Mastering Regular Expressions: Complete Guide
Why Learn Regex?
- ⏱️ 10x faster text processing
- 🔍 90% of text operations covered
- 💻 Supported in all major languages
Regex in Numbers
Used in 78% of production codebases
Performance Optimization
| Technique | Speed Gain | Example | 
|---|---|---|
| Atomic Groups | 40% faster | (?>pattern) | 
| Possessive Quantifiers | 30% faster | a++ | 
| Anchored Patterns | 2x faster | ^start.*end$ | 
Security Best Practices
🛡️ ReDoS Prevention
- Avoid nested quantifiers
- Set timeout limits
🔐 Input Validation
- Sanitize user patterns
- Use allow lists
📚 Safe Patterns
- Precompile static regex
- Limit backtracking
Common Use Cases
📧 Data Validation
/^[^\s@]+@[^\s@]+\.[^\s@]+$/Email validation pattern
🌐 URL Parsing
/(https?:\/\/[^\s]+)/gExtract URLs from text
🔢 Number Formatting
/\B(?=(\d{3})+(?!\d))/gAdd thousand separators
Regex Learning Path
                            Pro Tip: Start with simple patterns and use online testers!
                        
                        - Basic syntax (^ $ . * + ?)
- Character classes ([a-z], \d, \w)
- Grouping and capturing
- Lookaheads/lookbehinds
- Performance optimization
FAQ: Regular Expressions
.* is greedy (matches as much as possible), while .*? is lazy (matches as little as possible). Use lazy quantifiers to prevent over-matching.
                                    