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)

Optimization recommendations


In the following sections, we will find a number of recommendations that could be applied to improve regular expressions.

The best tool will always be common sense, and common sense will need to be used even while following these recommendations. It has to be understood when the recommendation is applicable and when it is not. For instance, the recommendation don't be greedy cannot be used in all the cases.

Reuse compiled patterns

We have learned in Chapter 2, Regular Expressions with Python, that to use a regular expression we have to convert it from its string representation to a compiled form as RegexObject.

This compilation takes some time. If we are using the rest of the module operations instead of using the compile function to avoid the creation of the RegexObject, we should understand that the compilation is executed anyway and a number of compiled RegexObject are cached automatically.

However, when we are compiling, that cache won't back us. Every single...