Add Celery for Background Task Processing

[chukaibejih]

As the project grows and handles more complex tasks, it would be beneficial to incorporate Celery into the system for efficient and scalable background task processing. Celery is a powerful distributed task queue that will enable the API to handle asynchronous tasks, such as sending emails, processing large data uploads, or performing resource-intensive operations in the background.

By introducing Celery, we can improve the overall performance and responsiveness of the Smart Learning API. Tasks that may take longer to complete, such as generating reports or processing large datasets, can be offloaded to background workers, preventing delays or timeouts in the API's responses.

Some potential use cases for Celery integration include:

• Asynchronous email sending: Instead of blocking the API's response while sending emails, we can utilize Celery to handle email sending asynchronously, ensuring a smooth user experience.
• Background data processing: Celery can be used to process large data uploads, perform complex computations, or generate reports in the background without affecting the API's responsiveness.
• Scheduled tasks: We can leverage Celery's scheduling capabilities to automate periodic tasks, such as sending reminders or updating course data.

Integrating Celery into the project will require configuring a message broker, such as RabbitMQ or Redis, and setting up worker processes to handle the tasks. The implementation should also consider error handling, task monitoring, and potential security implications.