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README
Apache-2.0

Stateless Future

stateless-future is a set of DSL for asynchronous programming, in the pure functional favor.

Usage

import scala.concurrent.duration._
import scala.util.control.Exception.Catcher
import com.qifun.statelessFuture.Future

val executor = java.util.concurrent.Executors.newSingleThreadScheduledExecutor

// Manually implements a stateless future, which is the asynchronous version of `Thread.sleep()`
def asyncSleep(duration: Duration) = new Future[Unit] {
  import scala.util.control.TailCalls._
  def onComplete(handler: Unit => TailRec[Unit])(implicit catcher: Catcher[TailRec[Unit]]) = {
    executor.schedule(new Runnable {
      def run() {
        handler().result
      }
    }, duration.length, duration.unit)
    done()
  }
}

// Without the keyword `new`, you have the magic version of `Future` constructor,
// which enables the magic postfix `await`.
val sleep10seconds = Future {
  var i = 0
  while (i < 10) {
    println(s"I have sleeped $i times.")
    // The magic postfix `await` invokes the asynchronous method `asyncSleep`.
    // It looks like normal `Thread.sleep()`, but does not block any thread.
    asyncSleep(1.seconds).await
    i += 1
  }
  i
}

// When `sleep10seconds` is running, it could report failture to this catcher
implicit def catcher: Catcher[Unit] = {
  case e: Exception => {
    println("An exception occured when I was sleeping: " + e.getMessage)
  }
}

// A stateless future instance is lazy, only evaluating when you query it.
println("Before the evaluation of the stateless future `sleep10seconds`.")
for (total <- sleep10seconds) {
  println("After the evaluation of the stateless future `sleep10seconds`.")
  println(s"I sleeped $total times in total.")
  executor.shutdown()
}

Run it and you will see the output:

Before evaluation of the stateless future `sleep10seconds`.
I have sleeped 0 times.
I have sleeped 1 times.
I have sleeped 2 times.
I have sleeped 3 times.
I have sleeped 4 times.
I have sleeped 5 times.
I have sleeped 6 times.
I have sleeped 7 times.
I have sleeped 8 times.
I have sleeped 9 times.
After evaluation of the stateless future `sleep10seconds`.
I sleeped 10 times in total.

Further Information

There are two sorts of API to use a stateless future, the for-comprehensions style API and "A-Normal Form" style API.

For-Comprehensions

The for-comprehensions style API for stateless-future is like the for-comprehensions for scala.concurrent.Future.

for (total <- sleep10seconds) {
  println("After evaluation of the stateless future `sleep10seconds`")
  println(s"I sleeped $total times in total.")
  executor.shutdown()
}

A notable difference between the two for-comprehensions implementation is the required implicit parameter. A scala.concurrent.Future requires an ExecutionContext, while a stateless future requires a Catcher.

import scala.util.control.Exception.Catcher
implicit def catcher: Catcher[Unit] = {
  case e: Exception => {
    println("An exception occured when I was sleeping: " + e.getMessage)
  }
}

A-Normal Form

"A-Normal Form" style API for stateless futures is like the pending proposal scala.async.

val sleep10seconds = Future {
  var i = 0
  while (i < 10) {
    println(s"I have sleeped $i times")
    // The magic postfix `await` invokes asynchronous method like normal `Thread.sleep()`,
    // and does not block any thread.
    asyncSleep(1.seconds).await
    i += 1
  }
  i
}

The Future functions for stateless futures correspond to async method in Async, and the await postfixes to stateless futures corresponds to await method in Async.

Design

Regardless of the familiar veneers between stateless futures and scala.concurrent.Future, I have made some different designed choices on stateless futures.

Statelessness

The stateless futures are pure functional, they will never store result values or exceptions. Instead, stateless futures evaluate lazily, and they do the same work for every time you invoke foreach or onComplete. The behavior of stateless futures is more like monads in Haskell than futures in Java.

Also, there is no isComplete method in stateless futures. As a result, the users of stateless futures are forced not to share futures between threads, not to check the states in futures. They have to care about control flows instead of threads, and build the control flows by defining stateless futures.

By the way, stateless futures can be easy adapted to other stateful future implementation, and then the users can use the other future's stateful API on the adapted futures. For example, you can perform scala.concurrent.Await.result on a stateless future which is implicitly adapted to a Future.ToConcurrentFuture. By this approach, I have ported the most of scala.async test cases for stateless futures.

Threading-free Model

There are too many threading models and implimentations in the Java/Scala world, java.util.concurrent.Executor, scala.concurrent.ExecutionContext, javax.swing.SwingUtilities.invokeLater, java.util.Timer, ... It is very hard to communicate between threading models. When a developer is working with multiple threading models, he must very carefully pass messages between threading models, or he have to maintain bulks of synchronized methods to properly deal with the shared variables between threads.

Why does he need multiple threading models? Because the libraries that he uses depend on different threading modes. For example, you must update Swing components in the Swing's UI thread, you must specify java.util.concurrent.ExecutionServices for java.nio.channels.CompletionHandler, and, you must specify scala.concurrent.ExecutionContexts for scala.concurrent.Future and scala.async.Async. Oops!

Think about somebody who uses Swing to develop a text editor software. He wants to create a state machine to update UI. He have heard the cool scala.async, then he uses the cool "A-Normal Form" expression in async to build the state machine that updates UI, and he types import scala.concurrent.ExecutionContext.Implicits._ to suppress the compiler errors. Everything looks pretty, except the software always crashes.

Fortunately, stateless-future depends on none of these threading model, and cooperates with all of these threading models. If the poor guy tries stateless future, replacing async { } to stateless-future's Future { }, deleting the import scala.concurrent.ExecutionContext.Implicits._, he will find that everything looks pretty like before, and does not crash any more. That's why threading-free model is important.

Exception Handling

There were two Future implementations in Scala standard library, scala.actors.Future and scala.concurrent.Future. scala.actors.Futures are not designed to handling exceptions, since exceptions are always handled by actors. There is no way to handle a particular exception in a particular subrange of an actor.

Unlike scala.actors.Futures, scala.concurrent.Futures are designed to handle exceptions. But, unfortunately, scala.concurrent.Futures provide too many mechanisms to handle an exception. For example:

import scala.concurrent.Await
import scala.concurrent.ExecutionContext
import scala.concurrent.duration.Duration
import scala.util.control.Exception.Catcher
import scala.concurrent.forkjoin.ForkJoinPool
val threadPool = new ForkJoinPool()
val catcher1: Catcher[Unit] = { case e: Exception => println("catcher1") }
val catcher2: Catcher[Unit] = {
  case e: java.io.IOException => println("catcher2")
  case other: Exception => throw new RuntimeException(other)
}
val catcher3: Catcher[Unit] = {
  case e: java.io.IOException => println("catcher4")
  case other: Exception => throw new RuntimeException(other)
}
val catcher4: Catcher[Unit] = { case e: Exception => println("catcher4") }
val catcher5: Catcher[Unit] = { case e: Exception => println("catcher5") }
val catcher6: Catcher[Unit] = { case e: Exception => println("catcher6") }
val catcher7: Catcher[Unit] = { case e: Exception => println("catcher7") }
def future1 = scala.concurrent.future { 1 }(ExecutionContext.fromExecutor(threadPool, catcher1))
def future2 = scala.concurrent.Future.failed(new Exception)
val composedFuture = future1.flatMap { _ => future2 }(ExecutionContext.fromExecutor(threadPool, catcher2))
composedFuture.onFailure(catcher3)(ExecutionContext.fromExecutor(threadPool, catcher4))
composedFuture.onFailure(catcher5)(ExecutionContext.fromExecutor(threadPool, catcher6))
try { Await.result(composedFuture, Duration.Inf) } catch { case e if catcher7.isDefinedAt(e) => catcher7(e) }

Is any sane developer able to tell which catchers will receive the exceptions?

There are too many concepts about exceptions when you work with scala.concurrent.Future. You have to remember the different exception handling strategies between flatMap, recover, recoverWith and onFailure, and the difference between scala.concurrent.Future.failed(new Exception) and scala.concurrent.future { throw new Exception }.

scala.async does not make things better, because scala.async will produce compiler errors for every await in try statements.

Fortunately, you can get rid of all those concepts if you switch to stateless-future. There is no catcher implicit parameter in flatMap or map in stateless Futures, nor onFailure nor recover method at all. You just simply try, and things get done. See the examples to learn that.

Tail Call Optimization

Tail call optimization is an important feature for pure functional programming. Without tail call optimization, many recursive algorithm will fail at run-time, and you will get the well-known StackOverflowError.

The Scala language provides scala.annotation.tailrec to automatically optimize simple tail recursions, and scala.util.control.TailCalls to manually optimize complex tail calls.

stateless-future project internally bases on scala.util.control.TailCalls, and automatically performs tail call optimization in the magic Future blocks, without any additional special syntax.

See this example. It just works, and no StackOverflowError or OutOfMemoryError occures. Note that if you port this example for scala.async it will throw OutOfMemoryError or TimeoutException.

Comparison

There was a continuation plugin for Scala. The continuation plugin also provide a DSL to define control flows like stateless-future or scala.async. I created the following table to compare the three DSL:

stateless-future scala.concurrent.Future and scala.async scala.util.continuations
Stateless Yes No Yes
Threading-free Yes No Yes
Exception handling in "A-Normal Form" Yes No No
Tail call optimization in "A-Normal Form" Yes No No
Pattern matching in "A-Normal Form" Yes Yes Buggy
Lazy val in "A-Normal Form" No, because of some underlying scala.reflect bugs Only for those not contain await Buggy

Installation

Put these lines in your build.sbt if you use Sbt:

libraryDependencies += "com.qifun" %% "stateless-future" % "0.1"

stateless-future should work with Scala 2.10.3, 2.10.4, or 2.11.0.

Known issues

  • lazy vals in magic Future block are not supported.
  • In some rare cases, if you create multiple val with same name in one Future block, the last val may be referred unexpectly.
  • Some complex existential types may cause compiler errors.

Clone stateless-future-test and run the test cases to check these limitations.

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A set of DSL for asynchronous programming, in the pure functional favor. 展开 收起
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