batch 1.3.0 copy "batch: ^1.3.0" to clipboard
batch: ^1.3.0 copied to clipboard

A Lightweight and Powerful Job Scheduling Framework written in Dart. With this framework, you can easily develop a scheduled workflow in Dart.

batch

A Lightweight and Powerful Job Scheduling Framework.


pub package Dart SDK Version Test Analyzer codecov CodeFactor Issues Pull Requests Stars Code size Last Commits License Contributor Covenant FOSSA Status


Do you need a scheduled and long-lived server-side processing?
If so, this is the framework you are looking for!


1. Guide #

1.1. Mission #

The goal of this project is to provide a high-performance and intuitive job scheduling in the Dart language. And to enable people around the world to automate their tasks more easily.

And the development concept of this framework is "DRY", "KISS" and "YAGNI", which has been said in software engineering circles for a long time.

1.2. Features #

  • Easy and intuitive job scheduling.
  • No complicated configuration files.
  • Supports scheduling in Cron format.
  • Supports powerful logging feature and it's customizable.
  • Supports easily define parallel processes.
  • Supports conditional branching of jobs and steps.
  • Supports convenient callback functions at each event.
  • Supports skipping and retrying according to user defined conditions.
  • and etc...

1.3. Getting Started #

1.3.1. Install Library #

 dart pub add batch

Note: Pub.dev automatically labels this library as usable for Flutter, but the intended use of this library is long-lived server-side processing.

1.3.2. Import #

The following import will provide all the materials for developing job scheduling using Batch.dart.

import 'package:batch/batch.dart';

1.3.3. Basic Concept #

Batch.dart represents the unit of scheduled processing as an Event. And Event is composed of the following elements.

Description
Job This Job event is a unit of batch processing in the broad sense. And Job has multiple Step events.
ScheduledJob It represents a scheduled job. And ScheduledJob has multiple Step events.
Step This event expresses the sequential processing. Each Step has a Task that defines one specific process.
ParallelStep This event expresses the parallel processing. Each ParallelStep has ParallelTasks that define specific processes.

1.3.4. Schedule Jobs #

1.3.4.1. Sequential Process

Scheduling jobs using this framework is very easy.

First, create a class that defines a class extends the Task class and define processes in execute method. The execute method can define any process and supports both synchronous and asynchronous processing.

Second, you need to define a scheduled job. It is also easy to define a scheduled job by implementing the build method in a class that implements ScheduledJobBuilder, as in the following example. And Batch.dart supports standard Cron specifications.

Finally, let's execute runWorkflow method on main method with scheduled jobs as arguments!

When the runWorkflow method is executed, the scheduled batch process is started.

Example

import 'package:batch/batch.dart';

void main() => runWorkflow(
      jobs: [SayHelloWorldJob()],
    );


class SayHelloWorldJob implements ScheduledJobBuilder {
  @override
  ScheduledJob build() => ScheduledJob(
        name: 'Test Job',
        schedule: CronParser('*/2 * * * *'), // Execute every 2 minutes
        steps: [
          Step(
            name: 'Test Step',
            task: SayHelloWorldTask(),
          )
        ],
      );
}

class SayHelloWorldTask extends Task<SayHelloWorldTask> {
  @override
  void execute(ExecutionContext context) {
    log.info('Hello, World!');
  }
}

You can see more examples at Official Examples.

1.3.4.2. Parallel Process

Batch.dart supports powerful parallel processing and is easy to define.

When defining parallel processing, all you have to do is just inherit from ParallelTask and describe the process you want to parallelize in the execute method.

SharedParameters and JobParameters set in the main thread can be referenced through ExecutionContext. However, note that under the current specification, changes to the ExecutionContext value during parallel processing are not reflected in the main thread's ExecutionContext.

Example

import 'dart:async';

import 'package:batch/batch.dart';

void main() => runWorkflow(
      jobs: [DoHeavyProcessJob()],
    );

class DoHeavyProcessJob implements ScheduledJobBuilder {
  @override
  ScheduledJob build() => ScheduledJob(
        name: 'Job',
        schedule: CronParser('*/2 * * * *'), // Execute every 2 minutes
        steps: [
          ParallelStep(
            name: 'Parallel Step',
            tasks: [
              DoHeavyTask(),
              DoHeavyTask(),
              DoHeavyTask(),
              DoHeavyTask(),
            ],
          )
        ],
      );
}


class DoHeavyTask extends ParallelTask<DoHeavyTask> {
  @override
  FutureOr<void> execute(ExecutionContext context) {
    int i = 0;
    while (i < 10000000000) {
      i++;
    }
  }
}

1.3.5. Logging #

The Batch.dart provides the following well-known logging features as a standard. And the default log level is trace.

  • trace
  • debug
  • info
  • warn
  • error
  • fatal

The logging feature provided by Batch.dart has extensive customization options. For more information, you can refer to the Official Documents describing logging on Batch.dart.

1.3.5.1. On Sequential Process

It's very easy to use logging functions on sequential process.

The logging methods provided by the Batch.dart can be used from any class that imports batch.dart. So no need to instantiate any Loggers by yourself!

All you need to specify about logging in Batch.dart is the configuration of the log before run BatchApplication, and the Logger is provided safely under the lifecycle of the Batch.dart.

Example

import 'package:batch/batch.dart';

class TestLogTask extends Task<TestLogTask> {
  @override
  void execute() {
    log.trace('Test trace');
    log.debug('Test debug');
    log.info('Test info');
    log.warn('Test warning');
    log.error('Test error');
    log.fatal('Test fatal');
  }
}

For example, if you run example, you can get the following log output.

yyyy-MM-dd 19:25:10.575109 [info ] (_BatchApplication.run:129:11  ) - 🚀🚀🚀🚀🚀🚀🚀 The batch process has started! 🚀🚀🚀🚀🚀🚀🚀
yyyy-MM-dd 19:25:10.579318 [info ] (_BatchApplication.run:130:11  ) - Logger instance has completed loading
yyyy-MM-dd 19:25:10.580177 [info ] (_BootDiagnostics.run:32:9     ) - Batch application diagnostics have been started
yyyy-MM-dd 19:25:10.583234 [info ] (_BootDiagnostics.run:46:9     ) - Batch application diagnostics have been completed
yyyy-MM-dd 19:25:10.583344 [info ] (_BootDiagnostics.run:47:9     ) - Batch applications can be started securely
yyyy-MM-dd 19:25:10.585729 [info ] (JobScheduler.run:37:9         ) - Started Job scheduling on startup
yyyy-MM-dd 19:25:10.585921 [info ] (JobScheduler.run:38:9         ) - Detected 3 Jobs on the root
yyyy-MM-dd 19:25:10.586023 [info ] (JobScheduler.run:41:11        ) - Scheduling Job [name=Job1]
yyyy-MM-dd 19:25:10.595706 [info ] (JobScheduler.run:41:11        ) - Scheduling Job [name=Job2]
yyyy-MM-dd 19:25:10.597471 [info ] (JobScheduler.run:41:11        ) - Scheduling Job [name=Job4]
yyyy-MM-dd 19:25:10.597692 [info ] (JobScheduler.run:56:9         ) - Job scheduling has been completed and the batch application is now running

Note: The setup of the logger is done when executing the runWorkflow. If you want to use the logging feature outside the life cycle of this library, be sure to do so after executing the runWorkflow.

1.3.5.2. On Parallel Process

Parallel processing cannot directly use the convenient logging features described above. This is because parallel processing in the Dart language does not share any instances.

Instead, use the following methods in classes that extend ParallelTask for parallel processing.

  • sendMessageAsTrace
  • sendMessageAsDebug
  • sendMessageAsInfo
  • sendMessageAsWarn
  • sendMessageAsError
  • sendMessageAsFatal

Example

class TestParallelTask extends ParallelTask<TestParallelTask> {
  @override
  FutureOr<void> execute() {
    super.sendMessageAsTrace('Trace');
    super.sendMessageAsDebug('Debug');
    super.sendMessageAsInfo('Info');
    super.sendMessageAsWarn('Warn');
    super.sendMessageAsError('Error');
    super.sendMessageAsFatal('Fatal');
  }
}

It should be noted that log output does not occur at the moment the above sendMessageAsX method is used.

This is only a function that simulates log output in parallel processing, and all messages are output at once when all parallel processing included in Parallel is completed.

And you can get the following log output from parallel processes.

yyyy-MM-dd 10:05:06.662561 [trace] (solatedLogMessage.output:36:13) - Received from the isolated thread [message=Trace]
yyyy-MM-dd 10:05:06.662666 [debug] (solatedLogMessage.output:39:13) - Received from the isolated thread [message=Debug]
yyyy-MM-dd 10:05:06.662760 [info ] (solatedLogMessage.output:42:13) - Received from the isolated thread [message=Info]
yyyy-MM-dd 10:05:06.662856 [warn ] (solatedLogMessage.output:45:13) - Received from the isolated thread [message=Warn]
yyyy-MM-dd 10:05:06.662947 [error] (solatedLogMessage.output:48:13) - Received from the isolated thread [message=Error]
yyyy-MM-dd 10:05:06.663039 [fatal] (solatedLogMessage.output:51:13) - Received from the isolated thread [message=Fatal]

1.3.6. Branch #

Batch.dart supports conditional branching for each scheduled event (it's just called "Branch" in Batch.dart).

Branch is designed to be derived from each event, such as Job and Step. There is no limit to the number of branches that can be set up, and a recursive nesting structure is also possible.

Creating a branch for each event is very easy.

To create branch

    Step(
      name: 'Step',
      task: SwitchBranchStatusTask(),

      // Each branch can be multiple and nested
      branchesOnSucceeded: [Step(name: 'Step on succeeded', task: doSomethingTask)],
      branchesOnFailed: [Step(name: 'Step on failed', task: doSomethingTask)],
      branchesOnCompleted: [Step(name: 'Step on completed', task: doSomethingTask)],
    );

And the conditional branching of Batch.dart is controlled by switching the BranchStatus of each Executions that can be referenced from the ExecutionContext. The default branch status is "completed".

To manage branch

class SwitchBranchStatusTask extends Task<SwitchBranchStatusTask> {
  @override
  void execute(ExecutionContext context) {
    // You can easily manage branch status through methods as below.
    context.jobExecution!.switchBranchToSucceeded();
    context.stepExecution!.switchBranchToFailed();
  }
}

1.4. More Examples #

You can check more at Official Examples.

1.5. Contribution #

If you would like to contribute to Batch.dart, please create an issue or create a Pull Request.

Owner will respond to issues and review pull requests as quickly as possible.

1.6. Support #

The simplest way to show us your support is by giving the project a star at here.

And I'm always looking for sponsors to support this project. I do need support to continue ongoing open source development.

Sponsors can be individuals or corporations, and the amount is optional.

👇 Click on the button below to see more details! 👇

myconsciousness

1.7. License #

All resources of Batch.dart is provided under the BSD-3 license.

FOSSA Status

Note: License notices in the source are strictly validated based on .github/header-checker-lint.yml. Please check header-checker-lint.yml for the permitted standards.

1.8. More Information #

Batch.dart was designed and implemented by Kato Shinya.

28
likes
130
pub points
49%
popularity

Publisher

verified publishershinyakato.dev

A Lightweight and Powerful Job Scheduling Framework written in Dart. With this framework, you can easily develop a scheduled workflow in Dart.

Repository (GitHub)
View/report issues
Contributing

Documentation

API reference

License

BSD-3-Clause (license)

Dependencies

args, async_task, clock, console_color, http, intl, meta

More

Packages that depend on batch