You're reading from Mastering Python 2E Write powerful and efficient code using the full range of Python's capabilities

Product type Paperback

Published in May 2022

Last Updated in May 2022

Publisher Packt

ISBN-13 9781800207721

Length 710 pages

Edition 2nd Edition

Languages

Python

Tools

Dask

Concepts

Programming Language

Author (1):

Rick Hattem

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Table of Contents (21) Chapters

Preface

1. Getting Started – One Environment per Project FREE CHAPTER

2. Interactive Python Interpreters

3. Pythonic Syntax and Common Pitfalls

4. Pythonic Design Patterns

5. Functional Programming – Readability Versus Brevity

6. Decorators – Enabling Code Reuse by Decorating

7. Generators and Coroutines – Infinity, One Step at a Time

8. Metaclasses – Making Classes (Not Instances) Smarter

9. Documentation – How to Use Sphinx and reStructuredText

10. Testing and Logging – Preparing for Bugs

11. Debugging – Solving the Bugs

12. Performance – Tracking and Reducing Your Memory and CPU Usage

13. asyncio – Multithreading without Threads

14. Multiprocessing – When a Single CPU Core Is Not Enough

15. Scientific Python and Plotting

16. Artificial Intelligence

17. Extensions in C/C++, System Calls, and C/C++ Libraries

18. Packaging – Creating Your Own Libraries or Applications

19. Other Books You May Enjoy

20. Index

What is performance?

Performance is a very broad term. It has many different meanings and, in many cases, it is defined incorrectly. Within this chapter, we will attempt to measure and improve performance in terms of CPU usage/time and memory usage. Many of the examples here are a trade-off between execution time and memory usage. Note that a fast algorithm that can only use a single CPU core can be outperformed in terms of execution time by a slower algorithm that is easily parallelizable given enough CPU cores.

When it comes to incorrect statements about performance, you have probably heard statements similar to “Language X is faster than Python.” That statement is inherently wrong. Python is neither fast nor slow; Python is a programming language, and a language has no performance metrics whatsoever. If you were to say that the CPython interpreter is faster or slower than interpreter Y for language X, that would be possible. The performance characteristics of...