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

Time complexity – The big O notation

Before we can begin with this chapter, there is a simple notation that you need to understand. This chapter uses the big O notation to indicate the time complexity for an operation. Feel free to skip this section if you are already familiar with this notation. While the notation sounds really complicated, the concept is actually quite simple.

The big O letter refers to the capital version of the Greek letter Omicron, which means small-o (micron o).

When we say that a function takes O(1) time, it means that it generally only takes 1 step to execute. Similarly, a function with O(n) time would take n steps to execute, where n is generally the size (or length) of the object. This time complexity is just a basic indication of what to expect when executing the code, as it is generally what matters most.

In addition to O, several other characters might pop up in literature. Here’s an overview of the characters...