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

Processes, threads, or a single thread?

Now that we know how to use multiprocessing, threading and concurrent.futures, which should you choose for your case?

Since concurrent.futures implements both threading, and multiprocessing, you can mentally exchange threading in this section with concurrent.futures.ThreadPoolExecutor. The same goes for multiprocessing and concurrent.futures.ProcessPoolExecutor, of course.

When we consider the choice between single-threaded, multithreaded, and multiprocess, there are multiple factors that we can consider.

The first and most important question you should ask yourself is whether you really need to use threading or multiprocessing. Often, code is fast enough and you should ask yourself if the cost of dealing with the potential side effects of memory sharing and such is worth it. Not only does writing code become more complicated when parallel processing is involved, but the complexity of debugging is multiplied as well.

Second,...