# Overview Conventional Haskell stream programming forces you to choose only two of the following three features: * Effects * Streaming * Composability If you sacrifice *Effects* you get Haskell's pure and lazy lists, which you can transform using composable functions in constant space, but without interleaving effects. If you sacrifice *Streaming* you get `mapM`, `forM` and "ListT done wrong", which are composable and effectful, but do not return a single result until the whole list has first been processed and loaded into memory. If you sacrifice *Composability* you write a tightly coupled read, transform, and write loop in `IO`, which is streaming and effectful, but is not modular or separable. `pipes` gives you all three features: effectful, streaming, and composable programming. `pipes` also provides a wide variety of stream programming abstractions which are all subsets of a single unified machinery: * effectful `Producer`s (like generators), * effectful `Consumer`s (like iteratees), * effectful `Pipe`s (like Unix pipes), and: * `ListT` done right. All of these are connectable and you can combine them together in clever and unexpected ways because they all share the same underlying type. `pipes` requires a basic understanding of monad transformers, which you can learn about by reading either: * the paper "Monad Transformers - Step by Step", * chapter 18 of "Real World Haskell" on monad transformers, or: * the documentation of the `transformers` library. If you want a Quick Start guide to `pipes`, read [the documentation in `Pipes.Prelude`](http://hackage.haskell.org/package/pipes-4.1.0/docs/Pipes-Prelude.html) from top to bottom. This tutorial is more extensive and explains the `pipes` API in greater detail and illustrates several idioms. # Introduction The `pipes` library decouples stream processing stages from each other so that you can mix and match diverse stages to produce useful streaming programs. If you are a library writer, `pipes` lets you package up streaming components into a reusable interface. If you are an application writer, `pipes` lets you connect pre-made streaming components with minimal effort to produce a highly-efficient program that streams data in constant memory. To enforce loose coupling, components can only communicate using two commands: * `yield`: Send output data * `await`: Receive input data `pipes` has four types of components built around these two commands: * `Producer`s can only `yield` values and they model streaming sources * `Consumer`s can only `await` values and they model streaming sinks * `Pipe`s can both `yield` and `await` values and they model stream transformations * `Effect`s can neither `yield` nor `await` and they model non-streaming components You can connect these components together in four separate ways which parallel the four above types: * `for` handles `yield`s * `(>~)` handles `await`s * `(>->)` handles both `yield`s and `await`s * `(>>=)` handles return values As you connect components their types will change to reflect inputs and outputs that you've fused away. You know that you're done connecting things when you get an `Effect`, meaning that you have handled all inputs and outputs. You run this final `Effect` to begin streaming. # Producers `Producer`s are effectful streams of input. Specifically, a `Producer` is a monad transformer that extends any base monad with a new `yield` command. This `yield` command lets you send output downstream to an anonymous handler, decoupling how you generate values from how you consume them. The following `stdinLn` `Producer` shows how to incrementally read in `String`s from standard input and `yield` them downstream, terminating gracefully when reaching the end of the input: ```haskell import Control.Monad (unless) import Pipes import System.IO (isEOF) -- +--------+-- A 'Producer' that yields 'String's -- | | -- | | +-- Every monad transformer has a base monad. -- | | | This time the base monad is 'IO'. -- | | | -- | | | +-- Every monadic action has a return value. -- | | | | This action returns '()' when finished -- v v v v stdinLn :: Producer String IO () stdinLn = do eof <- lift isEOF -- 'lift' an 'IO' action from the base monad unless eof $ do str <- lift getLine yield str -- 'yield' the 'String' stdinLn -- Loop ``` `yield` emits a value, suspending the current `Producer` until the value is consumed. If nobody consumes the value (which is possible) then `yield` never returns. You can think of `yield` as having the following type: ```haskell yield :: Monad m => a -> Producer a m () ``` The true type of `yield` is actually more general and powerful. Throughout the tutorial I will present type signatures like this that are simplified at first and then later reveal more general versions. So read the above type signature as simply saying: "You can use `yield` within a `Producer`, but you may be able to use `yield` in other contexts, too." If you navigate to the [documentation for `yield`](http://hackage.haskell.org/package/pipes-4.1.0/docs/Pipes.html#v:yield) you will see that `yield` actually uses the `Producer'` (with an apostrophe) type synonym which hides a lot of polymorphism behind a simple veneer. The documentation for `yield` says that you can also use `yield` within a `Pipe`, too, because of this polymorphism: ```haskell yield :: Monad m => a -> Pipe x a m () ``` Use simpler types like these to guide you until you understand the fully general type. `for` loops are the simplest way to consume a `Producer` like `stdinLn`. `for` has the following type: ```haskell -- +-- Producer +-- The body of the +-- Result -- | to loop | loop | -- v over v v -- -------------- ------------------ ---------- for :: Monad m => Producer a m r -> (a -> Effect m ()) -> Effect m r ``` `for producer body` loops over `producer`, substituting each `yield` in `producer` with `body`. You can also deduce that behavior purely from the type signature: * The body of the loop takes exactly one argument of type `a`, which is the same as the output type of the `Producer`. Therefore, the body of the loop must get its input from that `Producer` and nowhere else. * The return value of the input `Producer` matches the return value of the result, therefore `for` must loop over the entire `Producer` and not skip anything. The above type signature is not the true type of `for`, which is actually more general. Think of the above type signature as saying: "If the first argument of `for` is a `Producer` and the second argument returns an `Effect`, then the final result must be an `Effect`." If you navigate to the [documentation for `for`](http://hackage.haskell.org/package/pipes-4.1.0/docs/Pipes.html#v:for) you will see the fully general type and underneath you will see equivalent simpler types. One of these says that if the body of the loop is a `Producer`, then the result is a `Producer`, too: ```haskell for :: Monad m => Producer a m r -> (a -> Producer b m ()) -> Producer b m r ``` The first type signature I showed for `for` was a special case of this slightly more general signature because a `Producer` that never `yield`s is also an `Effect`: ```haskell data X -- The uninhabited type type Effect m r = Producer X m r ``` This is why `for` permits two different type signatures. The first type signature is just a special case of the second one: ```haskell for :: Monad m => Producer a m r -> (a -> Producer b m ()) -> Producer b m r -- Specialize 'b' to 'X' for :: Monad m => Producer a m r -> (a -> Producer X m ()) -> Producer X m r -- Producer X = Effect for :: Monad m => Producer a m r -> (a -> Effect m ()) -> Effect m r ``` This is the same trick that all `pipes` functions use to work with various combinations of `Producer`s, `Consumer`s, `Pipe`s, and `Effect`s. Each function really has just one general type, which you can then simplify down to multiple useful alternative types. Here's an example use of a `for` loop, where the second argument (the loop body) is an `Effect`: ```haskell loop :: Effect IO () loop = for stdinLn $ \str -> do -- Read this like: "for str in stdinLn" lift $ putStrLn str -- The body of the 'for' loop -- more concise: loop = for stdinLn (lift . putStrLn) ``` In this example, `for` loops over `stdinLn` and replaces every `yield` in `stdinLn` with the body of the loop, printing each line. This is exactly equivalent to the following code, which I've placed side-by-side with the original definition of `stdinLn` for comparison: ```haskell loop = do eof <- lift isEOF unless eof $ do str <- lift getLine {-hi-}(lift . putStrLn){-/hi-} str loop stdinLn = do eof <- lift isEOF unless eof $ do str <- lift getLine {-hi-}yield{-/hi-} str stdinLn ``` You can think of `yield` as creating a hole and a `for` loop is one way to fill that hole. Notice how the final `loop` only `lift`s actions from the base monad and does nothing else. This property is true for all `Effect`s, which are just glorified wrappers around actions in the base monad. This means we can run these `Effect`s to remove their `lift`s and lower them back to the equivalent computation in the base monad: ```haskell runEffect :: Monad m => Effect m r -> m r ``` This is the real type signature of `runEffect`, which refuses to accept anything other than an `Effect`. This ensures that we handle all inputs and outputs before streaming data: ```haskell main :: IO () main = runEffect loop ``` ... or you could inline the entire `loop` into the following one-liner: ```active haskell import Control.Monad (unless) import Pipes import System.IO (isEOF) stdinLn :: Producer String IO () stdinLn = do eof <- lift isEOF unless eof $ do str <- lift getLine yield str stdinLn -- show -- Try me! main = runEffect $ for stdinLn (lift . putStrLn) ``` Run the above program and it will loop over standard input and echo every line to standard output. If you run the program from the command line instead of School of Haskell you can also test how the program handles end of input: ``` $ ./echo Test Test ABC ABC $ ``` The final behavior is indistinguishable from just removing all the `lift`s from `loop`: ```haskell main = do eof <- isEOF unless eof $ do str <- getLine putStrLn str main loop = do eof <- {-hi-}lift{-/hi-} isEOF unless eof $ do str <- {-hi-}lift{-/hi-} getLine {-hi-}lift{-/hi-} $ putStrLn str main ``` This `main` is what we might have written by hand if we were not using `pipes`, but with `pipes` we can decouple the input and output logic from each other. When we connect them back together, we still produce streaming code equivalent to what a sufficiently careful Haskell programmer would have written. You can also use `for` to loop over lists, too. To do so, convert the list to a `Producer` using `each`, which is exported by default from the `Pipes` module: ```haskell each :: Monad m => [a] -> Producer a m () each as = mapM_ yield as ``` Combine `for` and `each` to iterate over lists using a "foreach" loop: ```active haskell import Pipes main = runEffect $ for (each [1..4]) (lift . print) ``` `each` is actually more general and works for any `Foldable`: ```haskell each :: (Monad m, Foldable f) => f a -> Producer a m () ``` So you can loop over any `Foldable` container or even a `Maybe`: ```active haskell import Pipes main = runEffect $ for (each (Just 1)) (lift . print) ``` # Producers You might wonder why the body of a `for` loop can be a `Producer`. Let's test out this feature by defining a new loop body that `duplicate`s every value: ```haskell import Pipes import qualified Pipes.Prelude as Pipes -- Pipes.Prelude already has 'stdinLn' duplicate :: Monad m => a -> Producer a m () duplicate x = do yield x yield x loop :: Producer String IO () loop = for Pipes.stdinLn duplicate -- This is the exact same as: -- -- loop = for P.stdinLn $ \x -> do -- yield x -- yield x ``` This time our `loop` is a `Producer` that outputs `String`s, specifically two copies of each line that we read from standard input. Since `loop` is a `Producer` we cannot run it because there is still unhandled output. However, we can use yet another `for` to handle this new duplicated stream: ```active haskell import Pipes import qualified Pipes.Prelude as Pipes -- Pipes.Prelude already has 'stdinLn' duplicate :: Monad m => a -> Producer a m () duplicate x = do yield x yield x loop :: Producer String IO () loop = for Pipes.stdinLn duplicate -- show main = runEffect $ for loop (lift . putStrLn) ``` Run the above program, which will echo every line from standard input to standard output twice. However, are is this really necessary? Couldn't we have instead written this using a nested for loop? ```haskell main = runEffect $ for Pipes.stdinLn $ \str1 -> for (duplicate str1) $ \str2 -> lift $ putStrLn str2 ``` Yes, we could have! In fact, this is a special case of the following equality, which always holds no matter what: ```haskell s :: Monad m => Producer a m () -- i.e. Pipes.stdinLn f :: Monad m => a -> Producer b m () -- i.e. duplicate g :: Monad m => b -> Producer c m () -- i.e. lift . putStrLn for (for s f) g = for s (\x -> for (f x) g) ``` We can understand the rationale behind this equality if we first define the following operator that is the point-free counterpart to `for`: ```haskell (~>) :: Monad m => (a -> Producer b m r) -> (b -> Producer c m r) -> (a -> Producer c m r) (f ~> g) x = for (f x) g ``` Using `(~>)` (pronounced "into"), we can transform our original equality into the following more symmetric equation: ```haskell f :: Monad m => a -> Producer b m r g :: Monad m => b -> Producer c m r h :: Monad m => c -> Producer d m r -- Associativity (f ~> g) ~> h = f ~> (g ~> h) ``` This looks just like an associativity law. In fact, `(~>)` has another nice property, which is that `yield` is its left and right identity: ```haskell -- Left Identity yield ~> f = f -- Right Identity f ~> yield = f ``` In other words, `yield` and `(~>)` form a `Category`, specifically the generator category, where `(~>)` plays the role of the composition operator and `yield` is the identity. If you don't know what a `Category` is, that's okay, and category theory is not a prerequisite for using `pipes`. All you really need to know is that `pipes` uses some simple category theory to keep the API intuitive and easy to use. Notice that if we translate the left identity law to use `for` instead of `(~>)` we get: ```haskell for (yield x) f = f x ``` This just says that if you iterate over a pure single-element `Producer`, then you could instead cut out the middle man and directly apply the body of the loop to that single element. If we translate the right identity law to use `for` instead of (`~>`) we get: ```haskell for s yield = s ``` This just says that if the only thing you do is re-`yield` every element of a stream, you get back your original stream. These three "for loop" laws summarize our intuition for how `for` loops should behave and because these are `Category` laws in disguise that means that `Producer`s are composable in a rigorous sense of the word. In fact, we get more out of this than just a bunch of equations. We also get a useful operator: `(~>)`. We can use this operator to condense our original code into the following more succinct form that composes two transformations: ```haskell main = runEffect $ for Pipes.stdinLn (duplicate ~> lift . putStrLn) ``` This means that we can also choose to program in a more functional style and think of stream processing in terms of composing transformations using `(~>)` instead of nesting a bunch of `for` loops. The above example is a microcosm of the design philosophy behind the `pipes` library: * Define the API in terms of categories * Specify expected behavior in terms of category laws * Think compositionally instead of sequentially # Consumers Sometimes you don't want to use a `for` loop because you don't want to consume every element of a `Producer` or because you don't want to process every value of a `Producer` the exact same way. The most general solution is to externally iterate over the `Producer` using the `next` command: ```haskell next :: Monad m => Producer a m r -> m (Either r (a, Producer a m r)) ``` Think of `next` as pattern matching on the head of the `Producer`. This `Either` returns a `Left` if the `Producer` is done or it returns a `Right` containing the next value, `a`, along with the remainder of the `Producer`. However, sometimes we can get away with something a little more simple and elegant, like a `Consumer`, which represents an effectful sink of values. A `Consumer` is a monad transformer that extends the base monad with a new `await` command. This `await` command lets you receive input from an anonymous upstream source. The following `stdoutLn` `Consumer` shows how to incrementally `await` `String`s and print them to standard output, terminating gracefully when receiving a broken pipe error: ```haskell import Control.Monad (unless) import Control.Exception (try, throwIO) import qualified GHC.IO.Exception as G import Pipes -- +--------+-- A 'Consumer' that awaits 'String's -- | | -- v v stdoutLn :: Consumer String IO () stdoutLn = do str <- await -- 'await' a 'String' x <- lift $ try $ putStrLn str case x of -- Gracefully terminate if we got a broken pipe error Left e@(G.IOError { G.ioe_type = t}) -> lift $ unless (t == G.ResourceVanished) $ throwIO e -- Otherwise loop Right () -> stdoutLn ``` `await` is the dual of `yield`: we suspend our `Consumer` until we receive a new value. If nobody provides a value (which is possible) then `await` never returns. You can think of `await` as having the following type: ```haskell await :: Monad m => Consumer a m a ``` One way to feed a `Consumer` is to repeatedly feed the same input using using `(>~)` (pronounced "feed"): ```haskell -- +- Feed +- Consumer to +- Returns new -- | action | feed | Effect -- v v v -- ---------- -------------- ---------- (>~) :: Monad m => Effect m b -> Consumer b m c -> Effect m c ``` `draw >~ consumer` loops over `consumer`, substituting each `await` in `consumer` with `draw`. So the following code replaces every `await` in `stdoutLn` with `lift getLine` and then removes all the `lift`s: ```active haskell import Control.Monad (unless) import Control.Exception (try, throwIO) import qualified GHC.IO.Exception as G import Pipes stdoutLn :: Consumer String IO () stdoutLn = do str <- await x <- lift $ try $ putStrLn str case x of Left e@(G.IOError { G.ioe_type = t}) -> lift $ unless (t == G.ResourceVanished) $ throwIO e Right () -> stdoutLn -- show main = runEffect $ lift getLine >~ stdoutLn ``` Run the above program and it will echo standard input to standard input. The difference is that this time it checks for a broken output pipe instead of end of input. You might wonder why (`>~`) uses an `Effect` instead of a raw action in the base monad. The reason why is that `(>~)` actually permits the following more general type: ```haskell (>~) :: Monad m => Consumer a m b -> Consumer b m c -> Consumer a m c ``` `(>~)` is the dual of `(~>)`, composing `Consumer`s instead of `Producer`s. This means that you can feed a `Consumer` with yet another `Consumer` so that you can `await` while you `await`. For example, we could define the following intermediate `Consumer` that requests two `String`s and returns them concatenated: ```haskell doubleUp :: Monad m => Consumer String m String doubleUp = do str1 <- await str2 <- await return (str1 ++ str2) -- more concise: doubleUp = (++) <$> await <*> await ``` We can now insert this in between `lift getLine` and `stdoutLn` and see what happens: ```active haskell import Control.Monad (unless) import Control.Exception (try, throwIO) import qualified GHC.IO.Exception as G import Pipes stdoutLn :: Consumer String IO () stdoutLn = do str <- await x <- lift $ try $ putStrLn str case x of Left e@(G.IOError { G.ioe_type = t}) -> lift $ unless (t == G.ResourceVanished) $ throwIO e Right () -> stdoutLn doubleUp :: Monad m => Consumer String m String doubleUp = do str1 <- await str2 <- await return (str1 ++ str2) -- show main = runEffect $ lift getLine >~ doubleUp >~ stdoutLn ``` If you run the above example it will repeatedly request two lines of input and output them concatenated. `doubleUp` splits every request from `stdoutLn` into two separate requests and returns back the concatenated result. We didn't need to parenthesize the above chain of `(>~)` operators, because `(>~)` is associative: ```haskell -- Associativity (f >~ g) >~ h = f >~ (g >~ h) ``` ... so we can always omit the parentheses since the meaning is unambiguous: ```haskell f >~ g >~ h ``` Also, `(>~)` has an identity, which is `await`! ```haskell -- Left identity await >~ f = f -- Right Identity f >~ await = f ``` In other words, `(>~)` and `await` form a `Category`, too, specifically the iteratee category, and `Consumer`s are also composable. # Pipes Our previous programs were unsatisfactory because they were biased either towards the `Producer` end or the `Consumer` end. As a result, we had to choose between gracefully handling end of input (using `stdinLn`) or gracefully handling end of output (using `stdoutLn`), but not both at the same time. However, we don't need to restrict ourselves to using `Producer`s exclusively or `Consumer`s exclusively. We can connect `Producer`s and `Consumer`s directly together using (`>->`) (pronounced "pipe"): ```haskell (>->) :: Monad m => Producer a m r -> Consumer a m r -> Effect m r ``` This returns an `Effect` which we can run: ```active haskell import Pipes import qualified Pipes.Prelude as Pipes -- Pipes.Prelude also provides 'stdoutLn' main = runEffect $ Pipes.stdinLn >-> Pipes.stdoutLn ``` This program is more declarative of our intent: we want to stream values from `stdinLn` to `stdoutLn`. The above "pipeline" not only echoes standard input to standard output, but also handles both end of input and broken pipe errors. `(>->)` is "pull-based" meaning that control flow begins at the most downstream component (i.e. `stdoutLn` in the above example). Any time a component `await`s a value it blocks and transfers control upstream and every time a component `yield`s a value it blocks and restores control back downstream, satisfying the `await`. So in the above example, `(>->)` matches every `await` from `P.stdoutLn` with a `yield` from `stdinLn`. Streaming stops when either `stdinLn` terminates (i.e. end of input) or `stdoutLn` terminates (i.e. broken pipe). This is why `(>->)` requires that both the `Producer` and `Consumer` share the same type of return value: whichever one terminates first provides the return value for the entire `Effect`. Let's test this by modifying our `Producer` and `Consumer` to each return a diagnostic `String`: ```active haskell import Control.Applicative ((<$)) -- (<$) modifies return values import Pipes import qualified Pipes.Prelude as P import System.IO main = do hSetBuffering stdout NoBuffering str <- runEffect $ ("End of input!" <$ P.stdinLn) >-> ("Broken pipe!" <$ P.stdoutLn) hPutStrLn stderr str ``` If you run this program on the command line you can trigger both termination scenarios: ``` $ ./echo2 Test Test End of input! $ ./echo2 | perl -e 'close STDIN' Test Broken pipe! $ ``` You might wonder why `(>->)` returns an `Effect` that we have to run instead of directly returning an action in the base monad. This is because you can connect things other than `Producer`s and `Consumer`s, like `Pipe`s, which are effectful stream transformations. A `Pipe` is a monad transformer that is a mix between a `Producer` and `Consumer`, because a `Pipe` can both `await` and `yield`. The following example `Pipe` is analogous to the Prelude's `take`, only allowing a fixed number of values to flow through: ```haskell import Control.Monad (replicateM_) import Pipes import Prelude hiding (take) -- +--------- A 'Pipe' that -- | +---- 'await's 'a's and -- | | +-- 'yield's 'a's -- | | | -- v v v take :: Int -> Pipe a a IO () take n = do replicateM_ n $ do -- Repeat this block 'n' times x <- await -- 'await' a value of type 'a' yield x -- 'yield' a value of type 'a' lift $ putStrLn "You shall not pass!" -- Fly, you fools! ``` You can use `Pipe`s to transform `Producer`s, `Consumer`s, or even other `Pipe`s using the same `(>->)` operator: ```haskell (>->) :: Monad m => Producer a m r -> Pipe a b m r -> Producer b m r (>->) :: Monad m => Pipe a b m r -> Consumer b m r -> Consumer a m r (>->) :: Monad m => Pipe a b m r -> Pipe b c m r -> Pipe' a c m r ``` For example, you can compose `take` after `stdinLn` to limit the number of lines drawn from standard input: ```active haskell import Control.Monad (replicateM_) import Pipes import qualified Pipes.Prelude as Pipes import Prelude hiding (take) take :: Int -> Pipe a a IO () take n = do replicateM_ n $ do x <- await yield x lift $ putStrLn "You shall not pass!" -- show maxInput :: Int -> Producer String IO () maxInput n = Pipes.stdinLn >-> take n main = runEffect $ maxInput 3 >-> Pipes.stdoutLn ``` ... or you can pre-compose `take` before `stdoutLn` to limit the number of lines written to standard output: ```active haskell import Control.Monad (replicateM_) import Pipes import qualified Pipes.Prelude as Pipes import Prelude hiding (take) take :: Int -> Pipe a a IO () take n = do replicateM_ n $ do x <- await yield x lift $ putStrLn "You shall not pass!" -- show maxOutput :: Int -> Consumer String IO () maxOutput n = take n >-> Pipes.stdoutLn -- Exact same behavior main = runEffect $ Pipes.stdinLn >-> maxOutput 3 ``` Those both gave the same behavior because `(>->)` is associative: ```haskell (p1 >-> p2) >-> p3 = p1 >-> (p2 >-> p3) ``` Therefore we can just leave out the parentheses: ```active haskell import Control.Monad (replicateM_) import Pipes import qualified Pipes.Prelude as Pipes import Prelude hiding (take) take :: Int -> Pipe a a IO () take n = do replicateM_ n $ do x <- await yield x lift $ putStrLn "You shall not pass!" -- show -- Exact same behavior main = runEffect $ Pipes.stdinLn >-> take 3 >-> Pipes.stdoutLn ``` `(>->)` is designed to behave like the Unix pipe operator, except with less quirks. In fact, we can continue the analogy to Unix by defining `cat` (named after the Unix `cat` utility), which reforwards elements endlessly: ```haskell cat :: Monad m => Pipe a a m r cat = forever $ do x <- await yield x ``` `cat` is the identity of `(>->)`, meaning that `cat` satisfies the following two laws: ```haskell -- Useless use of 'cat cat >-> p = p -- Forwarding output to 'cat' does nothing p >-> cat = p ``` Therefore, `(>->)` and `cat` form a `Category`, specifically the category of Unix pipes, and `Pipe`s are also composable. A lot of Unix tools have very simple definitions when written using `pipes`: ```active haskell import Control.Monad (forever) import Pipes import qualified Pipes.Prelude as Pipes -- Pipes.Prelude provides 'take', too import Prelude hiding (head) head :: Monad m => Int -> Pipe a a m () head = Pipes.take yes :: Monad m => Producer String m r yes = forever $ yield "y" main = runEffect $ yes >-> head 3 >-> Pipes.stdoutLn ``` This prints out 3 `y`s, just like the equivalent Unix pipeline: ``` $ yes | head -3 y y y $ ``` This lets us write "Haskell pipes" instead of Unix pipes. These are much easier to build than Unix pipes and we can connect them directly within Haskell for interoperability with the Haskell language and ecosystem. # ListT `pipes` also provides a ["ListT done right" implementation](http://www.haskell.org/haskellwiki/ListT_done_right). This differs from the implementation in `transformers` because this `ListT`: * obeys the monad laws, and * streams data immediately instead of collecting all results into memory. The latter property is actually an elegant consequence of obeying the monad laws. To bind a list within a `ListT` computation, combine `Select` and `each`: ```haskell import Pipes pair :: ListT IO (Int, Int) pair = do x <- Select $ each [1, 2] lift $ putStrLn $ "x = " ++ show x y <- Select $ each [3, 4] lift $ putStrLn $ "y = " ++ show y return (x, y) ``` You can then loop over a `ListT` by using `every`: ```haskell every :: Monad m => ListT m a -> Producer a m () ``` So you can use your `ListT` within a `for` loop: ```active haskell import Pipes pair :: ListT IO (Int, Int) pair = do x <- Select $ each [1, 2] lift $ putStrLn $ "x = " ++ show x y <- Select $ each [3, 4] lift $ putStrLn $ "y = " ++ show y return (x, y) -- show -- Try me! main = runEffect $ for (every pair) (lift . print) ``` ... or a pipeline: ```active haskell import Pipes import qualified Pipes.Prelude as Pipes pair :: ListT IO (Int, Int) pair = do x <- Select $ each [1, 2] lift $ putStrLn $ "x = " ++ show x y <- Select $ each [3, 4] lift $ putStrLn $ "y = " ++ show y return (x, y) -- show main = runEffect $ every pair >-> Pipes.print ``` Note that `ListT` is lazy and only produces as many elements as we request: ```active haskell import Pipes import qualified Pipes.Prelude as Pipes pair :: ListT IO (Int, Int) pair = do x <- Select $ each [1, 2] lift $ putStrLn $ "x = " ++ show x y <- Select $ each [3, 4] lift $ putStrLn $ "y = " ++ show y return (x, y) -- show -- Try me! main = runEffect $ for (every pair >-> Pipes.take 2) (lift . print) ``` You can also go the other way, binding `Producer`s directly within a `ListT`. In fact, this is actually what `Select` was already doing: ```haskell Select :: Producer a m () -> ListT m a ``` This lets you write crazy code like: ```haskell import Pipes import qualified Pipes.Prelude as Pipes input :: Producer String IO () input = Pipes.stdinLn >-> Pipes.takeWhile (/= "quit") name :: ListT IO String name = do firstName <- Select input lastName <- Select input return (firstName ++ " " ++ lastName) ``` Here we're binding standard input non-deterministically (twice) as if it were an effectful list: ```active haskell import Pipes import qualified Pipes.Prelude as Pipes input :: Producer String IO () input = Pipes.stdinLn >-> Pipes.takeWhile (/= "quit") name :: ListT IO String name = do firstName <- Select input lastName <- Select input return (firstName ++ " " ++ lastName) -- show main = runEffect $ every name >-> Pipes.stdoutLn ``` Here is an example session using the above program: ``` > Daniel > Fischer Daniel Fischer > Wagner Daniel Wagner > quit > Donald > Stewart Donald Stewart > Duck Donald Duck > quit > quit ``` Notice how this streams out values immediately as they are generated, rather than building up a large intermediate result and then printing all the values in one batch at the end. # Tricks `pipes` is more powerful than meets the eye so this section presents some non-obvious tricks you may find useful. Many pipe combinators will work on unusual pipe types and the next few examples will use the `cat` pipe to demonstrate this. For example, you can loop over the output of a `Pipe` using `for`, which is how `map` is defined: ```haskell map :: Monad m => (a -> b) -> Pipe a b m r map f = for cat $ \x -> yield (f x) -- Read this as: For all values flowing downstream, apply 'f' ``` This is equivalent to: ```haskell map f = forever $ do x <- await yield (f x) ``` You can also feed a `Pipe` input using `(>~)`. This means we could have instead defined the `yes` pipe like this: ```haskell yes :: Monad m => Producer String m r yes = return "y" >~ cat -- Read this as: Keep feeding "y" downstream ``` This is equivalent to: ```haskell yes = forever $ yield "y" ``` You can also sequence two `Pipe`s together. This is how `drop` is defined: ```haskell drop :: Monad m => Int -> Pipe a a m r drop n = do replicateM_ n await cat ``` This is equivalent to: ```haskell drop n = do replicateM_ n await forever $ do x <- await yield x ``` You can even compose pipes inside of another pipe: ```haskell customerService :: Producer String IO () customerService = do each [ "Hello, how can I help you?" -- Begin with a script , "Hold for one second." ] Pipes.stdinLn >-> Pipes.takeWhile (/= "Goodbye!") -- Now continue with a human ``` Also, you can often use `each` in conjunction with (`~>`) to traverse nested data structures. For example, you can print all non-`Nothing` elements from a doubly-nested list: ```active haskell import Pipes main = runEffect $ (each ~> each ~> each ~> lift . print) [[Just 1, Nothing], [Just 2, Just 3]] ``` Another neat thing to know is that 'every' has a more general type: ```haskell every :: (Monad m, Enumerable t) => t m a -> Producer a m () ``` `Enumerable` generalizes `Foldable` and if you have an effectful container of your own that you want others to traverse using `pipes`, just have your container implement the `toListT` method of the `Enumerable` class: ```haskell class Enumerable t where toListT :: Monad m => t m a -> ListT m a ``` You can even use `Enumerable` to traverse effectful types that are not even proper containers, like `MaybeT`: ```active haskell import Control.Monad (guard) import Control.Monad.Trans.Maybe import Pipes import qualified Pipes.Prelude as Pipes input :: MaybeT IO String input = do str <- lift getLine guard (str /= "Fail") return str main = runEffect $ every input >-> Pipes.stdoutLn ``` # Conclusion This tutorial covers the concepts of connecting, building, and reading `pipes` code. However, this library is only the core component in an ecosystem of streaming components. Derived libraries that build immediately upon `pipes` include: * `pipes-concurrency`: Concurrent reactive programming and message passing * `pipes-parse`: Minimal utilities for stream parsing * `pipes-safe`: Resource management and exception safety for @pipes@ These libraries provide functionality specialized to common streaming domains. Additionally, there are several libraries on Hackage that provide even higher-level functionality, which you can find by searching under the "Pipes" category or by looking for packages with a `pipes-` prefix in their name. Current examples include: * `pipes-network`/`pipes-network-tls`: Networking * `pipes-zlib`: Compression and decompression * `pipes-binary`: Binary serialization * `pipes-attoparsec`: High-performance parsing * `pipes-aeson`: JSON serialization and deserialization Even these derived packages still do not explore the full potential of `pipes` functionality, which actually permits bidirectional communication. Advanced `pipes` users can explore this library in greater detail by studying the documentation in [the `Pipes.Core` module](http://hackage.haskell.org/package/pipes-4.1.0/docs/Pipes-Core.html) to learn about the symmetry of the underlying `Proxy` type and operators. To learn more about `pipes`, ask questions, or follow `pipes` development, you can subscribe to [the `haskell-pipes` mailing list](https://groups.google.com/forum/#!forum/haskell-pipes) or you can [mail the list directly](mailto:haskell-pipes@googlegroups.com).