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# Streamly
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2017-08-31 03:59:22 +03:00
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2017-11-20 21:51:27 +03:00
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[](https://gitter.im/composewell/streamly)
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[](https://travis-ci.org/harendra-kumar/streamly)
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[](https://ci.appveyor.com/project/harendra-kumar/streamly)
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2017-11-20 15:33:13 +03:00
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[](https://coveralls.io/github/harendra-kumar/streamly?branch=master)
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2017-09-04 13:37:46 +03:00
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2017-11-21 12:11:09 +03:00
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## Stream`ing` `Concurrent`ly
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Streamly unifies concurrency and streaming in a single monad transformer with a
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concise and simple API. It provides two ways to combine streams, a monadic
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product composition as well as the standard pipelined composition provided by
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streaming libraries. A natural extension of regular monadic composition to
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2017-11-21 20:46:45 +03:00
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streaming and concurrency makes it intuitive and concise with almost universal
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application. You can write concurrent or non-concurrent applications using
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simple IO, logic programming, streaming IO or reactive programming (FRP) using
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the same API. You can also think about it as representing concurrent and
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composable state machines in imperative terms. It unifies the core
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functionality provided by [async](https://hackage.haskell.org/package/async),
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[logict](https://hackage.haskell.org/package/logict),
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[list-t](https://hackage.haskell.org/package/list-t),
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[conduit](https://hackage.haskell.org/package/conduit)\/[pipes](https://hackage.haskell.org/package/pipes),
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[Yampa](https://hackage.haskell.org/package/Yampa)\/[reflex](https://hackage.haskell.org/package/reflex)
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under one type and API. It interworks with the existing streaming libraries.
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## Magical Concurrency
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Streamly provides high level concurrency primitives (higher level than async)
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and hides the low level concurrency details completely from the programmer.
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Concurrency can be used with ease in applicative or monadic contexts. The
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programmer just expresses whether a task can run in parallel with another.
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Threads, synchronization and concurrency rate control are handled
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automatically under the hood. The concurrency facilities provided by streamly
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can be compared with [OpenMP](https://en.wikipedia.org/wiki/OpenMP) and
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[Cilk](https://en.wikipedia.org/wiki/Cilk) but with a more declarative
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expression. Concurrency support does not compromise performance in
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non-concurrent cases, the performance of the library is at par or better than
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most of the existing streaming libraries.
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## Example
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Here is a simple example to concurrently and recursively list the contents of a
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directory tree:
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``` haskell
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import Path.IO (listDir, getCurrentDir)
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import Streamly
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main = runStreaming $ serially $ getCurrentDir >>= readdir
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where readdir d = do
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(dirs, files) <- lift $ listDir d
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liftIO $ mapM_ putStrLn $ map show files
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foldMapWith (<|>) readdir dirs
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```
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See "Streamly.Tutorial" and "Streamly.Examples" for more details.
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This library was originally inspired by the `transient`
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package authored by Alberto G. Corona.
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