
Comment:

Renamed Trampoline to Coroutine to match the API

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• ## Architecture

v1 v2
55== The lowest layer: trampoline-style nestable coroutines ==
66
7 This layer, implemented by the Control.Concurrent.Trampoline module, provides a limited coroutine functionality in Haskell. The centerpiece of the approach is the monad transformer Trampoline, that transforms an arbitrary monadic computation into a suspendable and resumable one. The basic definition is simple:
7This layer, implemented by the Control.Concurrent.Coroutine module, provides a limited coroutine functionality in Haskell. The centerpiece of the approach is the monad transformer Coroutine, that transforms an arbitrary monadic computation into a suspendable and resumable one. The basic definition is simple:
88
99{{{
10 newtype Trampoline s m r = Trampoline {bounce :: m (TrampolineState s m r)}
10newtype Coroutine s m r = Coroutine {resume :: m (CoroutineState s m r)}
1111
12 data TrampolineState s m r = Done r | Suspend! (s (Trampoline s m r))
12data CoroutineState s m r = Done r | Suspend! (s (Coroutine s m r))
1313
14 instance (Functor s, Monad m) => Monad (Trampoline s m) where
15    return x = Trampoline (return (Done x))
16    t >>= f = Trampoline (bounce t >>= apply f)
17       where apply f (Done x) = bounce (f x)
15   return x = Coroutine (return (Done x))
16   t >>= f = Coroutine (resume t >>= apply f)
17      where apply f (Done x) = resume (f x)
1818            apply f (Suspend s) = return (Suspend (fmap (>>= f) s))
1919}}}
2020
21 The Trampoline transformer type is parameterized by a functor. Here is an example of one functor particularly useful for a Trampoline computation:
21The Coroutine transformer type is parameterized by a functor. Here is an example of one functor particularly useful for a Coroutine computation:
2222
2323{{{

2929== Streams ==
3030
31 The next layer builds on the trampoline foundation to provide streaming computations. The main idea here is to introduce sinks and sources:
31The next layer builds on the coroutine foundation to provide streaming computations. The main idea here is to introduce sinks and sources:
3232
3333{{{
3434data Sink (m :: * -> *) a x = Sink {
35    put :: forall d. (AncestorFunctor a d) => x -> Trampoline d m Bool,
36    canPut :: forall d. (AncestorFunctor a d) => Trampoline d m Bool
35   put :: forall d. (AncestorFunctor a d) => x -> Coroutine d m Bool,
36   canPut :: forall d. (AncestorFunctor a d) => Coroutine d m Bool
3737   }
3838
3939newtype Source (m :: * -> *) a x = Source {
40    get :: forall d. (AncestorFunctor a d) => Trampoline d m (Maybe x)
40   get :: forall d. (AncestorFunctor a d) => Coroutine d m (Maybe x)
4141   }
4242}}}

4646{{{
4747pipe :: forall m a a1 a2 x r1 r2. (Monad m, Functor a, a1 ~ SinkFunctor a x, a2 ~ SourceFunctor a x) =>
48         (Sink m a1 x -> Trampoline a1 m r1) -> (Source m a2 x -> Trampoline a2 m r2) -> Trampoline a m (r1, r2)
48        (Sink m a1 x -> Coroutine a1 m r1) -> (Source m a2 x -> Coroutine a2 m r2) -> Coroutine a m (r1, r2)
4949}}}
5050

5656
5757{{{
58 type OpenConsumer m a d x r = AncestorFunctor a d => Source m a x -> Trampoline d m r
59 type OpenProducer m a d x r = AncestorFunctor a d => Sink m a x -> Trampoline d m r
58type OpenConsumer m a d x r = AncestorFunctor a d => Source m a x -> Coroutine d m r
59type OpenProducer m a d x r = AncestorFunctor a d => Sink m a x -> Coroutine d m r
6060type OpenTransducer m a1 a2 d x y =
61    (AncestorFunctor a1 d, AncestorFunctor a2 d) => Source m a1 x -> Sink m a2 y -> Trampoline d m [x]
61   (AncestorFunctor a1 d, AncestorFunctor a2 d) => Source m a1 x -> Sink m a2 y -> Coroutine d m [x]
6262type OpenSplitter m a1 a2 a3 a4 d x b =
6363   (AncestorFunctor a1 d, AncestorFunctor a2 d, AncestorFunctor a3 d, AncestorFunctor a4 d) =>
64    Source m a1 x -> Sink m a2 x -> Sink m a3 x -> Sink m a4 b -> Trampoline d m [x]
64   Source m a1 x -> Sink m a2 x -> Sink m a3 x -> Sink m a4 b -> Coroutine d m [x]
6565
6666newtype Consumer m x r = Consumer {consume :: forall a d. OpenConsumer m a d x r}