Package Info


An elementary streaming prelude and general stream type


This package contains two modules, < Streaming> and < Streaming.Prelude>. The principal module, < Streaming.Prelude>, exports an elementary streaming prelude focused on a simple "source" or "producer" type, namely 'Stream (Of a) m r'. This is a sort of effectful version of '([a],r)' in which successive elements of type 'a' arise from some sort of monadic action before the succession ends with a value of type 'r'. Everything in the library is organized to make programming with this type as simple as possible, by the simple expedient of making it as close to 'Prelude' and 'Data.List' as possible. Thus for example the trivial program

> >>> S.sum $ S.take 3 (S.readLn :: Stream (Of Int) IO ()) > 1<Enter> > 2<Enter> > 3<Enter> > 6 :> ()

sums the first three valid integers from user input. Similarly,

> >>> S.stdoutLn $ (map toUpper) $ S.take 2 S.stdinLn > hello<Enter> > HELLO > world!<Enter> > WORLD!

upper-cases the first two lines from stdin as they arise, and sends them to stdout. And so on, with filtering, mapping, breaking, chunking, zipping, unzipping, replicating and so forth: we program with streams of 'Int's or 'String's directly as if they constituted something like a list. That's because streams really do constitute something like a list, and the associated operations can mostly have the same names. (A few, like 'reverse', don't stream and thus disappear; others like 'unzip' are here given properly streaming formulation for the first time.) And we everywhere oppose "extracting a pure list from IO", which is the origin of typical Haskell memory catastrophes. Basically any case where you are tempted to use 'mapM', 'replicateM', 'traverse' or 'sequence' with Haskell lists, you would do better to use something like 'Stream (Of a) m r'. The type signatures are a little fancier, but the programs themselves are mostly the same. /In fact, they are mostly simpler./ Thus, consider the trivial demo program mentioned in < this SO question>

> main = mapM newIORef [1..10^8::Int] >>= mapM readIORef >>= mapM_ print

The new user notices that this exhausts memory, and worries about the efficiency of Haskell 'IORefs'. But of course it exhausts memory! Look what it says! The problem is immediately cured by writing

> main = S.print $ S.mapM readIORef $ S.mapM newIORef $ S.each [1..10^8::Int]

which really does what the other program was meant to do, uses no more memory than 'hello-world', /and is simpler anyway/, since it doesn't involve the detour of "extracting a list from IO". Almost every use of list 'mapM', 'replicateM', 'traverse' and 'sequence' produces this problem on a smaller scale. People get used to it, as if it were characteristic of Haskell programs to use a lot of memory. But in truth "extracting a list or sequence from IO" is mostly just bad practice pure and simple. Of course, 'mapM', 'replicateM', 'traverse' and 'sequence' make sense for lists, under certain conditions! But 'unsafePerformIO' also makes sense under certain conditions.

The < Streaming> module exports the general type, 'Stream f m r', which can be used to stream successive distinct steps characterized by /any/ functor 'f', though we are mostly interested in organizing computations of the form 'Stream (Of a) m r'. The streaming-IO libraries have various devices for dealing with effectful variants of '[a]' or '([a],r)' in which the emergence of successive elements somehow depends on IO. But it is only with the general type 'Stream f m r', or some equivalent, that one can envisage (for example) the connected streaming of their sorts of stream - as one makes lists of lists in the Haskell 'Prelude' and 'Data.List'. One needs some such type if we are to express properly streaming equivalents of e.g.

> group :: Ord a => [a] -> [[a]] > chunksOf :: Int -> [a] -> [[a]] > lines :: [Char] -> [[Char]] -- but similarly with byte streams, etc.

to mention a few obviously desirable operations. (This is explained more elaborately in the < readme> below.)

One could throw of course throw something like the present 'Stream' type on top of a prior stream concept: this is how 'pipes' and 'pipes-group' (which are very much our model here) use 'FreeT'. But once one grasps the iterable stream concept needed to express those functions then one will also see that, with it, one is /already/ in possession of a complete elementary streaming library - since one possesses 'Stream ((,) a) m r' or equivalently 'Stream (Of a) m r'. This is the type of a 'generator' or 'producer' or 'source' or whatever you call an effectful stream of items. /The present Streaming.Prelude is thus the simplest streaming library that can replicate anything like the API of the Prelude and Data.List/.

The emphasis of the library is on interoperation; for the rest its advantages are: extreme simplicity, re-use of intuitions the user has gathered from mastery of 'Prelude' and 'Data.List', and a total and systematic rejection of type synonyms. The two conceptual pre-requisites are some comprehension of monad transformers and some familiarity with 'rank 2 types'. It is hoped that experimentation with this simple material, starting with the ghci examples in 'Streaming.Prelude', will give people who are new to these concepts some intuition about their importance. The most fundamental purpose of the library is to express elementary streaming ideas without reliance on a complex framework, but in a way that integrates transparently with the rest of Haskell, using ideas - e.g. rank 2 types, which are here implicit or explicit in most mapping - that the user can carry elsewhere, rather than chaining her understanding to the curiosities of a so-called streaming IO framework (as necessary as that is for certain purposes.)

See the < readme> below for further explanation, including the examples linked there. Elementary usage can be divined from the ghci examples in 'Streaming.Prelude' and perhaps from this rough beginning of a < tutorial>. Note also the < streaming bytestring> and < streaming utils> packages. Questions about usage can be put raised on StackOverflow with the tag '[haskell-streaming]', or as an issue on Github, or on the <!forum/haskell-pipes pipes list> (the package understands itself as part of the pipes 'ecosystem'.)

The simplest form of interoperation with < pipes> is accomplished with this isomorphism:

> Pipes.unfoldr :: Stream (Of a) m r -> Producer a m r > Streaming.unfoldr :: Producer a m r -> Stream (Of a) m r

Interoperation with < io-streams> is thus:

> Streaming.reread :: InputStream a -> Stream (Of a) IO () > IOStreams.unfoldM Streaming.uncons :: Stream (Of a) IO () -> IO (InputStream a)

With < conduit> one might use, e.g.:

> Conduit.unfoldM Streaming.uncons :: Stream (Of a) m () -> Source m a > str -> Streaming.mapM_ Conduit.yield (hoist lift str) :: Stream (Of o) m r -> ConduitM i o m r > src -> hoist lift str $$ Conduit.mapM_ Streaming.yield :: Source m a -> Stream (Of a) m ()

These conversions should never be more expensive than a single '>->' or '=$='. The simplest interoperation with regular Haskell lists is provided by, say

> Streaming.each :: [a] -> Stream (Of a) m () > Streaming.toList_ :: Stream (Of a) m r -> m [a]

The latter of course accumulates the whole list in memory, and is mostly what we are trying to avoid. Every use of 'Prelude.mapM f' should be reconceived as using the composition 'Streaming.toList_ . Streaming.mapM f . Streaming.each' with a view to considering whether the accumulation required by 'Streaming.toList_' is really necessary.

Here are the results of some < microbenchmarks> based on the < benchmarks> included in the machines package:


Because these are microbenchmarks for individual functions, they represent a sort of "worst case"; many other factors can influence the speed of a complex program. .

License: BSD-3-Clause



Package Version Update ID Released Package Hub Version Platforms Subpackages info GA Release 2022-05-09 15 SP4
  • AArch64
  • ppc64le
  • x86-64
  • ghc-streaming
  • ghc-streaming-devel info GA Release 2018-07-30 15
  • AArch64
  • ppc64le
  • x86-64
  • ghc-streaming
  • ghc-streaming-devel