Threaded Asynchronous Magic and How to Wield It
Ok let’s face it. Clock speeds no longer govern the pace at which computer processors improve. Instead we see increased transistor density and higher core counts. Translating to software terms, this means that code won’t run faster, but more of it can run in parallel.
Although making good use of our new-found silicon real estate requires improvements in software, a lot of programming languages have already started down this path by adding features that help with parallel execution. In fact, they’ve been there for years waiting for us to take advantage.
So why don’t we? A good engineer always has an ear to the ground, listening for the latest trends in his industry, so let’s take a look at what Python is building for us.
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