Add options stats holding time metrics and lightweight charts.

Show average hold duration for wins and losses, open positions, and CSS ring/bar visualizations in the stats tab.

Co-authored-by: Cursor <cursoragent@cursor.com>

lib/options/options_hub_lib.py

@@ -4,41 +4,11 @@ from __future__ import annotations
 
 from typing import Any
 
-from lib.instance.instance_embed_context_lib import profit_loss_ratio_from_averages
-from lib.options.options_db import init_options_tables
+from lib.options.options_stats_lib import compute_options_stats
 
 
 def _compute_options_stats(get_db) -> dict[str, Any]:
-    conn = get_db()
-    try:
-        init_options_tables(conn)
-        rows = conn.execute(
-            """
-            SELECT realized_pnl FROM options_trades
-            WHERE status = 'closed' AND realized_pnl IS NOT NULL
-            """
-        ).fetchall()
-    finally:
-        conn.close()
-    wins: list[float] = []
-    losses: list[float] = []
-    for row in rows:
-        pnl = float(row["realized_pnl"])
-        if pnl > 0:
-            wins.append(pnl)
-        elif pnl < 0:
-            losses.append(pnl)
-    total_closed = len(wins) + len(losses)
-    win_rate = round(len(wins) / total_closed * 100, 2) if total_closed else 0
-    avg_win = sum(wins) / len(wins) if wins else None
-    avg_loss = sum(losses) / len(losses) if losses else None
-    return {
-        "total_closed": total_closed,
-        "win_rate": win_rate,
-        "profit_loss_ratio": profit_loss_ratio_from_averages(avg_win, avg_loss),
-        "total_profit": round(sum(wins), 4) if wins else 0.0,
-        "total_loss": round(abs(sum(losses)), 4) if losses else 0.0,
-    }
+    return compute_options_stats(get_db)
 
 
 def build_options_hub_snapshot(cfg: dict[str, Any]) -> dict[str, Any]: