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feature/is
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feature/is
| Author | SHA1 | Date | |
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b1f48d859e | ||
| 03f8d220a4 | |||
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305120f599 | ||
| faa23b3f1b | |||
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5844ec5ad3 |
149
src/main.py
149
src/main.py
@@ -106,6 +106,82 @@ def _extract_symbol_from_holding(item: dict[str, Any]) -> str:
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return ""
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return ""
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def _extract_held_codes_from_balance(
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balance_data: dict[str, Any],
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*,
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is_domestic: bool,
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) -> list[str]:
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"""Return stock codes with a positive orderable quantity from a balance response.
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Uses the broker's live output1 as the source of truth so that partial fills
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and manual external trades are always reflected correctly.
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"""
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output1 = balance_data.get("output1", [])
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if isinstance(output1, dict):
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output1 = [output1]
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if not isinstance(output1, list):
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return []
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codes: list[str] = []
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for holding in output1:
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if not isinstance(holding, dict):
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continue
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code_key = "pdno" if is_domestic else "ovrs_pdno"
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code = str(holding.get(code_key, "")).strip().upper()
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if not code:
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continue
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if is_domestic:
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qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
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else:
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qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
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if qty > 0:
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codes.append(code)
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return codes
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def _extract_held_qty_from_balance(
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balance_data: dict[str, Any],
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stock_code: str,
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*,
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is_domestic: bool,
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) -> int:
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"""Extract the broker-confirmed orderable quantity for a stock.
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Uses the broker's live balance response (output1) as the source of truth
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rather than the local DB, because DB records reflect order quantity which
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may differ from actual fill quantity due to partial fills.
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Domestic fields (VTTC8434R output1):
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pdno — 종목코드
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ord_psbl_qty — 주문가능수량 (preferred: excludes unsettled)
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hldg_qty — 보유수량 (fallback)
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Overseas fields (output1):
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ovrs_pdno — 종목코드
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ovrs_cblc_qty — 해외잔고수량 (preferred)
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hldg_qty — 보유수량 (fallback)
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"""
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output1 = balance_data.get("output1", [])
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if isinstance(output1, dict):
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output1 = [output1]
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if not isinstance(output1, list):
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return 0
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for holding in output1:
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if not isinstance(holding, dict):
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continue
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code_key = "pdno" if is_domestic else "ovrs_pdno"
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held_code = str(holding.get(code_key, "")).strip().upper()
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if held_code != stock_code.strip().upper():
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continue
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if is_domestic:
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qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
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else:
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qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
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return qty
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return 0
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def _determine_order_quantity(
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def _determine_order_quantity(
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*,
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*,
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action: str,
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action: str,
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@@ -113,10 +189,11 @@ def _determine_order_quantity(
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total_cash: float,
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total_cash: float,
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candidate: ScanCandidate | None,
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candidate: ScanCandidate | None,
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settings: Settings | None,
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settings: Settings | None,
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broker_held_qty: int = 0,
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) -> int:
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) -> int:
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"""Determine order quantity using volatility-aware position sizing."""
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"""Determine order quantity using volatility-aware position sizing."""
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if action != "BUY":
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if action == "SELL":
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return 1
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return broker_held_qty
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if current_price <= 0 or total_cash <= 0:
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if current_price <= 0 or total_cash <= 0:
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return 0
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return 0
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@@ -387,8 +464,10 @@ async def trading_cycle(
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if entry_price > 0:
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if entry_price > 0:
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loss_pct = (current_price - entry_price) / entry_price * 100
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loss_pct = (current_price - entry_price) / entry_price * 100
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stop_loss_threshold = -2.0
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stop_loss_threshold = -2.0
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take_profit_threshold = 3.0
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if stock_playbook and stock_playbook.scenarios:
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if stock_playbook and stock_playbook.scenarios:
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stop_loss_threshold = stock_playbook.scenarios[0].stop_loss_pct
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stop_loss_threshold = stock_playbook.scenarios[0].stop_loss_pct
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take_profit_threshold = stock_playbook.scenarios[0].take_profit_pct
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if loss_pct <= stop_loss_threshold:
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if loss_pct <= stop_loss_threshold:
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decision = TradeDecision(
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decision = TradeDecision(
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@@ -406,6 +485,22 @@ async def trading_cycle(
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loss_pct,
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loss_pct,
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stop_loss_threshold,
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stop_loss_threshold,
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)
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)
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elif loss_pct >= take_profit_threshold:
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decision = TradeDecision(
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action="SELL",
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confidence=90,
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rationale=(
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f"Take-profit triggered ({loss_pct:.2f}% >= "
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f"{take_profit_threshold:.2f}%)"
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),
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)
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logger.info(
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"Take-profit override for %s (%s): %.2f%% >= %.2f%%",
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stock_code,
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market.name,
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loss_pct,
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take_profit_threshold,
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)
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logger.info(
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logger.info(
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"Decision for %s (%s): %s (confidence=%d)",
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"Decision for %s (%s): %s (confidence=%d)",
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stock_code,
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stock_code,
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@@ -466,12 +561,20 @@ async def trading_cycle(
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trade_price = current_price
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trade_price = current_price
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trade_pnl = 0.0
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trade_pnl = 0.0
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if decision.action in ("BUY", "SELL"):
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if decision.action in ("BUY", "SELL"):
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broker_held_qty = (
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_extract_held_qty_from_balance(
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balance_data, stock_code, is_domestic=market.is_domestic
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)
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if decision.action == "SELL"
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else 0
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)
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quantity = _determine_order_quantity(
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quantity = _determine_order_quantity(
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action=decision.action,
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action=decision.action,
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current_price=current_price,
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current_price=current_price,
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total_cash=total_cash,
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total_cash=total_cash,
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candidate=candidate,
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candidate=candidate,
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settings=settings,
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settings=settings,
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broker_held_qty=broker_held_qty,
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)
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)
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if quantity <= 0:
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if quantity <= 0:
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logger.info(
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logger.info(
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@@ -891,12 +994,20 @@ async def run_daily_session(
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trade_pnl = 0.0
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trade_pnl = 0.0
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order_succeeded = True
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order_succeeded = True
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if decision.action in ("BUY", "SELL"):
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if decision.action in ("BUY", "SELL"):
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daily_broker_held_qty = (
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_extract_held_qty_from_balance(
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balance_data, stock_code, is_domestic=market.is_domestic
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)
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if decision.action == "SELL"
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else 0
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)
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quantity = _determine_order_quantity(
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quantity = _determine_order_quantity(
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action=decision.action,
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action=decision.action,
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current_price=stock_data["current_price"],
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current_price=stock_data["current_price"],
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total_cash=total_cash,
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total_cash=total_cash,
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candidate=candidate_map.get(stock_code),
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candidate=candidate_map.get(stock_code),
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settings=settings,
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settings=settings,
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broker_held_qty=daily_broker_held_qty,
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)
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)
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if quantity <= 0:
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if quantity <= 0:
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logger.info(
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logger.info(
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@@ -1863,8 +1974,38 @@ async def run(settings: Settings) -> None:
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except Exception as exc:
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except Exception as exc:
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logger.error("Smart Scanner failed for %s: %s", market.name, exc)
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logger.error("Smart Scanner failed for %s: %s", market.name, exc)
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# Get active stocks from scanner (dynamic, no static fallback)
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# Get active stocks from scanner (dynamic, no static fallback).
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stock_codes = active_stocks.get(market.code, [])
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# Also include currently-held positions so stop-loss /
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# take-profit can fire even when a holding drops off the
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# scanner. Broker balance is the source of truth here —
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# unlike the local DB it reflects actual fills and any
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# manual trades done outside the bot.
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scanner_codes = active_stocks.get(market.code, [])
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try:
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if market.is_domestic:
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held_balance = await broker.get_balance()
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else:
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held_balance = await overseas_broker.get_overseas_balance(
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market.exchange_code
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)
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held_codes = _extract_held_codes_from_balance(
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held_balance, is_domestic=market.is_domestic
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)
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except Exception as exc:
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logger.warning(
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"Failed to fetch holdings for %s: %s — skipping holdings merge",
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market.name, exc,
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)
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held_codes = []
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stock_codes = list(dict.fromkeys(scanner_codes + held_codes))
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extra_held = [c for c in held_codes if c not in set(scanner_codes)]
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if extra_held:
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logger.info(
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"Holdings added to loop for %s (not in scanner): %s",
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market.name, extra_held,
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)
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if not stock_codes:
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if not stock_codes:
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logger.debug("No active stocks for market %s", market.code)
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logger.debug("No active stocks for market %s", market.code)
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continue
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continue
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@@ -75,6 +75,7 @@ class PreMarketPlanner:
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market: str,
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market: str,
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candidates: list[ScanCandidate],
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candidates: list[ScanCandidate],
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today: date | None = None,
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today: date | None = None,
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current_holdings: list[dict] | None = None,
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) -> DayPlaybook:
|
) -> DayPlaybook:
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"""Generate a DayPlaybook for a market using Gemini.
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"""Generate a DayPlaybook for a market using Gemini.
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@@ -82,6 +83,10 @@ class PreMarketPlanner:
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market: Market code ("KR" or "US")
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market: Market code ("KR" or "US")
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candidates: Stock candidates from SmartVolatilityScanner
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candidates: Stock candidates from SmartVolatilityScanner
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today: Override date (defaults to date.today()). Use market-local date.
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today: Override date (defaults to date.today()). Use market-local date.
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current_holdings: Currently held positions with entry_price and unrealized_pnl_pct.
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Each dict: {"stock_code": str, "name": str, "qty": int,
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"entry_price": float, "unrealized_pnl_pct": float,
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"holding_days": int}
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Returns:
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Returns:
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DayPlaybook with scenarios. Empty/defensive if no candidates or failure.
|
DayPlaybook with scenarios. Empty/defensive if no candidates or failure.
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@@ -106,6 +111,7 @@ class PreMarketPlanner:
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context_data,
|
context_data,
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self_market_scorecard,
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self_market_scorecard,
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cross_market,
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cross_market,
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current_holdings=current_holdings,
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)
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)
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# 3. Call Gemini
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# 3. Call Gemini
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@@ -118,7 +124,8 @@ class PreMarketPlanner:
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# 4. Parse response
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# 4. Parse response
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playbook = self._parse_response(
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playbook = self._parse_response(
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decision.rationale, today, market, candidates, cross_market
|
decision.rationale, today, market, candidates, cross_market,
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current_holdings=current_holdings,
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)
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)
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playbook_with_tokens = playbook.model_copy(
|
playbook_with_tokens = playbook.model_copy(
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update={"token_count": decision.token_count}
|
update={"token_count": decision.token_count}
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@@ -230,6 +237,7 @@ class PreMarketPlanner:
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context_data: dict[str, Any],
|
context_data: dict[str, Any],
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self_market_scorecard: dict[str, Any] | None,
|
self_market_scorecard: dict[str, Any] | None,
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cross_market: CrossMarketContext | None,
|
cross_market: CrossMarketContext | None,
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|
current_holdings: list[dict] | None = None,
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) -> str:
|
) -> str:
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"""Build a structured prompt for Gemini to generate scenario JSON."""
|
"""Build a structured prompt for Gemini to generate scenario JSON."""
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max_scenarios = self._settings.MAX_SCENARIOS_PER_STOCK
|
max_scenarios = self._settings.MAX_SCENARIOS_PER_STOCK
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@@ -241,6 +249,26 @@ class PreMarketPlanner:
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for c in candidates
|
for c in candidates
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)
|
)
|
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|
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|
holdings_text = ""
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|
if current_holdings:
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|
lines = []
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|
for h in current_holdings:
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|
code = h.get("stock_code", "")
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|
name = h.get("name", "")
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|
qty = h.get("qty", 0)
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|
entry_price = h.get("entry_price", 0.0)
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|
pnl_pct = h.get("unrealized_pnl_pct", 0.0)
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|
holding_days = h.get("holding_days", 0)
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|
lines.append(
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|
f" - {code} ({name}): {qty}주 @ {entry_price:,.0f}, "
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|
f"미실현손익 {pnl_pct:+.2f}%, 보유 {holding_days}일"
|
||||||
|
)
|
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|
holdings_text = (
|
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|
"\n## Current Holdings (보유 중 — SELL/HOLD 전략 고려 필요)\n"
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|
+ "\n".join(lines)
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|
+ "\n"
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|
)
|
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|
|
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cross_market_text = ""
|
cross_market_text = ""
|
||||||
if cross_market:
|
if cross_market:
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||||||
cross_market_text = (
|
cross_market_text = (
|
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@@ -273,10 +301,20 @@ class PreMarketPlanner:
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for key, value in list(layer_data.items())[:5]:
|
for key, value in list(layer_data.items())[:5]:
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context_text += f" - {key}: {value}\n"
|
context_text += f" - {key}: {value}\n"
|
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|
|
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|
holdings_instruction = ""
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|
if current_holdings:
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|
holding_codes = [h.get("stock_code", "") for h in current_holdings]
|
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|
holdings_instruction = (
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|
f"- Also include SELL/HOLD scenarios for held stocks: "
|
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|
f"{', '.join(holding_codes)} "
|
||||||
|
f"(even if not in candidates list)\n"
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||||||
|
)
|
||||||
|
|
||||||
return (
|
return (
|
||||||
f"You are a pre-market trading strategist for the {market} market.\n"
|
f"You are a pre-market trading strategist for the {market} market.\n"
|
||||||
f"Generate structured trading scenarios for today.\n\n"
|
f"Generate structured trading scenarios for today.\n\n"
|
||||||
f"## Candidates (from volatility scanner)\n{candidates_text}\n"
|
f"## Candidates (from volatility scanner)\n{candidates_text}\n"
|
||||||
|
f"{holdings_text}"
|
||||||
f"{self_market_text}"
|
f"{self_market_text}"
|
||||||
f"{cross_market_text}"
|
f"{cross_market_text}"
|
||||||
f"{context_text}\n"
|
f"{context_text}\n"
|
||||||
@@ -308,7 +346,8 @@ class PreMarketPlanner:
|
|||||||
f'}}\n\n'
|
f'}}\n\n'
|
||||||
f"Rules:\n"
|
f"Rules:\n"
|
||||||
f"- Max {max_scenarios} scenarios per stock\n"
|
f"- Max {max_scenarios} scenarios per stock\n"
|
||||||
f"- Only use stocks from the candidates list\n"
|
f"- Candidates list is the primary source for BUY candidates\n"
|
||||||
|
f"{holdings_instruction}"
|
||||||
f"- Confidence 0-100 (80+ for actionable trades)\n"
|
f"- Confidence 0-100 (80+ for actionable trades)\n"
|
||||||
f"- stop_loss_pct must be <= 0, take_profit_pct must be >= 0\n"
|
f"- stop_loss_pct must be <= 0, take_profit_pct must be >= 0\n"
|
||||||
f"- Return ONLY the JSON, no markdown fences or explanation\n"
|
f"- Return ONLY the JSON, no markdown fences or explanation\n"
|
||||||
@@ -321,12 +360,19 @@ class PreMarketPlanner:
|
|||||||
market: str,
|
market: str,
|
||||||
candidates: list[ScanCandidate],
|
candidates: list[ScanCandidate],
|
||||||
cross_market: CrossMarketContext | None,
|
cross_market: CrossMarketContext | None,
|
||||||
|
current_holdings: list[dict] | None = None,
|
||||||
) -> DayPlaybook:
|
) -> DayPlaybook:
|
||||||
"""Parse Gemini's JSON response into a validated DayPlaybook."""
|
"""Parse Gemini's JSON response into a validated DayPlaybook."""
|
||||||
cleaned = self._extract_json(response_text)
|
cleaned = self._extract_json(response_text)
|
||||||
data = json.loads(cleaned)
|
data = json.loads(cleaned)
|
||||||
|
|
||||||
valid_codes = {c.stock_code for c in candidates}
|
valid_codes = {c.stock_code for c in candidates}
|
||||||
|
# Holdings are also valid — AI may generate SELL/HOLD scenarios for them
|
||||||
|
if current_holdings:
|
||||||
|
for h in current_holdings:
|
||||||
|
code = h.get("stock_code", "")
|
||||||
|
if code:
|
||||||
|
valid_codes.add(code)
|
||||||
|
|
||||||
# Parse market outlook
|
# Parse market outlook
|
||||||
outlook_str = data.get("market_outlook", "neutral")
|
outlook_str = data.get("market_outlook", "neutral")
|
||||||
|
|||||||
@@ -14,6 +14,9 @@ from src.evolution.scorecard import DailyScorecard
|
|||||||
from src.logging.decision_logger import DecisionLogger
|
from src.logging.decision_logger import DecisionLogger
|
||||||
from src.main import (
|
from src.main import (
|
||||||
_apply_dashboard_flag,
|
_apply_dashboard_flag,
|
||||||
|
_determine_order_quantity,
|
||||||
|
_extract_held_codes_from_balance,
|
||||||
|
_extract_held_qty_from_balance,
|
||||||
_handle_market_close,
|
_handle_market_close,
|
||||||
_run_context_scheduler,
|
_run_context_scheduler,
|
||||||
_run_evolution_loop,
|
_run_evolution_loop,
|
||||||
@@ -68,6 +71,141 @@ def _make_sell_match(stock_code: str = "005930") -> ScenarioMatch:
|
|||||||
)
|
)
|
||||||
|
|
||||||
|
|
||||||
|
class TestExtractHeldQtyFromBalance:
|
||||||
|
"""Tests for _extract_held_qty_from_balance()."""
|
||||||
|
|
||||||
|
def _domestic_balance(self, stock_code: str, ord_psbl_qty: int) -> dict:
|
||||||
|
return {
|
||||||
|
"output1": [{"pdno": stock_code, "ord_psbl_qty": str(ord_psbl_qty)}],
|
||||||
|
"output2": [{"dnca_tot_amt": "1000000"}],
|
||||||
|
}
|
||||||
|
|
||||||
|
def test_domestic_returns_ord_psbl_qty(self) -> None:
|
||||||
|
balance = self._domestic_balance("005930", 7)
|
||||||
|
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 7
|
||||||
|
|
||||||
|
def test_domestic_fallback_to_hldg_qty(self) -> None:
|
||||||
|
balance = {"output1": [{"pdno": "005930", "hldg_qty": "3"}]}
|
||||||
|
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 3
|
||||||
|
|
||||||
|
def test_domestic_returns_zero_when_not_found(self) -> None:
|
||||||
|
balance = self._domestic_balance("005930", 5)
|
||||||
|
assert _extract_held_qty_from_balance(balance, "000660", is_domestic=True) == 0
|
||||||
|
|
||||||
|
def test_domestic_returns_zero_when_output1_empty(self) -> None:
|
||||||
|
balance = {"output1": [], "output2": [{}]}
|
||||||
|
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 0
|
||||||
|
|
||||||
|
def test_overseas_returns_ovrs_cblc_qty(self) -> None:
|
||||||
|
balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "10"}]}
|
||||||
|
assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 10
|
||||||
|
|
||||||
|
def test_overseas_fallback_to_hldg_qty(self) -> None:
|
||||||
|
balance = {"output1": [{"ovrs_pdno": "AAPL", "hldg_qty": "4"}]}
|
||||||
|
assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 4
|
||||||
|
|
||||||
|
def test_case_insensitive_match(self) -> None:
|
||||||
|
balance = {"output1": [{"pdno": "005930", "ord_psbl_qty": "2"}]}
|
||||||
|
assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 2
|
||||||
|
|
||||||
|
|
||||||
|
class TestExtractHeldCodesFromBalance:
|
||||||
|
"""Tests for _extract_held_codes_from_balance()."""
|
||||||
|
|
||||||
|
def test_returns_codes_with_positive_qty(self) -> None:
|
||||||
|
balance = {
|
||||||
|
"output1": [
|
||||||
|
{"pdno": "005930", "ord_psbl_qty": "5"},
|
||||||
|
{"pdno": "000660", "ord_psbl_qty": "3"},
|
||||||
|
]
|
||||||
|
}
|
||||||
|
result = _extract_held_codes_from_balance(balance, is_domestic=True)
|
||||||
|
assert set(result) == {"005930", "000660"}
|
||||||
|
|
||||||
|
def test_excludes_zero_qty_holdings(self) -> None:
|
||||||
|
balance = {
|
||||||
|
"output1": [
|
||||||
|
{"pdno": "005930", "ord_psbl_qty": "0"},
|
||||||
|
{"pdno": "000660", "ord_psbl_qty": "2"},
|
||||||
|
]
|
||||||
|
}
|
||||||
|
result = _extract_held_codes_from_balance(balance, is_domestic=True)
|
||||||
|
assert "005930" not in result
|
||||||
|
assert "000660" in result
|
||||||
|
|
||||||
|
def test_returns_empty_when_output1_missing(self) -> None:
|
||||||
|
balance: dict = {}
|
||||||
|
assert _extract_held_codes_from_balance(balance, is_domestic=True) == []
|
||||||
|
|
||||||
|
def test_overseas_uses_ovrs_pdno(self) -> None:
|
||||||
|
balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "3"}]}
|
||||||
|
result = _extract_held_codes_from_balance(balance, is_domestic=False)
|
||||||
|
assert result == ["AAPL"]
|
||||||
|
|
||||||
|
|
||||||
|
class TestDetermineOrderQuantity:
|
||||||
|
"""Test _determine_order_quantity() — SELL uses broker_held_qty."""
|
||||||
|
|
||||||
|
def test_sell_returns_broker_held_qty(self) -> None:
|
||||||
|
result = _determine_order_quantity(
|
||||||
|
action="SELL",
|
||||||
|
current_price=105.0,
|
||||||
|
total_cash=50000.0,
|
||||||
|
candidate=None,
|
||||||
|
settings=None,
|
||||||
|
broker_held_qty=7,
|
||||||
|
)
|
||||||
|
assert result == 7
|
||||||
|
|
||||||
|
def test_sell_returns_zero_when_broker_qty_zero(self) -> None:
|
||||||
|
result = _determine_order_quantity(
|
||||||
|
action="SELL",
|
||||||
|
current_price=105.0,
|
||||||
|
total_cash=50000.0,
|
||||||
|
candidate=None,
|
||||||
|
settings=None,
|
||||||
|
broker_held_qty=0,
|
||||||
|
)
|
||||||
|
assert result == 0
|
||||||
|
|
||||||
|
def test_buy_without_position_sizing_returns_one(self) -> None:
|
||||||
|
result = _determine_order_quantity(
|
||||||
|
action="BUY",
|
||||||
|
current_price=50000.0,
|
||||||
|
total_cash=1000000.0,
|
||||||
|
candidate=None,
|
||||||
|
settings=None,
|
||||||
|
)
|
||||||
|
assert result == 1
|
||||||
|
|
||||||
|
def test_buy_with_zero_cash_returns_zero(self) -> None:
|
||||||
|
result = _determine_order_quantity(
|
||||||
|
action="BUY",
|
||||||
|
current_price=50000.0,
|
||||||
|
total_cash=0.0,
|
||||||
|
candidate=None,
|
||||||
|
settings=None,
|
||||||
|
)
|
||||||
|
assert result == 0
|
||||||
|
|
||||||
|
def test_buy_with_position_sizing_calculates_correctly(self) -> None:
|
||||||
|
settings = MagicMock(spec=Settings)
|
||||||
|
settings.POSITION_SIZING_ENABLED = True
|
||||||
|
settings.POSITION_VOLATILITY_TARGET_SCORE = 50.0
|
||||||
|
settings.POSITION_BASE_ALLOCATION_PCT = 10.0
|
||||||
|
settings.POSITION_MAX_ALLOCATION_PCT = 30.0
|
||||||
|
settings.POSITION_MIN_ALLOCATION_PCT = 1.0
|
||||||
|
# 1,000,000 * 10% = 100,000 budget // 50,000 price = 2 shares
|
||||||
|
result = _determine_order_quantity(
|
||||||
|
action="BUY",
|
||||||
|
current_price=50000.0,
|
||||||
|
total_cash=1000000.0,
|
||||||
|
candidate=None,
|
||||||
|
settings=settings,
|
||||||
|
)
|
||||||
|
assert result == 2
|
||||||
|
|
||||||
|
|
||||||
class TestSafeFloat:
|
class TestSafeFloat:
|
||||||
"""Test safe_float() helper function."""
|
"""Test safe_float() helper function."""
|
||||||
|
|
||||||
@@ -1240,13 +1378,14 @@ async def test_sell_updates_original_buy_decision_outcome() -> None:
|
|||||||
broker.get_current_price = AsyncMock(return_value=(120.0, 0.0, 0.0))
|
broker.get_current_price = AsyncMock(return_value=(120.0, 0.0, 0.0))
|
||||||
broker.get_balance = AsyncMock(
|
broker.get_balance = AsyncMock(
|
||||||
return_value={
|
return_value={
|
||||||
|
"output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
|
||||||
"output2": [
|
"output2": [
|
||||||
{
|
{
|
||||||
"tot_evlu_amt": "100000",
|
"tot_evlu_amt": "100000",
|
||||||
"dnca_tot_amt": "10000",
|
"dnca_tot_amt": "10000",
|
||||||
"pchs_amt_smtl_amt": "90000",
|
"pchs_amt_smtl_amt": "90000",
|
||||||
}
|
}
|
||||||
]
|
],
|
||||||
}
|
}
|
||||||
)
|
)
|
||||||
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
|
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
|
||||||
@@ -1330,13 +1469,14 @@ async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
|
|||||||
broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
|
broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
|
||||||
broker.get_balance = AsyncMock(
|
broker.get_balance = AsyncMock(
|
||||||
return_value={
|
return_value={
|
||||||
|
"output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
|
||||||
"output2": [
|
"output2": [
|
||||||
{
|
{
|
||||||
"tot_evlu_amt": "100000",
|
"tot_evlu_amt": "100000",
|
||||||
"dnca_tot_amt": "10000",
|
"dnca_tot_amt": "10000",
|
||||||
"pchs_amt_smtl_amt": "90000",
|
"pchs_amt_smtl_amt": "90000",
|
||||||
}
|
}
|
||||||
]
|
],
|
||||||
}
|
}
|
||||||
)
|
)
|
||||||
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
|
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
|
||||||
@@ -1396,6 +1536,318 @@ async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
|
|||||||
assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
|
assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.mark.asyncio
|
||||||
|
async def test_hold_overridden_to_sell_when_take_profit_triggered() -> None:
|
||||||
|
"""HOLD decision should be overridden to SELL when take-profit threshold is reached."""
|
||||||
|
db_conn = init_db(":memory:")
|
||||||
|
decision_logger = DecisionLogger(db_conn)
|
||||||
|
|
||||||
|
buy_decision_id = decision_logger.log_decision(
|
||||||
|
stock_code="005930",
|
||||||
|
market="KR",
|
||||||
|
exchange_code="KRX",
|
||||||
|
action="BUY",
|
||||||
|
confidence=90,
|
||||||
|
rationale="entry",
|
||||||
|
context_snapshot={},
|
||||||
|
input_data={},
|
||||||
|
)
|
||||||
|
log_trade(
|
||||||
|
conn=db_conn,
|
||||||
|
stock_code="005930",
|
||||||
|
action="BUY",
|
||||||
|
confidence=90,
|
||||||
|
rationale="entry",
|
||||||
|
quantity=1,
|
||||||
|
price=100.0,
|
||||||
|
market="KR",
|
||||||
|
exchange_code="KRX",
|
||||||
|
decision_id=buy_decision_id,
|
||||||
|
)
|
||||||
|
|
||||||
|
broker = MagicMock()
|
||||||
|
# Current price 106.0 → +6% gain, above take_profit_pct=3.0
|
||||||
|
broker.get_current_price = AsyncMock(return_value=(106.0, 6.0, 0.0))
|
||||||
|
broker.get_balance = AsyncMock(
|
||||||
|
return_value={
|
||||||
|
"output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
|
||||||
|
"output2": [
|
||||||
|
{
|
||||||
|
"tot_evlu_amt": "100000",
|
||||||
|
"dnca_tot_amt": "10000",
|
||||||
|
"pchs_amt_smtl_amt": "90000",
|
||||||
|
}
|
||||||
|
],
|
||||||
|
}
|
||||||
|
)
|
||||||
|
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
|
||||||
|
|
||||||
|
scenario = StockScenario(
|
||||||
|
condition=StockCondition(rsi_below=30),
|
||||||
|
action=ScenarioAction.BUY,
|
||||||
|
confidence=88,
|
||||||
|
stop_loss_pct=-2.0,
|
||||||
|
take_profit_pct=3.0,
|
||||||
|
rationale="take profit policy",
|
||||||
|
)
|
||||||
|
playbook = DayPlaybook(
|
||||||
|
date=date(2026, 2, 8),
|
||||||
|
market="KR",
|
||||||
|
stock_playbooks=[
|
||||||
|
{"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
|
||||||
|
],
|
||||||
|
)
|
||||||
|
engine = MagicMock(spec=ScenarioEngine)
|
||||||
|
engine.evaluate = MagicMock(return_value=_make_hold_match())
|
||||||
|
|
||||||
|
market = MagicMock()
|
||||||
|
market.name = "Korea"
|
||||||
|
market.code = "KR"
|
||||||
|
market.exchange_code = "KRX"
|
||||||
|
market.is_domestic = True
|
||||||
|
|
||||||
|
telegram = MagicMock()
|
||||||
|
telegram.notify_trade_execution = AsyncMock()
|
||||||
|
telegram.notify_fat_finger = AsyncMock()
|
||||||
|
telegram.notify_circuit_breaker = AsyncMock()
|
||||||
|
telegram.notify_scenario_matched = AsyncMock()
|
||||||
|
|
||||||
|
await trading_cycle(
|
||||||
|
broker=broker,
|
||||||
|
overseas_broker=MagicMock(),
|
||||||
|
scenario_engine=engine,
|
||||||
|
playbook=playbook,
|
||||||
|
risk=MagicMock(),
|
||||||
|
db_conn=db_conn,
|
||||||
|
decision_logger=decision_logger,
|
||||||
|
context_store=MagicMock(
|
||||||
|
get_latest_timeframe=MagicMock(return_value=None),
|
||||||
|
set_context=MagicMock(),
|
||||||
|
),
|
||||||
|
criticality_assessor=MagicMock(
|
||||||
|
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
|
||||||
|
get_timeout=MagicMock(return_value=5.0),
|
||||||
|
),
|
||||||
|
telegram=telegram,
|
||||||
|
market=market,
|
||||||
|
stock_code="005930",
|
||||||
|
scan_candidates={},
|
||||||
|
)
|
||||||
|
|
||||||
|
broker.send_order.assert_called_once()
|
||||||
|
assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.mark.asyncio
|
||||||
|
async def test_hold_not_overridden_when_between_stop_loss_and_take_profit() -> None:
|
||||||
|
"""HOLD should remain HOLD when P&L is within stop-loss and take-profit bounds."""
|
||||||
|
db_conn = init_db(":memory:")
|
||||||
|
decision_logger = DecisionLogger(db_conn)
|
||||||
|
|
||||||
|
buy_decision_id = decision_logger.log_decision(
|
||||||
|
stock_code="005930",
|
||||||
|
market="KR",
|
||||||
|
exchange_code="KRX",
|
||||||
|
action="BUY",
|
||||||
|
confidence=90,
|
||||||
|
rationale="entry",
|
||||||
|
context_snapshot={},
|
||||||
|
input_data={},
|
||||||
|
)
|
||||||
|
log_trade(
|
||||||
|
conn=db_conn,
|
||||||
|
stock_code="005930",
|
||||||
|
action="BUY",
|
||||||
|
confidence=90,
|
||||||
|
rationale="entry",
|
||||||
|
quantity=1,
|
||||||
|
price=100.0,
|
||||||
|
market="KR",
|
||||||
|
exchange_code="KRX",
|
||||||
|
decision_id=buy_decision_id,
|
||||||
|
)
|
||||||
|
|
||||||
|
broker = MagicMock()
|
||||||
|
# Current price 101.0 → +1% gain, within [-2%, +3%] range
|
||||||
|
broker.get_current_price = AsyncMock(return_value=(101.0, 1.0, 0.0))
|
||||||
|
broker.get_balance = AsyncMock(
|
||||||
|
return_value={
|
||||||
|
"output2": [
|
||||||
|
{
|
||||||
|
"tot_evlu_amt": "100000",
|
||||||
|
"dnca_tot_amt": "10000",
|
||||||
|
"pchs_amt_smtl_amt": "90000",
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
)
|
||||||
|
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
|
||||||
|
|
||||||
|
scenario = StockScenario(
|
||||||
|
condition=StockCondition(rsi_below=30),
|
||||||
|
action=ScenarioAction.BUY,
|
||||||
|
confidence=88,
|
||||||
|
stop_loss_pct=-2.0,
|
||||||
|
take_profit_pct=3.0,
|
||||||
|
rationale="within range policy",
|
||||||
|
)
|
||||||
|
playbook = DayPlaybook(
|
||||||
|
date=date(2026, 2, 8),
|
||||||
|
market="KR",
|
||||||
|
stock_playbooks=[
|
||||||
|
{"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
|
||||||
|
],
|
||||||
|
)
|
||||||
|
engine = MagicMock(spec=ScenarioEngine)
|
||||||
|
engine.evaluate = MagicMock(return_value=_make_hold_match())
|
||||||
|
|
||||||
|
market = MagicMock()
|
||||||
|
market.name = "Korea"
|
||||||
|
market.code = "KR"
|
||||||
|
market.exchange_code = "KRX"
|
||||||
|
market.is_domestic = True
|
||||||
|
|
||||||
|
telegram = MagicMock()
|
||||||
|
telegram.notify_trade_execution = AsyncMock()
|
||||||
|
telegram.notify_fat_finger = AsyncMock()
|
||||||
|
telegram.notify_circuit_breaker = AsyncMock()
|
||||||
|
telegram.notify_scenario_matched = AsyncMock()
|
||||||
|
|
||||||
|
await trading_cycle(
|
||||||
|
broker=broker,
|
||||||
|
overseas_broker=MagicMock(),
|
||||||
|
scenario_engine=engine,
|
||||||
|
playbook=playbook,
|
||||||
|
risk=MagicMock(),
|
||||||
|
db_conn=db_conn,
|
||||||
|
decision_logger=decision_logger,
|
||||||
|
context_store=MagicMock(
|
||||||
|
get_latest_timeframe=MagicMock(return_value=None),
|
||||||
|
set_context=MagicMock(),
|
||||||
|
),
|
||||||
|
criticality_assessor=MagicMock(
|
||||||
|
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
|
||||||
|
get_timeout=MagicMock(return_value=5.0),
|
||||||
|
),
|
||||||
|
telegram=telegram,
|
||||||
|
market=market,
|
||||||
|
stock_code="005930",
|
||||||
|
scan_candidates={},
|
||||||
|
)
|
||||||
|
|
||||||
|
broker.send_order.assert_not_called()
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.mark.asyncio
|
||||||
|
async def test_sell_order_uses_broker_balance_qty_not_db() -> None:
|
||||||
|
"""SELL quantity must come from broker balance output1, not DB.
|
||||||
|
|
||||||
|
The DB records order quantity which may differ from actual fill quantity.
|
||||||
|
This test verifies that we use the broker-confirmed orderable quantity.
|
||||||
|
"""
|
||||||
|
db_conn = init_db(":memory:")
|
||||||
|
decision_logger = DecisionLogger(db_conn)
|
||||||
|
|
||||||
|
buy_decision_id = decision_logger.log_decision(
|
||||||
|
stock_code="005930",
|
||||||
|
market="KR",
|
||||||
|
exchange_code="KRX",
|
||||||
|
action="BUY",
|
||||||
|
confidence=90,
|
||||||
|
rationale="entry",
|
||||||
|
context_snapshot={},
|
||||||
|
input_data={},
|
||||||
|
)
|
||||||
|
# DB records 10 shares ordered — but only 5 actually filled (partial fill scenario)
|
||||||
|
log_trade(
|
||||||
|
conn=db_conn,
|
||||||
|
stock_code="005930",
|
||||||
|
action="BUY",
|
||||||
|
confidence=90,
|
||||||
|
rationale="entry",
|
||||||
|
quantity=10, # ordered quantity (may differ from fill)
|
||||||
|
price=100.0,
|
||||||
|
market="KR",
|
||||||
|
exchange_code="KRX",
|
||||||
|
decision_id=buy_decision_id,
|
||||||
|
)
|
||||||
|
|
||||||
|
broker = MagicMock()
|
||||||
|
# Stop-loss triggers (price dropped below -2%)
|
||||||
|
broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
|
||||||
|
broker.get_balance = AsyncMock(
|
||||||
|
return_value={
|
||||||
|
# Broker confirms only 5 shares are actually orderable (partial fill)
|
||||||
|
"output1": [{"pdno": "005930", "ord_psbl_qty": "5"}],
|
||||||
|
"output2": [
|
||||||
|
{
|
||||||
|
"tot_evlu_amt": "100000",
|
||||||
|
"dnca_tot_amt": "10000",
|
||||||
|
"pchs_amt_smtl_amt": "90000",
|
||||||
|
}
|
||||||
|
],
|
||||||
|
}
|
||||||
|
)
|
||||||
|
broker.send_order = AsyncMock(return_value={"msg1": "OK"})
|
||||||
|
|
||||||
|
scenario = StockScenario(
|
||||||
|
condition=StockCondition(rsi_below=30),
|
||||||
|
action=ScenarioAction.BUY,
|
||||||
|
confidence=88,
|
||||||
|
stop_loss_pct=-2.0,
|
||||||
|
rationale="stop loss policy",
|
||||||
|
)
|
||||||
|
playbook = DayPlaybook(
|
||||||
|
date=date(2026, 2, 8),
|
||||||
|
market="KR",
|
||||||
|
stock_playbooks=[
|
||||||
|
{"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
|
||||||
|
],
|
||||||
|
)
|
||||||
|
engine = MagicMock(spec=ScenarioEngine)
|
||||||
|
engine.evaluate = MagicMock(return_value=_make_hold_match())
|
||||||
|
|
||||||
|
market = MagicMock()
|
||||||
|
market.name = "Korea"
|
||||||
|
market.code = "KR"
|
||||||
|
market.exchange_code = "KRX"
|
||||||
|
market.is_domestic = True
|
||||||
|
|
||||||
|
telegram = MagicMock()
|
||||||
|
telegram.notify_trade_execution = AsyncMock()
|
||||||
|
telegram.notify_fat_finger = AsyncMock()
|
||||||
|
telegram.notify_circuit_breaker = AsyncMock()
|
||||||
|
telegram.notify_scenario_matched = AsyncMock()
|
||||||
|
|
||||||
|
await trading_cycle(
|
||||||
|
broker=broker,
|
||||||
|
overseas_broker=MagicMock(),
|
||||||
|
scenario_engine=engine,
|
||||||
|
playbook=playbook,
|
||||||
|
risk=MagicMock(),
|
||||||
|
db_conn=db_conn,
|
||||||
|
decision_logger=decision_logger,
|
||||||
|
context_store=MagicMock(
|
||||||
|
get_latest_timeframe=MagicMock(return_value=None),
|
||||||
|
set_context=MagicMock(),
|
||||||
|
),
|
||||||
|
criticality_assessor=MagicMock(
|
||||||
|
assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
|
||||||
|
get_timeout=MagicMock(return_value=5.0),
|
||||||
|
),
|
||||||
|
telegram=telegram,
|
||||||
|
market=market,
|
||||||
|
stock_code="005930",
|
||||||
|
scan_candidates={},
|
||||||
|
)
|
||||||
|
|
||||||
|
broker.send_order.assert_called_once()
|
||||||
|
call_kwargs = broker.send_order.call_args.kwargs
|
||||||
|
assert call_kwargs["order_type"] == "SELL"
|
||||||
|
# Must use broker-confirmed qty (5), NOT DB-recorded ordered qty (10)
|
||||||
|
assert call_kwargs["quantity"] == 5
|
||||||
|
|
||||||
|
|
||||||
@pytest.mark.asyncio
|
@pytest.mark.asyncio
|
||||||
async def test_handle_market_close_runs_daily_review_flow() -> None:
|
async def test_handle_market_close_runs_daily_review_flow() -> None:
|
||||||
"""Market close should aggregate, create scorecard, lessons, and notify."""
|
"""Market close should aggregate, create scorecard, lessons, and notify."""
|
||||||
|
|||||||
@@ -830,3 +830,171 @@ class TestSmartFallbackPlaybook:
|
|||||||
]
|
]
|
||||||
assert len(buy_scenarios) == 1
|
assert len(buy_scenarios) == 1
|
||||||
assert buy_scenarios[0].condition.volume_ratio_above == 2.0 # VOL_MULTIPLIER default
|
assert buy_scenarios[0].condition.volume_ratio_above == 2.0 # VOL_MULTIPLIER default
|
||||||
|
|
||||||
|
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
# Holdings in prompt (#170)
|
||||||
|
# ---------------------------------------------------------------------------
|
||||||
|
|
||||||
|
|
||||||
|
class TestHoldingsInPrompt:
|
||||||
|
"""Tests for current_holdings parameter in generate_playbook / _build_prompt."""
|
||||||
|
|
||||||
|
def _make_holdings(self) -> list[dict]:
|
||||||
|
return [
|
||||||
|
{
|
||||||
|
"stock_code": "005930",
|
||||||
|
"name": "Samsung",
|
||||||
|
"qty": 10,
|
||||||
|
"entry_price": 71000.0,
|
||||||
|
"unrealized_pnl_pct": 2.3,
|
||||||
|
"holding_days": 3,
|
||||||
|
}
|
||||||
|
]
|
||||||
|
|
||||||
|
def test_build_prompt_includes_holdings_section(self) -> None:
|
||||||
|
"""Prompt should contain a Current Holdings section when holdings are given."""
|
||||||
|
planner = _make_planner()
|
||||||
|
candidates = [_candidate()]
|
||||||
|
holdings = self._make_holdings()
|
||||||
|
|
||||||
|
prompt = planner._build_prompt(
|
||||||
|
"KR",
|
||||||
|
candidates,
|
||||||
|
context_data={},
|
||||||
|
self_market_scorecard=None,
|
||||||
|
cross_market=None,
|
||||||
|
current_holdings=holdings,
|
||||||
|
)
|
||||||
|
|
||||||
|
assert "## Current Holdings" in prompt
|
||||||
|
assert "005930" in prompt
|
||||||
|
assert "+2.30%" in prompt
|
||||||
|
assert "보유 3일" in prompt
|
||||||
|
|
||||||
|
def test_build_prompt_no_holdings_omits_section(self) -> None:
|
||||||
|
"""Prompt should NOT contain a Current Holdings section when holdings=None."""
|
||||||
|
planner = _make_planner()
|
||||||
|
candidates = [_candidate()]
|
||||||
|
|
||||||
|
prompt = planner._build_prompt(
|
||||||
|
"KR",
|
||||||
|
candidates,
|
||||||
|
context_data={},
|
||||||
|
self_market_scorecard=None,
|
||||||
|
cross_market=None,
|
||||||
|
current_holdings=None,
|
||||||
|
)
|
||||||
|
|
||||||
|
assert "## Current Holdings" not in prompt
|
||||||
|
|
||||||
|
def test_build_prompt_empty_holdings_omits_section(self) -> None:
|
||||||
|
"""Empty list should also omit the holdings section."""
|
||||||
|
planner = _make_planner()
|
||||||
|
candidates = [_candidate()]
|
||||||
|
|
||||||
|
prompt = planner._build_prompt(
|
||||||
|
"KR",
|
||||||
|
candidates,
|
||||||
|
context_data={},
|
||||||
|
self_market_scorecard=None,
|
||||||
|
cross_market=None,
|
||||||
|
current_holdings=[],
|
||||||
|
)
|
||||||
|
|
||||||
|
assert "## Current Holdings" not in prompt
|
||||||
|
|
||||||
|
def test_build_prompt_holdings_instruction_included(self) -> None:
|
||||||
|
"""Prompt should include instruction to generate scenarios for held stocks."""
|
||||||
|
planner = _make_planner()
|
||||||
|
candidates = [_candidate()]
|
||||||
|
holdings = self._make_holdings()
|
||||||
|
|
||||||
|
prompt = planner._build_prompt(
|
||||||
|
"KR",
|
||||||
|
candidates,
|
||||||
|
context_data={},
|
||||||
|
self_market_scorecard=None,
|
||||||
|
cross_market=None,
|
||||||
|
current_holdings=holdings,
|
||||||
|
)
|
||||||
|
|
||||||
|
assert "005930" in prompt
|
||||||
|
assert "SELL/HOLD" in prompt
|
||||||
|
|
||||||
|
@pytest.mark.asyncio
|
||||||
|
async def test_generate_playbook_passes_holdings_to_prompt(self) -> None:
|
||||||
|
"""generate_playbook should pass current_holdings through to the prompt."""
|
||||||
|
planner = _make_planner()
|
||||||
|
candidates = [_candidate()]
|
||||||
|
holdings = self._make_holdings()
|
||||||
|
|
||||||
|
# Capture the actual prompt sent to Gemini
|
||||||
|
captured_prompts: list[str] = []
|
||||||
|
original_decide = planner._gemini.decide
|
||||||
|
|
||||||
|
async def capture_and_call(data: dict) -> TradeDecision:
|
||||||
|
captured_prompts.append(data.get("prompt_override", ""))
|
||||||
|
return await original_decide(data)
|
||||||
|
|
||||||
|
planner._gemini.decide = capture_and_call # type: ignore[method-assign]
|
||||||
|
|
||||||
|
await planner.generate_playbook(
|
||||||
|
"KR", candidates, today=date(2026, 2, 8), current_holdings=holdings
|
||||||
|
)
|
||||||
|
|
||||||
|
assert len(captured_prompts) == 1
|
||||||
|
assert "## Current Holdings" in captured_prompts[0]
|
||||||
|
assert "005930" in captured_prompts[0]
|
||||||
|
|
||||||
|
@pytest.mark.asyncio
|
||||||
|
async def test_holdings_stock_allowed_in_parse_response(self) -> None:
|
||||||
|
"""Holdings stocks not in candidates list should be accepted in the response."""
|
||||||
|
holding_code = "000660" # Not in candidates
|
||||||
|
stocks = [
|
||||||
|
{
|
||||||
|
"stock_code": "005930", # candidate
|
||||||
|
"scenarios": [
|
||||||
|
{
|
||||||
|
"condition": {"rsi_below": 30},
|
||||||
|
"action": "BUY",
|
||||||
|
"confidence": 85,
|
||||||
|
"rationale": "oversold",
|
||||||
|
}
|
||||||
|
],
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"stock_code": holding_code, # holding only
|
||||||
|
"scenarios": [
|
||||||
|
{
|
||||||
|
"condition": {"price_change_pct_below": -2.0},
|
||||||
|
"action": "SELL",
|
||||||
|
"confidence": 90,
|
||||||
|
"rationale": "stop-loss",
|
||||||
|
}
|
||||||
|
],
|
||||||
|
},
|
||||||
|
]
|
||||||
|
planner = _make_planner(gemini_response=_gemini_response_json(stocks=stocks))
|
||||||
|
candidates = [_candidate()] # only 005930
|
||||||
|
holdings = [
|
||||||
|
{
|
||||||
|
"stock_code": holding_code,
|
||||||
|
"name": "SK Hynix",
|
||||||
|
"qty": 5,
|
||||||
|
"entry_price": 180000.0,
|
||||||
|
"unrealized_pnl_pct": -1.5,
|
||||||
|
"holding_days": 7,
|
||||||
|
}
|
||||||
|
]
|
||||||
|
|
||||||
|
pb = await planner.generate_playbook(
|
||||||
|
"KR",
|
||||||
|
candidates,
|
||||||
|
today=date(2026, 2, 8),
|
||||||
|
current_holdings=holdings,
|
||||||
|
)
|
||||||
|
|
||||||
|
codes = [sp.stock_code for sp in pb.stock_playbooks]
|
||||||
|
assert "005930" in codes
|
||||||
|
assert holding_code in codes
|
||||||
|
|||||||
Reference in New Issue
Block a user