Wrapping Up
In this chapter, you learned about Broadway, which not only simplifies working with message brokers but also takes away the complexity of assembling data-processing pipelines. We configured our pipeline to connect to a RabbitMQ server and consume events. We used processors to perform work concurrently and batchers to do further processing in bulk. Finally, you saw how to make your own producer from scratch, which showed you how versatile Broadway can be.
There are even more features in Broadway that we didn’t explore in this book but are well documented online. Examples include rate limiting, partitioning, and metrics exposed using the telemetry library. There are also various helpers that make testing Broadway pipelines easy. I encourage ...
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