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Secret Recipes of the Python Ninja

You're reading from   Secret Recipes of the Python Ninja Over 70 recipes that uncover powerful programming tactics in Python

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788294874
Length 380 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (17) Chapters Close

Title Page
Copyright and Credits
Packt Upsell
Foreword
Contributors
Preface
1. Working with Python Modules FREE CHAPTER 2. Utilizing the Python Interpreter 3. Working with Decorators 4. Using Python Collections 5. Generators, Coroutines, and Parallel Processing 6. Working with Python's Math Module 7. Improving Python Performance with PyPy 8. Python Enhancement Proposals 9. Documenting with LyX 1. Other Books You May Enjoy Index

When to use parallel processing


Concurrency means stopping one task to work on another. With a coroutine, the function stops execution and waits for more input to continue. In this sense, you can have several operations pending at the same time; the computer simply switches to the next one when it is time.

This is where multitasking in operating systems comes from: a single CPU can handle multiple jobs at the same time by switching between them. In simple terms, concurrency is when multiple threads are being processed during a given time period. In contrast, parallelism means the system runs two or more threads simultaneously; that is, multiple threads are processed at a given point in time. This can only occur when there is more than one CPU core available.

The benefit of parallelizing code comes from doing more with less. In this case, it's doing more work with fewer CPU cycles. Before multi-core systems, the only real way to improve performance was to increase the clock speed on the computer...

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