Python RegEx

Python RegEx: Pattern Matching & Regex Module re

Regular expressions provide powerful string matching, extraction, and substitution capabilities via Python's built-in re module.

Regex Processing Flow

flowchart TD
    A["Raw Pattern String r'...'"] --> B["re.compile(pattern)"]
    B --> C["Regex Pattern Object"]
    C --> D["Search / Match / Findall Operation"]
    D --> E["Match Object (groups, start, end)"]

Key Functions in re

• re.search(pattern, string): Scans string for first pattern location; returns a Match object or None.
• re.findall(pattern, string): Returns all non-overlapping matches as a list of strings/tuples.
• re.sub(pattern, replacement, string): Replaces pattern occurrences with replacement string.
• re.compile(pattern): Pre-compiles regex pattern into a reusable Regex Object for performance.

Practical Code Example

import re
from typing import List, Dict

def extract_contact_info(text: str) -> Dict[str, List[str]]:
    # Use raw string r'...' to prevent backslash escaping issues
    email_pattern = re.compile(r'[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}')
    phone_pattern = re.compile(r'\d{3}[-.]?\d{3}[-.]?\d{4}')

    emails = email_pattern.findall(text)
    phones = phone_pattern.findall(text)

    # Clean telephone formats via re.sub
    cleaned_phones = [re.sub(r'[-.]', '', p) for p in phones]

    return {
        "emails": emails,
        "phones": cleaned_phones
    }

if __name__ == "__main__":
    raw_document = """
    For security support, contact [email protected] or [email protected].
    Emergency hotline: 555-123-4567 or direct line 555.987.6543.
    """
    
    info = extract_contact_info(raw_document)
    print("Extracted Emails:", info["emails"])
    print("Extracted Cleaned Phones:", info["phones"])

Best Practices & Gotchas

• Always Use Raw Strings r"...": Always prefix regex pattern strings with r to prevent Python from parsing , , or  as escape sequences.
• Pre-compile Frequent Regexes: Use re.compile() outside loops when evaluating the same pattern against thousands of strings.
• Avoid Catastrophic Backtracking: Avoid nested quantifiers like (a+)+ which cause exponential CPU execution times on non-matching strings.

Self-Check Challenge

Write a regex pattern that validates whether a given string is a valid IPv4 address (four dot-separated integers from 0 to 255).