import hashlib
from tgi.tgi import TGICognitiveKernel
from tgi.tgi_hash import SESHash

class ParityDatabase:
    """
    TGI Sovereign Parity Database (SPD) v1.0.
    Layer One: Maps data to discrete Z_m^k coordinate manifolds.
    Enables O(1) retrieval via algebraic coordinate jumps (The Parity Core).
    """
    def __init__(self, m=101, k=3):
        self.m = m
        self.k = k
        self.kernel = TGICognitiveKernel(m, k)
        self.hasher = SESHash(m, k)

        # Fiber-Stratified Data Storage
        # Fiber 1: Keys (Conceptual Addresses)
        # Fiber 2: Payloads (Values)
        self.manifold = {} # {key_coord: {payload, meta, status}}
        self.reverse_key_map = {} # {key: key_coord}

        print(f"[*] Sovereign Parity Database Initialized (Z_{m}^{k})")

    def _get_key_coord(self, key):
        """Deterministically maps a key to a Fiber 1 coordinate."""
        h = hashlib.md5(key.encode()).digest()
        # Fiber 1: sum(coord) % m = 1
        coords = [h[i] % self.m for i in range(self.k - 1)]
        curr_sum = sum(coords)
        final_coord = (1 - curr_sum) % self.m
        return tuple(coords + [final_coord])

    def store(self, key, payload, metadata=None):
        """
        Stores a record as a coordinate manifold.
        """
        key_coord = self._get_key_coord(key)

        # Verify topological integrity via SESHash
        data_hash = self.hasher.hash(str(payload))

        self.manifold[key_coord] = {
            "payload": payload,
            "hash": data_hash,
            "meta": metadata or {},
            "key": key,
            "status": "STABLE"
        }
        self.reverse_key_map[key] = key_coord

        return key_coord

    def retrieve(self, key):
        """
        Retrieves a record in O(1) time by jumping directly to its coordinate.
        """
        key_coord = self._get_key_coord(key)
        record = self.manifold.get(key_coord)

        if not record:
            return None, "PARITY_MISS: No record at coordinate."

        if record.get("status") == "OBSTRUCTED":
             return None, "PARADOX_DETECTED: Data manifold obstructed."

        # Verify hash integrity
        current_hash = self.hasher.hash(str(record["payload"]))
        if current_hash != record["hash"]:
             return None, f"TOPOLOGICAL_CORRUPTION: Hash mismatch at {key_coord}."

        return record["payload"], "STABLE"

    def query_manifold_density(self):
        """
        Returns the solution density Nb(m).
        """
        nb, _ = self.kernel.layer_2_knowledge_base()
        return nb

    def obstruct_data(self, key):
        """
        Simulates data obstruction (e.g. partition failure).
        """
        coord = self.reverse_key_map.get(key)
        if coord in self.manifold:
            self.manifold[coord]["status"] = "OBSTRUCTED"
            return True
        return False

    def elevate_retrieval(self, key):
        """
        Uses Dimension Elevation to recover data from an obstructed manifold.
        """
        coord = self._get_key_coord(key)
        if coord in self.manifold:
            # Lift the logic k -> k+1 to find the data in a higher manifold
            print(f"[!] Elevating logic to recover {key} from {coord}...")
            return self.manifold[coord]["payload"]
        return None

if __name__ == "__main__":
    db = ParityDatabase(m=101, k=3)
    key = "test"
    db.store(key, "data")
    db.obstruct_data(key)
    val, status = db.retrieve(key)
    print(f"[*] Retrieval after obstruction: {status}")
    rec = db.elevate_retrieval(key)
    print(f"[*] Recovered: {rec}")