Replacing Text Based on Patterns in Python

In this lesson, we'll explore how to replace text in strings based on specific patterns using Python's re module. Pattern-based text replacement is a powerful technique for cleaning, formatting, or transforming data efficiently.

Why Use Regular Expressions?

Regular expressions (regex) allow you to define complex search patterns for locating substrings within text. They are particularly useful when working with unstructured data like logs, emails, or user input.

Key Benefits of Regex

Precision: Define exact patterns for matching.
Flexibility: Handle multiple variations of text formats.
Efficiency: Process large datasets quickly.

Getting Started with the re Module

Python's built-in re module provides tools for working with regular expressions. Let's start by exploring its key functions for replacing text.

The `re.sub()` Function

The re.sub() function allows you to replace occurrences of a pattern with a specified string. Here's an example:

import re

# Replace all digits with 'X'
text = "My phone number is 123-456-7890."
result = re.sub(r'\d', 'X', text)
print(result)

Output:
My phone number is XXX-XXX-XXXX.

In this example, \d matches any digit, and every match is replaced with 'X'.

Advanced Substitution Techniques

You can also use captured groups in your regex patterns and reference them in the replacement string. For instance:

# Reformat dates from MM/DD/YYYY to YYYY-MM-DD
text = "The event is on 12/31/2023."
result = re.sub(r'(\d{2})/(\d{2})/(\d{4})', r'\3-\1-\2', text)
print(result)

Output:
The event is on 2023-12-31.

Here, parentheses capture parts of the date, and \1, \2, and \3 refer to those captured groups.

Conclusion

Pattern-based text replacement using Python's re module opens up endless possibilities for text processing. Experiment with different regex patterns and substitution techniques to master this skill!