fix(hub): merge strategy snapshots into archive for gate_bot
Include strategy_trade_snapshots when trade_records is empty, harden SQL for older schemas, and show per-exchange sync errors in the archive UI. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
dekun
+238
-25
@@ -228,6 +228,195 @@ def _normalize_archive_trade_row(
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}
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_SNAPSHOT_STATUS_TO_RESULT = {
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"stopped_sl": "止损",
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"stopped_tp": "止盈",
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"stopped_manual": "手动平仓",
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"stopped_external": "外部平仓",
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}
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def _table_columns(conn, table: str) -> set[str]:
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try:
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rows = conn.execute(f"PRAGMA table_info({table})").fetchall()
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except Exception:
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return set()
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out: set[str] = set()
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for r in rows:
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try:
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out.add(str(r[1]))
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except (IndexError, TypeError):
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try:
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out.add(str(r["name"]))
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except Exception:
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continue
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return out
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def _archive_ts_expr(cols: set[str]) -> str:
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parts = [c for c in ("reviewed_closed_at", "closed_at", "created_at", "opened_at") if c in cols]
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if not parts:
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return "''"
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return f"REPLACE(COALESCE({', '.join(parts)}), 'T', ' ')"
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def _archive_trade_select_sql(cols: set[str]) -> str:
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wanted = [
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"id",
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"symbol",
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"direction",
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"result",
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"reviewed_result",
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"pnl_amount",
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"reviewed_pnl_amount",
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"exchange_realized_pnl",
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"closed_at",
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"reviewed_closed_at",
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"opened_at",
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"reviewed_opened_at",
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"opened_at_ms",
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"closed_at_ms",
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"created_at",
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"monitor_type",
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"actual_rr",
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"planned_rr",
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"trade_style",
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"entry_reason",
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"trigger_price",
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"stop_loss",
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"take_profit",
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"reviewed_stop_loss",
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"reviewed_take_profit",
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"reviewed_at",
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"trend_plan_id",
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]
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select_cols = [c for c in wanted if c in cols]
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if "id" not in select_cols:
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select_cols = ["id"] + select_cols
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return ", ".join(select_cols)
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def _existing_trend_plan_ids(conn) -> set[int]:
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cols = _table_columns(conn, "trade_records")
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if "trend_plan_id" not in cols:
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return set()
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rows = conn.execute(
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"SELECT DISTINCT trend_plan_id FROM trade_records WHERE trend_plan_id IS NOT NULL"
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).fetchall()
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out: set[int] = set()
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for row in rows:
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d = _row_dict(row)
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try:
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out.add(int(d.get("trend_plan_id")))
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except (TypeError, ValueError):
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continue
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return out
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def _normalize_snapshot_archive_row(
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snap: dict,
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*,
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reset_hour: int = 8,
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) -> dict[str, Any] | None:
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result = str(snap.get("result_label") or "").strip()
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if not result:
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result = _SNAPSHOT_STATUS_TO_RESULT.get(
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str(snap.get("status_at_close") or "").strip(), ""
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)
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if result not in TRADE_COMPLETED_RESULTS:
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return None
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closed_at = snap.get("closed_at")
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close_dt = parse_dt_for_trading_day(closed_at)
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if not close_dt:
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return None
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opened_at = snap.get("opened_at")
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opened_ms = _parse_ms_from_row(snap.get("opened_at"))
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closed_ms = _parse_ms_from_row(closed_at)
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try:
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snap_id = int(snap.get("id"))
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except (TypeError, ValueError):
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return None
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try:
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pnl = float(snap.get("pnl_amount") or 0)
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except (TypeError, ValueError):
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pnl = 0.0
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st = str(snap.get("strategy_type") or "").strip()
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monitor_type = "trend_pullback" if st == "trend_pullback" else ("roll" if st == "roll" else st)
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return {
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"id": -snap_id,
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"symbol": (snap.get("symbol") or "").strip().upper(),
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"direction": snap.get("direction"),
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"result": result,
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"pnl_amount": round(pnl, 4),
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"closed_at": closed_at,
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"opened_at": opened_at,
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"opened_at_ms": opened_ms,
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"closed_at_ms": closed_ms,
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"monitor_type": monitor_type,
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"entry_reason": "trend_pullback" if st == "trend_pullback" else monitor_type,
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"from_snapshot": True,
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"snapshot_id": snap_id,
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"trend_plan_id": snap.get("source_id"),
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"trading_day": trading_day_from_dt(close_dt, reset_hour),
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}
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def _parse_ms_from_row(raw: Any) -> int | None:
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if raw in (None, ""):
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return None
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try:
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if isinstance(raw, (int, float)):
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v = int(raw)
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return v if v > 1_000_000_000_000 else v * 1000
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except (TypeError, ValueError):
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pass
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dt = parse_dt_for_trading_day(raw)
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return int(dt.timestamp() * 1000) if dt else None
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def _fetch_strategy_snapshots_for_archive(
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conn,
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*,
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days: int = 365,
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reset_hour: int = 8,
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limit: int = 2000,
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skip_plan_ids: set[int] | None = None,
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) -> list[dict[str, Any]]:
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cols = _table_columns(conn, "strategy_trade_snapshots")
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if not cols:
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return []
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lim = max(1, min(int(limit or 2000), 5000))
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day_span = max(1, min(int(days or 365), 3650))
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cutoff = datetime.now() - timedelta(days=day_span)
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cutoff_s = cutoff.strftime("%Y-%m-%d %H:%M:%S")
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ts_expr = "REPLACE(COALESCE(closed_at, opened_at, created_at), 'T', ' ')"
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rows = conn.execute(
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f"""
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SELECT * FROM strategy_trade_snapshots
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WHERE {ts_expr} >= ?
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ORDER BY {ts_expr} DESC
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LIMIT ?
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""",
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(cutoff_s, lim * 2),
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).fetchall()
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skip = skip_plan_ids or set()
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out: list[dict[str, Any]] = []
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for row in rows:
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d = _row_dict(row)
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try:
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source_id = int(d.get("source_id") or 0)
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except (TypeError, ValueError):
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source_id = 0
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if source_id > 0 and source_id in skip:
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continue
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norm = _normalize_snapshot_archive_row(d, reset_hour=reset_hour)
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if norm:
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out.append(norm)
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if len(out) >= lim:
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break
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return out
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def fetch_trades_for_archive(
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conn,
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*,
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@@ -235,36 +424,60 @@ def fetch_trades_for_archive(
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row_to_dict_fn: Optional[Callable] = None,
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reset_hour: int = 8,
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limit: int = 2000,
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include_strategy_snapshots: bool = True,
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) -> list[dict[str, Any]]:
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"""返回近 N 天已平仓记录（供币种档案聚合）。"""
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"""返回近 N 天已平仓记录（trade_records + 未落库的 strategy 快照）。"""
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lim = max(1, min(int(limit or 2000), 5000))
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day_span = max(1, min(int(days or 365), 3650))
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cutoff = datetime.now() - timedelta(days=day_span)
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cutoff_s = cutoff.strftime("%Y-%m-%d %H:%M:%S")
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ts_expr = "REPLACE(COALESCE(reviewed_closed_at, closed_at, created_at, opened_at), 'T', ' ')"
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rows = conn.execute(
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f"""
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SELECT id, symbol, direction, result, reviewed_result, pnl_amount, reviewed_pnl_amount,
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exchange_realized_pnl, closed_at, reviewed_closed_at, opened_at, reviewed_opened_at,
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opened_at_ms, closed_at_ms, created_at, monitor_type, actual_rr, planned_rr,
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trade_style, entry_reason, trigger_price, stop_loss, take_profit,
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reviewed_stop_loss, reviewed_take_profit, reviewed_at
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FROM trade_records
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WHERE {ts_expr} >= ?
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ORDER BY {ts_expr} DESC
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LIMIT ?
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""",
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(cutoff_s, lim * 2),
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).fetchall()
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out: list[dict[str, Any]] = []
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for row in rows:
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d = _row_dict(row, row_to_dict_fn)
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norm = _normalize_archive_trade_row(d, reset_hour=reset_hour)
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if norm:
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out.append(norm)
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if len(out) >= lim:
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break
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return out
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cols = _table_columns(conn, "trade_records")
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if not cols:
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records: list[dict[str, Any]] = []
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else:
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ts_expr = _archive_ts_expr(cols)
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sql = f"""
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SELECT {_archive_trade_select_sql(cols)}
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FROM trade_records
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WHERE {ts_expr} >= ?
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ORDER BY {ts_expr} DESC
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LIMIT ?
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"""
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rows = conn.execute(sql, (cutoff_s, lim * 2)).fetchall()
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records = []
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for row in rows:
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d = _row_dict(row, row_to_dict_fn)
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norm = _normalize_archive_trade_row(d, reset_hour=reset_hour)
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if norm:
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records.append(norm)
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if len(records) >= lim:
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break
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if not include_strategy_snapshots:
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return records
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skip_ids = _existing_trend_plan_ids(conn)
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for rec in records:
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try:
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pid = int(rec.get("trend_plan_id") or 0)
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except (TypeError, ValueError):
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pid = 0
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if pid > 0:
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skip_ids.add(pid)
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snaps = _fetch_strategy_snapshots_for_archive(
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conn,
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days=days,
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reset_hour=reset_hour,
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limit=max(0, lim - len(records)),
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skip_plan_ids=skip_ids,
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)
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merged = records + snaps
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merged.sort(
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key=lambda x: int(x.get("closed_at_ms") or 0),
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reverse=True,
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)
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return merged[:lim]
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def summarize_trades(trades: list[dict]) -> dict[str, Any]:
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