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Author SHA1 Message Date
agentson
60a22d6cd4 feat: add position-aware conditions to StockCondition (#171)
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- Add unrealized_pnl_pct_above/below and holding_days_above/below fields
  to StockCondition so AI can generate rules like 'P&L > 3% → SELL'
- Evaluate new fields in ScenarioEngine.evaluate_condition() with same
  AND-combining logic as existing technical indicator fields
- Include position fields in _build_match_details() for audit logging
- Parse new fields from AI JSON response in PreMarketPlanner._parse_scenario()
- Update prompt schema example to show new position-aware condition fields
- Add 13 tests covering all new condition combinations and edge cases

Closes #171

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-20 08:27:44 +09:00
03f8d220a4 Merge pull request 'fix: use broker balance API as source of truth for SELL qty and holdings (#164 #165)' (#169) from feature/issue-164-165-broker-api-holdings into main
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Reviewed-on: #169
2026-02-20 07:52:26 +09:00
agentson
305120f599 fix: use broker balance API as source of truth for SELL qty and holdings (#164 #165)
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DB의 주문 수량 기록은 실제 체결 수량과 다를 수 있음(부분 체결, 외부 수동 거래).
브로커 잔고 API(output1)를 source of truth로 사용하도록 수정.

## 변경 사항

### SELL 수량 (#164)
- _extract_held_qty_from_balance() 추가
  - 국내: output1의 ord_psbl_qty (→ hldg_qty fallback)
  - 해외: output1의 ovrs_cblc_qty (→ hldg_qty fallback)
- _determine_order_quantity()에 broker_held_qty 파라미터 추가
  - SELL 시 broker_held_qty 반환 (0이면 주문 스킵)
- trading_cycle / run_daily_session 양쪽 호출 지점 수정
  - 이미 fetch된 balance_data에서 수량 추출 (추가 API 호출 없음)

### 보유 종목 루프 (#165)
- _extract_held_codes_from_balance() 추가
  - ord_psbl_qty > 0인 종목 코드 목록 반환
- 실시간 루프에서 스캔 시점에 get_balance() 호출해 보유 종목 병합
  - 스캐너 후보 + 실제 보유 종목 union으로 trading_cycle 순회
  - 실패 시 경고 로그 후 스캐너 후보만으로 계속 진행

### 테스트
- TestExtractHeldQtyFromBalance: 7개 (국내/해외/fallback/미보유)
- TestExtractHeldCodesFromBalance: 4개 (qty>0 포함, qty=0 제외 등)
- TestDetermineOrderQuantity: 5개 (SELL qty, BUY sizing)
- test_sell_order_uses_broker_balance_qty_not_db:
  DB 10주 기록 vs 브로커 5주 확인 → 브로커 값(5) 사용 검증
- 기존 SELL/stop-loss/take-profit 테스트에 output1 mock 추가

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-20 07:40:45 +09:00
faa23b3f1b Merge pull request 'fix: enforce take_profit_pct in HOLD evaluation loop (#163)' (#166) from feature/issue-163-take-profit-enforcement into main
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Reviewed-on: #166
2026-02-20 07:24:14 +09:00
6 changed files with 574 additions and 8 deletions

View File

@@ -106,6 +106,82 @@ def _extract_symbol_from_holding(item: dict[str, Any]) -> str:
return ""
def _extract_held_codes_from_balance(
balance_data: dict[str, Any],
*,
is_domestic: bool,
) -> list[str]:
"""Return stock codes with a positive orderable quantity from a balance response.
Uses the broker's live output1 as the source of truth so that partial fills
and manual external trades are always reflected correctly.
"""
output1 = balance_data.get("output1", [])
if isinstance(output1, dict):
output1 = [output1]
if not isinstance(output1, list):
return []
codes: list[str] = []
for holding in output1:
if not isinstance(holding, dict):
continue
code_key = "pdno" if is_domestic else "ovrs_pdno"
code = str(holding.get(code_key, "")).strip().upper()
if not code:
continue
if is_domestic:
qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
else:
qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
if qty > 0:
codes.append(code)
return codes
def _extract_held_qty_from_balance(
balance_data: dict[str, Any],
stock_code: str,
*,
is_domestic: bool,
) -> int:
"""Extract the broker-confirmed orderable quantity for a stock.
Uses the broker's live balance response (output1) as the source of truth
rather than the local DB, because DB records reflect order quantity which
may differ from actual fill quantity due to partial fills.
Domestic fields (VTTC8434R output1):
pdno — 종목코드
ord_psbl_qty — 주문가능수량 (preferred: excludes unsettled)
hldg_qty — 보유수량 (fallback)
Overseas fields (output1):
ovrs_pdno — 종목코드
ovrs_cblc_qty — 해외잔고수량 (preferred)
hldg_qty — 보유수량 (fallback)
"""
output1 = balance_data.get("output1", [])
if isinstance(output1, dict):
output1 = [output1]
if not isinstance(output1, list):
return 0
for holding in output1:
if not isinstance(holding, dict):
continue
code_key = "pdno" if is_domestic else "ovrs_pdno"
held_code = str(holding.get(code_key, "")).strip().upper()
if held_code != stock_code.strip().upper():
continue
if is_domestic:
qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
else:
qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
return qty
return 0
def _determine_order_quantity(
*,
action: str,
@@ -113,10 +189,11 @@ def _determine_order_quantity(
total_cash: float,
candidate: ScanCandidate | None,
settings: Settings | None,
broker_held_qty: int = 0,
) -> int:
"""Determine order quantity using volatility-aware position sizing."""
if action != "BUY":
return 1
if action == "SELL":
return broker_held_qty
if current_price <= 0 or total_cash <= 0:
return 0
@@ -484,12 +561,20 @@ async def trading_cycle(
trade_price = current_price
trade_pnl = 0.0
if decision.action in ("BUY", "SELL"):
broker_held_qty = (
_extract_held_qty_from_balance(
balance_data, stock_code, is_domestic=market.is_domestic
)
if decision.action == "SELL"
else 0
)
quantity = _determine_order_quantity(
action=decision.action,
current_price=current_price,
total_cash=total_cash,
candidate=candidate,
settings=settings,
broker_held_qty=broker_held_qty,
)
if quantity <= 0:
logger.info(
@@ -909,12 +994,20 @@ async def run_daily_session(
trade_pnl = 0.0
order_succeeded = True
if decision.action in ("BUY", "SELL"):
daily_broker_held_qty = (
_extract_held_qty_from_balance(
balance_data, stock_code, is_domestic=market.is_domestic
)
if decision.action == "SELL"
else 0
)
quantity = _determine_order_quantity(
action=decision.action,
current_price=stock_data["current_price"],
total_cash=total_cash,
candidate=candidate_map.get(stock_code),
settings=settings,
broker_held_qty=daily_broker_held_qty,
)
if quantity <= 0:
logger.info(
@@ -1881,8 +1974,38 @@ async def run(settings: Settings) -> None:
except Exception as exc:
logger.error("Smart Scanner failed for %s: %s", market.name, exc)
# Get active stocks from scanner (dynamic, no static fallback)
stock_codes = active_stocks.get(market.code, [])
# Get active stocks from scanner (dynamic, no static fallback).
# Also include currently-held positions so stop-loss /
# take-profit can fire even when a holding drops off the
# scanner. Broker balance is the source of truth here —
# unlike the local DB it reflects actual fills and any
# manual trades done outside the bot.
scanner_codes = active_stocks.get(market.code, [])
try:
if market.is_domestic:
held_balance = await broker.get_balance()
else:
held_balance = await overseas_broker.get_overseas_balance(
market.exchange_code
)
held_codes = _extract_held_codes_from_balance(
held_balance, is_domestic=market.is_domestic
)
except Exception as exc:
logger.warning(
"Failed to fetch holdings for %s: %s — skipping holdings merge",
market.name, exc,
)
held_codes = []
stock_codes = list(dict.fromkeys(scanner_codes + held_codes))
extra_held = [c for c in held_codes if c not in set(scanner_codes)]
if extra_held:
logger.info(
"Holdings added to loop for %s (not in scanner): %s",
market.name, extra_held,
)
if not stock_codes:
logger.debug("No active stocks for market %s", market.code)
continue

View File

@@ -46,6 +46,18 @@ class StockCondition(BaseModel):
The ScenarioEngine evaluates all non-None fields as AND conditions.
A condition matches only if ALL specified fields are satisfied.
Technical indicator fields:
rsi_below / rsi_above — RSI threshold
volume_ratio_above / volume_ratio_below — volume vs previous day
price_above / price_below — absolute price level
price_change_pct_above / price_change_pct_below — intraday % change
Position-aware fields (require market_data enrichment from open position):
unrealized_pnl_pct_above — matches if unrealized P&L > threshold (e.g. 3.0 → +3%)
unrealized_pnl_pct_below — matches if unrealized P&L < threshold (e.g. -2.0 → -2%)
holding_days_above — matches if position held for more than N days
holding_days_below — matches if position held for fewer than N days
"""
rsi_below: float | None = None
@@ -56,6 +68,10 @@ class StockCondition(BaseModel):
price_below: float | None = None
price_change_pct_above: float | None = None
price_change_pct_below: float | None = None
unrealized_pnl_pct_above: float | None = None
unrealized_pnl_pct_below: float | None = None
holding_days_above: int | None = None
holding_days_below: int | None = None
def has_any_condition(self) -> bool:
"""Check if at least one condition field is set."""
@@ -70,6 +86,10 @@ class StockCondition(BaseModel):
self.price_below,
self.price_change_pct_above,
self.price_change_pct_below,
self.unrealized_pnl_pct_above,
self.unrealized_pnl_pct_below,
self.holding_days_above,
self.holding_days_below,
)
)

View File

@@ -294,7 +294,8 @@ class PreMarketPlanner:
f' "stock_code": "...",\n'
f' "scenarios": [\n'
f' {{\n'
f' "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0}},\n'
f' "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0,'
f' "unrealized_pnl_pct_above": 3.0, "holding_days_above": 5}},\n'
f' "action": "BUY|SELL|HOLD",\n'
f' "confidence": 85,\n'
f' "allocation_pct": 10.0,\n'
@@ -390,6 +391,10 @@ class PreMarketPlanner:
price_below=cond_data.get("price_below"),
price_change_pct_above=cond_data.get("price_change_pct_above"),
price_change_pct_below=cond_data.get("price_change_pct_below"),
unrealized_pnl_pct_above=cond_data.get("unrealized_pnl_pct_above"),
unrealized_pnl_pct_below=cond_data.get("unrealized_pnl_pct_below"),
holding_days_above=cond_data.get("holding_days_above"),
holding_days_below=cond_data.get("holding_days_below"),
)
if not condition.has_any_condition():

View File

@@ -206,6 +206,37 @@ class ScenarioEngine:
if condition.price_change_pct_below is not None:
checks.append(price_change_pct is not None and price_change_pct < condition.price_change_pct_below)
# Position-aware conditions
unrealized_pnl_pct = self._safe_float(market_data.get("unrealized_pnl_pct"))
if condition.unrealized_pnl_pct_above is not None or condition.unrealized_pnl_pct_below is not None:
if "unrealized_pnl_pct" not in market_data:
self._warn_missing_key("unrealized_pnl_pct")
if condition.unrealized_pnl_pct_above is not None:
checks.append(
unrealized_pnl_pct is not None
and unrealized_pnl_pct > condition.unrealized_pnl_pct_above
)
if condition.unrealized_pnl_pct_below is not None:
checks.append(
unrealized_pnl_pct is not None
and unrealized_pnl_pct < condition.unrealized_pnl_pct_below
)
holding_days = self._safe_float(market_data.get("holding_days"))
if condition.holding_days_above is not None or condition.holding_days_below is not None:
if "holding_days" not in market_data:
self._warn_missing_key("holding_days")
if condition.holding_days_above is not None:
checks.append(
holding_days is not None
and holding_days > condition.holding_days_above
)
if condition.holding_days_below is not None:
checks.append(
holding_days is not None
and holding_days < condition.holding_days_below
)
return len(checks) > 0 and all(checks)
def _evaluate_global_condition(
@@ -266,5 +297,9 @@ class ScenarioEngine:
details["current_price"] = self._safe_float(market_data.get("current_price"))
if condition.price_change_pct_above is not None or condition.price_change_pct_below is not None:
details["price_change_pct"] = self._safe_float(market_data.get("price_change_pct"))
if condition.unrealized_pnl_pct_above is not None or condition.unrealized_pnl_pct_below is not None:
details["unrealized_pnl_pct"] = self._safe_float(market_data.get("unrealized_pnl_pct"))
if condition.holding_days_above is not None or condition.holding_days_below is not None:
details["holding_days"] = self._safe_float(market_data.get("holding_days"))
return details

View File

@@ -14,6 +14,9 @@ from src.evolution.scorecard import DailyScorecard
from src.logging.decision_logger import DecisionLogger
from src.main import (
_apply_dashboard_flag,
_determine_order_quantity,
_extract_held_codes_from_balance,
_extract_held_qty_from_balance,
_handle_market_close,
_run_context_scheduler,
_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:
"""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_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"})
@@ -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_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"})
@@ -1430,13 +1570,14 @@ async def test_hold_overridden_to_sell_when_take_profit_triggered() -> None:
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"})
@@ -1597,6 +1738,116 @@ async def test_hold_not_overridden_when_between_stop_loss_and_take_profit() -> N
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
async def test_handle_market_close_runs_daily_review_flow() -> None:
"""Market close should aggregate, create scorecard, lessons, and notify."""

View File

@@ -440,3 +440,135 @@ class TestEvaluate:
assert result.action == ScenarioAction.BUY
assert result.match_details["rsi"] == 25.0
assert isinstance(result.match_details["rsi"], float)
# ---------------------------------------------------------------------------
# Position-aware condition tests (#171)
# ---------------------------------------------------------------------------
class TestPositionAwareConditions:
"""Tests for unrealized_pnl_pct and holding_days condition fields."""
def test_evaluate_condition_unrealized_pnl_above_matches(
self, engine: ScenarioEngine
) -> None:
"""unrealized_pnl_pct_above should match when P&L exceeds threshold."""
condition = StockCondition(unrealized_pnl_pct_above=3.0)
assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": 5.0}) is True
def test_evaluate_condition_unrealized_pnl_above_no_match(
self, engine: ScenarioEngine
) -> None:
"""unrealized_pnl_pct_above should NOT match when P&L is below threshold."""
condition = StockCondition(unrealized_pnl_pct_above=3.0)
assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": 2.0}) is False
def test_evaluate_condition_unrealized_pnl_below_matches(
self, engine: ScenarioEngine
) -> None:
"""unrealized_pnl_pct_below should match when P&L is under threshold."""
condition = StockCondition(unrealized_pnl_pct_below=-2.0)
assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": -3.5}) is True
def test_evaluate_condition_unrealized_pnl_below_no_match(
self, engine: ScenarioEngine
) -> None:
"""unrealized_pnl_pct_below should NOT match when P&L is above threshold."""
condition = StockCondition(unrealized_pnl_pct_below=-2.0)
assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": -1.0}) is False
def test_evaluate_condition_holding_days_above_matches(
self, engine: ScenarioEngine
) -> None:
"""holding_days_above should match when position held longer than threshold."""
condition = StockCondition(holding_days_above=5)
assert engine.evaluate_condition(condition, {"holding_days": 7}) is True
def test_evaluate_condition_holding_days_above_no_match(
self, engine: ScenarioEngine
) -> None:
"""holding_days_above should NOT match when position held shorter."""
condition = StockCondition(holding_days_above=5)
assert engine.evaluate_condition(condition, {"holding_days": 3}) is False
def test_evaluate_condition_holding_days_below_matches(
self, engine: ScenarioEngine
) -> None:
"""holding_days_below should match when position held fewer days."""
condition = StockCondition(holding_days_below=3)
assert engine.evaluate_condition(condition, {"holding_days": 1}) is True
def test_evaluate_condition_holding_days_below_no_match(
self, engine: ScenarioEngine
) -> None:
"""holding_days_below should NOT match when held more days."""
condition = StockCondition(holding_days_below=3)
assert engine.evaluate_condition(condition, {"holding_days": 5}) is False
def test_combined_pnl_and_holding_days(self, engine: ScenarioEngine) -> None:
"""Combined position-aware conditions should AND-evaluate correctly."""
condition = StockCondition(
unrealized_pnl_pct_above=3.0,
holding_days_above=5,
)
# Both met → match
assert engine.evaluate_condition(
condition,
{"unrealized_pnl_pct": 4.5, "holding_days": 7},
) is True
# Only pnl met → no match
assert engine.evaluate_condition(
condition,
{"unrealized_pnl_pct": 4.5, "holding_days": 3},
) is False
def test_missing_unrealized_pnl_does_not_match(
self, engine: ScenarioEngine
) -> None:
"""Missing unrealized_pnl_pct key should not match the condition."""
condition = StockCondition(unrealized_pnl_pct_above=3.0)
assert engine.evaluate_condition(condition, {}) is False
def test_missing_holding_days_does_not_match(
self, engine: ScenarioEngine
) -> None:
"""Missing holding_days key should not match the condition."""
condition = StockCondition(holding_days_above=5)
assert engine.evaluate_condition(condition, {}) is False
def test_match_details_includes_position_fields(
self, engine: ScenarioEngine
) -> None:
"""match_details should include position fields when condition specifies them."""
pb = _playbook(
scenarios=[
StockScenario(
condition=StockCondition(unrealized_pnl_pct_above=3.0),
action=ScenarioAction.SELL,
confidence=90,
rationale="Take profit",
)
]
)
result = engine.evaluate(
pb,
"005930",
{"unrealized_pnl_pct": 5.0},
{},
)
assert result.action == ScenarioAction.SELL
assert "unrealized_pnl_pct" in result.match_details
assert result.match_details["unrealized_pnl_pct"] == 5.0
def test_position_conditions_parse_from_planner(self) -> None:
"""StockCondition should accept and store new fields from JSON parsing."""
condition = StockCondition(
unrealized_pnl_pct_above=3.0,
unrealized_pnl_pct_below=None,
holding_days_above=5,
holding_days_below=None,
)
assert condition.unrealized_pnl_pct_above == 3.0
assert condition.holding_days_above == 5
assert condition.has_any_condition() is True