Add win rate and profit-loss ratio to archive stats.

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

docs/hub-symbol-archive-kline.md

@@ -93,7 +93,7 @@
 | `filter_profit` / `filter_loss` / `filter_sick` | 过滤列表与统计 |
 | `search` | 合约 / 交易所 / 备注搜索（同步过滤列表与统计） |
 
-返回 `stats` 含 `open_count`、`win_count`、`loss_count`、`avg_win`、`avg_loss`、`max_win`、`max_loss`、`sick_count`、`sick_pct`、`pnl_total`、`pnl_ex_sick`、`by_exchange`。
+返回 `stats` 含 `open_count`、`win_count`、`loss_count`、`win_rate`、`avg_win`、`avg_loss`、`profit_loss_ratio`、`max_win`、`max_loss`、`sick_count`、`sick_pct`、`pnl_total`、`pnl_ex_sick`、`by_exchange`。
 
 实例侧：
 

hub_symbol_archive_lib.py

@@ -1275,14 +1275,23 @@ def _empty_pnl_bucket() -> dict[str, Any]:
 def _finalize_pnl_bucket(bucket: dict[str, Any]) -> None:
     wins = bucket.pop("_wins", [])
     losses = bucket.pop("_losses", [])
-    bucket["win_count"] = len(wins)
+    open_count = int(bucket.get("open_count") or 0)
+    win_count = len(wins)
+    bucket["win_count"] = win_count
     bucket["loss_count"] = len(losses)
     bucket["avg_win"] = round(sum(wins) / len(wins), 4) if wins else None
-    bucket["avg_loss"] = round(sum(losses) / len(losses), 4) if losses else None
+    avg_loss = round(sum(losses) / len(losses), 4) if losses else None
+    bucket["avg_loss"] = avg_loss
     bucket["max_win"] = round(max(wins), 4) if wins else None
     bucket["max_loss"] = round(min(losses), 4) if losses else None
     bucket["pnl_total"] = round(float(bucket.get("pnl_total") or 0), 4)
     bucket["pnl_ex_sick"] = round(float(bucket.get("pnl_ex_sick") or 0), 4)
+    bucket["win_rate"] = round(win_count / open_count * 100, 1) if open_count else None
+    avg_win = bucket["avg_win"]
+    if avg_win is not None and avg_loss is not None and avg_loss != 0:
+        bucket["profit_loss_ratio"] = round(avg_win / abs(avg_loss), 2)
+    else:
+        bucket["profit_loss_ratio"] = None
 
 
 def _accumulate_trade_stat(bucket: dict[str, Any], *, pnl: float, is_sick: bool) -> None:
@@ -1329,6 +1338,8 @@ def _compute_period_stats(trade_rows: list[dict[str, Any]]) -> dict[str, Any]:
         "avg_loss": total_bucket["avg_loss"],
         "max_win": total_bucket["max_win"],
         "max_loss": total_bucket["max_loss"],
+        "win_rate": total_bucket["win_rate"],
+        "profit_loss_ratio": total_bucket["profit_loss_ratio"],
         "by_exchange": by_ex,
     }
 

manual_trading_hub/hub_ai/archive_quote.py

@@ -42,6 +42,22 @@ def _fmt_pnl(v: Any) -> str:
     return f"{sign}{n:.2f}U"
 
 
+def _fmt_pct(v: Any) -> str:
+    try:
+        n = float(v)
+    except (TypeError, ValueError):
+        return "—"
+    return f"{n:.1f}%"
+
+
+def _fmt_rr(v: Any) -> str:
+    try:
+        n = float(v)
+    except (TypeError, ValueError):
+        return "—"
+    return f"{n:.2f}:1"
+
+
 def format_archive_trades_for_ai(payload: dict[str, Any]) -> str:
     trades = payload.get("trades") or []
     stats = payload.get("stats") or {}
@@ -50,6 +66,7 @@ def format_archive_trades_for_ai(payload: dict[str, Any]) -> str:
             f"统计：开仓 {int(stats.get('open_count') or 0)} 笔，"
             f"盈利 {int(stats.get('win_count') or 0)} / 亏损 {int(stats.get('loss_count') or 0)}，"
             f"平均盈利 {_fmt_pnl(stats.get('avg_win'))}，平均亏损 {_fmt_pnl(stats.get('avg_loss'))}，"
+            f"胜率 {_fmt_pct(stats.get('win_rate'))}，盈亏比 {_fmt_rr(stats.get('profit_loss_ratio'))}，"
             f"最大盈利 {_fmt_pnl(stats.get('max_win'))}，最大亏损 {_fmt_pnl(stats.get('max_loss'))}，"
             f"犯病 {int(stats.get('sick_count') or 0)} 笔，"
             f"盈亏合计 {_fmt_pnl(stats.get('pnl_total'))}，"

manual_trading_hub/static/archive.js

@@ -427,6 +427,19 @@
     return fmtPnlStat(v);
   }
 
+  function fmtWinRate(v, openN, winN) {
+    if (v != null && v !== "") return Number(v).toFixed(1) + "%";
+    if (openN) return (Math.round(((winN || 0) / openN) * 1000) / 10) + "%";
+    return "—";
+  }
+
+  function fmtProfitLossRatio(v) {
+    if (v == null || v === "") return "—";
+    const n = Number(v);
+    if (!Number.isFinite(n)) return "—";
+    return n.toFixed(2) + ":1";
+  }
+
   function renderStatsRow(label, e, isTotal) {
     const openN = e.open_count || 0;
     const sickN = e.sick_count || 0;
@@ -444,10 +457,14 @@
       "</td><td>" +
       (e.loss_count || 0) +
       "</td><td>" +
+      fmtWinRate(e.win_rate, openN, e.win_count) +
+      "</td><td>" +
       fmtPnlStatOptional(e.avg_win) +
       "</td><td>" +
       fmtPnlStatOptional(e.avg_loss) +
       "</td><td>" +
+      fmtProfitLossRatio(e.profit_loss_ratio) +
+      "</td><td>" +
       fmtPnlStatOptional(e.max_win) +
       "</td><td>" +
       fmtPnlStatOptional(e.max_loss) +
@@ -482,6 +499,8 @@
           loss_count: st.loss_count,
           avg_win: st.avg_win,
           avg_loss: st.avg_loss,
+          win_rate: st.win_rate,
+          profit_loss_ratio: st.profit_loss_ratio,
           max_win: st.max_win,
           max_loss: st.max_loss,
         },
@@ -494,7 +513,7 @@
         .join("");
     elStats.innerHTML =
       '<table class="archive-stats-table"><thead><tr>' +
-      "<th>范围</th><th>开仓</th><th>盈利单</th><th>亏损单</th><th>平均盈利</th><th>平均亏损</th><th>最大盈利</th><th>最大亏损</th><th>犯病</th><th>犯病占比</th><th>盈亏</th><th>剔除犯病盈亏</th>" +
+      "<th>范围</th><th>开仓</th><th>盈利单</th><th>亏损单</th><th>胜率</th><th>平均盈利</th><th>平均亏损</th><th>盈亏比</th><th>最大盈利</th><th>最大亏损</th><th>犯病</th><th>犯病占比</th><th>盈亏</th><th>剔除犯病盈亏</th>" +
       "</tr></thead><tbody>" +
       rows +
       "</tbody></table>";

tests/test_hub_symbol_archive_lib.py

@@ -291,10 +291,14 @@ def test_compute_period_stats_win_loss_metrics():
     assert st["avg_loss"] == -4.5
     assert st["max_win"] == 10.0
     assert st["max_loss"] == -6.0
+    assert st["win_rate"] == 50.0
+    assert st["profit_loss_ratio"] == round(7.0 / 4.5, 2)
     assert st["sick_count"] == 1
     assert st["pnl_total"] == 5.0
     assert st["pnl_ex_sick"] == 8.0
     assert st["by_exchange"]["binance"]["win_count"] == 2
+    assert st["by_exchange"]["binance"]["win_rate"] == 100.0
+    assert st["by_exchange"]["binance"]["profit_loss_ratio"] is None
 
 
 def test_list_daily_trades_search_filters_stats():