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]+)/g
Extract URLs from text
🔢 Number Formatting
/\B(?=(\d{3})+(?!\d))/g
Add 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.