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GitHub - ProgrammerKR/HashX: HashX is a high-performance 512-bit hashing algorithm optimized for speed, security, and scalability. It features multi-threading, advanced mixing, and HMAC-style security, ensuring strong collision resistance and a powerful avalanche effect. Ideal for checksums, indexing, data integrity, and non-cryptographic applications.

The simplest & fastest open-source hashing library!

HashX is an ultra-fast, efficient, and secure 256-bit hashing algorithm designed for data integrity verification, indexing, checksums, and non-cryptographic applications.

Built with multi-threading, optimized bitwise operations, and an advanced mixing function, HashX delivers exceptional speed, collision resistance, and scalability.

🚀 Features & Enhancements

✅ High-Speed Processing – Optimized bitwise operations and low-level transformations.
✅ Multi-Threaded Execution – Parallel chunk processing for increased speed.
✅ 512-bit Strong Hash Output – Reduces collisions while maintaining efficiency.
✅ Advanced Mixing Function – Inspired by MurmurHash3 for better diffusion.
✅ Bitwise Rotation Optimization – Faster and more secure state transformations.
✅ Lightweight & Scalable – Low memory usage, works on large data sets.
✅ Strong Avalanche Effect – Small input changes drastically modify the hash.
✅ Cross-Platform & Extensible – Works seamlessly in Python, with future support planned for C/Rust.

📥 Installation

Clone the repository:

git clone https://github.com/ProgrammerKR/HashX.git

Navigate to the directory:

🛠️ Usage

Python Example

from hashx import HashX

hasher = HashX()
print(hasher.hash("Hello, World!"))  # Example usage

Output

3F2A9D7B89C4E6A5D12F1E4B67A3C9D5E8F7B2A6C3D1E0F4B6A2D9C7E3F5A5B1

⚙️ How It Works

  1. Initialization – Hash state consists of 4 unique parts, seeded for strong uniqueness.
  2. Chunk Processing – Data is split into 64-bit blocks, processed in parallel threads.
  3. Bitwise Mixing & Rotation – Advanced scrambling ensures strong randomness.
  4. Finalization Rounds – Enhanced diffusion eliminates weak patterns.
  5. Output Generation – 512-bit hexadecimal hash is returned.

🔬 Benchmarking

HashX has been tested against SHA-256, BLAKE3, xxHash, and MurmurHash3 for speed and efficiency.

Benchmark Results

For detailed benchmark results, check the full report:
📊 Benchmark Results

🛠️ Future Plans

  • C and Rust Implementation for ultra-fast performance.
  • GPU Acceleration using CUDA/OpenCL.
  • Cryptographic Security Mode for password hashing.

📢 Have questions or feedback?

  • 💬 Join discussions here
  • 🐛 Found a bug? Report here

🤝 Contributing

Contributions are welcome! Feel free to fork the repo, submit issues, or create pull requests.

🛠️ How to Contribute?

  1. Fork the Repository (Click the "Fork" button at the top of the repo).
  2. Clone your Fork 
    git clone https://github.com/your-username/HashX.git
  3. Create a New Branch 
    git checkout -b improve-docs
  4. Make Changes (Edit README.md and add documentation updates).
  5. Commit & Push 
    git add README.md
git commit -m "Improved documentation & usage examples"
git push origin improve-docs
  6. Create a Pull Request (Go to the original repo and submit a PR).

📜 License

This project is open-source and available under the MIT License.