- 스윙 체결가 확인 전 executed_price NULL + fill_sweep, 진입가 resolve(ActiveTrade↔Portfolio), 0체결/부분체결 매수 장부 원복 - DT 고아 감지(근거 한정)·0체결 매도 복원·stale 점검 확대, 시간손절 -0.3% 원복 - 폴백 손절 ATR 캐시, 거래량부족-차단 신호 매수 차단, 현금 5% 유보 재적용, MDD peak/reset 수정 - KIS 서킷브레이커 청산 우회·경보, db_worker 재큐잉 순서, heartbeat·health-watch 사이드카 - 실시간 WS 재구독·41건 우선순위·다건 프레임 분할, 차트 샘플 제거·당일봉 합성, WS 서브프로토콜 인증 - 프론트: 미관리 그룹·확인 모달·차트 실시간 반영·예수금 표시 정정 - 전문가 에이전트 6종 추가(.claude/agents) - 유닛 스위트 2667 passed (소켓 차단 하), tsc OK Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Y83Za98XsNw9zuA4FTUytN
121 lines
3.6 KiB
Python
121 lines
3.6 KiB
Python
from types import SimpleNamespace as NS
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from app.services.ml_retrain_pipeline import _resolve_trade_price_v2
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def test_executed_price_preferred():
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assert _resolve_trade_price_v2(NS(executed_price=100, total_amount=1, executed_quantity=1, order_price=5)) == 100.0
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def test_null_falls_back_to_amount_over_qty():
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assert _resolve_trade_price_v2(NS(executed_price=None, total_amount=1000, executed_quantity=10, order_price=5)) == 100.0
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def test_null_falls_back_to_order_price():
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assert _resolve_trade_price_v2(NS(executed_price=None, total_amount=None, executed_quantity=None, order_price=55)) == 55.0
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def test_all_missing_zero():
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assert _resolve_trade_price_v2(NS(executed_price=None, total_amount=None, executed_quantity=None, order_price=None)) == 0.0
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# ─── 라운드4: 성능 저하 감시 / 장중 재학습 방지 ───────────────────────────
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import asyncio
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from datetime import datetime
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import pandas as pd
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import pytest
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from app.services import ml_retrain_pipeline as mrp
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def test_filled_statuses_include_completed():
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assert "COMPLETED" in mrp._FILLED_TRADE_STATUSES
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def test_load_trade_history_filters_completed(monkeypatch):
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captured = {}
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class _Res:
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def scalars(self):
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return self
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def all(self):
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return []
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class _Sess:
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async def __aenter__(self):
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return self
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async def __aexit__(self, *a):
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return False
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async def execute(self, stmt):
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captured["sql"] = str(stmt.compile(compile_kwargs={"literal_binds": True}))
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return _Res()
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monkeypatch.setattr(mrp, "AsyncSessionLocal", lambda: _Sess())
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asyncio.run(mrp._load_trade_history(months=1))
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assert "COMPLETED" in captured["sql"]
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@pytest.mark.parametrize(
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"dt,expected",
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[
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(datetime(2026, 10, 7, 9, 30), False), # 수 장중
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(datetime(2026, 10, 7, 15, 0), False),
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(datetime(2026, 10, 7, 20, 0), True), # 수 야간
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(datetime(2026, 10, 7, 3, 0), True),
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(datetime(2026, 10, 10, 11, 0), True), # 토
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],
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)
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def test_safe_window(dt, expected):
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assert mrp._is_retrain_safe_window_v2(dt) is expected
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def test_run_retrain_builds_features_in_thread(monkeypatch):
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seen = {}
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async def fake_load(months=6):
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return pd.DataFrame({"stock_code": ["A"], "close": [1.0]})
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def fake_build(df):
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import threading
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seen["thread"] = threading.current_thread()
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return [], []
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monkeypatch.setattr(mrp, "_load_daily_prices", fake_load)
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monkeypatch.setattr(mrp, "_build_training_lists_impl", fake_build)
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import threading
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res = asyncio.run(mrp.run_retrain(force=True))
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assert res["status"] == "skipped"
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assert seen["thread"] is not threading.main_thread()
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def test_scheduler_defers_retrain_during_market_hours(monkeypatch):
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calls = {"retrain": 0}
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async def fake_check():
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return True, {"degraded": True}
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async def fake_retrain(*a, **k):
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calls["retrain"] += 1
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return {"status": "completed"}
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class _FakeDT(datetime):
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@classmethod
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def now(cls, tz=None):
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return cls(2026, 10, 7, 9, 45, tzinfo=tz)
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async def fake_sleep(sec):
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if sec == 3600:
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raise asyncio.CancelledError
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monkeypatch.setattr(mrp, "check_performance_degradation", fake_check)
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monkeypatch.setattr(mrp, "run_retrain", fake_retrain)
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monkeypatch.setattr(mrp, "datetime", _FakeDT)
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monkeypatch.setattr(mrp.asyncio, "sleep", fake_sleep)
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with pytest.raises(asyncio.CancelledError):
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asyncio.run(mrp.ml_retrain_scheduler())
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assert calls["retrain"] == 0
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