Regular Expressions in Python

Learn how to search, match, validate and replace text patterns using Python regular expressions.

What is a Regular Expression?

A regular expression, also called a regex, is a pattern used to search and match text.

Python provides the built-in re module for working with regular expressions.

Regular Expression Flow

Importing the re Module

The re module provides functions for working with regular expressions.

import re

re.search()

The re.search() function searches the complete string for a matching pattern.

import re

text = "Python is easy to learn"

result = re.search("Python", text)

if result:

    print("Pattern found")

Output:

Pattern found

Search When No Match Exists

import re

text = "Python is easy to learn"

result = re.search("Java", text)

if result:

    print("Pattern found")

else:

    print("Pattern not found")

Output:

Pattern not found

re.match()

The re.match() function checks whether the pattern matches at the beginning of the string.

import re

text = "Python programming"

result = re.match("Python", text)

if result:

    print("Match found")

else:

    print("No match")

Output:

Match found

re.findall()

The re.findall() function returns all matching values found in the string.

import re

text = "Python Java Python C#"

result = re.findall("Python", text)

print(result)

Output:

['Python', 'Python']

re.split()

The re.split() function splits a string wherever the pattern is found.

import re

text = "Python,Java,C#"

result = re.split(",", text)

print(result)

Output:

['Python', 'Java', 'C#']

re.sub()

The re.sub() function replaces matching text with another value.

import re

text = "Python is easy"

result = re.sub("easy", "powerful", text)

print(result)

Output:

Python is powerful

Common Regex Patterns

\d

\w

\s

Finding Digits

import re

text = "My marks are 85"

result = re.findall(r"\d+", text)

print(result)

Output:

['85']

Finding Words

import re

text = "Python is easy"

result = re.findall(r"\w+", text)

print(result)

Output:

['Python', 'is', 'easy']

Example: Phone Number Validation

import re

phone = "9876543210"

pattern = r"^[0-9]{10}$"

if re.match(pattern, phone):

    print("Valid phone number")

else:

    print("Invalid phone number")

Output:

Valid phone number

Example: Email Validation

The following pattern uses \x40 to represent the email separator character.

import re

email = "student@example.com"

pattern = r"^[\w.-]+\x40[\w.-]+\.\w+$"

if re.match(pattern, email):

    print("Valid email")

else:

    print("Invalid email")

Output:

Valid email

Example 📩🤓

The following example finds all numbers inside a text string.

import re

text = "Python course costs 30000 and lasts 5 months"

numbers = re.findall(r"\d+", text)

print(numbers)

Output:

['30000', '5']

Advantages of Regular Expressions

Best Practices

Common Mistakes

• Writing an incorrect regex pattern.
• Forgetting to import the re module.
• Using re.match() when a complete string search is required.
• Not testing both matching and non-matching values.

Practice Programs

1. Search for a word inside a string using re.search().
2. Find all numbers in a string using re.findall().
3. Split a string using re.split().
4. Replace a word using re.sub().
5. Validate a phone number using a regular expression.
6. Validate an email address using a regular expression.