Book Image

Mastering Python Regular Expressions

Book Image

Mastering Python Regular Expressions

Overview of this book

Regular expressions are used by many text editors, utilities, and programming languages to search and manipulate text based on patterns. They are considered the Swiss army knife of text processing. Powerful search, replacement, extraction and validation of strings, repetitive and complex tasks are reduced to a simple pattern using regular expressions. Mastering Python Regular Expressions will teach you about Regular Expressions, starting from the basics, irrespective of the language being used, and then it will show you how to use them in Python. You will learn the finer details of what Python supports and how to do it, and the differences between Python 2.x and Python 3.x. The book starts with a general review of the theory behind the regular expressions to follow with an overview of the Python regex module implementation, and then moves on to advanced topics like grouping, looking around, and performance. You will explore how to leverage Regular Expressions in Python, some advanced aspects of Regular Expressions and also how to measure and improve their performance. You will get a better understanding of the working of alternators and quantifiers. Also, you will comprehend the importance of grouping before finally moving on to performance optimization techniques like the RegexBuddy Tool and Backtracking. Mastering Python Regular Expressions provides all the information essential for a better understanding of Regular Expressions in Python.
Table of Contents (12 chapters)

Chapter 5. Performance of Regular Expressions

Up to this point, we worried about learning how to leverage a feature or obtain a result without caring too much about how fast the process would be. Our only goals were correctness and readability.

In this chapter, we are going to steer towards a completely different concern—performance. However, we will find that often an improvement in performance will result in degradation of readability. When we are modifying something to make it faster, we are probably making it easier for the machine to understand, and therefore, we are probably compromising on human readability.

On December 4, 1974, Donald Knuth, the author of the famous book The Art of Computer Programming, wrote the paper Structured Programming with go-to statements. This well-known quote is extracted from the paper:

"Programmers waste enormous amounts of time thinking about, or worrying about, the speed of noncritical parts of their programs, and these attempts at efficiency actually...