name: streaming
version: 0.1.0.19
cabal-version: >=1.10
build-type: Simple
synopsis: an elementary streaming prelude and a free monad transformer optimized for streaming applications
description: /A. The freely-developed stream on a streamable functor/
.
@Stream@ can be used wherever
is used. The compiler's
standard range of optimizations work better for operations
written in terms of `Stream`. @FreeT f m r@ and @Stream f m r@
are of course extremely general, and many functor-general combinators
are exported by the general module @Streaming@.
.
/B. The general idea of streaming/
.
As soon as you consider the idea of an effectful stream of any kind
whatsoever, for example, a stream of bytes from a handle, however
constituted, you will inevitably be forced to contemplate the
idea of a streaming /succession/ of /such streams/. Thus, for example,
however you imagine your bytes streaming from a handle,
you will want to consider a /succession/ of /such streams/ divided
on newlines. Similarly, suppose you have the idea the unfolding of
some sort of stream from a Haskell value, a seed - a file name,
as it might be. And suppose you /also/ have some idea of a stream of
such Haskell values - maybe a stream of file names coming from
something like @du@, subjected
to some filter. Then you will also have the idea of a streaming
/succession/ of /such unfoldings/ linked together end to end in
accordance with the initial succession of seed values.
.
Call those 5 sentences the ABCs of streaming. If you understood these ABCs
you have a total comprehension of @Stream f m r@.
.
* @Stream@ itself expresses what the word "succession" meant in the ABCs
.
* The general parameter @f@ expresses what was meant by "such streams"
.
* @m@ expresses the relevant form of "effect".
.
General combinators for working with this idea of succession irrespective
of the form of succession are
contained in the module @Stream@. They can be used, or example,
to organize a succession of io-streams @Generator@s or pipes
@Producer@s or the effectful
bytestreams of the library,
or whatever stream-form you can express in a Haskell functor.
.
/C. A freely generated stream of/ connected individual Haskell values /is a Producer, Generator or Source/
.
But, of course, as soon as you grasp the general form of /succession/,
you are already in possession of the most basic concrete form: a simple
/succession of individual Haskell values/ one after another.
This is just @Stream ((,) a) m r@, or as we write it here,
@Stream (Of a) m r@, strictifying the left element of the pair.
The pairing just links the present element with the rest of the
stream. The primitive @yield@ statement just expresses the
pairing of the yielded item with the rest of the stream; or rather
it is itself the trivial singleton stream.
@Streaming.Prelude@ is focused on the manipulation of this
all-important stream-form, which appears in the streaming
IO libraries under titles like:
.
> io-streams: Generator a r
> pipes: Producer a m r
> conduit: ConduitM () o m r
> streaming: Stream (Of a) m r
.
The only difference is that in @streaming@ the simple Generator or Producer
concept is formulated explicitly in terms of the
/general/ concept of successive connection. But this is
a concept you need and already possess anyway, as your comprehension of
the four sentences above showed.
.
The special case of a
/stream of individual Haskell values/
that simply /comes to an end without a special result/ is variously
expressed thus:
.
> io-streams: InputStream a
> pipes: Producer a m ()
> conduit: Source m a
> machines: SourceT m a (= forall k. MachineT m k a)
> streaming: Stream (Of a) m ()
.
/D./ @Streaming.Prelude@
.
@Streaming.Prelude@ closely follows @Pipes.Prelude@.
But since it restricts itself to use
only of the general idea of streaming, it cleverly /omits the pipes/:
.
> ghci> S.stdoutLn $ S.take 2 S.stdinLn
> let's
> let's
> stream
> stream
.
Here's a little /connect and resume/, as the streaming-io experts call it:
.
> ghci> rest <- S.print $ S.splitAt 3 $ S.each [1..10]
> 1
> 2
> 3
> ghci> S.sum rest
> 49
.
Somehow, we didn't even need a four-character operator for that, nor advice
about best practices! - just ordinary Haskell common sense.
.
/E. Mother's/ @Prelude@ /vs./ @Streaming.Prelude@
.
The effort of
@Streaming.Prelude@ is to leverage the intuition the user has acquired
in mastering @Prelude@ and @Data.List@ and to elevate her understanding
into a general comprehension of effectful streaming transformations.
Unsurprisingly, it takes longer to type out
the signatures. It cannot be emphasized enough, thought, that
/the transpositions are totally mechanical/:
.
> Data.List.Split.chunksOf :: Int -> [a] -> [[a]]
> Streaming.chunksOf :: Int -> Stream f m r -> Stream (Stream f m) m r
.
> Prelude.splitAt :: Int -> [a] -> ([a],[a])
> Streaming.splitAt :: Int -> Stream f m r -> Stream f m (Stream f m r)
.
These concepts are "functor general", in the jargon used in the documentation,
and are thus exported by the main @Streaming@ module.
Something like @break@ requires us to inspect individual values for
their properties, so it is found in the @Streaming.Prelude@
.
> Prelude.break :: (a -> Bool) -> [a] -> ([a],[a])
> Streaming.Prelude.break :: (a -> Bool) -> Stream (Of a) m r -> Stream (Of a) m (Stream (Of a) m r)
.
It is easy to prove that /resistance to these types is resistance to effectful streaming itself/.
I will labor this point a bit more below, but you can also find it developed, with
greater skill, in the documentation for the pipes libraries.
.
/F. How come there's not one of those fancy "ListT done right" implementations in here?/
.
The use of the final return value appears to be a complication, but in fact
it is essentially contained in the idea of effectful streaming. This is why
this library does not export a /ListT done right/, which would be simple enough -
following @pipes@, as usual:
.
> newtype ListT m a = ListT (Stream (Of a) m ())
.
The associated monad instance would wrap
.
> yield :: (Monad m) => a -> Stream (Of a) m ()
> for :: (Monad m, Functor f) => Stream (Of a) m r -> (a -> Stream f m ()) -> Stream f m r
.
To see the trouble, consider
for splitting a ListT very much done right. Here's what becomes of
.
As long as we are trapped in ListT, however much rightly implements, these operation can't be made to stream;
something like a list must be accumulated. Similarly, try to imagine
adding a @splitAt@ or @lines@ function to
.
It would accumulate strict text forever, just as
and and
The difference is simply that the latter libraries operate with the general concept of streaming, and
the whole implementation is governed by it.
The attractions of the various "@ListT@ done right" implementations are superficial; the concept
belongs to logic programming, not stream programming.
.
Note similarly that you can write a certain kind of
and
with the
@machines@ library - as you can even with a "@ListT@ done right". But I
wish you luck writing @splitAt@! Similarly you can write a
;
but I wish you luck dividing the resulting bytestream on its lines.
This is - as usual! - because the library was not written with the general concept of
effectful succession or streaming in view. Materials for
sinking some elements of a stream in one way, and others in other ways - copying
each line to a different file, as it might be, but without accumulation
- are documented within. So are are myriad other elementary operations of streaming io.
.
/G. Didn't I hear that free monads are a dog from the point of view of efficiency?/
.
We noted above that if we instantiate @Stream f m r@ to @Stream ((,) a) m r@
or the like, we get the standard idea of a producer or generator.
If it is instantiated to @Stream f Identity m r@ then we have
the standard /free monad construction/. This construction is subject to
certain familiar
objections from an efficiency perspective; efforts have been made to
substitute exotic cps-ed implementations and so forth.
It is an interesting topic.
.
But in fact, the standard alarmist talk about /retraversing binds/ and /quadratic explosions/ and
/costly appends/, and so on become __transparent__ nonsense with @Stream f m r@
in its streaming use. The conceptual power needed to see this is
basically nil: Where @m@ is read as
@IO@, or some transformed @IO@, then the dreaded /retraversing of the binds/
in a stream expression would involve repeating all the past actions. Don't worry, to get e.g. the
second chunk of bytes from a handle, you won't need to start over and get the first
one again! The first chunk has vanished into an unrepeatable past.
.
All of the difficulties a streaming library is attempting to avoid
are concentrated in the deep irrationality of
.
> sequence :: (Monad m, Traversable t) => t (m a) -> m (t a)
.
In the streaming context, this becomes
.
> sequence :: Monad m, Functor f => Stream f m r -> Stream f m r
> sequence = id
.
It is of course easy enough to define
.
> accumulate :: Monad m, Functor f => Stream f m r -> m (Stream f Identity r)
.
or @reifyBindsRetraversingWherePossible@ or @_ICan'tTakeThisStreamingAnymore@,
as you might call it. /The types themselves/
teach the user how to avoid or control the sort of accumulation
characteristic of @sequence@ in its various guises e.g. @mapM f = sequence . map f@ and
@traverse f = sequence . fmap f@ and @replicateM n = sequence . replicate n@.
See for example the types of
.
> Control.Monad.replicateM :: Int -> m a -> m [a]
> Streaming.Prelude.replicateM :: Int -> m a -> Stream (Of a) m ()
.
If you want to tempt fate and replicate the irrationality of @Control.Monad.replicateM@,
then sure, you can define the hermaphroditic chimera
.
> accumulate . Streaming.Prelude.replicateM :: Int -> m a -> m (Stream (Of a) Identity ())
.
which is what we find in our diseased base libraries.
But once you know how to operate with a stream directly you will see less and less point
in what is called /extracting the (structured) value from IO/. The
distinction between
.
> "getContents" :: String
.
and
.
> getContents :: IO String
.
but, omitting consideration of eof, we might define @getContents@ thus
.
> getContents = sequence $ repeat getChar
.
There it is again! The very devil! By contrast there is no distinction
between
.
> "getContents" :: Stream (Of Char) m ()
.
and
.
> getContents :: MonadIO m => Stream (Of Char) m ()
.
They unify just fine. That is, if I make the type synonym
.
> type String m r = Stream (Of Char) m r
.
I get, for example:
.
> "getLine" :: String m ()
> getLine :: String IO ()
> "getLine" >> getLine :: String IO ()
> splitAt 20 $ "getLine" >> getLine :: String IO (String IO ())
> length $ "getLine" >> getLine :: IO Int
.
and can dispense with half the advice they will give you on @#haskell@.
It is only a slight exaggeration to say that a stream should never be "extracted from IO".
.
With @sequence@ and @traverse@,
we accumulate a pure succession of pure values from a pure
succession of monadic values.
Why bother if you have intrinsically monadic conception of
succession or traversal? @Stream f m r@
gives you an immense body of such structures and a
simple discipline for working with them. Spinkle @id@ freely
though your program if you get homesick.
.
/H. Interoperation with the streaming-io libraries/
.
The simplest form of interoperation with
is accomplished with this isomorphism:
.
> Pipes.unfoldr Streaming.next :: Stream (Of a) m r -> Producer a m r
> Streaming.unfoldr Pipes.next :: Producer a m r -> Stream (Of a) m r
.
Of course, @streaming@ can be mixed with @pipes@ wherever @pipes@
itself employs @Control.Monad.Trans.Free@; speedups are frequently
appreciable. (This was the original purpose of the main @Streaming@ module,
which just mechanically transposes a simple optimization employed in @Pipes.Internal@.)
Interoperation with
is thus:
.
> Streaming.reread IOStreams.read :: InputStream a -> Stream (Of a) IO ()
> IOStreams.unfoldM Streaming.uncons :: Stream (Of a) IO () -> IO (InputStream a)
.
A simple exit to would be, e.g.:
.
> Conduit.unfoldM Streaming.uncons :: Stream (Of a) m () -> Source m a
.
These conversions should never be more expensive than a single @>->@ or @=$=@.
.
At a much more general level, we also of course have interoperation with
:
.
> Free.iterTM Stream.wrap :: FreeT f m a -> Stream f m a
> Stream.iterTM Free.wrap :: Stream f m a -> FreeT f m a
.
/I. Where can I find examples of use?/
.
For some simple ghci examples, see the commentary throughout the Prelude module.
For slightly more advanced usage see the commentary in the haddocks of
and e.g.
of shell-like programs from
the io-streams tutorial.
Here's a simple with
intrinsically streaming byte streams.
.
/J. Problems/
.
Questions about this library can be put as issues through the github site or
on the .
(This library understands itself as part of the pipes "ecosystem.")
license: BSD3
license-file: LICENSE
author: michaelt
maintainer: what_is_it_to_do_anything@yahoo.com
stability: Experimental
homepage: https://github.com/michaelt/streaming
bug-reports: https://github.com/michaelt/streaming/issues
category: Data, Pipes, Streaming
extra-source-files: README.md
source-repository head
type: git
location: https://github.com/michaelt/streaming
library
exposed-modules: Streaming,
Streaming.Prelude,
Streaming.Internal
-- other-modules:
other-extensions: RankNTypes, CPP,
StandaloneDeriving, FlexibleContexts,
DeriveDataTypeable, DeriveFoldable,
DeriveFunctor, DeriveTraversable,
UndecidableInstances
build-depends: base >=4.6 && <5
, mtl >=2.1 && <2.3
, mmorph >=1.0 && <1.2
, transformers >=0.4 && <0.5
, bytestring
default-language: Haskell2010