Regex Introduction in Python

Introduction

Regular expressions, or regex, are powerful tools used to search, match, and manipulate text based on specific patterns.

Python provides a built-in module called 're' that allows you to work with regex efficiently.

This tutorial introduces the fundamental concepts of regex in Python, helping you understand how to create and use patterns.

Regex is like a Swiss Army knife for text processing.

What is Regex?

Regex stands for regular expressions, which are sequences of characters defining search patterns.

They are commonly used for validating input, searching within strings, and replacing text.

• Match specific characters or sequences.
• Search for patterns in large text data.
• Validate formats like emails, phone numbers, and dates.

Basic Regex Syntax

Regex patterns consist of ordinary characters and special symbols that represent sets, repetitions, or positions.

Understanding these symbols is key to building effective regex patterns.

• `.` matches any single character except newline.
• `^` matches the start of a string.
• `$` matches the end of a string.
• `*` matches zero or more repetitions of the preceding element.
• `+` matches one or more repetitions.
• `?` matches zero or one repetition.
• `[]` defines a character class.
• `\d` matches any digit (0-9).
• `\w` matches any alphanumeric character or underscore.
• `\s` matches any whitespace character.

Using Python's re Module

Python's 're' module provides functions to work with regex patterns.

Common functions include 'match', 'search', 'findall', and 'sub'.

• `re.match(pattern, string)` checks for a match at the beginning of the string.
• `re.search(pattern, string)` searches for the first occurrence anywhere in the string.
• `re.findall(pattern, string)` returns all non-overlapping matches as a list.
• `re.sub(pattern, repl, string)` replaces matches with a replacement string.

Example: Matching an Email Address

Let's see a practical example of using regex to validate an email address format.