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Python
8 Levels of Using Multiprocessing in Python
Leverage process-based parallelism for high-performance code
Python is simple until you meet multiprocessing.
Because, unlike other straightforward syntax, multiprocessing demands a deeper understanding of system-level operations and concepts, like process management, race conditions, and locks.
It’s a bit complex but can help you leverage modern multi-core CPUs to write high-performance Python applications.
This article will guide you step by step. It explains Python’s multiprocessing usages with beginner-friendly examples in 8 progressive levels, ensuring you understand the concepts and apply them effectively.
Level 1: Know How To Create a New Process
When it comes to multiprocessing in Python, the multiprocessing module is our friend.
Although different operation systems may have different ways of creating and managing processes, this module has encapsulated common operations, so in most cases, we only need to use its interfaces without worrying about the underlying mechanisms of the operating system.
For example, the following code snippet forks a new process named p from the main…
