Initialize crypto_monitor_user (user edition) from monitor codebase.
Retarget git remote, install path, and deploy docs from crypto_monitor to crypto_monitor_user. Co-authored-by: Cursor <cursoragent@cursor.com>
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dekun
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"""期权本地交易统计(胜率 / 盈亏 / 持仓时长)."""
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from __future__ import annotations
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from datetime import datetime
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from typing import Any
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from lib.instance.instance_embed_context_lib import profit_loss_ratio_from_averages
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from lib.options.options_db import init_options_tables
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def _parse_ts(raw: Any) -> datetime | None:
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if raw is None or raw == "":
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return None
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s = str(raw).strip().replace(" ", "T", 1)
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try:
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return datetime.fromisoformat(s)
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except (TypeError, ValueError):
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return None
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def _hold_seconds(created_at: Any, closed_at: Any) -> float | None:
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start = _parse_ts(created_at)
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end = _parse_ts(closed_at)
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if start is None or end is None:
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return None
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sec = (end - start).total_seconds()
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return sec if sec >= 0 else None
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def _avg_seconds(values: list[float]) -> float | None:
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if not values:
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return None
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return round(sum(values) / len(values), 1)
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def compute_options_stats_from_history(history: list[dict[str, Any]]) -> dict[str, Any]:
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"""基于期权历史列表(交易所)计算统计."""
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wins: list[float] = []
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losses: list[float] = []
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win_holds: list[float] = []
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loss_holds: list[float] = []
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all_holds: list[float] = []
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open_holds: list[float] = []
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now = datetime.now()
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for row in history:
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if row.get("status") == "open":
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start = _parse_ts(row.get("created_at"))
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if start is not None:
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sec = (now - start).total_seconds()
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if sec >= 0:
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open_holds.append(sec)
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continue
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pnl_raw = row.get("realized_pnl")
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if pnl_raw is None:
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continue
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try:
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pnl = float(pnl_raw)
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except (TypeError, ValueError):
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continue
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hold = _hold_seconds(row.get("created_at"), row.get("closed_at"))
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if hold is not None:
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all_holds.append(hold)
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if pnl > 0:
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wins.append(pnl)
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if hold is not None:
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win_holds.append(hold)
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elif pnl < 0:
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losses.append(pnl)
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if hold is not None:
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loss_holds.append(hold)
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total_closed = len(wins) + len(losses)
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win_rate = round(len(wins) / total_closed * 100, 2) if total_closed else 0
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avg_win = sum(wins) / len(wins) if wins else None
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avg_loss = sum(losses) / len(losses) if losses else None
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total_profit = round(sum(wins), 4) if wins else 0.0
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total_loss = round(abs(sum(losses)), 4) if losses else 0.0
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net_realized = round(sum(wins) + sum(losses), 4)
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return {
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"total_closed": total_closed,
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"win_count": len(wins),
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"loss_count": len(losses),
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"win_rate": win_rate,
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"profit_loss_ratio": profit_loss_ratio_from_averages(avg_win, avg_loss),
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"avg_win": round(avg_win, 4) if avg_win is not None else None,
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"avg_loss": round(abs(avg_loss), 4) if avg_loss is not None else None,
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"total_profit": total_profit,
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"total_loss": total_loss,
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"net_realized_pnl": net_realized,
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"avg_hold_sec": _avg_seconds(all_holds),
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"avg_win_hold_sec": _avg_seconds(win_holds),
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"avg_loss_hold_sec": _avg_seconds(loss_holds),
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"open_count": len(open_holds),
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"avg_open_hold_sec": _avg_seconds(open_holds),
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}
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def compute_options_stats(get_db) -> dict[str, Any]:
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conn = get_db()
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try:
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init_options_tables(conn)
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closed_rows = conn.execute(
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"""
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SELECT realized_pnl, created_at, closed_at
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FROM options_trades
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WHERE status = 'closed' AND realized_pnl IS NOT NULL
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"""
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).fetchall()
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open_rows = conn.execute(
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"""
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SELECT created_at FROM options_trades WHERE status = 'open'
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"""
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).fetchall()
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finally:
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conn.close()
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wins: list[float] = []
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losses: list[float] = []
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win_holds: list[float] = []
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loss_holds: list[float] = []
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all_holds: list[float] = []
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now = datetime.now()
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for row in closed_rows:
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pnl = float(row["realized_pnl"])
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hold = _hold_seconds(row["created_at"], row["closed_at"])
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if hold is not None:
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all_holds.append(hold)
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if pnl > 0:
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wins.append(pnl)
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if hold is not None:
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win_holds.append(hold)
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elif pnl < 0:
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losses.append(pnl)
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if hold is not None:
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loss_holds.append(hold)
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open_holds: list[float] = []
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for row in open_rows:
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start = _parse_ts(row["created_at"])
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if start is None:
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continue
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sec = (now - start).total_seconds()
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if sec >= 0:
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open_holds.append(sec)
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total_closed = len(wins) + len(losses)
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win_rate = round(len(wins) / total_closed * 100, 2) if total_closed else 0
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avg_win = sum(wins) / len(wins) if wins else None
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avg_loss = sum(losses) / len(losses) if losses else None
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total_profit = round(sum(wins), 4) if wins else 0.0
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total_loss = round(abs(sum(losses)), 4) if losses else 0.0
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net_realized = round(sum(wins) + sum(losses), 4)
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return {
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"total_closed": total_closed,
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"win_count": len(wins),
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"loss_count": len(losses),
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"win_rate": win_rate,
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"profit_loss_ratio": profit_loss_ratio_from_averages(avg_win, avg_loss),
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"avg_win": round(avg_win, 4) if avg_win is not None else None,
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"avg_loss": round(abs(avg_loss), 4) if avg_loss is not None else None,
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"total_profit": total_profit,
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"total_loss": total_loss,
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"net_realized_pnl": net_realized,
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"avg_hold_sec": _avg_seconds(all_holds),
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"avg_win_hold_sec": _avg_seconds(win_holds),
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"avg_loss_hold_sec": _avg_seconds(loss_holds),
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"open_count": len(open_holds),
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"avg_open_hold_sec": _avg_seconds(open_holds),
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}
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