Task queues are used to handle asynchronous tasks, allowing operations to be executed in the background without blocking the main application. This is ideal for long-running processes.

Task queues play a vital role in Python web applications by enabling asynchronous processing of tasks that may be time-consuming or resource-intensive. By using a task queue, developers can offload these tasks to a background worker, allowing the main application to continue running without interruption. This is particularly useful for long-running processes, such as sending emails, generating reports, or processing data, which can otherwise lead to slow response times or unresponsive applications. Popular task queue frameworks in Python include Celery and RQ (Redis Queue), which provide robust features for managing asynchronous tasks. These frameworks allow developers to define tasks as Python functions, which can be queued for execution by worker processes. Once a task is queued, it is executed independently of the main application flow, freeing up resources for handling incoming requests. Task queues can also provide mechanisms for task scheduling, retries, and monitoring, enabling developers to manage background jobs effectively. By implementing a task queue, developers can enhance application performance, improve user experience, and ensure that resource-intensive operations do not impact the responsiveness of the web application.