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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20
Index

Multiple threads and processes

The multiprocessing module was introduced in Python 2.6, and it has been a game changer when it comes to working with multiple processes in Python. Specifically, it has made it rather easy to work around the limitations of the GIL because each process has its own GIL.

The usage of the multiprocessing module is largely similar to the threading module, but it has several really useful extra features that make much more sense with multiple processes. Alternatively, you can also use it with concurrent.futures.ProcessPoolExecutor, which has an interface nearly identical to concurrent.futures.ThreadPoolExecutor.

These similarities mean that in many cases you can simply swap out the modules and your code will keep running as expected. Don’t be fooled, however; while threads can still use the same memory objects and only have thread safety and deadlocks to worry about, multiple processes also have these issues and introduce several other issues...