Book Image

Secret Recipes of the Python Ninja

Book Image

Secret Recipes of the Python Ninja

Overview of this book

This book covers the unexplored secrets of Python, delve into its depths, and uncover its mysteries. You’ll unearth secrets related to the implementation of the standard library, by looking at how modules actually work. You’ll understand the implementation of collections, decimals, and fraction modules. If you haven’t used decorators, coroutines, and generator functions much before, as you make your way through the recipes, you’ll learn what you’ve been missing out on. We’ll cover internal special methods in detail, so you understand what they are and how they can be used to improve the engineering decisions you make. Next, you’ll explore the CPython interpreter, which is a treasure trove of secret hacks that not many programmers are aware of. We’ll take you through the depths of the PyPy project, where you’ll come across several exciting ways that you can improve speed and concurrency. Finally, we’ll take time to explore the PEPs of the latest versions to discover some interesting hacks.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell
Foreword
Contributors
Preface
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...