Celery - A Talk Through
In the contemporary world, speed is king. Nobody likes a page that takes an eternity to load up. But when we work on data-intensive applications, the laborious tasks may take up minutes to complete and can make the page sluggish for the user. How can we solve this problem and improve the user experience and not test his patience?
This is where the concept of asynchronous comes into play. We divide and distribute the tasks to various background task-based servers, which are performing the assigned works simultaneously so as to reduce the latency and to load pages instantaneously for the user. The goal is to reduce the workload of the webserver by assigning tasks like processing of databases, files, and more to the background task-based servers called “workers” so that our web server remains free to respond to user requests.
So what is Celery? It is an open-source asynchronous task manager which distributes and allocates the to-do-list of tasks to different workers. It schedules the tasks in the form of queues.(Put simply, a queue is a first-in, first-out data structure.)
Also, depending on the time complexity of the task, more than one worker can be assigned to get the job done quickly. This results in effective distribution of the heavier jobs of the task queues to more number of workers and vice versa. Celery allows python applications to quickly implement tasks for many workers. It takes care of the organizing and assigning of tasks appropriately to various workers.
We can add workers if the number of tasks increases and each worker will remove their assigned tasks from the queue in order, thus empowering us to handle more than one task simultaneously. Thus, using the power of Celery we can efficiently manage a bunch of tasks to achieve asynchronously and improve the response time of our pages saving time for our happy user!
Thanks for reading!
