shuim
a264561576
- 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
45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
from datetime import datetime
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import pytest
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from app.services import execution_quality as eq
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def test_side_adjust_no_cancellation():
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rows = [
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{"order_type": "BUY", "slippage": 0.1, "strategy_type": "daytrading"},
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{"order_type": "SELL", "slippage": 0.1, "strategy_type": "daytrading"},
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]
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r = eq.aggregate_execution_quality_v1(rows)["overall"]
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assert r["mean_cost_bp"] == 0.0
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assert r["mean_abs_bp"] == 10.0
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assert eq.slippage_cost_bp_v3("BUY", 0.1) == pytest.approx(10.0)
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assert eq.slippage_cost_bp_v3("SELL", 0.1) == pytest.approx(-10.0)
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def test_matches_trade_executor_v2():
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te = pytest.importorskip("app.services.trade_executor")
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for side in ("BUY", "SELL", "HOLD"):
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for v in (0.1, -0.3, None, "x"):
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assert eq.slippage_cost_bp_v3(side, v) == te.slippage_cost_bp_v2(side, v)
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def test_low_sample_null_and_groups():
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rows = [
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{"order_type": "BUY", "slippage": None, "strategy_type": "swing", "executed_quantity": 0},
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{"order_type": "BUY", "slippage": 0.2, "strategy_type": "daytrading", "executed_quantity": 5,
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"executed_at": datetime(2026, 10, 7, 9, 5), "fill_verified": True},
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]
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r = eq.aggregate_execution_quality_v1(rows)
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assert r["overall"]["low_sample"] and r["overall"]["n_slippage"] == 1
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assert r["by_strategy"]["swing"]["mean_cost_bp"] is None
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assert r["by_hour"][9]["fill_verified_ratio"] == 1.0
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big = [{"order_type": "BUY", "slippage": 0.1}] * eq.LOW_SAMPLE_THRESHOLD
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assert not eq.aggregate_execution_quality_v1(big)["overall"]["low_sample"]
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def test_invalid_inputs():
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for bad in (None, "x", float("nan"), float("inf")):
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assert eq.slippage_cost_bp_v3("BUY", bad) is None
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assert eq.slippage_cost_bp_v3("HOLD", 0.1) is None
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