Moving data around could be slow. Here’s how you’ll be able to squeeze every little bit of performance optimization out of Python.
Python is commonly criticized for being among the many slowest programming languages. While that claim does hold some weight, it’s vital to indicate that Python is commonly the primary programming language newcomers learn. Hence, many of the code is extremely unoptimized.
But Python does have a few tricks up its sleeve. Making the most of concurrent function execution is stupidly easy to implement, yet it will possibly reduce the runtime of your data pipelines tenfold. As a substitute of hours, it’ll take minutes. All free of charge.
Today you’ll see how concurrency works in Python, and also you’ll also learn the right way to take care of exception handling, custom callbacks, and rate limiting. Let’s dig in!
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