fastregex 0.1.0

High-performance regex with JIT/SIMD optimizations

FastRegex

A high-performance regular expression library for Python with JIT compilation and SIMD optimizations.

🚀 Features

• JIT Compilation: LLVM-based just-in-time compilation for complex patterns
• SIMD Optimizations: AVX2/AVX512/SSE4.2/NEON support for vectorized operations
• Smart Caching: Automatic caching of compiled patterns to avoid recompilation
• Python Integration: Seamless integration via pybind11
• High Performance: Up to 1000x faster than standard re module for complex patterns

📊 Performance Benchmarks

Test Case	Python re (ms)	FastRegex (ms)	Speedup
Email validation	2.250 ±0.157	0.021 ±0.002	107x ✅
Word boundaries	0.166 ±0.011	0.025 ±0.002	6.6x ✅
Complex pattern	19.665 ±4.100	0.017 ±0.003	1156x ✅
Multiline text	0.855 ±0.163	0.219 ±0.002	3.9x ✅

Key insights:

• Up to 1156x faster for complex patterns
• 3-100x acceleration for typical scenarios
• Best performance on repetitive operations

🛠 Installation

From PyPI (Recommended)

pip install fastregex

From Source

git clone https://github.com/baksvell/fastregex.git
cd fastregex
pip install -e .

Prerequisites

• CMake 3.20+
• Python 3.10+
• C++17 compiler (GCC/MSVC/Clang)

📖 Usage

Basic Usage

import fastregex

# Simple search
result = fastregex.search(r'\d+', 'abc123def')
print(result)  # True

# Find all matches
matches = fastregex.find_all(r'\w+', 'hello world test')
print(matches)  # ['hello', 'world', 'test']

# Replace
new_text = fastregex.replace(r'\d+', 'abc123def456', 'XXX')
print(new_text)  # 'abcXXXdefXXX'

# Compile for reuse
compiled = fastregex.compile(r'\d+')
result = compiled.search('abc123def')
print(result)  # True

Advanced Features

# Check cache statistics
print(f"Cache size: {fastregex.cache_size()}")
print(f"Hit rate: {fastregex.hit_rate():.2%}")

# SIMD capabilities
caps = fastregex.simd_capabilities()
print(f"AVX2 support: {caps['avx2']}")
print(f"AVX512 support: {caps['avx512']}")

# SIMD statistics
stats = fastregex.get_simd_stats()
print(f"Total calls: {stats['total_calls']}")

🎯 When to Use FastRegex

✅ Use FastRegex when:

• Complex patterns (JIT compilation shines)
• Repetitive matching (cache pays off)
• SIMD-friendly patterns (literals, digit checks)
• Large texts (>1MB optimized chunks)

⚠️ Use standard re when:

• Simple one-time matches (no JIT overhead)
• Need 100% compatibility with Python's regex
• Dynamic patterns (generated on-the-fly)

🔄 Hybrid approach:

import re
import fastregex as fr

def smart_match(pattern, text):
    if len(pattern) > 15 and len(text) > 1000:
        return fr.search(pattern, text)
    return re.search(pattern, text)

🧪 Testing

Run the test suite:

python -m pytest tests/

Run performance benchmarks:

python tests/benchmark.py

📚 API Reference

Core Functions

• fastregex.match(pattern, text) - Match from start of string
• fastregex.search(pattern, text) - Search anywhere in string
• fastregex.find_all(pattern, text) - Find all matches
• fastregex.replace(pattern, text, replacement) - Replace matches
• fastregex.compile(pattern) - Compile pattern for reuse

Cache Management

• fastregex.cache_size() - Get current cache size
• fastregex.hit_rate() - Get cache hit rate
• fastregex.clear_cache() - Clear the cache

SIMD Features

• fastregex.simd_capabilities() - Get SIMD support info
• fastregex.get_simd_stats() - Get SIMD usage statistics
• fastregex.set_simd_mode(mode) - Set SIMD mode
• fastregex.get_simd_mode() - Get current SIMD mode

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for details.

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🔗 Links

• GitHub Repository
• Documentation
• Issue Tracker

🙏 Acknowledgments

• pybind11 for Python bindings
• LLVM for JIT compilation
• SIMD for vectorized operations