feat数据统计曲线改为各机累计已实现盈亏叠加，不再用余额采样。

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

lib/bridge_client_lib.py

@@ -325,6 +325,77 @@ def pull_all_stats(window: str = "7d") -> list[dict[str, Any]]:
     return results
 
 
+def fetch_one_pnl_curve(inst: dict[str, Any], *, range_key: str = "7d") -> dict[str, Any]:
+    """拉取单机累计已实现盈亏曲线."""
+    base = (inst.get("base_url") or "").rstrip("/")
+    token = (inst.get("bridge_token") or "").strip()
+    out: dict[str, Any] = {
+        "id": inst.get("id"),
+        "name": inst.get("name"),
+        "online": False,
+        "error": "",
+        "points": [],
+        "trade_count": 0,
+        "latest": None,
+        "metric": "realized_pnl",
+    }
+    if not base or not token:
+        out["error"] = "缺少 URL 或 Token"
+        return out
+    url = f"{base}/api/hub/options/pnl_curve"
+    try:
+        r = requests.get(
+            url,
+            headers={"X-Hub-Token": token, "Accept": "application/json"},
+            params={"range": range_key},
+            timeout=max(_timeout(), 15.0),
+        )
+        data = {}
+        try:
+            data = r.json()
+        except Exception:
+            data = {}
+        if r.status_code != 200 or not isinstance(data, dict) or not data.get("ok"):
+            out["error"] = (data.get("msg") if isinstance(data, dict) else None) or f"HTTP {r.status_code}"
+            return out
+        out["online"] = True
+        pts = data.get("points") if isinstance(data.get("points"), list) else []
+        out["points"] = pts
+        out["trade_count"] = int(data.get("trade_count") or 0)
+        out["latest"] = data.get("latest")
+        out["metric"] = data.get("metric") or "realized_pnl"
+        out["start_ms"] = data.get("start_ms")
+        out["end_ms"] = data.get("end_ms")
+        return out
+    except requests.Timeout:
+        out["error"] = "超时"
+        return out
+    except Exception as e:
+        out["error"] = str(e) or "拉取失败"
+        return out
+
+
+def pull_all_pnl_curves(range_key: str = "7d") -> list[dict[str, Any]]:
+    instances = list_instances(enabled_only=True)
+    if not instances:
+        return []
+    results: list[dict[str, Any]] = []
+    with ThreadPoolExecutor(max_workers=min(8, len(instances))) as pool:
+        futs = {
+            pool.submit(fetch_one_pnl_curve, inst, range_key=range_key): inst["id"]
+            for inst in instances
+        }
+        by_id: dict[Any, dict[str, Any]] = {}
+        for fut in as_completed(futs):
+            row = fut.result()
+            by_id[row.get("id")] = row
+        for inst in instances:
+            results.append(
+                by_id.get(inst["id"]) or fetch_one_pnl_curve(inst, range_key=range_key)
+            )
+    return results
+
+
 def fetch_client_version(inst: dict[str, Any]) -> dict[str, Any]:
     """探测客户端 git 版本 / 在线."""
     base = (inst.get("base_url") or "").rstrip("/")

lib/stats_agg_lib.py

@@ -1,12 +1,12 @@
-"""中控统计汇总:KPI 对比 + 余额曲线."""
+"""中控统计汇总:KPI 对比 + 已实现盈亏曲线."""
 from __future__ import annotations
 
+import time
 from typing import Any
 
-from lib.bridge_client_lib import pull_all_enabled, pull_all_stats
+from lib.bridge_client_lib import pull_all_enabled, pull_all_pnl_curves, pull_all_stats
 from lib.cash_sample_lib import (
     first_cash_by_instance,
-    query_cash_series,
     record_cash_samples_from_overview,
 )
 
@@ -185,7 +185,84 @@ def build_stats_summary(
 
 
 def build_stats_curve(range_key: str = "7d") -> dict[str, Any]:
-    # 曲线只读本地采样库;余额采样由总览常驻 pull 负责
+    """多机累计已实现盈亏曲线(各机台阶叠加;划转/提现不影响)."""
-    data = query_cash_series(range_key=range_key)
+    rk = normalize_window(range_key)
-    data["ok"] = True
+    now_ms = int(time.time() * 1000)
-    return data
+    rows = pull_all_pnl_curves(rk)
+    series: list[dict[str, Any]] = []
+    by_id: dict[Any, list[dict[str, float]]] = {}
+    start_ms = None
+    end_ms = now_ms
+    for row in rows:
+        iid = row.get("id")
+        pts_raw = row.get("points") if isinstance(row.get("points"), list) else []
+        pts: list[dict[str, float]] = []
+        for p in pts_raw:
+            if not isinstance(p, dict):
+                continue
+            try:
+                t = int(p.get("t"))
+                v = float(p.get("v"))
+            except (TypeError, ValueError):
+                continue
+            pts.append({"t": t, "v": v})
+        pts.sort(key=lambda x: x["t"])
+        if row.get("start_ms") is not None:
+            try:
+                sm = int(row.get("start_ms"))
+                start_ms = sm if start_ms is None else min(start_ms, sm)
+            except (TypeError, ValueError):
+                pass
+        if row.get("end_ms") is not None:
+            try:
+                end_ms = max(end_ms, int(row.get("end_ms")))
+            except (TypeError, ValueError):
+                pass
+        by_id[iid] = pts
+        series.append(
+            {
+                "id": iid,
+                "name": row.get("name") or str(iid),
+                "online": bool(row.get("online")),
+                "error": row.get("error") or "",
+                "points": pts,
+                "trade_count": int(row.get("trade_count") or 0),
+                "latest": row.get("latest"),
+            }
+        )
+
+    # 合计:按 1 分钟桶,各机该桶最后值求和并前向填充
+    last_in_bucket: dict[int, dict[Any, float]] = {}
+    for iid, pts in by_id.items():
+        for p in pts:
+            bt = (int(p["t"]) // 60000) * 60000
+            last_in_bucket.setdefault(bt, {})[iid] = float(p["v"])
+    running: dict[Any, float] = {}
+    total_pts: list[dict[str, float]] = []
+    for bt in sorted(last_in_bucket.keys()):
+        running.update(last_in_bucket[bt])
+        if running:
+            total_pts.append({"t": bt, "v": round(sum(running.values()), 4)})
+
+    if start_ms is None:
+        if rk in ("today", "1d"):
+            import datetime as dt
+
+            start = dt.datetime.now().replace(hour=0, minute=0, second=0, microsecond=0)
+            start_ms = int(start.timestamp() * 1000)
+        elif rk in ("30d", "30"):
+            start_ms = now_ms - 30 * 86400 * 1000
+        elif rk in ("all", "0"):
+            start_ms = 0
+        else:
+            start_ms = now_ms - 7 * 86400 * 1000
+
+    return {
+        "ok": True,
+        "metric": "realized_pnl",
+        "series": series,
+        "total": total_pts,
+        "range": rk,
+        "start_ms": start_ms,
+        "end_ms": end_ms,
+    }

templates/stats.html

@@ -5,7 +5,7 @@
   <div>
     <p class="settings-eyebrow">Analytics</p>
     <h1>数据统计</h1>
-    <p class="muted settings-lead">多机 KPI 对比与余额曲线(不含权利金/浮盈)。后台常驻刷新,打开即读缓存。</p>
+    <p class="muted settings-lead">多机 KPI 对比与累计已实现盈亏曲线。划转/提现不影响曲线。后台常驻刷新,打开即读缓存。</p>
   </div>
   <div class="stats-window-tabs" id="stats-window-tabs" role="tablist">
     <button type="button" class="stats-win-btn" data-window="today">今日</button>
@@ -56,8 +56,8 @@
 <section class="panel stats-curve-panel stats-curve-panel--large">
   <div class="stats-card-head-inline">
     <div>
-      <h2>余额曲线</h2>
+      <h2>已实现盈亏曲线</h2>
-      <p class="muted">主指标为账户现金余额,不含已用权利金与浮盈。可勾选机器叠加对比。</p>
+      <p class="muted">主指标为各机累计已实现盈亏(期权平仓真盈亏U累加)。可勾选机器叠加对比。</p>
     </div>
     <label class="stats-curve-toggle">
       <input type="checkbox" id="stats-show-total" checked>
@@ -67,11 +67,11 @@
   <div class="stats-machine-picker" id="stats-machine-picker" aria-label="选择机器"></div>
   <div class="stats-chart-wrap stats-chart-wrap--large">
     <canvas id="stats-curve-canvas" width="960" height="480"></canvas>
-    <div class="stats-chart-empty muted" id="stats-curve-empty" hidden>暂无采样数据,后台巡检运行后会逐渐出现。</div>
+    <div class="stats-chart-empty muted" id="stats-curve-empty" hidden>暂无已实现盈亏数据;实例更新并有平仓记录后显示。</div>
   </div>
   <div class="stats-legend" id="stats-curve-legend"></div>
 </section>
 {% endblock %}
 {% block scripts %}
-<script src="{{ url_for('static', filename='stats.js') }}?v=4"></script>
+<script src="{{ url_for('static', filename='stats.js') }}?v=5"></script>
 {% endblock %}

tests/test_stats_realized_pnl_curve.py

@@ -0,0 +1,52 @@
+"""中控统计曲线:各机累计已实现盈亏叠加合计."""
+from __future__ import annotations
+
+import unittest
+from unittest.mock import patch
+
+
+class TestStatsRealizedPnlCurve(unittest.TestCase):
+    def test_build_stats_curve_sums_machines(self):
+        from lib.stats_agg_lib import build_stats_curve
+
+        t0 = 1_700_000_040_000  # 已对齐到分钟桶
+        t1 = t0 + 60_000
+        t2 = t0 + 120_000
+        fake_rows = [
+            {
+                "id": "a",
+                "name": "A",
+                "online": True,
+                "error": "",
+                "points": [{"t": t0, "v": 10.0}, {"t": t2, "v": 15.0}],
+                "trade_count": 2,
+                "latest": 15.0,
+                "start_ms": t0,
+                "end_ms": t2,
+            },
+            {
+                "id": "b",
+                "name": "B",
+                "online": True,
+                "error": "",
+                "points": [{"t": t1, "v": 5.0}],
+                "trade_count": 1,
+                "latest": 5.0,
+                "start_ms": t1,
+                "end_ms": t2,
+            },
+        ]
+        with patch("lib.stats_agg_lib.pull_all_pnl_curves", return_value=fake_rows):
+            out = build_stats_curve("all")
+        self.assertTrue(out["ok"])
+        self.assertEqual(out["metric"], "realized_pnl")
+        self.assertEqual(len(out["series"]), 2)
+        totals = {p["t"]: p["v"] for p in out["total"]}
+        # t0: only A=10; t1: A=10 + B=5; t2: A=15 + B=5
+        self.assertAlmostEqual(totals[t0], 10.0)
+        self.assertAlmostEqual(totals[t1], 15.0)
+        self.assertAlmostEqual(totals[t2], 20.0)
+
+
+if __name__ == "__main__":
+    unittest.main()