数据统计页：多机 KPI 对比与余额曲线采样。

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

lib/stats_agg_lib.py

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+"""中控统计汇总:KPI 对比 + 余额曲线."""
+from __future__ import annotations
+
+from typing import Any
+
+from lib.bridge_client_lib import pull_all_enabled, pull_all_stats
+from lib.cash_sample_lib import query_cash_series, record_cash_samples_from_overview
+
+
+def _safe_float(v: Any) -> float | None:
+    if v is None or v == "":
+        return None
+    try:
+        return float(v)
+    except (TypeError, ValueError):
+        return None
+
+
+def _safe_int(v: Any) -> int:
+    try:
+        return int(float(v))
+    except (TypeError, ValueError):
+        return 0
+
+
+def normalize_window(raw: Any) -> str:
+    w = str(raw or "7d").strip().lower()
+    if w in ("1d", "day", "今日"):
+        return "today"
+    if w in ("7", "week"):
+        return "7d"
+    if w in ("30", "month"):
+        return "30d"
+    if w in ("0", "全部", "total"):
+        return "all"
+    return w if w in ("today", "7d", "30d", "all") else "7d"
+
+
+def build_stats_summary(window: str = "7d") -> dict[str, Any]:
+    w = normalize_window(window)
+    # 实时状态(余额/权利金/浮盈)来自快照;窗口 KPI 来自各机 stats
+    snaps = pull_all_enabled()
+    try:
+        record_cash_samples_from_overview(snaps)
+    except Exception:
+        pass
+    stats_rows = pull_all_stats(w)
+    stats_by_id = {r.get("id"): r for r in stats_rows}
+
+    machines: list[dict[str, Any]] = []
+    sum_cash = 0.0
+    sum_premium = 0.0
+    sum_unreal = 0.0
+    sum_net = 0.0
+    sum_profit = 0.0
+    sum_loss = 0.0
+    sum_closed = 0
+    sum_wins = 0
+    sum_losses = 0
+    online_n = 0
+    cash_known = False
+    premium_known = False
+    unreal_known = False
+
+    for snap in snaps:
+        iid = snap.get("id")
+        st = stats_by_id.get(iid) or {}
+        stats = st.get("stats") if isinstance(st.get("stats"), dict) else {}
+        body = snap.get("snapshot") if isinstance(snap.get("snapshot"), dict) else {}
+        premium = body.get("premium") if isinstance(body.get("premium"), dict) else {}
+        pnl = body.get("pnl") if isinstance(body.get("pnl"), dict) else {}
+        brief = body.get("positions_brief") if isinstance(body.get("positions_brief"), list) else []
+        cash = _safe_float(premium.get("cash_usdt"))
+        paid = _safe_float(premium.get("paid_usdt"))
+        ratio = _safe_float(premium.get("ratio_pct"))
+        unreal = _safe_float(pnl.get("unrealized_usdt"))
+        net = _safe_float(stats.get("net_realized_pnl"))
+        profit = _safe_float(stats.get("total_profit"))
+        loss = _safe_float(stats.get("total_loss"))
+        closed = _safe_int(stats.get("total_closed"))
+        wins = _safe_int(stats.get("win_count"))
+        losses = _safe_int(stats.get("loss_count"))
+        win_rate = _safe_float(stats.get("win_rate"))
+        avg_hold = _safe_float(stats.get("avg_hold_sec"))
+        online = bool(snap.get("online"))
+        if online:
+            online_n += 1
+        if cash is not None:
+            sum_cash += cash
+            cash_known = True
+        if paid is not None:
+            sum_premium += paid
+            premium_known = True
+        if unreal is not None:
+            sum_unreal += unreal
+            unreal_known = True
+        if online and stats.get("ok"):
+            if net is not None:
+                sum_net += net
+            if profit is not None:
+                sum_profit += profit
+            if loss is not None:
+                sum_loss += loss
+            sum_closed += closed
+            sum_wins += wins
+            sum_losses += losses
+        machines.append(
+            {
+                "id": iid,
+                "name": snap.get("name"),
+                "online": online,
+                "error": snap.get("error") or st.get("error") or "",
+                "mode": ((body.get("instance") or {}) if isinstance(body.get("instance"), dict) else {}).get(
+                    "mode"
+                ),
+                "cash_usdt": cash,
+                "premium_usdt": paid,
+                "ratio_pct": ratio,
+                "unrealized_usdt": unreal,
+                "pos_count": len(brief),
+                "total_closed": closed if online and stats.get("ok") else None,
+                "win_count": wins if online and stats.get("ok") else None,
+                "loss_count": losses if online and stats.get("ok") else None,
+                "win_rate": win_rate if online and stats.get("ok") else None,
+                "net_realized_pnl": net if online and stats.get("ok") else None,
+                "total_profit": profit if online and stats.get("ok") else None,
+                "total_loss": loss if online and stats.get("ok") else None,
+                "avg_hold_sec": avg_hold if online and stats.get("ok") else None,
+                "stats_ok": bool(online and stats.get("ok")),
+            }
+        )
+
+    agg_win_rate = round(sum_wins / sum_closed * 100, 2) if sum_closed else 0.0
+    return {
+        "ok": True,
+        "window": w,
+        "totals": {
+            "online": online_n,
+            "machines": len(machines),
+            "cash_usdt": round(sum_cash, 4) if cash_known else None,
+            "premium_usdt": round(sum_premium, 4) if premium_known else None,
+            "unrealized_usdt": round(sum_unreal, 4) if unreal_known else None,
+            "net_realized_pnl": round(sum_net, 4),
+            "total_profit": round(sum_profit, 4),
+            "total_loss": round(sum_loss, 4),
+            "total_closed": sum_closed,
+            "win_count": sum_wins,
+            "loss_count": sum_losses,
+            "win_rate": agg_win_rate,
+        },
+        "machines": machines,
+    }
+
+
+def build_stats_curve(range_key: str = "7d") -> dict[str, Any]:
+    # 顺手采一笔,让打开页面时也有点
+    try:
+        snaps = pull_all_enabled()
+        record_cash_samples_from_overview(snaps)
+    except Exception:
+        pass
+    data = query_cash_series(range_key=range_key)
+    data["ok"] = True
+    return data