What is Python Regex | Regular Expression?

In Python, regular expressions (regex) are a powerful way to search for and manipulate strings. Python’s built-in re module provides functionality for working with regular expressions.

Here’s a basic overview of how to use regular expressions in Python:

1. Importing the re Module

To use regular expressions in Python, you need to import the re module.

import re

2. Basic Syntax for Regular Expressions

• .: Matches any character except a newline.
• ^: Matches the start of the string.
• $: Matches the end of the string.
• []: Matches any character within the brackets.
• |: Acts like a logical OR, matches the pattern on the left or right of it.
• (): Groups patterns together for applying quantifiers or capturing groups.
• \: Escapes a special character or signals a special sequence (like \d for digits, \w for word characters, etc.).

3. Commonly Used Functions in re Module

• re.match(pattern, string): Tries to match the pattern at the start of the string.
• re.search(pattern, string): Searches for the first match of the pattern anywhere in the string.
• re.findall(pattern, string): Returns all non-overlapping matches of the pattern in the string as a list.
• re.finditer(pattern, string): Returns an iterator yielding match objects for all matches.
• re.sub(pattern, repl, string): Replaces the occurrences of the pattern with the replacement string.
• re.split(pattern, string): Splits the string by the occurrences of the pattern.

4. Special Sequences in Regex

• \d: Matches any digit (0-9).
• \D: Matches any non-digit character.
• \w: Matches any alphanumeric character (letters and digits) plus the underscore.
• \W: Matches any non-alphanumeric character.
• \s: Matches any whitespace character (spaces, tabs, newlines).
• \S: Matches any non-whitespace character.
• \b: Matches a word boundary.
• \B: Matches a non-word boundary.

5. Example Usage

Example 1: Matching a Pattern at the Start of a String

import re

text = "Hello, world!"
pattern = r"^Hello"
match = re.match(pattern, text)

if match:
    print("Match found:", match.group())
else:
    print("No match")

Example 2: Searching for a Pattern Anywhere in the String

text = "The rain in Spain falls mainly in the plain."
pattern = r"rain"
result = re.search(pattern, text)

if result:
    print("Match found:", result.group())
else:
    print("No match")

Example 3: Finding All Matches

text = "cat, bat, rat, flat"
pattern = r"\b\w{3}\b"  # Matches all 3-letter words
matches = re.findall(pattern, text)
print(matches)

Example 4: Replacing Text Using re.sub

text = "The sky is blue."
pattern = r"blue"
replacement = "clear"
new_text = re.sub(pattern, replacement, text)
print(new_text)

6. Using Groups in Regex

You can capture parts of the matched string using parentheses () to create groups.

text = "My number is 123-456-7890."
pattern = r"(\d{3})-(\d{3})-(\d{4})"
match = re.search(pattern, text)

if match:
    print("Area code:", match.group(1))
    print("First part of number:", match.group(2))
    print("Second part of number:", match.group(3))

7. Quantifiers

• *: Matches 0 or more occurrences of the preceding pattern.
• +: Matches 1 or more occurrences of the preceding pattern.
• ?: Matches 0 or 1 occurrence of the preceding pattern.
• {n}: Matches exactly n occurrences of the preceding pattern.
• {n,}: Matches n or more occurrences of the preceding pattern.
• {n,m}: Matches between n and m occurrences of the preceding pattern.

8. Example: Validating an Email Address

import re

email = "[email protected]"
pattern = r"^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$"

if re.match(pattern, email):
    print("Valid email")
else:
    print("Invalid email")

This is just a brief overview of regular expressions in Python. Regular expressions are highly flexible and can be used for complex pattern matching and text manipulation tasks. If you have a specific regex problem or pattern you’re working with, feel free to ask for more tailored help!