#!/usr/bin/env python3
"""Compare snake decisions and latency on deterministic synthetic positions.

For outcome/win-rate tournaments use the local Battlesnake CLI. This harness is
fast enough for CI and detects move disagreements, crashes, and latency changes.
"""

import argparse
import json
import sys
from pathlib import Path
from statistics import mean, median
from time import perf_counter

sys.path.insert(0, str(Path(__file__).resolve().parents[1]))

from scripts.benchmark_snakes_from_db import load_states, percentile
from scripts.snake_arena_scenarios import SCENARIOS, synthetic_states
from server.GameBoard import GameBoard
from snakes import SnakeBuilder

def evaluate(name: str, states: list[tuple[dict, dict]]) -> tuple[list[str], dict]:
  moves: list[str] = []
  durations: list[float] = []
  duel_depths: list[int] = []
  rollout_depths: list[int] = []
  duel_nodes = 0
  rollout_nodes = 0
  cache_hits = 0
  deadline_exits = 0
  scenario_durations: dict[str, list[float]] = {}
  for index, (board_data, metadata) in enumerate(states):
    snake = SnakeBuilder.build(name)
    game_id = f"arena-{name}-{index}-{metadata['game_id']}"
    board = GameBoard(
      game_id=game_id, width=board_data["width"], height=board_data["height"],
      ruleset=metadata["ruleset"], source=metadata["source"],
      map=metadata["map"], snake_class=snake,
    )
    board.read_game_data({
      "game": {
        "id": game_id, "ruleset": metadata["ruleset"],
        "source": metadata["source"], "map": metadata["map"], "timeout": 500,
      },
      "turn": metadata["turn"], "board": board_data, "you": metadata["you"],
    })
    started = perf_counter()
    moves.append(snake.choose_move(board))
    duration = (perf_counter() - started) * 1000.0
    durations.append(duration)
    scenario = metadata.get("scenario", "recorded")
    scenario_durations.setdefault(scenario, []).append(duration)
    history = snake.get_history() if hasattr(snake, "get_history") else []
    if history:
      thinking = history[-1]
      duel_depths.append(int(thinking.get("prism_duel_depth", thinking.get("minimax_depth_reached", 0))))
      rollout_depths.append(int(thinking.get("prism_rollout_depth", 0)))
      duel_nodes += int(thinking.get("prism_duel_nodes", 0))
      rollout_nodes += int(thinking.get("prism_rollout_nodes", 0))
      cache_hits += int(thinking.get("prism_duel_cache_hits", 0))
      cache_hits += int(thinking.get("prism_rollout_cache_hits", 0))
      deadline_exits += int(thinking.get("prism_duel_deadline_exits", 0))
      deadline_exits += int(thinking.get("prism_rollout_deadline_exits", 0))
  return moves, {
    "snake": name, "positions": len(states),
    "mean_ms": mean(durations), "median_ms": median(durations),
    "p95_ms": percentile(durations, 0.95), "max_ms": max(durations),
    "mean_duel_depth": mean(duel_depths) if duel_depths else 0.0,
    "mean_rollout_depth": mean(rollout_depths) if rollout_depths else 0.0,
    "duel_nodes": duel_nodes, "rollout_nodes": rollout_nodes,
    "cache_hits": cache_hits, "deadline_exits": deadline_exits,
    "scenario_mean_ms": {
      scenario: mean(values) for scenario, values in scenario_durations.items()
    },
  }

def main() -> None:
  parser = argparse.ArgumentParser()
  parser.add_argument("--snake", action="append", default=[])
  parser.add_argument("--database")
  parser.add_argument("--positions", type=int, default=100)
  parser.add_argument("--stride", type=int, default=997)
  parser.add_argument("--scenario", action="append", choices=sorted(SCENARIOS))
  parser.add_argument("--json-output")
  args = parser.parse_args()

  states = (
    load_states(args.database, max(1, args.positions), max(1, args.stride))
    if args.database else synthetic_states(max(1, args.positions), args.scenario)
  )
  if not states:
    raise SystemExit("No benchmark positions found")

  names = args.snake or ["ApexBattleSnake", "PrismBattleSnake_GPT_5_6_Sol"]
  move_sets: dict[str, list[str]] = {}
  reports: list[dict] = []
  for name in names:
    moves, report = evaluate(name, states)
    move_sets[name] = moves
    reports.append(report)
    print(
      f"{name}: mean={report['mean_ms']:.3f} ms, "
      f"p95={report['p95_ms']:.3f} ms, max={report['max_ms']:.3f} ms, "
      f"duel-depth={report['mean_duel_depth']:.2f}, "
      f"rollout-depth={report['mean_rollout_depth']:.2f}, "
      f"nodes={report['duel_nodes'] + report['rollout_nodes']}, "
      f"cache-hits={report['cache_hits']}, deadline-exits={report['deadline_exits']}"
    )
  baseline = names[0]
  disagreements = {
    name: sum(a != b for a, b in zip(move_sets[baseline], move_sets[name]))
    for name in names[1:]
  }
  if disagreements:
    print(f"Move disagreements versus {baseline}: {disagreements}")

  scenario_disagreements = {}
  for name in names[1:]:
    counts: dict[str, int] = {}
    for index, (baseline_move, candidate_move) in enumerate(
      zip(move_sets[baseline], move_sets[name])
    ):
      if baseline_move != candidate_move:
        scenario = states[index][1].get("scenario", "recorded")
        counts[scenario] = counts.get(scenario, 0) + 1
    scenario_disagreements[name] = counts
  if any(scenario_disagreements.values()):
    print(f"Disagreements by scenario: {scenario_disagreements}")

  payload = {
    "reports": reports,
    "baseline": baseline,
    "disagreements": disagreements,
    "scenario_disagreements": scenario_disagreements,
  }
  if args.json_output:
    Path(args.json_output).write_text(json.dumps(payload, indent=2) + "\n")

if __name__ == "__main__":
  main()