async_task 1.0.1

Asynchronous tasks and parallel executors (similar to thread pools) for all Dart platforms (transparently), without having to deal with `Isolate` complexity.

async_task

This package brings asynchronous tasks and parallel executors (similar to classic thread pools) for all Dart platforms (JS/Web, Flutter, VM/Native) through transparent internal implementations, based on dart:isolate or only dart:async, without having to deal with the Isolate complexity.

Motivation

Dart parallelism is based on asynchronous, non-blocking and thread-safe code. This creates a language that facilitates the creation of safe concurrency code, but all running in the same thread, using only 1 thread/core of a device.

If you want to use more than 1 thread/core of a device, Dart VM/Native has Isolate, but the paradigm is not easy to use like classical Thread Pools, or like environments that shares all the memory/objects between threads.

This package was created to facilitate the creation and execution of multiple tasks asynchronously in all Dart Platforms, avoiding platform specific codes by the developer.

Usage

import 'dart:async';

import 'package:async_task/async_task.dart';

void main() async {
  // The tasks to execute:
  var tasks = [
    PrimeChecker(8779),
    PrimeChecker(1046527),
    PrimeChecker(3139581), // Not Prime
    PrimeChecker(16769023),
  ];

  // Instantiate the task executor:
  var asyncExecutor = AsyncExecutor(
    sequential: false, // Non-sequential tasks.
    parallelism: 2, // Concurrency with 2 threads.
    taskTypeRegister: _taskTypeRegister, // The top-level function to register the tasks types.
  );

  // Enable logging output:
  asyncExecutor.logger.enabled = true ;

  // Execute all tasks:
  var executions = asyncExecutor.executeAll(tasks);

  // Wait tasks executions:
  await Future.wait(executions);

  for (var task in tasks) {
    var n = task.n; // Number to check for prime.
    var prime = task.result; // Task result: true if is prime.
    print('$n\t-> $prime \t $task');
  }
}

// This top-level function returns the tasks types that will be registered
// for execution. Task instances are returned, but won't be executed and
// will be used only to identify the task type:
List<AsyncTask> _taskTypeRegister() => [PrimeChecker(0)];

// A task that checks if a number is prime:
class PrimeChecker extends AsyncTask<int, bool> {
  // The number to check if is prime.
  final int n;

  PrimeChecker(this.n);

  // Instantiates a `PrimeChecker` task with `parameters`.
  @override
  AsyncTask<int, bool> instantiate(int parameters) {
    return PrimeChecker(parameters);
  }

  // The parameters of this task:
  @override
  int parameters() {
    return n;
  }

  // Runs the task code:
  @override
  FutureOr<bool> run() {
    return isPrime(n);
  }

  // A simple prime check function:
  bool isPrime(int n) {
    if (n < 2) return false;

    var limit = n ~/ 2;
    for (var p = 2; p < limit; ++p) {
      if (n % p == 0) return false;
    }

    return true;
  }
}

Output:

[INFO] Starting AsyncExecutor{ sequential: false, parallelism: 2, executorThread: _AsyncExecutorMultiThread{ totalThreads: 2, queue: 0 } }
[INFO] Starting _AsyncExecutorMultiThread{ totalThreads: 2, queue: 0 }
[INFO] Created _IsolateThread{ id: 2 ; registeredTasksTypes: [PrimeChecker] }
[INFO] Created _IsolateThread{ id: 1 ; registeredTasksTypes: [PrimeChecker] }
8779     -> true 	 PrimeChecker(8779)[finished]{ result: true ; executionTime: 2 ms }
1046527  -> true 	 PrimeChecker(1046527)[finished]{ result: true ; executionTime: 2 ms }
3139581  -> false 	 PrimeChecker(3139581)[finished]{ result: false ; executionTime: 0 ms }
16769023 -> true 	 PrimeChecker(16769023)[finished]{ result: true ; executionTime: 35 ms }

Source

The official source code is hosted @ GitHub:

• https://github.com/eneural-net/async_task

Features and bugs

Please file feature requests and bugs at the issue tracker.

Contribution

Any help from the open-source community is always welcome and needed:

• Found an issue?
  • Please fill a bug report with details.
• Wish a feature?
  • Open a feature request with use cases.
• Are you using and liking the project?
  • Promote the project: create an article, do a post or make a donation.
• Are you a developer?
  • Fix a bug and send a pull request.
  • Implement a new feature, like other training algorithms and activation functions.
  • Improve the Unit Tests.
• Have you already helped in any way?
  • Many thanks from me, the contributors and everybody that uses this project!

Author

Graciliano M. Passos: gmpassos@GitHub.

License

Apache License - Version 2.0