Python RegEx Module

Python RegEx Module: Advanced Flags, Groups, & Substitutions

Python's re module supports advanced pattern matching capabilities including named capture groups, lookaheads, lookbehinds, and pattern flags.

Regex Match Groups & Flags

• (?P<name>pattern): Named capture group accessible via match.group('name').
• (?=pattern): Positive lookahead assertion.
• (?<=pattern): Positive lookbehind assertion.
• re.IGNORECASE / re.MULTILINE / re.VERBOSE: Modifiers for regex engine execution.

Practical Code Example

import re
from typing import Dict, Optional

def parse_log_line(log_line: str) -> Optional[Dict[str, str]]:
    """Extract structured metadata from log string using named capture groups."""
    pattern = re.compile(
        r'\[(?P<timestamp>[^\]]+)\]\s+'
        r'(?P<level>INFO|WARN|ERROR)\s+'
        r'(?P<component>\w+):\s+'
        r'(?P<message>.*)',
        re.VERBOSE
    )

    match = pattern.search(log_line)
    if match:
        return match.groupdict()
    return None

if __name__ == "__main__":
    sample_log = "[2026-08-15 14:20:00] ERROR DatabaseService: Connection timeout after 3000ms"
    parsed = parse_log_line(sample_log)
    print("Parsed Log Metadata:", parsed)

Best Practices & Gotchas

• Use re.VERBOSE for Complex Patterns: re.VERBOSE allows adding whitespace and comments inside multi-line regex patterns for readability.
• Named Groups: Use (?P<name>...) instead of positional groups (1) for self-documenting code.
• match() vs search(): re.match() checks only at the start of the string; re.search() scans the entire string.

Self-Check Challenge

Write a regex with named capture groups (?P<year>\d{4})-(?P<month>\d{2})-(?P<day>\d{2}) to parse ISO dates.