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Python: Parallelism Vs Concurrency Vs Threading
Intro:
I believe understanding Concurrency, Threading, and Parallelism is essential, if you’re managing multiple tasks, speeding up processes, or ensuring independent workflows. These concepts might seem similar at first glance, but each has distinct roles in optimizing performance, much like how a café manages its staff and equipment.
In this article I will dive into these paradigms using relatable café scenarios to make these technical concepts accessible. I will also explore practical Python implementations using powerful libraries like asyncio, threading, and multiprocessing. Whether you're managing a single thread or leveraging multiple cores, you'll gain a clearer understanding of how to apply these concepts effectively in your projects.
Let's get brewing!
Concurrency 🕒:
Imagine you’re a single-barista café. You start brewing coffee for one order, and while it brews, you take another customer’s order, start steaming milk, then quickly begin assembling a sandwich for yet another customer.
You’re making progress on each order by constantly switching between tasks, ensuring everything gets done in an efficient…
