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An asynchronous programming facility for Scala

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scala-async

A Scala DSL to enable a direct style of coding when composing Futures.

Usage

As of scala-async 1.0, Scala 2.12.12+ or 2.13.3+ are required.

Add dependency

SBT Example

libraryDependencies += "org.scala-lang.modules" %% "scala-async" % "1.0.1"
libraryDependencies += "org.scala-lang" % "scala-reflect" % scalaVersion.value % Provided

For Maven projects add the following to your (make sure to use the correct Scala version suffix to match your project’s Scala binary version):

Maven Example

<dependency>
  <groupId>org.scala-lang.modules</groupId>
  <artifactId>scala-async_2.13</artifactId>
  <version>1.0.1</version>
</dependency>
<dependency>
  <groupId>org.scala-lang</groupId>
  <artifactId>scala-reflect</artifactId>
  <version>2.13.8</version>
  <scope>provided</scope>
</dependency>

Enable compiler support for async

Add the -Xasync to the Scala compiler options.

SBT Example

scalacOptions += "-Xasync"

Maven Example

<project>
  ...
  <plugin>
    <groupId>net.alchim31.maven</groupId>
    <artifactId>scala-maven-plugin</artifactId>
    <version>4.4.0</version>
    <configuration>
      <args>
        <arg>-Xasync</arg>
      </args>
    </configuration>
  </plugin>
  ...
</project>

Start coding

import scala.concurrent.ExecutionContext.Implicits.global
import scala.async.Async.{async, await}

val future = async {
  val f1: Future[Boolean] = async { ...; true }
  val f2 = async { ...; 42 }
  if (await(f1)) await(f2) else 0
}

What is async?

async marks a block of asynchronous code. Such a block usually contains one or more await calls, which marks a point at which the computation will be suspended until the awaited Future is complete.

By default, async blocks operate on scala.concurrent.{Future, Promise}. The system can be adapted to alternative implementations of the Future pattern.

Consider the following example:

def slowCalcFuture: Future[Int] = ...             // 01
def combined: Future[Int] = async {               // 02
  await(slowCalcFuture) + await(slowCalcFuture)   // 03
}
val x: Int = Await.result(combined, 10.seconds)   // 05

Line 1 defines an asynchronous method: it returns a Future.

Line 2 begins an async block. During compilation, the contents of this block will be analyzed to identify the await calls, and transformed into non-blocking code.

Control flow will immediately pass to line 5, as the computation in the async block is not executed on the caller's thread.

Line 3 begins by triggering slowCalcFuture, and then suspending until it has been calculated. Only after it has finished, we trigger it again, and suspend again. Finally, we add the results and complete combined, which in turn will release line 5 (unless it had already timed out).

It is important to note that while lines 1-4 are non-blocking, they are not parallel. If we wanted to parallelize the two computations, we could rearrange the code as follows:

def combined: Future[Int] = async {
  val future1 = slowCalcFuture
  val future2 = slowCalcFuture
  await(future1) + await(future2)
}

Limitations

await must be directly in the control flow of the async expression

The await cannot be nested under a local method, object, class or lambda:

async {
  List(1).foreach { x => await(f(x) } // invalid
}

await must be not be nested within try / catch / finally.

This implementation restriction may be lifted in future versions.

Comparison with direct use of Future API

This computation could also be expressed by directly using the higher-order functions of Futures:

def slowCalcFuture: Future[Int] = ...
val future1 = slowCalcFuture
val future2 = slowCalcFuture
def combined: Future[Int] = for {
  r1 <- future1
  r2 <- future2
} yield r1 + r2

The async approach has two advantages over the use of map and flatMap:

  1. The code more directly reflects the programmer's intent, and does not require us to name the results r1 and r2. This advantage is even more pronounced when we mix control structures in async blocks.
  2. async blocks are compiled to a single anonymous class, as opposed to a separate anonymous class for each closure required at each generator (<-) in the for-comprehension. This reduces the size of generated code, and can avoid boxing of intermediate results.