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An asynchronous effect monad and threading model for PureScript.

main = launchAff do
  response <- Ajax.get ""
  log response.body


bower install purescript-aff


An example of Aff is shown below:

deleteBlankLines path = do
  contents <- loadFile path
  let contents' = S.join "\n" $ A.filter (\a -> S.length a > 0) (S.split "\n" contents)
  saveFile path contents'

This looks like ordinary, synchronous, imperative code, but actually operates asynchronously without any callbacks. Error handling is baked in so you only deal with it when you want to.

The library contains instances for Semigroup, Monoid, Apply, Applicative, Bind, Monad, Alt, Plus, MonadEffect, MonadError, and Parallel. These instances allow you to compose asynchronous code as easily as Effect, as well as interop with existing Effect code.

Escaping Callback Hell

Hopefully, you're using libraries that already use the Aff type, so you don't even have to think about callbacks!

If you're building your own library, then you can make an Aff from low-level Effect callbacks with makeAff.

makeAff :: forall a. ((Either Error a -> Effect Unit) -> Effect Canceler) -> Aff a

This function expects you to provide a handler, which should call the supplied callback with the result of the asynchronous computation.

You should also return Canceler, which is just a cleanup effect. Since Aff threads may be killed, all asynchronous operations should provide a mechanism for unscheduling it.

Effect.Aff.Compat provides functions for easily binding FFI definitions:

exports._ajaxGet = function (request) { // accepts a request
  return function (onError, onSuccess) { // and callbacks
    var req = doNativeRequest(request, function (err, response) { // make the request
      if (err != null) {
        onError(err); // invoke the error callback in case of an error
      } else {
        onSuccess(response); // invoke the success callback with the reponse

    // Return a canceler, which is just another Aff effect.
    return function (cancelError, cancelerError, cancelerSuccess) {
      req.cancel(); // cancel the request
      cancelerSuccess(); // invoke the success callback for the canceler
foreign import _ajaxGet :: Request -> EffectFnAff Response

We can wrap this into an asynchronous computation like so:

ajaxGet :: Request -> Aff Response
ajaxGet = fromEffectFnAff <<< _ajaxGet

This eliminates callback hell and allows us to write code simply using do notation:

example = do
  response <- ajaxGet req
  log response.body


All purely synchronous computations (Effect) can be lifted to asynchronous computations with liftEffect defined in Effect.Class.

liftEffect $ log "Hello world!"

This lets you write your whole program in Aff, and still call out to synchronous code.

Dealing with Failure

Aff has error handling baked in, so ordinarily you don't have to worry about it.

When you need to deal with failure, you have a few options.

  1. Alt
  2. MonadError
  3. Bracketing

1. Alt

Because Aff has an Alt instance, you may also use the operator <|> to provide an alternative computation in the event of failure:

example = do
  result <- Ajax.get "" <|> Ajax.get ""
  pure result

2. MonadError

Aff has a MonadError instance, which comes with two functions: catchError, and throwError.

These are defined in purescript-transformers. Here's an example of how you can use them:

example = do
  resp <- Ajax.get "" `catchError` \_ -> pure defaultResponse
  when (resp.statusCode /= 200) do
    throwError myErr
  pure resp.body

3. Bracketing

Aff threads can be cancelled, but sometimes we need to guarantee an action gets run even in the presence of exceptions or cancellation. Use bracket to acquire resources and clean them up.

example =
    (openFile myFile)
    (\file -> closeFile file)
    (\file -> appendFile "hello" file)

In this case, closeFile will always be called regardless of exceptions once openFile completes.


Using forkAff, you can "fork" an asynchronous computation, which means that its activities will not block the current thread of execution:

forkAff myAff

Because Javascript is single-threaded, forking does not actually cause the computation to be run in a separate thread. Forking just allows the subsequent actions to execute without waiting for the forked computation to complete.

Forking returns a Fiber a, representing the deferred computation. You can kill a Fiber with killFiber, which will run any cancelers and cleanup, and you can observe a Fiber's final value with joinFiber. If a Fiber threw an exception, it will be rethrown upon joining.

example = do
  fiber <- forkAff myAff
  killFiber (error "Just had to cancel") fiber
  result <- try (joinFiber fiber)
  if isLeft result
    then (log "Canceled")
    else (log "Not Canceled")

Parallel Execution

The Parallel instance for Aff makes writing parallel computations a breeze.

Using parallel from Control.Parallel will turn a regular Aff into ParAff. ParAff has an Applicative instance which will run effects in parallel, and an Alternative instance which will race effects, returning the one which completes first (canceling the others). To get an Aff back, just run it with sequential.

-- Make two requests in parallel
example =
  sequential $
    Tuple <$> parallel (Ajax.get "")
          <*> parallel (Ajax.get "")
-- Make a request with a 3 second timeout
example =
  sequential $ oneOf
    [ parallel (Just <$> Ajax.get "")
    , parallel (Nothing <$ delay (Milliseconds 3000.0))
tvShows =
  [ "Stargate_SG-1"
  , "Battlestar_Galactica"
  , "Farscape"

getPage page =
  Ajax.get $ "" <> page

-- Get all pages in parallel
allPages = parTraverse getPage tvShows

-- Get the page that loads the fastest
fastestPage = parOneOfMap getPage tvShows

API documentation is published on Pursuit.