Regex Basics and the re Module

A regular expression (regex) is a pattern that describes a set of strings. Python's re module provides functions to search, match, and manipulate text using these patterns.

import re

# re.search() - find first match anywhere in string
result = re.search(r"\d+", "Order #4523 confirmed")
print(result.group())  # 4523

# re.match() - match only at the START of string
result = re.match(r"Hello", "Hello, World!")
print(result.group())  # Hello

# re.findall() - find ALL matches, return as list
emails = "Contact [email protected] or [email protected]"
found = re.findall(r"\w+@\w+\.\w+", emails)
print(found)  # ['[email protected]', '[email protected]']

# re.sub() - search and replace
text = "My phone is 0412-345-678"
cleaned = re.sub(r"-", "", text)
print(cleaned)  # My phone is 0412345678

Always use raw strings (r"...") for regex patterns to avoid issues with backslash escaping.

Common Regex Patterns

Regex uses special characters called metacharacters to build patterns. Here are the most important ones for Year 12.

Pattern	Meaning	Example Match
\d	Any digit (0-9)	"7" in "Year 7"
\w	Word character (a-z, A-Z, 0-9, _)	"Hello"
\s	Whitespace (space, tab, newline)	" " in "hello world"
.	Any character except newline	"a", "1", "!"
+	One or more of previous	\d+ matches "123"
*	Zero or more of previous	a* matches "", "aaa"
?	Zero or one of previous	colou?r matches "color", "colour"
[abc]	Character class (a, b, or c)	[aeiou] matches vowels

# Combining patterns
import re

# Match Australian phone numbers: 04XX-XXX-XXX
phone_pattern = r"04\d{2}-\d{3}-\d{3}"
text = "Call me at 0412-345-678 or 0498-765-432"
phones = re.findall(phone_pattern, text)
print(phones)  # ['0412-345-678', '0498-765-432']

# Match email addresses
email_pattern = r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}"
text = "Email [email protected] or [email protected]"
print(re.findall(email_pattern, text))
# ['[email protected]', '[email protected]']

Groups and Advanced Substitution

Capturing groups use parentheses to extract specific parts of a match. You can reference groups in substitutions using \1, \2, etc.

import re

# Capturing groups with ()
date_text = "Born on 15/03/2008"
match = re.search(r"(\d{2})/(\d{2})/(\d{4})", date_text)
if match:
    day, month, year = match.groups()
    print(f"Day: {day}, Month: {month}, Year: {year}")
    # Day: 15, Month: 03, Year: 2008

# Named groups with (?P<name>...)
pattern = r"(?P<first>\w+)\s(?P<last>\w+)"
m = re.match(pattern, "Jane Smith")
print(m.group("first"))  # Jane
print(m.group("last"))   # Smith

# Substitution with groups - reformat dates
dates = "15/03/2008 and 22/07/2010"
reformatted = re.sub(r"(\d{2})/(\d{2})/(\d{4})", r"\3-\2-\1", dates)
print(reformatted)  # 2008-03-15 and 2010-07-22

Key Vocabulary

Regular Expression

A pattern string used to match, search, and manipulate text based on rules and special characters.

Metacharacter

A character with special meaning in regex (e.g., ., *, +, ?, \d).

Capturing Group

A part of a regex enclosed in parentheses that extracts the matched text for later use.

Raw String

A string prefixed with r that treats backslashes as literal characters, essential for regex patterns.

Worked Examples

1

Validate an Australian postcode (4 digits)

import re

def is_valid_postcode(code):
    """Check if string is a valid 4-digit Australian postcode."""
    pattern = r"^\d{4}$"
    return bool(re.match(pattern, code))

print(is_valid_postcode("2000"))   # True (Sydney)
print(is_valid_postcode("3000"))   # True (Melbourne)
print(is_valid_postcode("123"))    # False (too short)
print(is_valid_postcode("12345"))  # False (too long)
print(is_valid_postcode("abcd"))   # False (not digits)

^ and $ anchor the pattern to the start and end of the string, ensuring the entire string is exactly 4 digits.

2

Extract all hashtags from a social media post

import re

def extract_hashtags(text):
    """Find all #hashtags in text."""
    return re.findall(r"#(\w+)", text)

post = "Loving #Python and #coding! #Year12 is challenging but fun"
tags = extract_hashtags(post)
print(tags)  # ['Python', 'coding', 'Year12']

The parentheses around \w+ create a capturing group that returns just the tag name without the # symbol.

3

Censor profanity by replacing words with asterisks

import re

def censor_words(text, banned_words):
    """Replace banned words with asterisks."""
    for word in banned_words:
        pattern = re.compile(re.escape(word), re.IGNORECASE)
        replacement = "*" * len(word)
        text = pattern.sub(replacement, text)
    return text

banned = ["spam", "scam"]
message = "This is SPAM and a Scam alert"
print(censor_words(message, banned))
# This is **** and a **** alert

re.IGNORECASE makes the match case-insensitive. re.escape() ensures special regex characters in the word are treated literally.

Knowledge Check

Select the correct answer for each question. Click "Check Answer" to see if you are right.

Question 1

What does \d+ match?

Exactly one digit Zero or more digits One or more digits Any word character

Question 2

What is the difference between re.search() and re.match()?

match() is faster because it uses binary search They are identical in behaviour search() returns a list; match() returns a single result search() looks anywhere; match() only checks the start of the string

Question 3

What does re.findall(r"\w+", "Hello World") return?

["Hello", "World"] ["Hello World"] "Hello" ["H","e","l","l","o","W","o","r","l","d"]

Question 4

Why should you use raw strings (r"...") for regex patterns?

They make the regex run faster They prevent backslashes from being interpreted as escape characters They are required by the re module They allow Unicode characters

Question 5

What does re.sub(r"\s+", " ", text) do?

Removes all spaces from text Adds spaces between words Replaces one or more whitespace characters with a single space Counts the number of spaces

Python Regular Expressions