Python Regular Expressions

What are Regular Expressions?

Regular expressions (regex) are patterns for matching and extracting text. Instead of searching for one exact string, you write a pattern that matches any string fitting a rule — like "any email address" or "any UK phone number". Python's re module provides all regex functionality. Key pattern characters: \d = digit, \w = word character, \s = whitespace, . = any character, + = one or more, * = zero or more, ? = optional.

search() and match()

re.search() finds the pattern anywhere in the string and returns a match object (or None). re.match() only matches at the very start. Call .group() on the match to get the matched text.

import re

text = "Contact us at hello@example.com for help"
m = re.search(r"\w+@\w+\.\w+", text)
if m:
    print("Found:", m.group())
    print("At position:", m.start())

Found: hello@example.com
At position: 14

findall() — All Matches

re.findall() returns a list of every non-overlapping match. This is the most commonly used regex function when you want to extract multiple pieces of data from text.

import re

text = "Prices: £10, £25.50, £3.99, £100"
print(re.findall(r"£[\d.]+", text))

text2 = "Phone: 020-7946-0321 or 07700-900123"
print(re.findall(r"[\d-]+", text2))

['£10', '£25.50', '£3.99', '£100']
['020-7946-0321', '07700-900123']

Substitution with sub()

re.sub(pattern, replacement, text) replaces every match with the replacement string. Powerful for cleaning and transforming text data.

import re

# Remove all punctuation
clean = re.sub(r"[^\w\s]", "", "Hello, World! How are you?")
print(clean)

# Convert DD/MM/YYYY to YYYY-MM-DD
date = re.sub(r"(\d{{2}})/(\d{{2}})/(\d{{4}})", r"\3-\2-\1", "Date: 25/12/2024")
print(date)

Hello World How are you
Date: 2024-12-25