🔍 Python Regular Expressions (RegEx) Made Easy

📘 What is RegEx?

RegEx (Regular Expression) is a powerful tool used to search, match, and manipulate strings using patterns.

Think of RegEx as a special search language. Instead of just checking if a string contains "hello", you can check if it contains a valid email, a phone number, or even specific word patterns.

Python provides support for RegEx using the re module.

🛠️ Getting Started: Importing the `re` Module

import re

This gives you access to RegEx functions like search, match, findall, and sub.

🔎 Basic RegEx Functions in Python

Function	Description
`re.match()`	Checks for a match at the beginning
`re.search()`	Searches the entire string
`re.findall()`	Returns all matches as a list
`re.sub()`	Replaces pattern matches 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`, `0`
`\w`	Any alphanumeric character	`a`, `1`, `_`
`\s`	Any whitespace	space, tab, newline

✅ Practical Examples

1. Check if a string starts with a word

import re

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 if a string is a phone number

phone = "123-456-7890"
pattern = r"^\d{3}-\d{3}-\d{4}$"
print(bool(re.match(pattern, phone)))  # True

🧠 When to Use RegEx

Validating inputs (email, phone numbers, usernames)
Extracting specific data from text
Text replacements and cleanups
Searching large text files or logs

⚠️ Tips for Using RegEx Safely

Test your patterns on small examples first.
Use raw strings r"pattern" in Python to avoid escaping backslashes.
Use online tools like regex101.com to test and explain patterns.

🚀 Final Thoughts

Regular expressions may seem tricky at first, but they’re an essential skill for any Python developer dealing with text, data validation, or web scraping. With practice, RegEx becomes a superpower that makes our code more efficient and capable.

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