Mastering Python RegEx: A Complete Guide
What is RegEx?
RegEx (Regular Expression) is a powerful tool for searching, matching, and manipulating text using patterns.
Think of RegEx as a special search language. Instead of just checking for a literal word, you can match patterns like:
- Valid emails
- Phone numbers
- Specific word structures
Python provides RegEx support via the re module.
Getting Started: Import the re Module
import re
This gives you access to functions like search, match, findall, and sub.
Basic RegEx Functions in Python
| Function | Description |
|---|---|
re.match() |
Checks for a match at the beginning of a string |
re.search() |
Searches for a pattern anywhere in the string |
re.findall() |
Returns all matches as a list |
re.sub() |
Replaces matched patterns with a string |
📌 Common RegEx Patterns Cheat Sheet
| Pattern | Meaning | Example Match |
|---|---|---|
. | Any character except newline | a.c → abc, axc |
^ | Start of string | ^Hello |
$ | End of string | world$ |
* | 0 or more repetitions | lo* → looo |
+ | 1 or more repetitions | lo+ → loo |
? | 0 or 1 occurrence | colou?r → color, colour |
{n} | Exactly n times | a{3} → aaa |
[abc] | Any one of a, b, or c | b |
\d | Any digit (0–9) | 1, 7 |
\w | Any alphanumeric character | a, 1, _ |
\s | Whitespace character | space, tab, newline |
Practical Examples
1. Check if a string starts with a word
text = "Python is awesome"
result = re.match(r"Python", text)
print(bool(result)) # True
2. Find all digits in a string
text = "My number is 123-456-7890"
digits = re.findall(r"\d+", text)
print(digits) # ['123', '456', '7890']
3. Extract email addresses
text = "Contact us at support@example.com or info@domain.org"
emails = re.findall(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}", text)
print(emails) # ['support@example.com', 'info@domain.org']
4. Replace all whitespace with hyphens
text = "This is a test"
new_text = re.sub(r"\s", "-", text)
print(new_text) # This-is-a-test
5. Validate a phone number format
phone = "123-456-7890"
pattern = r"^\d{3}-\d{3}-\d{4}$"
print(bool(re.match(pattern, phone))) # True
When to Use RegEx
- Input validation (emails, phone numbers, usernames)
- Extracting specific data from text
- Text replacement or cleanup
- Searching large text files or logs
Tips for Using RegEx Safely
- Test patterns on small examples first.
- Use raw strings
r"pattern"to avoid escaping backslashes. - Try online tools like regex101.com for testing and debugging patterns.
Final Thoughts
Regular expressions may seem tricky initially, but they are an essential skill for Python developers dealing with text, validation, or data extraction. With practice, RegEx becomes a superpower that simplifies and strengthens your code.
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