feat: expand header stats with total funds and profit-loss ratio

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

lib/instance/instance_embed_context_lib.py

@@ -7,6 +7,8 @@ from typing import Any
 
 EMBED_STRATEGY_PAGES = frozenset({"strategy", "strategy_trend", "strategy_roll", "strategy_records"})
 
+_WIN_EPS = 1e-9
+
 
 @dataclass(frozen=True)
 class EmbedRenderPlan:
@@ -50,6 +52,48 @@ def embed_render_plan(page: str, embed_mode: str | None) -> EmbedRenderPlan:
     )
 
 
+def profit_loss_ratio_from_averages(avg_win: float | None, avg_loss: float | None) -> float | None:
+    """盈亏比 = 平均盈利 / |平均亏损|。"""
+    if avg_win is None or avg_loss is None:
+        return None
+    try:
+        aw = float(avg_win)
+        al = float(avg_loss)
+    except (TypeError, ValueError):
+        return None
+    if al == 0:
+        return None
+    return round(aw / abs(al), 2)
+
+
+def profit_loss_ratio_from_trades(trades: list[dict[str, Any]] | None) -> float | None:
+    wins: list[float] = []
+    losses: list[float] = []
+    for row in trades or []:
+        if not isinstance(row, dict):
+            continue
+        try:
+            pnl = float(row.get("effective_pnl_amount") or row.get("pnl_amount") or 0)
+        except (TypeError, ValueError):
+            continue
+        if pnl > _WIN_EPS:
+            wins.append(pnl)
+        elif pnl < -_WIN_EPS:
+            losses.append(pnl)
+    avg_win = sum(wins) / len(wins) if wins else None
+    avg_loss = sum(losses) / len(losses) if losses else None
+    return profit_loss_ratio_from_averages(avg_win, avg_loss)
+
+
+def total_funds_usdt(funding_usdt: float | None, trading_usdt: float | None) -> float | None:
+    if funding_usdt is None:
+        return None
+    try:
+        return round(float(funding_usdt) + float(trading_usdt or 0), 2)
+    except (TypeError, ValueError):
+        return None
+
+
 def trade_records_summary(conn, start_bj: str, end_bj: str, tr_ts: str) -> dict[str, Any]:
     """顶栏统计用 COUNT，避免 embed 壳拉 1000 行交易记录。"""
     from lib.trade.trade_result_lib import sql_effective_pnl_expr
@@ -59,7 +103,9 @@ def trade_records_summary(conn, start_bj: str, end_bj: str, tr_ts: str) -> dict[
         f"""
         SELECT
             COUNT(*) AS total,
-            SUM(CASE WHEN {pnl_sql} > 0 THEN 1 ELSE 0 END) AS wins
+            SUM(CASE WHEN {pnl_sql} > 0 THEN 1 ELSE 0 END) AS wins,
+            AVG(CASE WHEN {pnl_sql} > 0 THEN {pnl_sql} END) AS avg_win,
+            AVG(CASE WHEN {pnl_sql} < 0 THEN {pnl_sql} END) AS avg_loss
         FROM trade_records
         WHERE {tr_ts} >= ? AND {tr_ts} <= ?
           AND COALESCE(result, '') != '错过'
@@ -70,10 +116,13 @@ def trade_records_summary(conn, start_bj: str, end_bj: str, tr_ts: str) -> dict[
     total = int(row["total"] or 0) if row else 0
     wins = int(row["wins"] or 0) if row else 0
     rate = round(wins / total * 100, 2) if total else 0
+    avg_win = float(row["avg_win"]) if row and row["avg_win"] is not None else None
+    avg_loss = float(row["avg_loss"]) if row and row["avg_loss"] is not None else None
     return {
         "records": [],
         "total": total,
         "rate": rate,
+        "profit_loss_ratio": profit_loss_ratio_from_averages(avg_win, avg_loss),
     }