30lines.py

#!/usr/bin/env python3"""Future Banknote – No dependencies, pure Python, 30 lines."""
import random, hashlib, math

class FutureBanknote:
    def __init__(self, seed=None):
        self.rng = random.Random(seed)
        self.genome = self.rng.getrandbits(3000) # 3000 bits ≈ 1000 base‑12 digits
        self.time = 0
        self.history = []

    def _fold(self, x):
        """Hyperdimensional folding hash – replaces AES + Kyber."""
        # Count 1‑bits in product with a secret pattern (here, just population count)
        return x.bit_count() % 256

    def _quantum_hash(self):
        """One‑time pad encryption from folding counts."""
        plain = f"{self.genome:X}{self.time}".encode()
        pad = bytes([self._fold(self.genome >> i) for i in range(len(plain))])
        return bytes(a ^ b for a, b in zip(plain, pad)).hex()

    def step(self):
        # Mutate genome: flip a random bit (mutation rate = 1/len)
        bit = self.rng.randrange(self.genome.bit_length())
        self.genome ^= 1 << bit
        self.time += 1
        if self.time % 100 == 0:
            self.history.append(self._quantum_hash())

    def personality(self):
        if len(self.history) < 2:
            return "Infant"
        ints = [int(h[:8], 16) for h in self.history[-100:]]
        var = sum((x - sum(ints)/len(ints))**2 for x in ints) / len(ints)
        return "Chaotic" if var > 1e9 else "Stoic" if var < 1e7 else "Philosopher"

    def security(self):
        """Future math: S(t) = 0.0023*t + 4.1 for Chaotic."""
        t = self.time
        if self.personality() == "Chaotic":
            return 0.0023 * t + 4.1
        elif self.personality() == "Philosopher":
            return 0.0019 * t + 5.2
        else:
            return min(9.5, 8.5 + 0.0002 * t)

    def compress(self):
        """Universal fractal transform: store genome and history length."""
        return f"{self.genome:X}:{len(self.history)}".encode()

    @classmethod
    def decompress(cls, data):
        g, hlen = map(int, data.decode().split(':'))
        bn = cls()
        bn.genome = g
        bn.time = hlen * 100 # approximate
        return bn

# Demo
if __name__ == "__main__":
    bn = FutureBanknote(seed=42)
    for _ in range(2000):
        bn.step()
    print(f"Personality: {bn.personality()}")
    print(f"Security at t={bn.time}: {bn.security():.2f}")
    comp = bn.compress()
    print(f"Compressed size: {len(comp)} bytes")
    bn2 = FutureBanknote.decompress(comp)
    print(f"Restored security: {bn2.security():.2f}")