Boosting Your Python Web App's Performance with Task Queues and Concurrency in Celery

So this session is going to be about how to use CELERY in your Python Based Web apps (I will use Django as an example), to divide the tasks and make the whole user experience a lot better. So a web apps main work is to handle clients, users, interact with databases and work with different requests etc. It is not meant to handle processes like running some time bound scripts, calling third party apis, handling scheduled tasks or even running ML models (tho it can, but not recommended). For this to isolate this whole process comes "CELERY" as a game changer. So for example If there is task to send 10,000 emails, this can be run by your web app, but it needs to wait until whole process is done. So instead you can just make a task file and write the logic to send mails, and in background this whole process is taking place and mails are being send and at the same time we can use our website without waiting for that certain process to end with the help of CELERY.

The second part of the session will be all about discussions over Concurrency, Multithreading and Multiprocessing in python! and how Celery uses it to do the job.

Session also involves some live demons on CPU usage with threads and more.