Files
crypto_okx_hub/lib/stats_agg_lib.py
T
2026-10-03 02:59:20 +08:00

165 lines
5.8 KiB
Python

"""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