Book Image

Mastering Python 2E - Second Edition

By : Rick van Hattem
5 (1)
Book Image

Mastering Python 2E - Second Edition

5 (1)
By: Rick van Hattem

Overview of this book

Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python’s capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code’s performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges
Table of Contents (21 chapters)
19
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Index

Multiprocessing – When a Single CPU Core Is Not Enough

In the previous chapter, we discussed asyncio, which can use the threading and multiprocessing modules but mainly uses single-thread/single-process parallelization. In this chapter, we will see how we can directly use multiple threads or processes to speed up our code and what caveats to keep in mind. This chapter can actually be seen as an extension to the list of performance tips.

The threading module makes it possible to run code in parallel in a single process. This makes threading very useful for I/O-related tasks such as reading/writing files or network communication, but a useless option for slow and heavy calculations, which is where the multiprocessing module shines.

With the multiprocessing module, you can run code in multiple processes, which means you can run code on multiple CPU cores, multiple processors, or even on multiple computers. This is an easy way to work around the Global Interpreter Lock...