In this chapter, we will continue with our exploration into RabbitMQ clients, but this time in Python.
Python provides an almost perfect environment into this work, because it is dynamic in nature and over the (many) years, it has established itself as an almost de-facto toolset for backend engineers and data scientists. It is only fitting that during earlier time, it has allowed great tooling to evolve, and we'll explore them here.
In this chapter, you will learn the following topics:
Using RabbitMQ from Python with the help of a library called Pika
Using Pika to implement a sample use case project
Exploring how Pika will help you tackle almost any AMQP-related task
Understanding Celery—a powerful background task library
Understanding how the work we did so far adapts into Celery, why it is better, and how to use its more-advanced usage