As far as I can see from the docs of "Advanced Python Scheduler", they do not provide a different process to run the scheduled tasks. That is left up to you to figure out.
From their docs, they are recommending a "BackgroundScheduler" which runs in a separate thread.
Now there are multiple issues which could arise:
- If you're running multiple Django instances (using gunicorn or uwsgi), APS scheduler will run in each of those processes. This is a non-trivial problem to solve unless APS has considered this (you will have to check the docs).
- BackgroundScheduler will run in a thread, but python is limited by the GIL. So if your background tasks are CPU intensive, your Django process will get slower at processing incoming requests.
- Regardless of thread or not, if your background job is CPU intensive + lasts a long time, it can affect your server performance.
APS seems like a much lower-level library, and my recommendation would be to use something simpler:
- Simply using system cronjobs to run every 3 days. Create a django management command, and use the cron to execute that.
- Use django supported libraries like celery, rq/rq-scheduler/django-rq, or django-background-tasks.
I think it would be wise to take a look at https://github.com/arteria/django-background-tasks as it is the simplest of all with the least amount of setup required. Once you get a bit familiar with this you can weigh the pros & cons on what is appropriate for your use case.
Once again, your server performance depends on what your background task is doing and how long does it lasts.