Python

Regular Expressions

Master pattern matching with regex. Learn to search, validate, and manipulate text using the re module.

By TechCoder TeamLast updated: 2026-06-02
In a Nutshell

Master pattern matching with regex. Learn to search, validate, and manipulate text using the re module. This hands-on tutorial focuses on practical implementation of regular expressions concepts.

Regular Expressions

Regular Expressions (regex) are powerful patterns for matching and manipulating text.

Basic Patterns

PatternMatchesExample
.Any charactera.c matches "abc", "a1c"
*0 or moreab*c matches "ac", "abc", "abbc"
+1 or moreab+c matches "abc", "abbc" (not "ac")
?0 or 1ab?c matches "ac", "abc"
^Start of string^Hello matches "Hello world"
$End of stringworld$ matches "Hello world"

Character Classes

PatternMatches
[abc]a, b, or c
[a-z]Any lowercase letter
[A-Z]Any uppercase letter
[0-9]Any digit
\dDigit (same as [0-9])
\wWord character (letter, digit, underscore)
\sWhitespace
\DNon-digit
\WNon-word character
\SNon-whitespace

The re Module

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Common Patterns

Email Validation

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Phone Number Extraction

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Capture Groups

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re.sub() - Find and Replace

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Regex Flags

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Coding Challenge: Log Parser 📋

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AI Mentor

Confused about "Python regular expressions regex pattern matching"? Ask our AI mentor for a simplified explanation.

Quiz

Quiz

Question 1 of 5

What does the + quantifier mean?

0 or more occurrences
1 or more occurrences
Exactly one occurrence
0 or 1 occurrence

Key Takeaways

Regex patterns match text using special syntax.
re.search() finds first match, re.findall() finds all.
Character classes like \d, \w, \s match common patterns.
Capture groups () extract parts of matches.
re.sub() replaces matched text.

What's Next?

In the next lesson, we'll learn about Iterators & Generators - memory-efficient ways to work with sequences.

Keep coding! 🚀