dekun
171 lines
6.1 KiB
Python
171 lines
6.1 KiB
Python
"""中控统计汇总:KPI 对比 + 余额曲线."""
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from __future__ import annotations
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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.cash_sample_lib import query_cash_series, record_cash_samples_from_overview
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def _safe_float(v: Any) -> float | None:
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if v is None or v == "":
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return None
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try:
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return float(v)
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except (TypeError, ValueError):
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return None
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def _safe_int(v: Any) -> int:
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try:
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return int(float(v))
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except (TypeError, ValueError):
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return 0
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def normalize_window(raw: Any) -> str:
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w = str(raw or "7d").strip().lower()
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if w in ("1d", "day", "今日"):
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return "today"
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if w in ("7", "week"):
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return "7d"
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if w in ("30", "month"):
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return "30d"
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if w in ("0", "全部", "total"):
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return "all"
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return w if w in ("today", "7d", "30d", "all") else "7d"
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def build_stats_summary(
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window: str = "7d",
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*,
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snaps: list[dict[str, Any]] | None = None,
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) -> dict[str, Any]:
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w = normalize_window(window)
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# 实时状态(余额/权利金/浮盈)来自快照;窗口 KPI 来自各机 stats
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# snaps 可由热缓存传入,避免统计页再现场重复拉全机
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if snaps is None:
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snaps = pull_all_enabled()
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try:
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record_cash_samples_from_overview(snaps)
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except Exception:
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pass
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stats_rows = pull_all_stats(w)
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stats_by_id = {r.get("id"): r for r in stats_rows}
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machines: list[dict[str, Any]] = []
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sum_cash = 0.0
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sum_premium = 0.0
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sum_unreal = 0.0
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sum_net = 0.0
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sum_profit = 0.0
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sum_loss = 0.0
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sum_closed = 0
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sum_wins = 0
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sum_losses = 0
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online_n = 0
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cash_known = False
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premium_known = False
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unreal_known = False
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for snap in snaps:
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iid = snap.get("id")
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st = stats_by_id.get(iid) or {}
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stats = st.get("stats") if isinstance(st.get("stats"), dict) else {}
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body = snap.get("snapshot") if isinstance(snap.get("snapshot"), dict) else {}
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premium = body.get("premium") if isinstance(body.get("premium"), dict) else {}
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pnl = body.get("pnl") if isinstance(body.get("pnl"), dict) else {}
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brief = body.get("positions_brief") if isinstance(body.get("positions_brief"), list) else []
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cash = _safe_float(premium.get("cash_usdt"))
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paid = _safe_float(premium.get("paid_usdt"))
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ratio = _safe_float(premium.get("ratio_pct"))
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unreal = _safe_float(pnl.get("unrealized_usdt"))
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net = _safe_float(stats.get("net_realized_pnl"))
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profit = _safe_float(stats.get("total_profit"))
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loss = _safe_float(stats.get("total_loss"))
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closed = _safe_int(stats.get("total_closed"))
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wins = _safe_int(stats.get("win_count"))
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losses = _safe_int(stats.get("loss_count"))
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win_rate = _safe_float(stats.get("win_rate"))
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avg_hold = _safe_float(stats.get("avg_hold_sec"))
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online = bool(snap.get("online"))
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mode = ((body.get("instance") or {}) if isinstance(body.get("instance"), dict) else {}).get(
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"mode"
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)
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return_pct = None
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if online and stats.get("ok") and net is not None and cash is not None and cash > 0:
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return_pct = round(float(net) / float(cash) * 100.0, 2)
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if online:
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online_n += 1
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if cash is not None:
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sum_cash += cash
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cash_known = True
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if paid is not None:
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sum_premium += paid
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premium_known = True
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if unreal is not None:
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sum_unreal += unreal
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unreal_known = True
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if online and stats.get("ok"):
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if net is not None:
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sum_net += net
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if profit is not None:
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sum_profit += profit
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if loss is not None:
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sum_loss += loss
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sum_closed += closed
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sum_wins += wins
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sum_losses += losses
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machines.append(
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{
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"id": iid,
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"name": snap.get("name"),
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"online": online,
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"error": snap.get("error") or st.get("error") or "",
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"mode": mode,
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"cash_usdt": cash,
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"premium_usdt": paid,
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"ratio_pct": ratio,
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"unrealized_usdt": unreal,
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"pos_count": len(brief),
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"total_closed": closed if online and stats.get("ok") else None,
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"win_count": wins if online and stats.get("ok") else None,
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"loss_count": losses if online and stats.get("ok") else None,
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"win_rate": win_rate if online and stats.get("ok") else None,
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"net_realized_pnl": net if online and stats.get("ok") else None,
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"return_rate_pct": return_pct,
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"total_profit": profit if online and stats.get("ok") else None,
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"total_loss": loss if online and stats.get("ok") else None,
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"avg_hold_sec": avg_hold if online and stats.get("ok") else None,
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"stats_ok": bool(online and stats.get("ok")),
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}
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)
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agg_win_rate = round(sum_wins / sum_closed * 100, 2) if sum_closed else 0.0
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return {
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"ok": True,
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"window": w,
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"totals": {
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"online": online_n,
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"machines": len(machines),
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"cash_usdt": round(sum_cash, 4) if cash_known else None,
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"premium_usdt": round(sum_premium, 4) if premium_known else None,
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"unrealized_usdt": round(sum_unreal, 4) if unreal_known else None,
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"net_realized_pnl": round(sum_net, 4),
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"total_profit": round(sum_profit, 4),
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"total_loss": round(sum_loss, 4),
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"total_closed": sum_closed,
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"win_count": sum_wins,
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"loss_count": sum_losses,
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"win_rate": agg_win_rate,
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},
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"machines": machines,
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}
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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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