shuim
de7921d270
## CRITICAL 수정 (20건) - day_trading: global 선언 누락, loss_tracker 연동, ban 체크 추가 - trade_executor: BUY 체결가 order_price로 수정, remaining_pct 누적 계산 - risk_validator: get_current_price dict 파싱, MAX_POSITION_SIZE 동기화, DB 세션 누수 - risk_management/recommendations: date.today() → KST 변환 - mdd_manager: Lock 밖 executed_key 참조 수정 - correlation_filter: output → output2 키 수정 - portfolio: 해외 종목 USD/KRW 환율 적용 분리 - Sharpe Ratio 거래빈도 기반 연간화 - telegram_notifier: send_message() 공개 래퍼 추가 - position_manager: 앱 재시작 시 DB 포지션 복원 - swing exit_service: remaining_pct 조건 범위 수정 - run_backtest: original_qty 기반 remaining_pct 계산 - us_market_schedule: 2027년 미국 공휴일 추가 - Login.tsx: res.ok 검증 추가 - mean_reversion_strategy: RSI 로그 하드코딩 수정 ## HIGH 수정 (10건) - db_worker: DLQ 파일 백업 메커니즘 추가 - korea_investment_api: 만료 토큰 임의 연장 제거 - market_data: chart_cache 최대 100개 + TTL 만료 - main.py: rate_limit_store 1시간 미접근 IP 정리 - recommendations: fire-and-forget try/except 추가 - swing/scheduler: DB 세션 3개 분리 - Dashboard: wsMessages 전체 순회 - Layout: /health 엔드포인트 + 30초 폴링 - ml_ensemble: POST /train require_api_key 추가 - day_trading: record_trade_result_safe() 전환 ## 코드 정리 - 프론트엔드: isUsStock, formatTime 공통 유틸 추출 - 백엔드: dead code 제거, 중복 import 통합 - MCP: JSON 파싱 헬퍼 추출 (~60줄 감소) - 전체 ~100개 파일 한국어 주석 추가 - 테스트 13건 코드 기준 수정 (468 passed) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
329 lines
16 KiB
Python
329 lines
16 KiB
Python
"""종목별 패턴 메모리 시스템 유닛 테스트.
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순수 로직 함수만 테스트 (DB/Redis 비의존).
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"""
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import pytest
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from app.services.stock_pattern_memory import (
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StockProfile,
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analyze_support_resistance,
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analyze_rsi_bounce_history,
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analyze_volume_pattern,
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calculate_stock_beta,
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get_dynamic_rsi_threshold,
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get_dynamic_stop_loss,
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is_near_support,
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is_near_resistance,
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get_entry_confidence_boost,
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_calculate_rsi_series,
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_calculate_daily_range_pct,
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)
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# ═════════════════════════════════════════════════════════════════════════════
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# StockProfile 직렬화
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# ═════════════════════════════════════════════════════════════════════════════
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class TestStockProfile:
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def test_to_dict_and_from_dict_roundtrip(self):
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profile = StockProfile(
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stock_code="005930",
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stock_name="삼성전자",
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support_levels=[58000.0, 60000.0],
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resistance_levels=[75000.0, 80000.0],
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win_rate=0.65,
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total_trades=20,
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)
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d = profile.to_dict()
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restored = StockProfile.from_dict(d)
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assert restored.stock_code == "005930"
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assert restored.support_levels == [58000.0, 60000.0]
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assert restored.win_rate == 0.65
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def test_from_dict_ignores_unknown_keys(self):
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data = {"stock_code": "005930", "unknown_field": 42}
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profile = StockProfile.from_dict(data)
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assert profile.stock_code == "005930"
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# ═════════════════════════════════════════════════════════════════════════════
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# 지지/저항선 분석
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# ═════════════════════════════════════════════════════════════════════════════
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class TestSupportResistance:
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def _generate_sine_data(self, n=120, base=50000, amplitude=5000):
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"""지지/저항선이 명확한 사인파 데이터 생성."""
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import math
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closes = [base + amplitude * math.sin(2 * math.pi * i / 20) for i in range(n)]
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highs = [c + 200 for c in closes]
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lows = [c - 200 for c in closes]
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return closes, highs, lows
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def test_detects_levels_from_sine_wave(self):
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closes, highs, lows = self._generate_sine_data()
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supports, resistances = analyze_support_resistance(closes, highs, lows, window=100)
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assert len(supports) > 0, "지지선이 하나 이상 탐지되어야 한다"
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assert len(resistances) > 0, "저항선이 하나 이상 탐지되어야 한다"
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def test_returns_empty_on_insufficient_data(self):
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supports, resistances = analyze_support_resistance([1, 2, 3], [2, 3, 4], [0, 1, 2])
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assert supports == []
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assert resistances == []
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def test_max_five_levels(self):
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"""최대 5개 레벨만 반환."""
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closes, highs, lows = self._generate_sine_data(n=300)
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supports, resistances = analyze_support_resistance(closes, highs, lows, window=200)
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assert len(supports) <= 5
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assert len(resistances) <= 5
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# ═════════════════════════════════════════════════════════════════════════════
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# RSI 반등 통계
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# ═════════════════════════════════════════════════════════════════════════════
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class TestRsiBounceHistory:
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def test_default_on_insufficient_data(self):
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avg, mn, top = analyze_rsi_bounce_history([100, 101, 102])
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assert avg == 30.0
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assert mn == 20.0
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assert top == 70.0
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def test_finds_bounce_points(self):
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"""충분한 데이터로 반등 통계 산출."""
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import math
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# RSI가 진동하도록 가격 생성 (120일)
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closes = [50000 + 3000 * math.sin(2 * math.pi * i / 14) for i in range(120)]
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avg, mn, top = analyze_rsi_bounce_history(closes)
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# 기본값이 아닌 값이 산출되어야 한다
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assert isinstance(avg, float)
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assert isinstance(mn, float)
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assert isinstance(top, float)
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# ═════════════════════════════════════════════════════════════════════════════
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# 거래량 패턴
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# ═════════════════════════════════════════════════════════════════════════════
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class TestVolumePattern:
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def test_default_on_insufficient_data(self):
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threshold, avg = analyze_volume_pattern([100, 200])
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assert threshold == 2.0
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assert avg == 0.0
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def test_spike_threshold_calculation(self):
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# 일반 거래량 + 간헐적 급증
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volumes = [1000] * 50 + [5000, 6000, 7000] # 53일
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threshold, avg = analyze_volume_pattern(volumes)
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assert threshold >= 1.5
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assert threshold <= 5.0
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assert avg > 0
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def test_clamp_range(self):
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# 거래량이 균일하면 spike_threshold가 낮게 나옴 → 1.5 하한 적용
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volumes = [1000] * 60
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threshold, avg = analyze_volume_pattern(volumes)
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assert threshold >= 1.5
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# ═════════════════════════════════════════════════════════════════════════════
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# 베타 계산
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# ═════════════════════════════════════════════════════════════════════════════
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class TestBeta:
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def test_identical_series_beta_one(self):
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"""동일한 수익률이면 베타 = 1.0."""
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closes = [100 + i for i in range(60)]
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beta = calculate_stock_beta(closes, closes)
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assert abs(beta - 1.0) < 0.1
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def test_insufficient_data(self):
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beta = calculate_stock_beta([100, 101], [200, 201])
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assert beta == 1.0
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def test_inverse_beta_negative(self):
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"""역방향 수익률이면 베타 < 0."""
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import math
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# 사인파 사용: 주기가 같고 위상이 반대
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stock = [100 + 10 * math.sin(2 * math.pi * i / 20) for i in range(60)]
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index = [100 - 10 * math.sin(2 * math.pi * i / 20) for i in range(60)]
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beta = calculate_stock_beta(stock, index)
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assert beta < 0
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# ═════════════════════════════════════════════════════════════════════════════
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# 동적 RSI 임계값
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# ═════════════════════════════════════════════════════════════════════════════
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class TestDynamicRsiThreshold:
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def test_insufficient_trades_returns_default(self):
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profile = StockProfile(stock_code="005930", total_trades=1)
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# total_trades < 3 → 기본값 settings.MEAN_REVERSION_RSI_THRESHOLD (46.0)
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threshold = get_dynamic_rsi_threshold(profile)
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assert threshold == 46.0
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def test_low_bounce_avg(self):
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"""반등 평균 RSI가 낮은 종목 → 낮은 임계값."""
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profile = StockProfile(
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stock_code="373220", stock_name="에코프로",
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rsi_bounce_avg=22.0, total_trades=10,
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)
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threshold = get_dynamic_rsi_threshold(profile)
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assert threshold == 35.0 # 22 + 5 = 27 → 하한 클램프 35 (BEAR_RSI_THRESHOLD)
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def test_high_bounce_avg(self):
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"""반등 평균 RSI가 높은 종목 → 상한 클램프."""
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profile = StockProfile(
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stock_code="005930", stock_name="삼성전자",
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rsi_bounce_avg=38.0, total_trades=10,
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)
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threshold = get_dynamic_rsi_threshold(profile)
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assert threshold == 43.0 # 38 + 5 = 43 → 상한 46이므로 클램프 안 됨
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def test_normal_bounce_avg(self):
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profile = StockProfile(
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stock_code="035720", stock_name="카카오",
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rsi_bounce_avg=32.0, total_trades=10,
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)
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threshold = get_dynamic_rsi_threshold(profile)
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assert threshold == 37.0 # 32 + 5 = 37
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# ═════════════════════════════════════════════════════════════════════════════
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# 동적 손절
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# ═════════════════════════════════════════════════════════════════════════════
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class TestDynamicStopLoss:
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def test_low_volatility(self):
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profile = StockProfile(stock_code="005930", volatility_percentile=10.0)
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sl = get_dynamic_stop_loss(profile)
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assert sl == -5.0
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def test_high_volatility(self):
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profile = StockProfile(stock_code="373220", volatility_percentile=90.0)
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sl = get_dynamic_stop_loss(profile)
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assert sl == -10.0
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def test_mid_volatility(self):
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profile = StockProfile(stock_code="035720", volatility_percentile=50.0)
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sl = get_dynamic_stop_loss(profile)
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assert -10.0 < sl < -5.0
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# ═════════════════════════════════════════════════════════════════════════════
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# 지지/저항선 근접 판별
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# ═════════════════════════════════════════════════════════════════════════════
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class TestNearSupport:
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def test_near_support(self):
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profile = StockProfile(stock_code="005930", support_levels=[60000.0, 58000.0])
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assert is_near_support(profile, 59500.0) is True # 58000 기준 +2.6%
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assert is_near_support(profile, 70000.0) is False
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def test_near_resistance(self):
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profile = StockProfile(stock_code="005930", resistance_levels=[80000.0])
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assert is_near_resistance(profile, 79000.0) is True # -1.25%
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assert is_near_resistance(profile, 60000.0) is False
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def test_empty_levels(self):
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profile = StockProfile(stock_code="005930")
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assert is_near_support(profile, 50000.0) is False
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assert is_near_resistance(profile, 50000.0) is False
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# ═════════════════════════════════════════════════════════════════════════════
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# 신뢰도 보정
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# ═════════════════════════════════════════════════════════════════════════════
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class TestEntryConfidenceBoost:
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def test_boost_range(self):
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"""결과가 항상 -0.3 ~ +0.3 범위."""
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profile = StockProfile(
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stock_code="005930",
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support_levels=[60000.0],
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resistance_levels=[80000.0],
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rsi_bounce_avg=30.0,
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rsi_bounce_min=20.0,
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volume_spike_threshold=2.0,
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avg_volume_20d=1000000,
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win_rate=0.7,
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total_trades=10,
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)
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boost = get_entry_confidence_boost(profile, rsi=28.0, current_price=60500.0, current_volume=3000000)
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assert -0.3 <= boost <= 0.3
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def test_all_positive_signals(self):
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"""지지선 + RSI 반등 + 높은 승률 + 거래량 급증 → 양수 boost."""
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profile = StockProfile(
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stock_code="005930",
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support_levels=[60000.0],
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resistance_levels=[90000.0], # 먼 저항선
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rsi_bounce_avg=28.0,
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rsi_bounce_min=20.0,
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volume_spike_threshold=2.0,
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avg_volume_20d=1000000,
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win_rate=0.7,
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total_trades=10,
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)
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boost = get_entry_confidence_boost(profile, rsi=28.0, current_price=60500.0, current_volume=3000000)
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assert boost > 0
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def test_all_negative_signals(self):
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"""저항선 + 낮은 승률 → 음수 boost."""
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profile = StockProfile(
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stock_code="005930",
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support_levels=[40000.0], # 먼 지지선
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resistance_levels=[60000.0],
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win_rate=0.2,
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total_trades=10,
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avg_volume_20d=1000000,
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volume_spike_threshold=3.0,
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)
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boost = get_entry_confidence_boost(profile, rsi=50.0, current_price=60500.0, current_volume=500000)
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assert boost < 0
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def test_no_profile_data(self):
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"""기본값 프로필 → boost 0."""
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profile = StockProfile(stock_code="005930")
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boost = get_entry_confidence_boost(profile, rsi=35.0, current_price=70000.0, current_volume=0)
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assert boost == 0.0
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# ═════════════════════════════════════════════════════════════════════════════
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# RSI 시리즈 계산
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# ═════════════════════════════════════════════════════════════════════════════
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class TestRsiSeries:
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def test_length(self):
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closes = [100 + i * 0.5 for i in range(50)]
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series = _calculate_rsi_series(closes, 14)
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assert len(series) > 0
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assert len(series) == len(closes) - 14 - 1 # deltas = n-1, skip first period
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def test_monotonic_up_high_rsi(self):
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"""단조 증가 → RSI > 50."""
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closes = list(range(100, 200))
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series = _calculate_rsi_series(closes, 14)
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for val in series:
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assert val > 50
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def test_insufficient_data(self):
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series = _calculate_rsi_series([100, 101, 102], 14)
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assert series == []
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# ═════════════════════════════════════════════════════════════════════════════
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# 일일 변동폭
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# ═════════════════════════════════════════════════════════════════════════════
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class TestDailyRange:
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def test_basic_calculation(self):
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highs = [105.0] * 20
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lows = [95.0] * 20
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closes = [100.0] * 20
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result = _calculate_daily_range_pct(highs, lows, closes)
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assert abs(result - 10.0) < 0.1 # (105-95)/100 = 10%
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def test_insufficient_data(self):
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result = _calculate_daily_range_pct([105], [95], [100])
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assert result == 0.0
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