"""期权本地交易统计(胜率 / 盈亏 / 持仓时长).""" from __future__ import annotations from datetime import datetime from typing import Any from lib.instance.instance_embed_context_lib import profit_loss_ratio_from_averages from lib.options.options_db import init_options_tables from lib.options.options_margin_mode_lib import margin_mode_from_inst_id, premium_ccy_for_mode def _parse_ts(raw: Any) -> datetime | None: if raw is None or raw == "": return None s = str(raw).strip().replace(" ", "T", 1) try: return datetime.fromisoformat(s) except (TypeError, ValueError): return None def _hold_seconds(created_at: Any, closed_at: Any) -> float | None: start = _parse_ts(created_at) end = _parse_ts(closed_at) if start is None or end is None: return None sec = (end - start).total_seconds() return sec if sec >= 0 else None def _avg_seconds(values: list[float]) -> float | None: if not values: return None return round(sum(values) / len(values), 1) 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 _row_premium_ccy(row: dict[str, Any]) -> str: ccy = str(row.get("premium_ccy") or "").strip().upper() if ccy: return ccy inst = str(row.get("inst_id") or "").strip() mode = str(row.get("margin_mode") or "").strip().lower() underly = str(row.get("underlying") or (inst.split("-")[0] if inst else "ETH") or "ETH") if mode: return premium_ccy_for_mode(mode, underly) if not inst: # 旧统计行无合约信息时按 USDC 口径,避免默认币本位把盈亏跳过 return "USDC" return premium_ccy_for_mode(margin_mode_from_inst_id(inst), underly) def _pnl_as_usdt(row: dict[str, Any], *, fallback_index: float | None = None) -> float | None: """已平/浮盈统一折算为 USDT(币本位×指数;USDC 原样).""" pnl = _safe_float(row.get("realized_pnl")) if pnl is None: pnl = _safe_float(row.get("upl")) if pnl is None: return None ccy = _row_premium_ccy(row) if ccy in ("ETH", "BTC"): px = _safe_float(row.get("idx_px") or row.get("idxPx") or row.get("index_px")) if px is None or px <= 0: px = fallback_index if px is None or px <= 0: return None return float(pnl) * float(px) return float(pnl) def _history_index_px(history: list[dict[str, Any]]) -> float | None: for row in history: px = _safe_float(row.get("idx_px") or row.get("idxPx") or row.get("index_px")) if px is not None and px > 0: return px return None def compute_options_stats_from_history( history: list[dict[str, Any]], *, index_px: float | None = None, ) -> dict[str, Any]: """基于期权历史列表计算统计;币本位盈亏按指数折算为 U.""" wins: list[float] = [] losses: list[float] = [] win_holds: list[float] = [] loss_holds: list[float] = [] all_holds: list[float] = [] open_holds: list[float] = [] now = datetime.now() fallback_idx = index_px if index_px is not None and index_px > 0 else _history_index_px(history) coinish = False for row in history: ccy = _row_premium_ccy(row) if ccy in ("ETH", "BTC"): coinish = True if row.get("status") == "open": start = _parse_ts(row.get("created_at")) if start is not None: sec = (now - start).total_seconds() if sec >= 0: open_holds.append(sec) continue pnl = _pnl_as_usdt(row, fallback_index=fallback_idx) if pnl is None: continue hold = _hold_seconds(row.get("created_at"), row.get("closed_at")) if hold is not None: all_holds.append(hold) if pnl > 0: wins.append(pnl) if hold is not None: win_holds.append(hold) elif pnl < 0: losses.append(pnl) if hold is not None: loss_holds.append(hold) total_closed = len(wins) + len(losses) win_rate = round(len(wins) / total_closed * 100, 2) if total_closed else 0 avg_win = sum(wins) / len(wins) if wins else None avg_loss = sum(losses) / len(losses) if losses else None total_profit = round(sum(wins), 4) if wins else 0.0 total_loss = round(abs(sum(losses)), 4) if losses else 0.0 net_realized = round(sum(wins) + sum(losses), 4) return { "total_closed": total_closed, "win_count": len(wins), "loss_count": len(losses), "win_rate": win_rate, "profit_loss_ratio": profit_loss_ratio_from_averages(avg_win, avg_loss), "avg_win": round(avg_win, 4) if avg_win is not None else None, "avg_loss": round(abs(avg_loss), 4) if avg_loss is not None else None, "total_profit": total_profit, "total_loss": total_loss, "net_realized_pnl": net_realized, "avg_hold_sec": _avg_seconds(all_holds), "avg_win_hold_sec": _avg_seconds(win_holds), "avg_loss_hold_sec": _avg_seconds(loss_holds), "open_count": len(open_holds), "avg_open_hold_sec": _avg_seconds(open_holds), "pnl_unit": "U" if coinish else "USDC", "index_px": fallback_idx, } def compute_options_stats(get_db) -> dict[str, Any]: conn = get_db() try: init_options_tables(conn) closed_rows = conn.execute( """ SELECT realized_pnl, created_at, closed_at, inst_id, premium_ccy, margin_mode FROM options_trades WHERE status = 'closed' AND realized_pnl IS NOT NULL """ ).fetchall() open_rows = conn.execute( """ SELECT created_at FROM options_trades WHERE status = 'open' """ ).fetchall() finally: conn.close() hist = [] for row in closed_rows: hist.append( { "status": "closed", "realized_pnl": row["realized_pnl"], "created_at": row["created_at"], "closed_at": row["closed_at"], "inst_id": row["inst_id"] if "inst_id" in row.keys() else None, "premium_ccy": row["premium_ccy"] if "premium_ccy" in row.keys() else None, "margin_mode": row["margin_mode"] if "margin_mode" in row.keys() else None, } ) for row in open_rows: hist.append({"status": "open", "created_at": row["created_at"]}) return compute_options_stats_from_history(hist)