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Informations about the package queue
Leaf Queue
Implementing a queuing system from scratch can be a daunting task, and can take a lot of time. For this reason, Leaf aims to provide a unified API for using queues across a variety of different backends, such as Amazon SQS, BeanStalk, Redis, or a database of your choice.
Basic Usage
In simple terms, this package allows you to push "heavy" tasks into a queue and run them in the background. This is useful for tasks that take a long time to complete, such as sending emails, processing images, etc.
We try to simplify the process of creating and running queues as much as possible, so, for most of the time, you'll only need to create your jobs and run the queue from the command line.
Creating a Job
Jobs are basically classes that extend the Leaf\Queues\Job
class. They must implement the handle
method, which is called when the job is run.
Running the Queue
To run the queue, all you need to do is run the queue:run
command from the command line. This will run all jobs in the queue.
Pushing Jobs to the Queue
To push a job to the queue, you can use the dispatch
method on your job class.
Stay In Touch
Learning Leaf 3
- Leaf has a very easy to understand documentation which contains information on all operations in Leaf.
- You can also check out our youtube channel which has video tutorials on different topics
- You can also learn from codelabs and contribute as well.
Contributing
We are glad to have you. All contributions are welcome! To get started, familiarize yourself with our contribution guide and you'll be ready to make your first pull request 🚀.
To report a security vulnerability, you can reach out to @mychidarko or @leafphp on twitter. We will coordinate the fix and eventually commit the solution in this project.
Sponsoring Leaf
Your cash contributions go a long way to help us make Leaf even better for you. You can sponsor Leaf and any of our packages on open collective or check the contribution page for a list of ways to contribute.
And to all our existing cash/code contributors, we love you all ❤️