django-beanstalkd's Introduction
Modification of django-beanstalkd (https://github.com/jonasvp/django-beanstalkd/) by jonasvp. New Features: Storing all jobs and the current statuses to the local db. - In an older version of beanstalk, the binlog functionality had issues, so this mitigated the risk when beanstalk is restarted. - Also if the beanstalk server goes down, no jobs will be lost. - There are jobs included that will requeue jobs that weren't processed. Proper shutdown of beanstalk workers. - The original method involved killing worker processes, but jobs can be killed midpoint leading to unexpected behaviour. Ability to run workers for specific django apps. MESSAGE PRODUCERS: How to create a new asynchronous job: 1.) In your django application, create a module called fdrasync_jobs.py (asynchronous jobs). Exact naming is necessary. 2.) Within that file define your business logic i.e @fdrasync_job def myBusinessLogic(args) #your business logic here Notes: 1.) You must annotate your business logic method with the @fdrasync_job decorator 2.) args will be returned as a json array Finally, call the asynchronous methods. 1.) The following control variables can be passed into your asynctask instance. @priority -> you can set a priority for your task, so the consumers can process it accordingly @delay -> you can set a delay, the default is 0 @ttr -> ttr value. see: http://github.com/kr/beanstalkd/wiki/faq 2.) Call the run method of BaseAsyncTask with the following parameters Mandatory Parameters @function -> the reference to the annotated asynchronous business logic function @args -> a json serializable list of parameters i.e: Subclassing the base tasks for domain specific behaviour class MyAsyncJobs(BaseAsyncTasks): def myBusinessLogicJob(self) : #myBusinessLogic is the actual business logic located somewhere. self.run( myBusinessLogic, {'arg1' : arg1}) @fdrasync_job def myBusinessLogic(args) #your business logic here MESSAGE CONSUMERS: run: python manage.py beanstalk_worker [app name] this will sit and wait for new work and process the tasks produced by the producers. specify a [app name] to spawn a worker that listens for jobs for a specific django application
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