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snake-python/scripts/move_trace_stats.py
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daniel156161 5e121c20cf
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feat: add gameplay stats and restore Zenith rollout depth
- Add read-only gameplay statistics with filters and opponent comparisons.
- Report move-trace latency percentiles and external timeout counts.
- Pair engine latency with the preceding turn to separate timing stages.
- Adjust Zenith rollout deepening for its larger timeout reserve.
- Bump Zenith to 1.2.0 and document the fix and snake-stats command.
- Cover statistics, trace aggregation, rollout depth, and verdict budgets.
2026-11-05 08:07:15 +01:00

111 lines
4.4 KiB
Python

"""Aggregate stored move traces into per-snake latency statistics.
Each move stores ``my_thinking.move_trace`` with server-side stage timings. The
engine-measured latency for turn ``T`` arrives with the board of turn ``T + 1``,
so both are paired here to split total latency into strategy, server overhead
and network/outside-handler time.
"""
from collections import defaultdict
from dataclasses import dataclass, field
from server.database.compact.replay_blob import unpack_replay
from server.database.compact.thinking import MASK_KEY
STAGES = ("strategy_ms", "overhead_ms", "handler_ms", "network_ms", "engine_ms")
@dataclass
class TraceGroup:
moves: int = 0
timeouts: int = 0
timeouts_fast_handler: int = 0
values: dict[str, list[float]] = field(default_factory=lambda: defaultdict(list))
def _thinking_dict(thinking: object) -> dict:
if not isinstance(thinking, dict):
return {}
if thinking.get(MASK_KEY) == 0 and isinstance(thinking.get("_raw"), dict):
return thinking["_raw"]
return thinking
def _number(value: object) -> float | None:
return float(value) if isinstance(value, (int, float)) and not isinstance(value, bool) else None
def _latency(value: object) -> float | None:
# Compact storage keeps latency as a small int; "" (no response) is negative.
number = _number(value)
return number if number is not None and number >= 0 else None
def add_game(groups: dict[tuple, TraceGroup], game: dict, you_id: str, turns: list, states: list) -> None:
"""Add every traced move of one game to ``groups`` keyed by snake/version/mode."""
latency_by_turn = {s.turn: _latency(s.latency) for s in states if s.snake_id == you_id}
for record in turns:
thinking = _thinking_dict(record.thinking)
trace = thinking.get("move_trace")
if not isinstance(trace, dict):
continue
handler = _number(trace.get("handler_ms"))
strategy = _number(trace.get("strategy_ms"))
if handler is None:
continue
key = (game["your_snake_type"], game["your_snake_version"], thinking.get("mode") or "fallback")
group = groups.setdefault(key, TraceGroup())
group.moves += 1
group.values["handler_ms"].append(handler)
if strategy is not None:
group.values["strategy_ms"].append(strategy)
group.values["overhead_ms"].append(max(0.0, handler - strategy))
engine = latency_by_turn.get(record.turn + 1)
if engine is None:
continue
group.values["engine_ms"].append(engine)
group.values["network_ms"].append(max(0.0, engine - handler))
timeout_ms = (_number(trace.get("budget_ms")) or 450.0) + 50.0
if engine >= timeout_ms:
group.timeouts += 1
if handler < timeout_ms - 100:
group.timeouts_fast_handler += 1
def percentile(values: list[float], quantile: float) -> float | None:
if not values:
return None
ordered = sorted(values)
return ordered[min(len(ordered) - 1, int(len(ordered) * quantile))]
def _fmt(value: float | None) -> str:
return "-" if value is None else f"{value:.0f}"
def summary_rows(groups: dict[tuple, TraceGroup]) -> tuple[list[str], list[list]]:
headers = ["snake", "version", "mode", "moves", "timeouts", "ext.timeouts"]
for stage in STAGES:
headers.append(f"{stage.removesuffix('_ms')} p50/p90/p99")
rows = []
for (snake, version, mode), group in sorted(groups.items(), key=lambda item: tuple(str(v) for v in item[0])):
row = [
snake, version, mode, group.moves,
f"{group.timeouts} ({100.0 * group.timeouts / group.moves:.1f}%)" if group.moves else "0",
group.timeouts_fast_handler,
]
for stage in STAGES:
values = group.values.get(stage, [])
row.append("/".join(_fmt(percentile(values, q)) for q in (0.5, 0.9, 0.99)))
rows.append(row)
return headers, rows
async def load_groups(connection, where: str, args: list, max_games: int) -> tuple[dict[tuple, TraceGroup], int]:
"""Read the newest finished replays matching ``where``; never writes."""
args = [*args, max(1, max_games)]
rows = await connection.fetch(f"""
SELECT g.game_id, g.your_snake_id, g.your_snake_type, g.your_snake_version,
r.format, r.data
FROM games AS g
JOIN game_replays AS r ON r.gid = g.gid
{where}
ORDER BY g.started_at DESC
LIMIT ${len(args)}
""", *args)
groups: dict[tuple, TraceGroup] = {}
for row in rows:
turns, states = unpack_replay(row["data"], row["format"])
add_game(groups, dict(row), row["your_snake_id"], turns, states)
return groups, len(rows)