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)

Python and regex special considerations


In this section, we will review differences with other flavors, how to deal with Unicode, and also differences in the re module between Python 2.x and Python 3.

Differences between Python and other flavors

As we mentioned at the beginning of the book, the re module has Perl-style regular expressions. However, that doesn't mean Python support every feature the Perl engine has.

There are too many differences to cover them in a short book like this, if you want to know them in-depth here you have two good places to start:

  • http://en.wikipedia.org/wiki/Comparison_of_regular_expression_engines

  • http://www.regular-expressions.info/reference.html

Unicode

When you're using Python 2.x and you want to match Unicode, the regex has to be Unicode escape. For example:

>>> re.findall(r"\u03a9", u"adeΩa")
[]
>>> re.findall(ur"\u03a9", u"adeΩa")
[u'\u03a9']

Note that if you use Unicode characters but the type of the string you're using is not Unicode, python...