Source code: Lib/re/ This module provides regular expression matching operations similar to those found in Perl. Both patterns and strings to be searched can be Unicode strings ( str) as well as 8-...

This document is an introductory tutorial to using regular expressions in Python with the re module. It provides a gentler introduction than the corresponding section in the Library Reference.

RegEx can be used to check if a string contains the specified search pattern. Python has a built-in package called re, which can be used to work with Regular Expressions.

Due to this, it’s not recommended to use raw Python strings (r"") for regular expressions. For example, r"\r\n" when used as the regular expression is equivalent to "rn". To match CR character followed by LF, use "\r\n". ... import re # As re doesn't support escapes itself, use of r"" strings is not # recommended. regex = re.compile("[\r\n]") regex.split("line1\rline2\nline3\r\n") # Result: # ['line1', 'line2', 'line3', '', '']

Regular expressions are a powerful language for matching text patterns. This page gives a basic introduction to regular expressions themselves sufficient for our Python exercises and shows how regular expressions work in Python.

August 14, 2025 - A Regular Expression or RegEx is a special sequence of characters that uses a search pattern to find a string or set of strings. It can detect the presence or absence of a text by matching it with a particular pattern and also can split a pattern ...

May 21, 2026 - In previous tutorials in this series, you've seen several different ways to compare string values with direct character-by-character comparison. In this tutorial, you'll learn how to perform more complex string pattern matching using regular expressions, or regexes, in Python.

In this tutorial, you will learn about regular expressions (RegEx), and use Python's re module to work with RegEx (with the help of examples).

June 2, 2025 - Regex101: An interactive online tool for testing and debugging regex patterns with real-time feedback. Python’s re Documentation: The official documentation (docs.python.org/3/library/re.html) provides detailed explanations and examples.

June 16, 2019 - It is important to note that most regular expression operations are available as module-level functions and methods on compiled regular expressions. The functions are shortcuts that don’t require you to compile a regex object first, but miss some fine-tuning parameters.

Python Regex Tutorial. Discusses the Python re and regex classes, provides working code for matching, replacing and splitting.

import re text = 'This is some text -- with punctuation.' pattern = r'(?i)\bT\w+' regex = re.compile(pattern) print 'Text :', text print 'Pattern :', pattern print 'Matches :', regex.findall(text) Because the options control the way the entire expression is evaluated or parsed, they should always come at the beginning of the expression. $ python re_flags_embedded.py Text : This is some text -- with punctuation.

In the regex (\s+)(?|(?P<foo>[A-Z]+)|(\w+) (?P<foo>[0-9]+) there are 2 groups: ... If you want to prevent (\w+) from being group 2, you need to name it (different name, different group number). The issue numbers relate to the Python bug tracker, except where listed otherwise.

July 22, 2025 - Download our Python regular expressions cheat sheet for syntax, character classes, groups, and re module functions—ideal for pattern matching.

A regular expression is a special sequence of characters that helps you match or find other strings or sets of strings, using a specialized syntax held in a pattern. Regular expression are popularly known as regex or regexp.

November 14, 2024 - Learn how to use regex in Python with the re module. Validate input, search text, and perform replacements easily using practical examples.

For a representation closer to Python one, please use PythonRegex · The concatenation can be represented either by a space or a dot ‘.’ · The union is represented either by ‘|’ or ‘+’ ... It is also possible to use parentheses. All symbols except the space, ‘.’, ‘|’, ‘+’, ‘*’, ‘(’, ‘)’, ‘epsilon’ and ‘$’ can be part of the alphabet. All other common regex operators (such as []) are syntactic sugar that can be reduced to the previous operators.

It is possible to tell an asterisk ... your regex will match the very first instance rather than the last instance. In the example above, using .+?@ would instead match the first at-sign, the one in [email protected]. For more details, see the Python documentation on greedy ...