A pull-based approach to streaming data.
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Conduits are an approach to the streaming data problem. It is meant as an alternative to enumerators/iterators, hoping to address the same issues with different trade-offs based on real-world experience with enumerators.

Current Documentation

The most up-to-date documentation is available in the Data.Conduit module itself, which is available for reading on Hackage.

The remainder of the contents of this page are kept for historical reasons, to give an idea of the original driving factors behind conduit. Note that plenty of the descriptions of the current state of the package are inaccurate.

General Goal

Let's start by defining the goal of enumerators, iterators, and conduits. We want a standard interface to represent streaming data from one point to another, possibly modifying the data along the way.

This goal is also achieved by lazy I/O; the problem with lazy I/O, however, is that of deterministic resource cleanup. That is to say, with lazy I/O, you cannot be guaranteed that your file handles will be closed as soon as you have finished reading data from them.

We want to keep the same properties of constant memory usage from lazy I/O, yet have guarantees that scarce resources will be freed as early as possible.


Note: This is biased towards John Millikin's enumerator package, as that is the package with which I have the most familiarity.

The concept of an enumerator is fairly simple. We have an Iteratee which "consumes" data. It keeps its state while being fed data by an Enumerator. The Enumerator will feed data a few chunks at a time to an Iteratee, transforming the Iteratee's state at each call. Additionally, there is an Enumeratee that acts as both an Enumerator and Iteratee.

As a result, there are a few changes to code structure that need to take place in order to fully leverage enumerators:

  • The Enumerators control code flow. This is an Inversion of Control (IoC) technique.

    Practical ramification: Iteratee code can be more difficult to structure. Note that this is a subjective opinion, noted by many newcomers to the enumerator paradigm.

    Requirement: Nothing specific, likely addressing the requirements below will automatically solve this.

  • Iteratees are not able to allocate scarce resources. Since they do not have any control of the flow of the program, they cannot guarantee that the resources will be released, especially in the presence of exceptions.

    Practical ramification: There is no way to create an iterFile, which will stream data into a file. Instead, you must allocate a file handle before entering the Iteratee and pass that in. In some cases, such an approach would mean file handles are kept open too long.

    Clarification: It is certainly possible to write iterFile, but there are no guarantees that it will close the allocated Handle, since the calling Enumerator may throw an exception before sending an EOF to the Iteratee.

    Requirement: We need a solution which would allow code something like the following to correctly open and close file handles, even in the presence of exceptions.

    run $ enumFile "input.txt" $$ iterFile "output.txt"
  • None of this plays nicely with monad transformers, though this does not seem to be an inherent problem with enumerators, instead with the current library.

    Practical ramification: You cannot enumerate a file when running in a ReaderT IO.

__Requirement__: The following pseudo-code should work:

     runReaderT (run $ enumFile "input" $$ iterFile "output") ()
  • Instead of passing around a Handle to pull data from, your code should live inside an Iteratee. This makes it difficult and/or impossible to interleave two different sources.

    Practical ramification: Even with libraries designed to interoperate (like http-enumerator and warp), it is not possible to create a proper streaming HTTP proxy.

    Note: This might actually be possible using the "nested iteratee" technique. I would still posit that this is far too complicated a solution to the problem.

    Requirement: It should be possible to pass around some type of producer which will be called piecemeal. For example, the request body in Warp should be expressible as:

    data Request = Request
        { ...
        , requestBody :: Enumerator ByteString IO ()

    Applications should be able to do something like:

    bs <- requestBody req $$ takeBytes 10
    someAction bs
    rest <- requestBody req $$ takeRest
    finalAction rest

    Note that there may be other approaches to solving the same problem, this is just one possibility.

  • While the concepts are simple, actually writing low-level Iteratee code is very complex. This in turn intimidates users from adopting the approach. Again, this is a subjective measurement.

    Requirement: Newcomers should be able to easily understand how to use the package, and with a little more training feel comfortable writing their own producers/consumers.


Conduits attempt to provide a similar high-level API to enumerators, while providing a drastically different low-level implementation. The first question to visit is: why does the enumerator need to control flow of the program? The main purpose is to ensure that resources are released properly. But this in fact solved only half the problem; iteratees still cannot release resources.


So our first issue to address is to create a new way to deal with resource allocation. We represent this as a monad transformer, ResourceT. It works as follows:

  • You can register a cleanup action, which will return a ReleaseKey.

  • If you pass your ReleaseKey to the release function, your action will be called automatically, and your action will be unregistered.

  • When the monad is exited (via runRelease), all remaining registered actions will be called.

  • All of this is provided in an exception-safe manner.

For example, you would be able to open a file handle, and then register an action to close the file handle. In your code, you would call release on your ReleaseKey as soon as you reach the end of the contents you are streaming. If that code is never reached, the file handle will be released when the monad terminates.


Now that we have a way to deal with resources, we can take a radically different approach to production of data streams. Instead of a push system, where the enumerators sends data down the pipeline, we have a pull system, where data is requested from the source. Additionally, a source allows buffering of input data, so data can be "pushed back" onto the source to be available for a later call.


A Sink is the corollary to an Iteratee. It takes a stream of data, and can return a result, consisting of leftover input and an output. Like an Iteratee, a Sink provides a Monad instance, which allows easy chaining together of Sinks.

However, a big difference is that your code needn't live in the Sink monad. You can easily pass around your sources and connect them to different Sinks. As a practical example, when the Web Application Interface (WAI) is translated to conduits, the application lives in the ResourceT IO monad, and the Request value contains a requestBody record, which is a Source IO ByteString.


Conduits are simply functions that take a stream of input data and return leftover input as well as a stream of output data. Conduits are far simpler to implement than their corollary, Enumeratees.


While you can directly pull data from a Source, or directly push to a Sink, the easiest approach is to use the built-in connect operators. These follow the naming convention from the enumerator package, e.g.:

sourceFile "myfile.txt" $$ sinkFile "mycopy.txt"
sourceFile "myfile.txt" $= uppercase {- a conduit -} $$ sinkFile "mycopy.txt"
fromList [1..10] $$ Data.Conduit.List.map (+ 1) =$ fold (+) 0


Overall, the approach achieves the goals I had hoped for. The main downside in its current form is its reliance on mutable data. Instead of having an Iteratee return a new Iteratee, thereby provide an illusion of mutability, in conduit the sources and sinks must maintain their state internally. As a result, code must live in IO and usually use something like an IORef to keep track of the current state.

I believe this to be an acceptable trade-off, since:

  1. Virtually all conduit code will be performing I/O, so staying in the IO monad is reasonable.
  2. By using monad-control, conduit can work with any monad based on IO, meaning all standard transformers (except ContT) can be used.
  3. Enumerator experience has shown that the majority of the time, you construct Iteratees by using built-in functions, such as fold and map. Therefore, the complication of tracking mutable state will usually be abstracted from users.

Another minor point is that, in order to provide an efficient Monad instance, the Sink type is complicated with tracking two cases: a Sink which expects data and one which does not. As expressed in point (3) above, this should not have a major impact for users.

Finally, since most Sources and Sinks begin their life by allocating some mutable variable, both types allow some arbitrary monadic action to be run before actual processing begins. The monad (et al) instances and connect functions are all built to run this action once and then continue operation.


This is currently no more than a proof-of-concept, to see the differences between enumerators and conduits for practical problems. This may serve as a basis for WAI and Yesod in the future, but that will only be after careful vetting of the idea. Your input is greatly appreciated!


This is just a collection of my personal notes, completely unorganized.

  • In enumerator, it's relatively easy to combined multiple Iteratees into an Enumeratee. The equivalent (turning Sinks into a Conduit) is harder. See, for example, chunking in http-conduit. Perhaps this can be improved with a better sequence.

  • Names and operators are very long right now. Is that a feature or a bug?

  • Should we use Vector in place of lists?

  • It might be worth transitioning to RegionT. Will the extra type parameter scare people away?

  • Perhaps the whole BSource/BConduit concept doesn't need to be exposed to the user. Advantage of exposing: it makes it obvious at the type level that a source/conduit can be reused, and possibly more efficient implementations (no double buffering). Disadvantage: more functions to implement/user to keep track of, so harder to use.

  • I dislike the travesty which is type FilePath = [Char], so I'm using the system-filepath package. I've used it for a lot of internal code at work, and it performs wonderfully. If anyone is concerned about this approach, let me know.

  • Should we rename ConduitM to Conduit (et al), and then give Conduit a name like ConduitRaw? After all, users interact with the current "M" versions more often than anything else.