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Mastering Python Regular Expressions
Mastering Python Regular Expressions

Mastering Python Regular Expressions: For Python developers, this concise and down-to-earth guide to regular expressions

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Mastering Python Regular Expressions

Chapter 2. Regular Expressions with Python

In the previous chapter, we've seen how generic regular expressions work. In this chapter, we walk you through all the operations Python provides us with to work with regular expressions and how Python deals with them.

To do so, we will see the quirks of the language when dealing with regular expressions, the different types of strings, the API it offers through the RegexObject and MatchObject classes, every operation that we can do with them in depth with many examples, as well as some problems generally faced by users. Lastly, we will see the small nuances and differences between Python and other regex engines and between Python 2 and Python 3.

A brief introduction


Since v1.5, Python provides a Perl-style regular expression with some subtle exceptions that we will see later. Both patterns and strings to be searched can be Unicode strings, as well as an 8-bit string (ASCII).

Tip

Unicode is the universal encoding with more than 110.00 characters and 100 scripts to represent all the world's living characters and even historic scripts. You can think of it as a mapping between numbers, or code points as they are called, and characters. So, we can represent every character, no matter in what language, with one single number. For example, the character is the number 26159, and it is represented as \u662f (hexadecimal) in Python.

Regular expressions are supported by the re module. So, as with all modules in Python, we only need to import it to start playing with them. For that, we need to start the Python interactive shell using the following line of code:

>>> import re

Once we have imported the module, we can start trying to match...

Backslash in string literals


Regular expressions aren't part of the core Python language. Thus, there isn't a special syntax for them and therefore they are handled as any other string. As we've seen in Chapter 1, Introducing Regular Expressions, the backslash character \ is used to indicate metacharacters or special forms in regular expressions. The backslash is also used in strings to escape special characters. In other words, it has a special meaning in Python. So, if we need to use the \ character, we'll have to escape it: \\. This will give the string literal meaning to the backslash. However, in order to match inside a regular expression, we should escape the backslashes, effectively writing four back slashes: \\\\.

Just as an example, let's write a regular expression to match \:

>>> pattern = re.compile("\\\\")
>>> pattern.match("\\author")
<_sre.SRE_Match at 0x104a88e68>

As you can see, this is tedious and difficult to understand when the pattern is long.

Python...

Building blocks for Python regex


In Python, there are two different objects dealing with Regex:

  • RegexObject: It is also known as Pattern Object. It represents a compiled regular expression

  • MatchObject: It represents the matched pattern

RegexObject

In order to start matching patterns, we'll have to compile the regex. Python gives us an interface to do that as we've seen previously. The result will be a pattern object or RegexObject. This object has several methods for typical operations on regular expressions. As we will see later, the re module provides a shorthand for every operation so that we can avoid compiling it first.

>>> pattern = re.compile(r'fo+')

The compilation of a regular expression produces a reusable pattern object that provides all the operations that can be done, such as matching a pattern and finding all substrings that match a particular regex. So, for example, if we want to know if a string starts with <HTML>, we can use the following code:

>>> pattern...

Compilation flags


When compiling a pattern string into a pattern object, it's possible to modify the standard behavior of the patterns. In order to do that, we have to use the compilation flags. These can be combined using the bitwise OR "|".

Flag

Python

Description

re.IGNORECASE or re.I

2.x

3.x

The pattern will match lower case and upper case.

re.MULTILINE or re.M

2.x

3.x

This flag changes the behavior of two metacharacters:

  • ^: Which now matches at the beginning of the string and at the beginning of each new line.

  • $: In this case, it matches at the end of the string and the end of each line. Concretely, it matches right before the newline character.

re.DOTALL or re.S

2.x

3.x

The metacharacter "." will match any character even the newline.

re.LOCALE or re.L

2.x

3.x

This flag makes \w, \W, \b, \B, \s, and \S dependent on the current locale.

"re.LOCALE just passes the character to the underlying C library. It really only works on bytestrings which have 1 byte per character. UTF...

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:

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...

Summary


This was a long chapter! We've covered a lot of material in it. We began with how strings work in Python and their different notations in Python 2.x and Python 3.x. After that, we looked at how to build regular expressions, the objects and interface the re module give us to deal with them, and the most important operations for searching and modifying strings. We also learned how to extract information from a pattern through MatchObject, such as the position or the groups of a match. We also learned how to modify the default behavior of some character classes and metacharacters using the compilation flags. And finally, we've seen how to deal with Unicode and the new features we can find in Python 3.x.

Throughout this chapter, we've seen that groups are crucial part of regular expressions and that many operations of the re module are meant to be used with groups. That's why we cover groups in depth in the following chapter.

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Description

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.

Who is this book for?

This book is aimed at Python developers who want to learn how to leverage Regular Expressions in Python. Basic knowledge of Python is required for a better understanding.

What you will learn

  • Explore the regular expressions syntax
  • Improve the readability and future maintenance of the regex
  • Find solutions for typical problems with regular expressions
  • Familiarize yourself with match and search operations
  • Leverage the look around technique to create powerful regular expressions
  • Gain insight on the uses of Groups
  • Get to know how the regex engine works through the Backtracking process
  • Enhance the performance of your regular expressions

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Table of Contents

5 Chapters
Introducing Regular Expressions Chevron down icon Chevron up icon
Regular Expressions with Python Chevron down icon Chevron up icon
Grouping Chevron down icon Chevron up icon
Look Around Chevron down icon Chevron up icon
Performance of Regular Expressions Chevron down icon Chevron up icon

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New Media Aug 06, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Great Learning tool.
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Javier Angulo Lucerón Jun 16, 2014
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It's a really well written book, with tons of examples to allow you understand from the basics to the most advanced features. I'm starting to leverage regular expressions thanks to this book, quite recommended.
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Doc Jun 19, 2018
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I used this book to learn and master regular expressions in Python. It is easy to follow and if you study each chapter carefully you will master regular expressions. It starts out with a brief overview of regex and then transitions to specific application of regex in python. Also great to have as a desk reference.
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Uncle Buck Sep 24, 2015
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If you are getting started with regular expressions the first chapter of this book is worth the price of the book in itself.I cannot praise this book enough. The well written and clear examples are fantastic. I've been struggling with regular expressions for a while but this book is a god send. Thank you Felix Lopez!!!!!
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DR Jan 05, 2020
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A great, concise and thorough book on using Regex in Python. Excellent, thoroughly recommended.
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