APScheduler in Django rest framework

There are multiple ways to schedule a job in the Django rest framework but APScheduler is one of the simplest and best ways to implement scheduling in Django.

So in this blog, we will be learning about how to schedule jobs in the Django rest framework with their types and which type is preferable for which tasks and advantages.

We have divided APScheduler learning into some points as below 

  1. Library required to use APScheduler in Django rest framework
  2. What is APScheduler
  3. APScheduler types and their details
  4. Scheduling implementation.
  5. Handling different methods in APScheduler.
  6. Advantages
  7. Conclusion

1. Library required to use APScheduler in Django rest framework

To use APScheduler we need to install an external library, APScheduler is a library with the latest version 3.6.3.

Command to install this library in Django, we need to use the following command

pip install APSchedular

2. What is APScheduler

APScheduler is a library that lets you schedule your job or particular task to be executed later, either just once or periodically APScheduler mainly has four component as below

  • Triggering job:
    In this component, we need to add when the job will going to run next and all information about scheduling is contained by this component.
  • Storing job:
    Storing job component is also known as the job memory component because it stores the job list with its details. It is helpful for saving, loading, updating and searching for jobs.
  • Executing job:
    Executing job means executor component which is helpful for running of the job and it also notifies the scheduler to remove particular job after execution is finished
  • Schedulers:
    A scheduler is an important part of the scheduling because for triggering, storing and executing it provides an interface for developers and it binds all rest of the processes.

 

3. APScheduler types and their details

Depending on what you’ll be using APScheduler for and the programming environment you are using we need to choose a scheduler

  • BlockingScheduler: Use when the scheduler is the only thing running in your process
  • BackgroundScheduler: Use when you’re not using any of the frameworks below and want the scheduler to run in the background inside your application
  • AsyncIOScheduler: Use if your application uses the asyncio module
  • GeventScheduler: Use if your application uses gevent
  • TornadoScheduler: Use if you’re building a Tornado application
  • TwistedScheduler: Use if you’re building a Twisted application
  • QtScheduler: Use if you’re building a Qt application

I will be using the BackgroundScheduler for this tutorial, as I wanted the task to run as a background process inside a Django server.

 

4. Scheduling implementation

In Implementation, I will be using the BackgroundScheduler for this tutorial, so  First, we need to import the APScheduler and also need to assign require type as below

from apscheduler.schedulers.background import BackgroundScheduler
scheduler = BackgroundScheduler()

After importing and assigning APScheduler we need to schedule a particular job as below

def our_job(self):
print(“Job triggering method”)
scheduler.add_job(self.our_job, 'date', run_date=send_time, args=[],id=’’id1”)


In the above method we have used the add_job scheduling method to schedule a job so in this method we need to pass some arguments, first argument in add_job method is our job method that we need to run so we have added our_job method so after that we also need to mention the running type in run_date argument and also we can pass the arguments to our_job method in args argument of add_job and also for identifying a particular job we also need to add id to every job, so in future, if we require to stop the particular job or update particular job then id argument will help.

Now our job is running in the background so in the next point we will see how to see a list of running jobs and reschedule particular jobs and many events.

 

5. Handling different methods in APScheduler

There are different method in APScheduler and depending upon our use we need to use these methods and methods are listed below

  • Getting a list of all running jobs: After scheduling jobs we also requires the list of scheduled jobs and In this, we also need to pass two parameters job store so for that we need to use the following method
    scheduler.get_jobs (jobstore=None, pending=None)

  • Rescheduling job:  This method is required when we need to changes the scheduled time of the method as shown below
    scheduler.reschedule_job(job_id, run_date=send_time)
  • Getting a particular job by id:  This method is used to get information about a particular job by passing their id
    scheduler.get_job(job_id)
  • Shutdown the job: In this method, we are stopping the job
    scheduler.shutdown()
  • Pause
    scheduler.pause()
  • Resume the job
    scheduler.resume()

6. Advantages

  • APScheduler can be used across different platforms
  • Compared to other schedulers it is simple to use
  • This scheduler library is Lightweight


7. Disadvantages

  • APScheduler makes logging really difficult
  • It doesn’t provide the functionality to reschedule failed tasks.

Conclusion:

In this tutorial, we learned about what is an APScheduler with its types, the implementation of APScheduler, and also methods used in APScheduler. How can we use an APScheduler in our project.

Code snippet

from apscheduler.schedulers.background import BackgroundScheduler
scheduler = BackgroundScheduler()
def our_job(self):
print(“Job triggering method”)
def scheduling_method(self):
scheduler.add_job(self.our_job, 'date', run_date=send_time, args=[],id=’’id1”)
scheduler.get_jobs (jobstore=None, pending=None)
def rescheduling_method(self):
scheduler.reschedule_job(“id1”, run_date=send_time)
scheduler.get_jobs (jobstore=None, pending=None)

Rishikesh

Full-stack developer

Rishikesh is a Full-stack developer with 3+ years of experience. He has experience in web technologies like AngularJS, ReactJS. His expertise is building Python integrated web applications, creating REST APIs with well-designed, testable and efficient and optimized code. He loves to learn new technologies.

Get in touch for a detailed discussion.

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