"""
T=SQL Engine — Temporal-to-Structured Query Language
Maps Vacuum Fluctuation timestamps -> Worm Chain indices.

Authors: Ahmad Ali Parr, Jessica L. Williams (SNAPKITTYWEST)

Evidence boundary
-----------------
"Worm Chain" is a data structure (dictionary).
T=SQL is a human-designed software/hardware wrapper around SHA-256 hashing.
Vacuum fluctuations are used as entropy seeds, NOT as an energy source.
Collisions are mathematically inevitable (Pigeonhole; 64->32 bit).
The P4 settler resolves them via monotone sequence counter.
"""

import hashlib
import struct
from dataclasses import dataclass
from typing import Dict, List, Optional, Tuple


# ── Types ──────────────────────────────────────────────────────────────────

@dataclass
class WormEvent:
    t_coord:      int    # Raw vacuum-derived timestamp (64-bit)
    sql_idx:      int    # T=SQL hashed index (32-bit)
    entropy_seed: bytes  # Normalized 256-bit seed from ANu
    p3q_state:    str    # Quantum circuit state snapshot label
    settlement_id: int   # P4 settlement sequence number (monotone)


# ── T=SQL Engine ───────────────────────────────────────────────────────────

class TSQLEngine:
    """
    T=SQL Engine: maps temporal vacuum fluctuation coordinates to
    structured Worm Chain indices, supporting SQL-like queries.

    Formal properties (see lean/TSQLFormal.lean):
      - Deterministic: same t_coord always yields same sql_idx
      - Collision-inevitable: Pigeonhole, |UInt64| > |UInt32|
      - Ordered: collision resolution via monotone settlement_id
    """

    def __init__(self):
        # The "Worm Chain": non-linear event store keyed by sql_idx
        self.worm_chain: Dict[int, WormEvent] = {}
        self.settlement_seq: int = 0
        self.salt = b"DEADBEEF_VACUUM_SALT"

    # ── Core hash ──────────────────────────────────────────────────────────

    def _compute_t_sql_index(self, t_coord: int) -> int:
        """
        T=SQL Mapping: T -> SQL
        Deterministic SHA-256 hash of the temporal coordinate.
        Returns first 4 bytes as the 32-bit SQL index.
        """
        t_bytes = struct.pack(">Q", t_coord & 0xFFFFFFFFFFFFFFFF)
        digest = hashlib.sha256(t_bytes + self.salt).digest()
        return struct.unpack(">I", digest[:4])[0]

    # ── Write path ─────────────────────────────────────────────────────────

    def ingest_event(
        self,
        t_coord: int,
        seed: bytes,
        state: str,
        settlement: Optional[int] = None,
    ) -> WormEvent:
        """
        Write a vacuum fluctuation event into the Worm Chain.
        settlement_id is automatically assigned if not provided.
        """
        self.settlement_seq += 1
        sid = settlement if settlement is not None else self.settlement_seq
        idx = self._compute_t_sql_index(t_coord)
        event = WormEvent(t_coord, idx, seed, state, sid)
        self.worm_chain[idx] = event
        print(f"[T=SQL] Ingested T={t_coord:#018x} -> SQL_IDX={idx:#010x} SID={sid}")
        return event

    # ── Query: by timestamp ────────────────────────────────────────────────

    def query_by_time(self, t_coord: int) -> Optional[WormEvent]:
        """
        T=SQL SELECT: retrieve state by temporal coordinate.
        SELECT * FROM WormChain WHERE t_coord = t;
        """
        idx = self._compute_t_sql_index(t_coord)
        return self.worm_chain.get(idx)

    # ── Query: by sql_idx range ────────────────────────────────────────────

    def query_manifold(self, lo: int, hi: int) -> List[WormEvent]:
        """
        T=SQL RANGE: retrieve events within an index manifold.
        SELECT * FROM WormChain WHERE sql_idx BETWEEN lo AND hi;
        """
        return [
            e for idx, e in self.worm_chain.items()
            if lo <= idx <= hi
        ]

    # ── Query: all events ordered by settlement ────────────────────────────

    def query_ordered(self) -> List[WormEvent]:
        """
        Return all events sorted by monotone settlement_id.
        Equivallent to: SELECT * FROM WormChain ORDER BY settlement_id;
        """
        return sorted(self.worm_chain.values(), key=lambda e: e.settlement_id)

    # ── Diagnostics ────────────────────────────────────────────────────────

    def stats(self) -> dict:
        return {
            "events": len(self.worm_chain),
            "settlement_seq": self.settlement_seq,
            "collision_probability": 1.0 / (2**32),
        }


# ── Self-test ──────────────────────────────────────────────────────────────

if __name__ == "__main__":
    engine = TSQLEngine()

    # Simulated vacuum events: (timestamp, seed, state, settlement_id)
    events = [
        (1692834001, b"\xaa" * 32, "S_0", 1001),
        (1692834005, b"\xbb" * 32, "S_1", 1002),
        (1692834010, b"\xcc" * 32, "S_2", 1003),
    ]

    for t, seed, state, sid in events:
        engine.ingest_event(t, seed, state, sid)

    print()

    # Query by time
    target = 1692834005
    result = engine.query_by_time(target)
    if result:
        print(f"[T=SQL Query] T={target} -> state={result.p3q_state} idx={result.sql_idx:#010x}")

    # Ordered query
    print("\n[T=SQL Ordered]")
    for e in engine.query_ordered():
        print(f"  SID={e.settlement_id} T={e.t_coord} state={e.p3q_state}")

    # Stats
    print("\n[T=SQL Stats]", engine.stats())