from pathlib import Path

# Define the path for the next file
rth_path = Path("src/rth.py")

# Define the content of the Recursive Tesseract Hashing module
rth_code = """
\"\"\"
Recursive Tesseract Hashing (RTH)
Hyperdimensional SHAKE256-based hash function operating on nested tensor blocks.
\"\"\"

import hashlib
import numpy as np

def recursive_tesseract_hash(data: bytes, depth: int = 4) -> bytes:
    \"\"\"
    Applies SHAKE256 recursively to simulate hyperdimensional compression layers.

    Args:
        data (bytes): Input binary data
        depth (int): Number of recursive SHAKE256 rounds (each representing a tesseract fold)

    Returns:
        bytes: Final hash output
    \"\"\"
    h = data
    for i in range(depth):
        shake = hashlib.shake_256()
        shake.update(h)
        h = shake.digest(64)
    return h

def hyperdimensional_entropy_tensor(seed: bytes, dimensions=(4, 4, 4, 4)) -> np.ndarray:
    \"\"\"
    Generates a hyperdimensional tensor lattice from seed hash.

    Args:
        seed (bytes): Initial seed hash.
        dimensions (tuple): Shape of the tesseract lattice.

    Returns:
        np.ndarray: Populated hyperdimensional tensor.
    \"\"\"
    tensor = np.frombuffer(seed * 16, dtype=np.uint8)[:np.prod(dimensions)]
    return tensor.reshape(dimensions)

if __name__ == "__main__":
    demo = b"tetra-rth-seed"
    final = recursive_tesseract_hash(demo)
    tensor = hyperdimensional_entropy_tensor(final)
    print("[+] Recursive hash digest:", final.hex()[:32], "...")
    print("[+] Tesseract tensor shape:", tensor.shape)
"""

# Write the file
rth_path.parent.mkdir(parents=True, exist_ok=True)
rth_path.write_text(rth_code)

rth_path.name
