Some data is received in a constant stream from various sources. For example, we might have a situation where multiple temperature probes are reporting values at set intervals via a Kafka server. Kafka is a streaming data message broker that passes messages to different processing agents based on topics.
Processing streaming data is the perfect application for asynchronous Python. This allows us to process larger quantities of data concurrently, which could be very important in applications. Of course, we can't directly perform long-running analysis on this data in an asynchronous context, since this will interfere with the execution of the event loop.
For working with Kafka streams using Python's asynchronous programming features, we can use the Faust package. This package allows us to define asynchronous functions that will act as processing agents or services that can process or otherwise interact with a stream of data from...
