Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Mastering Python Regular Expressions
  • Table Of Contents Toc
  • Feedback & Rating feedback
Mastering Python Regular Expressions

Mastering Python Regular Expressions

4.7 (10)
close
close
Mastering Python Regular Expressions

Mastering Python Regular Expressions

4.7 (10)

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)
close
close

Chapter 3. Grouping

Grouping is a powerful tool that allows you to perform operations such as:

  • Creating subexpressions to apply quantifiers. For instance, repeating a subexpression rather than a single character.

  • Limiting the scope of the alternation. Instead of alternating the whole expression, we can define exactly what has to be alternated.

  • Extracting information from the matched pattern. For example, extracting a date from lists of orders.

  • Using the extracted information again in the regex, which is probably the most useful property. One example would be to detect repeated words.

Throughout this chapter, we will explore groups, from the simplest to the most complex ones. We'll review some of the previous examples in order to bring clarity to how these operations work.

Visually different images
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Mastering Python Regular Expressions
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon