Metadata-Version: 2.4
Name: fortrand
Version: 1.0.0
Summary: Fortified Mersenne Twister for Python
Author-email: Hansana Prabashwara <prabashwara.h@gmail.com>
License-Expression: MIT
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.11
Description-Content-Type: text/markdown

# 🛡️ FortRand: A Fortified Mersenne Twister for Python
![Version](https://img.shields.io/badge/Version-1.0.0-blue)


**FortRand** is a high-performance, statistically-hardened Random Number Generator (RNG) implemented as a C-extension for Python. It provides the legendary speed of the Mersenne Twister (MT19937) while mitigating its inherent mathematical predictability through periodic entropy injection.

---

## 🚀 The Core Concept: Hybrid Randomness

Standard PRNGs (like Python's built-in `random`) follow a purely deterministic mathematical path once seeded. While excellent for simulations, they can be "solved" if enough output is observed. 

**FortRand** achieves a "Best of Both Worlds" architecture by pairing the high-speed MT19937 algorithm with a security-focused modification where the internal "twist" function is "hardened" to periodically inhale fresh entropy from the OS kernel. This hybrid approach allows the generator to pass the most rigorous statistical batteries while maintaining a throughput significantly higher than raw system entropy.

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## 🔬 Technical Architecture: XOR State Mutation
The core of FortRand's security lies in its periodic state mutation. To break the linearity of the Mersenne Twister, FortRand performs a Full-State XOR with high-quality OS entropy during the twist operation
By XORing the internal 624-word state with raw entropy, the generator effectively "moves the goalposts" for any potential state-reconstruction attack, making previously observed outputs useless for predicting future values.

## 📊 Performance & Validation

FortRand isn't just "conceptually" better; it has been mathematically proven through standardized testing.

### Efficiency (rands/second)
* **Python `random.Random`:** ~2.53e+06 r/s (Fast, but mathematically predictable)
* **Python `random.SystemRandom` :** ~0.54e+05 r/s (Secure, but slow system calls)
* **FortRand:** **~2.88e+06 r/s** (Fastest + Hardened)

### NIST SP 800-22 Certification
FortRand successfully passed the full NIST Statistical Test Suite. Its **Linear Complexity** p-values are significantly more uniform than the standard Mersenne Twister, confirming that the entropy injection successfully breaks linear patterns.

### Dieharder Battery
Achieved a 100% **PASSED** assessment across all tests, including those where the standard library occasionally shows "WEAK" results.

---

## 🛠️ Installation

### Prerequisites
* Python 3.11+

### Install
```bash
pip install fortrand
```

### Basic Usage

```python
import fortrand

# Works just like the standard random module!
x = fortrand.randint(1, 100)
print(x)
```

## ⚖️ Attribution & Credits

FortRand is a derivative work of the [CPython](https://github.com/python/cpython) `Random` module source code. 

* The core **MT19937** algorithm was developed by Takuji Nishimura and Makoto Matsumoto.
* The Python integration logic was originally wrapped by Raymond Hettinger and the PSF.

This project is released under the MIT License, but contains sub-components governed by the PSF License and the original 3-clause BSD Mersenne Twister license.
