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

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...