Python Multiprocessing Jump-Start: Develop Parallel Programs, Side-Step the GIL, and Use All CPU Cores
SuperFastPython, Jul 28, 2022 - Computers
Unlock parallel programming in Python (and run your code on all CPUs).
The multiprocessing module provides easy-to-use process-based concurrency in Python. Unlike Python threading, multiprocessing side-steps the infamous Global Interpreter Lock (GIL), allowing full parallelism in Python. This is not some random third-party library, this is an API provided in the Python standard library (already installed on your system).
This is the API you need to use to make your code run faster.
There's just one problem. Few developers know about it (or how to use it well).
Introducing: "Python Multiprocessing Jump-Start". A new book designed to teach you the multiprocessing module in Python, super fast! You will get a fast-paced, 7-part course to get you started and make you awesome at using the multiprocessing API.
Each of the 7 lessons was carefully designed to teach one critical aspect of the multiprocessing module, with explanations, code snippets and worked examples. Each lesson ends with an exercise for you to complete to confirm you understand the topic, a summary of what was learned, and links for further reading if you want to go deeper.
Stop copy-pasting code from StackOverflow answers.
Learn Python concurrency correctly, step-by-step.
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How to Configure the Start Method
Create and Start Child Processes
Configuring and Interacting with Processes
Synchronize and Coordinate Processes
Share Data Between Processes
Run Tasks with Reusable Workers in Pools
Share Centralized Objects with Managers