Lightweight composable continuation-based stream processors

Version on this page:
LTS Haskell 21.25:
Stackage Nightly 2024-06-13:
Latest on Hackage:

See all snapshots conduino appears in

BSD-3-Clause licensed by Justin Le
Maintained by [email protected]
This version can be pinned in stack with:conduino-,1621

Module documentation for


A lightweight continuation-based stream processing library.

It is similar in nature to pipes and conduit, but useful if you just want something quick to manage composable stream processing without focus on IO.

Why a stream processing library?

A stream processing library is a way to stream processors in a composable way: instead of defining your entire stream processing function as a single recursive loop with some global state, instead think about each “stage” of the process, and isolate each state to its own segment. Each component can contain its own isolated state:

runPipePure $ sourceList [1..10]
           .| scan (+) 0
           .| sinkList
-- [1,3,6,10,15,21,28,36,45,55]

All of these components have internal “state”:

  • sourceList keeps track of “which” item in the list to yield next
  • scan keeps track of the current running sum
  • sinkList keeps track of all items that have been seen so far, as a list

They all work together without knowing any other component’s internal state, so you can write your total streaming function without concerning yourself, at each stage, with the entire part.

In addition, there are useful functions to “combine” stream processors:

  • zipSink combines sinks in an “and” sort of way: combine two sinks in parallel and finish when all finish.
  • altSink combines sinks in an “or” sort of way: combine two sinks in parallel and finish when any of them finish
  • zipSource combines sources in parallel and collate their outputs.

Stream processing libraries are also useful for streaming composition of monadic effects (like IO or State), as well.

Details and usage

API-wise, is closer to conduit than pipes. Pull-based, where the main “running” function is:

runPipe :: Pipe () Void u m a -> m a

That is, the “production” and “consumption” is integrated into one single pipe, and then run all at once. Contrast this to pipes, where consumption is not integrated into the pipe, but rather your choice of “runner” determines how your pipe is consumed.

One extra advantage over conduit is that we have the ability to model pipes that will never stop producing output, so we can have an await function that can reliably fetch items upstream. This matches more pipes-style requests.

For a Pipe i o u m a, you have:

  • i: Type of input stream (the things you can await)
  • o: Type of output stream (the things you yield)
  • u: Type of the result of the upstream pipe (Outputted when upstream pipe terminates)
  • m: Underlying monad (the things you can lift)
  • a: Result type when pipe terminates (outputted when finished, with pure or return)

Some specializations:

  • If i is (), the pipe is a source — it doesn’t need anything to produce items. It will pump out items on its own, for pipes downstream to receive and process.

  • If o is Void, the pipe is a sink — it will never yield anything downstream. It will consume items from things upstream, and produce a result (a) if and when it terminates.

  • If u is Void, then the pipe’s upstream is limitless, and never terminates. This means that you can use awaitSurely instead of await, to get await a value that is guaranteed to come. You’ll get an i instead of a Maybe i.

    await       :: Pipe i o u m (Maybe i)
    awaitsurely :: Pipe i o Void m i
  • If a is Void, then the pipe never terminates — it will keep on consuming and/or producing values forever. If this is a sink, it means that the sink will never terminate, and so runPipe will also never terminate. If it is a source, it means that if you chain something downstream with .|, that downstream pipe can use awaitSurely to guarantee something being passed down.

Usually you would use it by chaining together pipes with .| and then running the result with runPipe.

runPipe $ someSource
       .| somePipe
       .| someOtherPipe
       .| someSink

Why does this package exist?

This package is taking some code I’ve used some closed-source projects and pulling it out as a full library. I wrote it, despite the existence of pipes and conduit, because:

  1. I wanted conduit-style semantics for stream composition (source - producer - sink all in one package).
  2. I wanted type-enforced guaranteed “awaits” based on type-enforced guaranteed infinite producers.
  3. I wanted to be able to combine stream processors “in parallel” in different ways (zipSink, for “and”, and altSink, for “or”).
  4. I wanted something lightweight without the dependencies dealing with IO, since I wasn’t really doing resource-sensitive IO.

conduino is a small, lightweight version that is focused not necessarily on “effects” streaming, but rather on composable bits of logic. It is basically a lightweight version of conduit-style streaming. It is slightly different from pipes in terms of API.

One major difference from conduit is the u parameter, which allows for things like awaitSurely, to ensure that upstream pipes will never terminate.

If you need to do some important IO and handle things like managing resources, or leverage interoperability with existing libraries…switch to a more mature library like conduit or pipes immediately :)




January 7, 2020

  • Added feedbackEither for more flexibility on top of feedback
  • Some documentation cleanup


January 7, 2020

  • hoistPipe exported from Data.Conduit
  • A handful of pipe primitive combinators added to Data.Conduit, including:
    • feedbackPipe
    • zipPipe
    • &| / fuseBoth
    • |. / fuseUpstream
    • fuseBothMaybe
  • Some pipe runners added to Data.Conduit, including:
    • squeezePipe / squeezePipeEither
    • feedPipe / feedPipeEither
  • Data.Conduit.Lift module, for working with monad transformers
  • iterM added to Data.Conduit.Combinators


October 30, 2019

  • Initial release


(Accidental incomplete release made by mistake)