Using the re Module

The re module in Python provides functions for working with regular expressions. It allows you to match, search, replace, and split text based on patterns.

Basic Usage

Python

import re

text = "The phone number is 415-555-1212."
pattern = r'\d{3}-\d{3}-\d{4}'

match = re.search(pattern, text)
if match:
    print("Phone number found:", match.group())
else:
    print("Phone number not found")

Common Functions

• re.match(): Matches the pattern at the beginning of the string.
• re.search(): Searches for the pattern anywhere in the string.
• re.findall(): Returns a list of all non-overlapping matches in the string.
• re.sub(): Replaces occurrences of the pattern with a new string.
• re.split(): Splits the string at occurrences of the pattern.

Example:

Python

import re

text = "The quick brown fox jumps over the lazy dog."

# Find all words
words = re.findall(r'\w+', text)
print(words)

# Replace 'fox' with 'cat'
new_text = re.sub(r'fox', 'cat', text)
print(new_text)

Match Object

The re.search() and re.match() functions return a match object if there is a match. This object contains information about the match, such as the matched text, start and end positions, and groups.

Python

match = re.search(r'(\d{3})-(\d{3})-(\d{4})', text)
if match:
    area_code, exchange, number = match.groups()
    print(area_code, exchange, number)

Compiling Regular Expressions

For performance reasons, you can compile a regular expression into a pattern object using re.compile().

Python

import re

phone_pattern = re.compile(r'\d{3}-\d{3}-\d{4}')
match = phone_pattern.search(text)

Additional Features

• Flags: Modify the behavior of regular expressions (e.g., re.IGNORECASE for case-insensitive matching).
• Groups: Capture specific parts of the matched text using parentheses.
• Lookahead and lookbehind assertions: Match text without including it in the match.

By understanding these core functions and concepts, you can effectively use regular expressions in your Python programs.

Using the re Module

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