Compute option stats from exchange history instead of local DB.

Share history loading between history and stats APIs so average profit/loss matches the option history tab.

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

lib/options/options_stats_lib.py

@@ -33,6 +33,66 @@ def _avg_seconds(values: list[float]) -> float | None:
     return round(sum(values) / len(values), 1)
 
 
+def compute_options_stats_from_history(history: list[dict[str, Any]]) -> dict[str, Any]:
+    """基于期权历史列表(交易所)计算统计."""
+    wins: list[float] = []
+    losses: list[float] = []
+    win_holds: list[float] = []
+    loss_holds: list[float] = []
+    all_holds: list[float] = []
+    open_holds: list[float] = []
+    now = datetime.now()
+
+    for row in history:
+        if row.get("status") == "open":
+            start = _parse_ts(row.get("created_at"))
+            if start is not None:
+                sec = (now - start).total_seconds()
+                if sec >= 0:
+                    open_holds.append(sec)
+            continue
+        pnl_raw = row.get("realized_pnl")
+        if pnl_raw is None:
+            continue
+        try:
+            pnl = float(pnl_raw)
+        except (TypeError, ValueError):
+            continue
+        hold = _hold_seconds(row.get("created_at"), row.get("closed_at"))
+        if hold is not None:
+            all_holds.append(hold)
+        if pnl > 0:
+            wins.append(pnl)
+            if hold is not None:
+                win_holds.append(hold)
+        elif pnl < 0:
+            losses.append(pnl)
+            if hold is not None:
+                loss_holds.append(hold)
+
+    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_count": len(wins),
+        "loss_count": len(losses),
+        "win_rate": win_rate,
+        "profit_loss_ratio": profit_loss_ratio_from_averages(avg_win, avg_loss),
+        "avg_win": round(avg_win, 4) if avg_win is not None else None,
+        "avg_loss": round(abs(avg_loss), 4) if avg_loss is not None else None,
+        "total_profit": round(sum(wins), 4) if wins else 0.0,
+        "total_loss": round(abs(sum(losses)), 4) if losses else 0.0,
+        "avg_hold_sec": _avg_seconds(all_holds),
+        "avg_win_hold_sec": _avg_seconds(win_holds),
+        "avg_loss_hold_sec": _avg_seconds(loss_holds),
+        "open_count": len(open_holds),
+        "avg_open_hold_sec": _avg_seconds(open_holds),
+    }
+
+
 def compute_options_stats(get_db) -> dict[str, Any]:
     conn = get_db()
     try: