mirror of
https://github.com/xavierchuan/FX-ML-Trading-Engine.git
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xiaochuan
91 lines
3.5 KiB
Python
91 lines
3.5 KiB
Python
#!/usr/bin/env python3
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"""
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Append a metrics row using TCA summary + KPI overrides.
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Example:
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python scripts/update_metrics_from_tca.py \
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--tca QuantTrader/results/execution/tca_summary.json \
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--run-id 20251112_parallel_demo_live \
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--status pass --latency-avg 28 --latency-p95 45 \
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--total-pnl 27.3 --max-exposure 500000 --max-drawdown 0.02 \
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--rolling-sharpe 1.5 --live-drawdown 0.03 \
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--live-latency-p95 45 --slippage-bps 1.2
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"""
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from __future__ import annotations
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import argparse
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import csv
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import json
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from datetime import datetime, timezone
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from pathlib import Path
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="Append metrics row from TCA summary.")
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parser.add_argument("--tca", required=True, help="Path to tca_summary.json")
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parser.add_argument("--metrics", default="results/risk/metrics.csv", help="Metrics CSV path")
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parser.add_argument("--run-id", required=True)
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parser.add_argument("--status", default="pass")
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parser.add_argument("--latency-avg", type=float, required=True)
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parser.add_argument("--latency-p95", type=float, required=True)
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parser.add_argument("--total-pnl", type=float, required=True)
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parser.add_argument("--max-exposure", type=float, required=True)
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parser.add_argument("--max-drawdown", type=float, required=True)
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parser.add_argument("--rolling-sharpe", type=float, required=True)
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parser.add_argument("--live-drawdown", type=float, required=True)
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parser.add_argument("--live-latency-p95", type=float, required=True)
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parser.add_argument("--slippage-bps", type=float, required=True)
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parser.add_argument("--rejects", type=int, default=0)
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parser.add_argument("--kills", type=int, default=0)
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parser.add_argument("--max-gross-notional", type=float, default=0.0)
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return parser.parse_args()
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def main() -> None:
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args = parse_args()
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tca_path = Path(args.tca)
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if not tca_path.exists():
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raise SystemExit(f"TCA summary not found: {tca_path}")
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with tca_path.open("r", encoding="utf-8") as f:
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tca = json.load(f)
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timestamp = datetime.now(timezone.utc).isoformat()
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row = {
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"timestamp": timestamp,
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"run_id": args.run_id,
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"rejects": args.rejects,
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"kills": args.kills,
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"status": args.status,
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"latency_ms_avg": args.latency_avg,
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"latency_ms_p95": args.latency_p95,
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"total_pnl": args.total_pnl,
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"max_gross_notional": args.max_gross_notional or args.max_exposure,
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"max_symbol_exposure": args.max_exposure,
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"max_drawdown_pct": args.max_drawdown,
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"rolling_sharpe_30d": args.rolling_sharpe,
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"live_drawdown_pct": args.live_drawdown,
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"live_latency_ms_p95": args.live_latency_p95,
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"slippage_bps": args.slippage_bps,
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"paper_trade_count": tca.get("paper_trade_count"),
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"paper_total_pnl": tca.get("paper_total_pnl"),
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"live_trade_count": tca.get("live_trade_count"),
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"live_total_pnl": tca.get("live_total_pnl"),
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"pnl_diff_mean": tca.get("pnl_diff_mean"),
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"pnl_diff_std": tca.get("pnl_diff_std"),
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}
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metrics_path = Path(args.metrics)
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metrics_path.parent.mkdir(parents=True, exist_ok=True)
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write_header = not metrics_path.exists()
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with metrics_path.open("a", newline="", encoding="utf-8") as f:
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writer = csv.DictWriter(f, fieldnames=row.keys())
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if write_header:
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writer.writeheader()
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writer.writerow(row)
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print(f"Appended metrics row for run={args.run_id}")
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if __name__ == "__main__":
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main()
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