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update README and cabal description
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Harendra Kumar
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README.md
79
README.md
@ -8,56 +8,55 @@
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## Stream`ing` `Concurrent`ly
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Streamly, short for streaming concurrently, is a simple yet powerful streaming
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library with concurrent merging and concurrent nested looping support. A stream
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is just like a list except that it is a list of monadic actions rather than
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pure values. Streamly streams can be generated, consumed, combined, or
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transformed serially or concurrently. We can loop over a stream serially or
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concurrently. We can also have serial or concurrent nesting of loops. For
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those familiar with the list transformer concept streamly is a concurrent list
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transformer. Streamly uses standard composition abstractions. Concurrent
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composition is just the same as serial composition except that we use a simple
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combinator to request a concurrent composition instead of serial. The
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programmer does not have to be aware of threads, locking or synchronization to
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write scalable concurrent programs.
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Streamly, short for streaming concurrently, provides monadic streams, with a
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simple API, almost identical to standard lists, and an in-built support for
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concurrency. By using stream-style combinators on stream composition,
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streams can be generated, merged, chained, mapped, zipped, and consumed
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concurrently – providing a generalized high level programming framework
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unifying streaming and concurrency. Controlled concurrency allows even infinite
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streams to be evaluated concurrently. Concurrency is auto scaled based on
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feedback from the stream consumer. The programmer does not have to be aware of
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threads, locking or synchronization to write scalable concurrent programs.
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Streamly provides functionality that is equivalent to streaming libraries
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like [pipes](https://hackage.haskell.org/package/pipes) and
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[conduit](https://hackage.haskell.org/package/conduit) but with a list like
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API. The streaming API of streamly is close to the monadic streams API of the
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[vector](https://hackage.haskell.org/package/vector) package and similar in
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concept to the [streaming](https://hackage.haskell.org/package/streaming)
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package. In addition to providing streaming functionality, streamly subsumes
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The basic streaming functionality of streamly is equivalent to that provided by
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streaming libraries like
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[vector](https://hackage.haskell.org/package/vector),
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[streaming](https://hackage.haskell.org/package/streaming),
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[pipes](https://hackage.haskell.org/package/pipes), and
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[conduit](https://hackage.haskell.org/package/conduit).
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In addition to providing streaming functionality, streamly subsumes
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the functionality of list transformer libraries like `pipes` or
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[list-t](https://hackage.haskell.org/package/list-t) and also the logic
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[list-t](https://hackage.haskell.org/package/list-t), and also the logic
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programming library [logict](https://hackage.haskell.org/package/logict). On
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the concurrency side, it subsumes the functionality of the
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[async](https://hackage.haskell.org/package/async) package. Because it supports
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streaming with concurrency we can write FRP applications similar in concept to
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[Yampa](https://hackage.haskell.org/package/Yampa) or
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[reflex](https://hackage.haskell.org/package/reflex). To understand the
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streaming library ecosystem and where streamly fits in you may want to read
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[streaming libraries](https://github.com/composewell/streaming-benchmarks#streaming-libraries)
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as well. Also see the [Comparison with Existing
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Packages](https://hackage.haskell.org/package/streamly/docs/Streamly-Tutorial.html)
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section in the streamly tutorial.
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[reflex](https://hackage.haskell.org/package/reflex).
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Why use streamly?
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* Simple list like streaming API, if you know how to use lists then you know
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how to use streamly.
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* Powerful yet simple and scalable concurrency. Concurrency is not intrusive,
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concurrent programs are written exactly the same way as non-concurrent
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ones. There is no other package that provides such high level, simple and
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flexible concurrency support.
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* It is a general programming framework providing you all the necessary tools
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to solve a wide range of programming problems, unifying the functionality
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provided by several disparate packages in a concise and simple API.
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* Best in class performance. See
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* _Simplicity_: Simple list like streaming API, if you know how to use lists
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then you know how to use streamly. This library is built with simplicity
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and ease of use as a design goal.
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* _Concurrency_: Simple, powerful, and scalable concurrency. Concurrency is
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built-in, and not intrusive, concurrent programs are written exactly the
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same way as non-concurrent ones.
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* _Generality_: Unifies functionality provided by several disparate packages
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(streaming, concurrency, list transformer, logic programming, reactive
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programming) in a concise API.
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* _Performance_: Streamly is designed for high performance. See
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[streaming-benchmarks](https://github.com/composewell/streaming-benchmarks)
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for a comparison of popular streaming libraries on micro-benchmarks.
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For more information, see:
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For more details on streaming library ecosystem and where streamly fits in,
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please see
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[streaming libraries](https://github.com/composewell/streaming-benchmarks#streaming-libraries).
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Also, see the [Comparison with Existing
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Packages](https://hackage.haskell.org/package/streamly/docs/Streamly-Tutorial.html)
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section in the streamly tutorial.
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For more information on streamly, see:
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* [Streamly.Tutorial](https://hackage.haskell.org/package/streamly/docs/Streamly-Tutorial.html) module in the haddock documentation for a detailed introduction
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* [examples](https://github.com/composewell/streamly/tree/master/examples) directory in the package for some simple practical examples
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@ -265,7 +264,7 @@ import Path.IO (listDir, getCurrentDir)
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import Streamly
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import qualified Streamly.Prelude as S
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main = runStream $ asyncly $ getCurrentDir >>= readdir
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main = runStream $ aheadly $ getCurrentDir >>= readdir
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where readdir d = do
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(dirs, files) <- S.once $ listDir d
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S.once $ mapM_ putStrLn $ map show files
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@ -275,8 +274,8 @@ main = runStream $ asyncly $ getCurrentDir >>= readdir
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In the above examples we do not think in terms of threads, locking or
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synchronization, rather we think in terms of what can run in parallel, the rest
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is taken care of automatically. When using `asyncly` the programmer does
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not have to worry about how many threads are to be created they are
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is taken care of automatically. When using `aheadly` the programmer does
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not have to worry about how many threads are to be created, they are
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automatically adjusted based on the demand of the consumer.
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The concurrency facilities provided by streamly can be compared with
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@ -2,28 +2,25 @@ name: streamly
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version: 0.2.1
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synopsis: Beautiful Streaming, Concurrent and Reactive Composition
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description:
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Streamly, short for streaming concurrently, is a simple yet powerful
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streaming library with concurrent merging and concurrent nested looping
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support. A stream is just like a list except that it is a list of monadic
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actions rather than pure values. Streamly streams can be generated,
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consumed, combined, or transformed serially or concurrently. We can loop over
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a stream serially or concurrently. We can also have serial or concurrent
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nesting of loops. For those familiar with list transformer concept streamly
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is a concurrent list transformer. Streamly uses standard composition
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abstractions. Concurrent composition is just the same as serial composition
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except that we use a simple combinator to request a concurrent composition
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instead of serial. The programmer does not have to be aware of threads,
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locking or synchronization to write scalable concurrent programs.
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Streamly, short for streaming concurrently, provides monadic streams, with a
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simple API, almost identical to standard lists, and an in-built support for
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concurrency. By using stream-style combinators on stream composition,
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streams can be generated, merged, chained, mapped, zipped, and consumed
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concurrently – providing a generalized high level programming framework
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unifying streaming and concurrency. Controlled concurrency allows even
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infinite streams to be evaluated concurrently. Concurrency is auto scaled
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based on feedback from the stream consumer. The programmer does not have to
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be aware of threads, locking or synchronization to write scalable concurrent
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programs.
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.
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Streamly provides functionality that is equivalent to streaming libraries
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like <https://hackage.haskell.org/package/pipes pipes> and
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<https://hackage.haskell.org/package/conduit conduit> but with a simple list
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like API. The streaming API of streamly is close to the monadic streams API
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of the <https://hackage.haskell.org/package/vector vector> package and
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similar in concept to the
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<https://hackage.haskell.org/package/streaming streaming> package. In
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addition to the streaming functionality, streamly subsumes the functionality
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of list transformer libraries like @pipes@ or
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The basic streaming functionality of streamly is equivalent to that provided by
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streaming libraries like
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<https://hackage.haskell.org/package/vector vector>,
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<https://hackage.haskell.org/package/streaming streaming>,
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<https://hackage.haskell.org/package/pipes pipes>, and
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<https://hackage.haskell.org/package/conduit conduit>.
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In addition to providing streaming functionality, streamly subsumes the
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functionality of list transformer libraries like @pipes@ or
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<https://hackage.haskell.org/package/list-t list-t> and also the logic
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programming library <https://hackage.haskell.org/package/logict logict>. On
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the concurrency side, it subsumes the functionality of the
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@ -32,13 +29,25 @@ description:
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concept to <https://hackage.haskell.org/package/Yampa Yampa> or
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<https://hackage.haskell.org/package/reflex reflex>.
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.
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Streamly has excellent performance, see
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<https://github.com/composewell/streaming-benchmarks streaming-benchmarks>
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for a comparison of popular streaming libraries on micro-benchmarks. For
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file IO, currently the library provides only one API to stream the lines in
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the file as Strings. Future versions will provide better streaming file IO
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options. Streamly interworks with the popular streaming libraries, see the
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interworking section in "Streamly.Tutorial".
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For file IO, currently the library provides only one API to stream the lines
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in the file as Strings. Future versions will provide better streaming file
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IO options. Streamly interworks with the popular streaming libraries, see
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the interworking section in "Streamly.Tutorial".
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.
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Why use streamly?
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.
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* /Simplicity/: Simple list like streaming API, if you know how to use lists
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then you know how to use streamly. This library is built with simplicity
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and ease of use as a primary design goal.
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* /Concurrency/: Simple, powerful, and scalable concurrency. Concurrency is
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built-in, and not intrusive, concurrent programs are written exactly the
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same way as non-concurrent ones.
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* /Generality/: Unifies functionality provided by several disparate packages
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(streaming, concurrency, list transformer, logic programming, reactive
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programming) in a concise API.
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* /Performance/: Streamly is designed for high performance. See
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<https://github.com/composewell/streaming-benchmarks streaming-benchmarks>
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for a comparison of popular streaming libraries on micro-benchmarks.
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.
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Where to find more information:
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.
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