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Re Module

Regular expressions are powerful tools in programming languages for searching, matching, and manipulating text. The re module in Python provides support for regular expressions.

Task​

Write a program that accepts a list of email addresses and uses regular expressions to extract the username and domain of each address.

JavaScript implementation​

const emailAddresses = [
  "john.doe@example1.com",
  "jane.smith@example2.com",
  "foo@bar.com",
];

const regex = /([^@]+)@(.+)/;

emailAddresses.forEach((email) => {
  const [_, username, domain] = email.match(regex);
  console.log(`Username: ${username}, Domain: ${domain}`);
});

Python implementation:

import re

email_addresses = [
  "john.doe@example1.com",
  "jane.smith@example2.com",
  "foo@bar.com",
]

regex = re.compile(r"([^@]+)@(.+)")

for email in email_addresses:
  match = regex.match(email)
  if match:
    username, domain = match.groups()
    print(f"Username: {username}, Domain: {domain}")
tip

In Python, prefixing a string with r indicates a raw string literal, which treats backslashes as literal characters.

Code Highlight​

  • In JavaScript, regular expressions can be defined using /.../ or new Regex(...), while in Python, you can create a regular expression using the re.compile() function.

Difference Quick View​

FeatureJavaScriptPython
Creating a regular expressionconst myReg = /pattern/; or new Regex(pattern)my_regex = re.compile(r'pattern')
Matching a regular expressionmyReg.test(myStr)my_regex.match(my_str)
Finding the first matchmyReg.exec(myStr)my_regex.search(my_str)
Finding all matchesmyStr.match(myReg)my_regex.findall(my_str)
Replacing matchesmyStr.replace(myReg, replacement)my_regex.sub(replacement, my_str)
Splitting a string using a regular expressionmyStr.split(myReg)my_regex.split(my_str)
tip

In addition to using re.compile() to create a regular expression, you can also directly use methods like re.search() and re.split() from the re module to achieve the same functionality, such as:

import re

re.search(r'pattern', my_str)
re.split(r'pattern', my_str)

Resources​