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>
This commit is contained in:
@@ -325,6 +325,77 @@ def pull_all_stats(window: str = "7d") -> list[dict[str, Any]]:
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return results
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def fetch_one_pnl_curve(inst: dict[str, Any], *, range_key: str = "7d") -> dict[str, Any]:
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"""拉取单机累计已实现盈亏曲线."""
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base = (inst.get("base_url") or "").rstrip("/")
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token = (inst.get("bridge_token") or "").strip()
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out: dict[str, Any] = {
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"id": inst.get("id"),
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"name": inst.get("name"),
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"online": False,
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"error": "",
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"points": [],
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"trade_count": 0,
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"latest": None,
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"metric": "realized_pnl",
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}
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if not base or not token:
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out["error"] = "缺少 URL 或 Token"
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return out
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url = f"{base}/api/hub/options/pnl_curve"
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try:
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r = requests.get(
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url,
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headers={"X-Hub-Token": token, "Accept": "application/json"},
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params={"range": range_key},
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timeout=max(_timeout(), 15.0),
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)
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data = {}
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try:
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data = r.json()
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except Exception:
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data = {}
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if r.status_code != 200 or not isinstance(data, dict) or not data.get("ok"):
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out["error"] = (data.get("msg") if isinstance(data, dict) else None) or f"HTTP {r.status_code}"
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return out
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out["online"] = True
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pts = data.get("points") if isinstance(data.get("points"), list) else []
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out["points"] = pts
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out["trade_count"] = int(data.get("trade_count") or 0)
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out["latest"] = data.get("latest")
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out["metric"] = data.get("metric") or "realized_pnl"
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out["start_ms"] = data.get("start_ms")
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out["end_ms"] = data.get("end_ms")
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return out
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except requests.Timeout:
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out["error"] = "超时"
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return out
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except Exception as e:
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out["error"] = str(e) or "拉取失败"
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return out
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def pull_all_pnl_curves(range_key: str = "7d") -> list[dict[str, Any]]:
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instances = list_instances(enabled_only=True)
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if not instances:
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return []
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results: list[dict[str, Any]] = []
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with ThreadPoolExecutor(max_workers=min(8, len(instances))) as pool:
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futs = {
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pool.submit(fetch_one_pnl_curve, inst, range_key=range_key): inst["id"]
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for inst in instances
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}
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by_id: dict[Any, dict[str, Any]] = {}
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for fut in as_completed(futs):
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row = fut.result()
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by_id[row.get("id")] = row
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for inst in instances:
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results.append(
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by_id.get(inst["id"]) or fetch_one_pnl_curve(inst, range_key=range_key)
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)
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return results
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def fetch_client_version(inst: dict[str, Any]) -> dict[str, Any]:
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"""探测客户端 git 版本 / 在线."""
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base = (inst.get("base_url") or "").rstrip("/")
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+84
-7
@@ -1,12 +1,12 @@
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"""中控统计汇总:KPI 对比 + 余额曲线."""
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"""中控统计汇总:KPI 对比 + 已实现盈亏曲线."""
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from __future__ import annotations
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import time
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from typing import Any
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from lib.bridge_client_lib import pull_all_enabled, pull_all_stats
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from lib.bridge_client_lib import pull_all_enabled, pull_all_pnl_curves, pull_all_stats
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from lib.cash_sample_lib import (
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first_cash_by_instance,
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query_cash_series,
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record_cash_samples_from_overview,
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)
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@@ -185,7 +185,84 @@ def build_stats_summary(
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def build_stats_curve(range_key: str = "7d") -> dict[str, Any]:
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# 曲线只读本地采样库;余额采样由总览常驻 pull 负责
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data = query_cash_series(range_key=range_key)
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data["ok"] = True
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return data
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"""多机累计已实现盈亏曲线(各机台阶叠加;划转/提现不影响)."""
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rk = normalize_window(range_key)
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now_ms = int(time.time() * 1000)
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rows = pull_all_pnl_curves(rk)
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series: list[dict[str, Any]] = []
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by_id: dict[Any, list[dict[str, float]]] = {}
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start_ms = None
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end_ms = now_ms
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for row in rows:
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iid = row.get("id")
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pts_raw = row.get("points") if isinstance(row.get("points"), list) else []
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pts: list[dict[str, float]] = []
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for p in pts_raw:
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if not isinstance(p, dict):
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continue
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try:
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t = int(p.get("t"))
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v = float(p.get("v"))
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except (TypeError, ValueError):
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continue
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pts.append({"t": t, "v": v})
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pts.sort(key=lambda x: x["t"])
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if row.get("start_ms") is not None:
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try:
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sm = int(row.get("start_ms"))
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start_ms = sm if start_ms is None else min(start_ms, sm)
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except (TypeError, ValueError):
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pass
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if row.get("end_ms") is not None:
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try:
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end_ms = max(end_ms, int(row.get("end_ms")))
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except (TypeError, ValueError):
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pass
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by_id[iid] = pts
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series.append(
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{
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"id": iid,
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"name": row.get("name") or str(iid),
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"online": bool(row.get("online")),
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"error": row.get("error") or "",
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"points": pts,
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"trade_count": int(row.get("trade_count") or 0),
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"latest": row.get("latest"),
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}
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)
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# 合计:按 1 分钟桶,各机该桶最后值求和并前向填充
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last_in_bucket: dict[int, dict[Any, float]] = {}
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for iid, pts in by_id.items():
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for p in pts:
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bt = (int(p["t"]) // 60000) * 60000
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last_in_bucket.setdefault(bt, {})[iid] = float(p["v"])
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running: dict[Any, float] = {}
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total_pts: list[dict[str, float]] = []
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for bt in sorted(last_in_bucket.keys()):
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running.update(last_in_bucket[bt])
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if running:
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total_pts.append({"t": bt, "v": round(sum(running.values()), 4)})
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if start_ms is None:
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if rk in ("today", "1d"):
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import datetime as dt
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start = dt.datetime.now().replace(hour=0, minute=0, second=0, microsecond=0)
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start_ms = int(start.timestamp() * 1000)
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elif rk in ("30d", "30"):
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start_ms = now_ms - 30 * 86400 * 1000
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elif rk in ("all", "0"):
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start_ms = 0
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else:
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start_ms = now_ms - 7 * 86400 * 1000
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return {
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"ok": True,
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"metric": "realized_pnl",
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"series": series,
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"total": total_pts,
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"range": rk,
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"start_ms": start_ms,
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"end_ms": end_ms,
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}
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