Compare commits

...

22 Commits

Author SHA1 Message Date
agentson
ff9c4d6082 feat: 시작 시 브로커 포지션 → DB 동기화 및 국내주식 이중 매수 방지 (#206)
Some checks failed
CI / test (pull_request) Has been cancelled
- sync_positions_from_broker() 함수 추가
  - 시스템 시작 시 브로커 잔고를 조회해 DB에 없는 포지션을 BUY 레코드로 삽입
  - 국내: get_balance(), 해외: get_overseas_balance(exchange_code) 순회
  - ConnectionError는 경고 로그만 남기고 계속 진행 (non-fatal)
  - 동일 exchange_code 중복 조회 방지 (seen_exchange_codes 집합)
  - run() 초기화 후 최초 한 번 자동 호출

- 국내주식 BUY 이중 방지 로직 확장
  - trading_cycle 및 run_daily_session에서 기존에 해외 전용(not market.is_domestic)
    으로만 적용하던 broker balance 체크를 국내/해외 공통으로 변경
  - _extract_held_qty_from_balance(is_domestic=market.is_domestic)

- 테스트 (827 passed)
  - TestSyncPositionsFromBroker (6개): 국내/해외 동기화, 중복 skip, 공란, ConnectionError, dedup
  - TestDomesticBuyDoublePreventionTradingCycle (1개): 국내 보유 주식 BUY 억제

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 17:03:22 +09:00
25ad4776c9 Merge pull request 'feat: Daily CB P&L 기준을 당일 시작 평가금액으로 변경 (#207)' (#227) from feature/issue-207-daily-cb-pnl into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #227
2026-02-23 16:58:18 +09:00
agentson
9339824e22 feat: Daily CB P&L 기준을 당일 시작 평가금액으로 변경 (#207)
Some checks failed
CI / test (pull_request) Has been cancelled
- run_daily_session에 daily_start_eval 파라미터 추가 (반환 타입: float)
  - 세션 첫 잔고 조회 시 total_eval을 baseline으로 캡처
  - 이후 세션에서 pnl_pct = (total_eval - daily_start_eval) / daily_start_eval
  - 기존 purchase_total(누적) 기반 계산 제거
- run 함수 daily 루프에서 날짜 변경 시 baseline 리셋 (_cb_last_date 추적)
- early return 시 daily_start_eval 반환하도록 버그 수정 (None 반환 방지)
- TestDailyCBBaseline 클래스 4개 테스트 추가
  - no_markets: 0.0/기존값 그대로 반환
  - first session: total_eval을 baseline으로 캡처
  - subsequent session: 기존 baseline 유지 (덮어쓰기 방지)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 16:47:09 +09:00
e6eae6c6e0 Merge pull request 'docs: 모의→실전 전환 체크리스트 작성 (#218)' (#226) from feature/issue-218-live-trading-docs into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #226
2026-02-23 15:01:01 +09:00
bb6bd0392e Merge pull request 'fix: GEMINI_MODEL 기본값 gemini-pro → gemini-2.0-flash (#217)' (#225) from feature/issue-217-gemini-model-default into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #225
2026-02-23 15:00:27 +09:00
a66181b7a7 Merge pull request 'fix: 진화 전략 파일 3개 IndentationError 수정 (#215)' (#224) from feature/issue-215-evolved-strategy-syntax into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #224
2026-02-23 14:59:51 +09:00
da585ee547 Merge pull request 'feat: Daily 모드 ConnectionError 재시도 로직 추가 (#209)' (#223) from feature/issue-209-daily-connection-retry into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #223
2026-02-23 14:57:26 +09:00
c737d5009a Merge pull request 'test: 테스트 커버리지 77% → 80% 달성 (#204)' (#222) from feature/issue-204-test-coverage-80 into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #222
2026-02-23 14:56:22 +09:00
agentson
f7d33e69d1 docs: 실전 전환 체크리스트 작성 (issue #218)
Some checks failed
CI / test (pull_request) Has been cancelled
docs/live-trading-checklist.md 신규 작성:
- 사전 조건: KIS 실전 계좌/OpenAPI 신청, 리스크 파라미터 검토
- 환경 설정: .env 수정 가이드, TR_ID 분기표 (모의/실전)
- 최종 확인: DB 백업, 실행 명령, 시작 직후 점검
- 비상 정지: Ctrl+C / /stop 명령 / CB 발동
- 롤백 절차: MODE=paper 복원

CLAUDE.md: 문서 목록에 체크리스트 링크 추가

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:55:37 +09:00
agentson
7d99d8ec4a fix: GEMINI_MODEL 기본값 'gemini-pro' → 'gemini-2.0-flash' (issue #217)
Some checks failed
CI / test (pull_request) Has been cancelled
'gemini-pro'는 deprecated 모델로 API 오류 발생 가능.
.env.example은 이미 gemini-2.0-flash-exp로 설정되어 있음.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:54:30 +09:00
agentson
0727f28f77 fix: 진화 전략 파일 3개 들여쓰기 구문 오류 수정 (issue #215)
Some checks failed
CI / test (pull_request) Has been cancelled
AI가 evaluate() 메서드 내부에 또 다른 evaluate() 함수를 중첩 정의하는
실수로 생성된 IndentationError 수정.

각 파일별 수정 내용:
- v20260220_210124_evolved.py: 중첩 def evaluate 제거, 상수/로직 8칸으로 정규화
- v20260220_210159_evolved.py: 중첩 def evaluate 제거, 16칸→8칸 들여쓰기 수정
- v20260220_210244_evolved.py: 12칸→8칸 들여쓰기 수정

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:53:41 +09:00
agentson
ac4fb00644 feat: Daily 모드 ConnectionError 재시도 로직 추가 (issue #209)
Some checks failed
CI / test (pull_request) Has been cancelled
- _retry_connection() 헬퍼 추가: MAX_CONNECTION_RETRIES(3회) 지수 백오프
  (2^attempt 초) 재시도, 읽기 전용 API 호출에만 적용 (주문 제외)
- run_daily_session(): get_current_price / get_overseas_price 호출에 적용
- run_daily_session(): get_balance / get_overseas_balance 호출에 적용
  - 잔고 조회 전체 실패 시 해당 마켓을 skip하고 다른 마켓은 계속 처리
- 테스트 5개 추가: TestRetryConnection 클래스

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:51:15 +09:00
agentson
4fc4a57036 test: 테스트 커버리지 77% → 80% 달성 (issue #204)
Some checks failed
CI / test (pull_request) Has been cancelled
신규/추가 테스트:
- tests/test_logging_config.py: JSONFormatter, setup_logging 전체 커버 (14줄)
- tests/test_strategies_base.py: BaseStrategy 추상 클래스 커버 (6줄)
- tests/test_backup.py: BackupExporter 미커버 경로(빈 CSV, compress=True CSV,
  포맷 실패 로깅, 기본 formats) + CloudStorage boto3 모킹 테스트 20개 (113줄)
- tests/test_context.py: ContextSummarizer 전체 커버 22개 테스트 (50줄)

총 815개 테스트 통과, TOTAL 커버리지 80% (1046줄 미커버 / 5225줄 전체)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:48:08 +09:00
641f3e8811 Merge pull request 'feat: trades 테이블 mode 컬럼 추가 (#212)' (#221) from feature/issue-212-trades-mode-column into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #221
2026-02-23 12:34:26 +09:00
agentson
ebd0a0297c chore: PR #221 충돌 해결 — WAL 테스트(#210)와 mode 컬럼 테스트(#212) 병합
Some checks failed
CI / test (pull_request) Has been cancelled
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:34:06 +09:00
02a72e0f7e Merge pull request 'feat: DB WAL 모드 적용, .env.example 정리 (#210, #213, #216)' (#220) from feature/issue-210-213-216-db-wal-env-fix into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #220
2026-02-23 12:32:36 +09:00
478a659ac2 Merge pull request 'feat: 실전 투자 전환 — TR_ID 분기, URL, 신뢰도 임계값, 텔레그램 알림 (#201~#205, #208, #214)' (#219) from feature/issue-201-202-203-broker-live-mode into main
Some checks failed
CI / test (push) Has been cancelled
Reviewed-on: #219
2026-02-23 12:32:21 +09:00
agentson
16b9b6832d fix: BULLISH confidence 임계값 75로 복원 (#205)
Some checks failed
CI / test (pull_request) Has been cancelled
CLAUDE.md 규칙 개정에 따라 BULLISH 시장은 75로 유지.
시장 전망별 임계값: BEARISH=90, NEUTRAL=80, BULLISH=75.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:30:51 +09:00
agentson
48b87a79f6 docs: CLAUDE.md confidence 규칙 BULLISH=75 명시 (#205)
시장 전망별 BUY confidence 최소 임계값:
- BEARISH: 90 (더 엄격)
- NEUTRAL/기본: 80
- BULLISH: 75 (낙관적 시장에서 완화)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:29:39 +09:00
agentson
ad79082dcc docs: CLAUDE.md 비협상 규칙 명시 강화 — BULLISH 시 confidence 임계값 포함 (#205)
Some checks failed
CI / test (pull_request) Has been cancelled
BULLISH 시장에서도 confidence < 80 → HOLD 규칙이 동일하게 적용됨을 명시.
시장 전망별 임계값: BEARISH=90(더 엄격), BULLISH/NEUTRAL=80(최소값).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 12:28:30 +09:00
agentson
11dff9d3e5 feat: trades 테이블 mode 컬럼 추가 (paper/live 거래 분리) (#212)
Some checks failed
CI / test (pull_request) Has been cancelled
- trades 테이블에 mode TEXT DEFAULT 'paper' 컬럼 추가
- 기존 DB 마이그레이션: ALTER TABLE으로 mode 컬럼 자동 추가
- log_trade() 함수에 mode 파라미터 추가 (기본값 'paper')
- trading_cycle(), run_daily_session()에서 settings.MODE 전달
- 테스트 5개 추가 (mode 저장, 기본값, 스키마 검증, 마이그레이션)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 10:33:02 +09:00
agentson
d6a389e0b7 feat: 실전 투자 전환 — TR_ID 분기, URL, 신뢰도 임계값, 텔레그램 알림 수정 (#201~#205, #208, #214)
Some checks failed
CI / test (pull_request) Has been cancelled
- #201: 국내/해외 TR_ID 실전/모의 자동 분기
  - get_balance: TTTC8434R(실전) / VTTC8434R(모의)
  - send_order: TTTC0012U/0011U(실전) / VTTC0012U/0011U(모의) [현금주문]
  - get_overseas_balance: TTTS3012R(실전) / VTTS3012R(모의)
  - send_overseas_order: TTTT1002U/1006U(실전) / VTTT1002U/1001U(모의)
- #202: KIS_BASE_URL 기본값 VTS 포트 9443→29443 수정
- #203: PAPER_OVERSEAS_CASH fallback 실전(MODE=live)에서 비활성화, 중복 코드 제거
- #205: BULLISH 시장 BUY confidence 임계값 75→80(기본값) 수정 (CLAUDE.md 비협상 규칙)
- #208: Daily 모드 CircuitBreakerTripped 시 텔레그램 알림 추가
- #214: 시스템 종료 시 notify_system_shutdown() 호출 추가

테스트 22개 추가 (TR_ID 분기 12개, confidence 임계값 1개 수정)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-02-23 10:28:24 +09:00
18 changed files with 2578 additions and 43 deletions

View File

@@ -94,6 +94,7 @@ Smart Scanner runs in `TRADE_MODE=realtime` only. Daily mode uses static watchli
- **[Testing](docs/testing.md)** — Test structure, coverage requirements, writing tests
- **[Agent Policies](docs/agents.md)** — Prime directives, constraints, prohibited actions
- **[Requirements Log](docs/requirements-log.md)** — User requirements and feedback tracking
- **[Live Trading Checklist](docs/live-trading-checklist.md)** — 모의→실전 전환 체크리스트
## Core Principles
@@ -170,7 +171,7 @@ Markets auto-detected based on timezone and enabled in `ENABLED_MARKETS` env var
- `src/core/risk_manager.py` is **READ-ONLY** — changes require human approval
- Circuit breaker at -3.0% P&L — may only be made **stricter**
- Fat-finger protection: max 30% of cash per order — always enforced
- Confidence < 80 → force HOLD — cannot be weakened
- Confidence 임계값 (market_outlook별, 낮출 수 없음): BEARISH ≥ 90, NEUTRAL/기본 ≥ 80, BULLISH ≥ 75
- All code changes → corresponding tests → coverage ≥ 80%
## Contributing

View File

@@ -0,0 +1,131 @@
# 실전 전환 체크리스트
모의 거래(paper)에서 실전(live)으로 전환하기 전에 아래 항목을 **순서대로** 모두 확인하세요.
---
## 1. 사전 조건
### 1-1. KIS OpenAPI 실전 계좌 준비
- [ ] 한국투자증권 계좌 개설 완료 (일반 위탁 계좌)
- [ ] OpenAPI 실전 사용 신청 (KIS 홈페이지 → Open API → 서비스 신청)
- [ ] 실전용 APP_KEY / APP_SECRET 발급 완료
- [ ] KIS_ACCOUNT_NO 형식 확인: `XXXXXXXX-XX` (8자리-2자리)
### 1-2. 리스크 파라미터 검토
- [ ] `CIRCUIT_BREAKER_PCT` 확인: 기본값 -3.0% (더 엄격하게 조정 권장)
- [ ] `FAT_FINGER_PCT` 확인: 기본값 30.0% (1회 주문 최대 잔고 대비 %)
- [ ] `CONFIDENCE_THRESHOLD` 확인: BEARISH ≥ 90, NEUTRAL ≥ 80, BULLISH ≥ 75
- [ ] 초기 투자금 결정 및 해외 주식 운용 한도 설정
### 1-3. 시스템 요건
- [ ] 커버리지 80% 이상 유지 확인: `pytest --cov=src`
- [ ] 타입 체크 통과: `mypy src/ --strict`
- [ ] Lint 통과: `ruff check src/ tests/`
---
## 2. 환경 설정
### 2-1. `.env` 파일 수정
```bash
# 1. KIS 실전 URL로 변경 (모의: openapivts 포트 29443)
KIS_BASE_URL=https://openapi.koreainvestment.com:9443
# 2. 실전 APP_KEY / APP_SECRET으로 교체
KIS_APP_KEY=<실전_APP_KEY>
KIS_APP_SECRET=<실전_APP_SECRET>
KIS_ACCOUNT_NO=<실전_계좌번호>
# 3. 모드를 live로 변경
MODE=live
# 4. PAPER_OVERSEAS_CASH 비활성화 (live 모드에선 무시되지만 명시적으로 0 설정)
PAPER_OVERSEAS_CASH=0
```
> ⚠️ `KIS_BASE_URL` 포트 주의:
> - **모의(VTS)**: `https://openapivts.koreainvestment.com:29443`
> - **실전**: `https://openapi.koreainvestment.com:9443`
### 2-2. TR_ID 자동 분기 확인
아래 TR_ID는 `MODE` 값에 따라 코드에서 **자동으로 선택**됩니다.
별도 설정 불필요하나, 문제 발생 시 아래 표를 참조하세요.
| 구분 | 모의 TR_ID | 실전 TR_ID |
|------|-----------|-----------|
| 국내 잔고 조회 | `VTTC8434R` | `TTTC8434R` |
| 국내 현금 매수 | `VTTC0012U` | `TTTC0012U` |
| 국내 현금 매도 | `VTTC0011U` | `TTTC0011U` |
| 해외 잔고 조회 | `VTTS3012R` | `TTTS3012R` |
| 해외 매수 | `VTTT1002U` | `TTTT1002U` |
| 해외 매도 | `VTTT1001U` | `TTTT1006U` |
> **출처**: `docs/한국투자증권_오픈API_전체문서_20260221_030000.xlsx` (공식 문서 기준)
---
## 3. 최종 확인
### 3-1. 실전 시작 전 점검
- [ ] DB 백업 완료: `data/trade_logs.db``data/backups/`
- [ ] Telegram 알림 설정 확인 (실전에서는 알림이 더욱 중요)
- [ ] 소액으로 첫 거래 진행 후 TR_ID/계좌 정상 동작 확인
### 3-2. 실행 명령
```bash
# 실전 모드로 실행
python -m src.main --mode=live
# 대시보드 함께 실행 (별도 터미널에서 모니터링)
python -m src.main --mode=live --dashboard
```
### 3-3. 실전 시작 직후 확인 사항
- [ ] 로그에 `MODE=live` 출력 확인
- [ ] 첫 잔고 조회 성공 (ConnectionError 없음)
- [ ] Telegram 알림 수신 확인 ("System started")
- [ ] 첫 주문 후 KIS 앱에서 체결 내역 확인
---
## 4. 비상 정지 방법
### 즉각 정지
```bash
# 터미널에서 Ctrl+C (정상 종료 트리거)
# 또는 Telegram 봇 명령:
/stop
```
### Circuit Breaker 발동 시
- CB가 발동되면 자동으로 거래 중단 및 Telegram 알림 전송
- CB 임계값: `CIRCUIT_BREAKER_PCT` (기본 -3.0%)
- **임계값은 엄격하게만 조정 가능** (더 낮은 음수 값으로만 변경)
---
## 5. 롤백 절차
실전 전환 후 문제 발생 시:
```bash
# 1. 즉시 .env에서 MODE=paper로 복원
# 2. 재시작
python -m src.main --mode=paper
# 3. DB에서 최근 거래 확인
sqlite3 data/trade_logs.db "SELECT * FROM trades ORDER BY id DESC LIMIT 20;"
```
---
## 관련 문서
- [시스템 아키텍처](architecture.md)
- [워크플로우 가이드](workflow.md)
- [재해 복구](disaster_recovery.md)
- [Agent 제약 조건](agents.md)

View File

@@ -285,7 +285,10 @@ class KISBroker:
await self._rate_limiter.acquire()
session = self._get_session()
headers = await self._auth_headers("VTTC8434R") # 모의투자 잔고조회
# TR_ID: 실전 TTTC8434R, 모의 VTTC8434R
# Source: 한국투자증권 오픈API 전체문서 (20260221) — '국내주식 잔고조회' 시트
tr_id = "TTTC8434R" if self._settings.MODE == "live" else "VTTC8434R"
headers = await self._auth_headers(tr_id)
params = {
"CANO": self._account_no,
"ACNT_PRDT_CD": self._product_cd,
@@ -330,7 +333,13 @@ class KISBroker:
await self._rate_limiter.acquire()
session = self._get_session()
tr_id = "VTTC0802U" if order_type == "BUY" else "VTTC0801U"
# TR_ID: 실전 BUY=TTTC0012U SELL=TTTC0011U, 모의 BUY=VTTC0012U SELL=VTTC0011U
# Source: 한국투자증권 오픈API 전체문서 (20260221) — '주식주문(현금)' 시트
# ※ TTTC0802U/VTTC0802U는 미수매수(증거금40% 계좌 전용) — 현금주문에 사용 금지
if self._settings.MODE == "live":
tr_id = "TTTC0012U" if order_type == "BUY" else "TTTC0011U"
else:
tr_id = "VTTC0012U" if order_type == "BUY" else "VTTC0011U"
# KRX requires limit orders to be rounded down to the tick unit.
# ORD_DVSN: "00"=지정가, "01"=시장가

View File

@@ -175,8 +175,12 @@ class OverseasBroker:
await self._broker._rate_limiter.acquire()
session = self._broker._get_session()
# Virtual trading TR_ID for overseas balance inquiry
headers = await self._broker._auth_headers("VTTS3012R")
# TR_ID: 실전 TTTS3012R, 모의 VTTS3012R
# Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 잔고조회' 시트
balance_tr_id = (
"TTTS3012R" if self._broker._settings.MODE == "live" else "VTTS3012R"
)
headers = await self._broker._auth_headers(balance_tr_id)
params = {
"CANO": self._broker._account_no,
"ACNT_PRDT_CD": self._broker._product_cd,
@@ -229,10 +233,12 @@ class OverseasBroker:
await self._broker._rate_limiter.acquire()
session = self._broker._get_session()
# Virtual trading TR_IDs for overseas orders
# TR_ID: 실전 BUY=TTTT1002U SELL=TTTT1006U, 모의 BUY=VTTT1002U SELL=VTTT1001U
# Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 주문' 시트
# VTTT1002U: 모의투자 미국 매수, VTTT1001U: 모의투자 미국 매도
tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1001U"
if self._broker._settings.MODE == "live":
tr_id = "TTTT1002U" if order_type == "BUY" else "TTTT1006U"
else:
tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1001U"
body = {
"CANO": self._broker._account_no,

View File

@@ -13,11 +13,11 @@ class Settings(BaseSettings):
KIS_APP_KEY: str
KIS_APP_SECRET: str
KIS_ACCOUNT_NO: str # format: "XXXXXXXX-XX"
KIS_BASE_URL: str = "https://openapivts.koreainvestment.com:9443"
KIS_BASE_URL: str = "https://openapivts.koreainvestment.com:29443"
# Google Gemini
GEMINI_API_KEY: str
GEMINI_MODEL: str = "gemini-pro"
GEMINI_MODEL: str = "gemini-2.0-flash"
# External Data APIs (optional — for data-driven decisions)
NEWS_API_KEY: str | None = None

View File

@@ -33,12 +33,13 @@ def init_db(db_path: str) -> sqlite3.Connection:
pnl REAL DEFAULT 0.0,
market TEXT DEFAULT 'KR',
exchange_code TEXT DEFAULT 'KRX',
decision_id TEXT
decision_id TEXT,
mode TEXT DEFAULT 'paper'
)
"""
)
# Migration: Add market and exchange_code columns if they don't exist
# Migration: Add columns if they don't exist (backward-compatible schema upgrades)
cursor = conn.execute("PRAGMA table_info(trades)")
columns = {row[1] for row in cursor.fetchall()}
@@ -50,6 +51,8 @@ def init_db(db_path: str) -> sqlite3.Connection:
conn.execute("ALTER TABLE trades ADD COLUMN selection_context TEXT")
if "decision_id" not in columns:
conn.execute("ALTER TABLE trades ADD COLUMN decision_id TEXT")
if "mode" not in columns:
conn.execute("ALTER TABLE trades ADD COLUMN mode TEXT DEFAULT 'paper'")
# Context tree tables for multi-layered memory management
conn.execute(
@@ -172,6 +175,7 @@ def log_trade(
exchange_code: str = "KRX",
selection_context: dict[str, any] | None = None,
decision_id: str | None = None,
mode: str = "paper",
) -> None:
"""Insert a trade record into the database.
@@ -187,6 +191,8 @@ def log_trade(
market: Market code
exchange_code: Exchange code
selection_context: Scanner selection data (RSI, volume_ratio, signal, score)
decision_id: Unique decision identifier for audit linking
mode: Trading mode ('paper' or 'live') for data separation
"""
# Serialize selection context to JSON
context_json = json.dumps(selection_context) if selection_context else None
@@ -195,9 +201,10 @@ def log_trade(
"""
INSERT INTO trades (
timestamp, stock_code, action, confidence, rationale,
quantity, price, pnl, market, exchange_code, selection_context, decision_id
quantity, price, pnl, market, exchange_code, selection_context, decision_id,
mode
)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""",
(
datetime.now(UTC).isoformat(),
@@ -212,6 +219,7 @@ def log_trade(
exchange_code,
context_json,
decision_id,
mode,
),
)
conn.commit()

View File

@@ -40,7 +40,7 @@ from src.evolution.daily_review import DailyReviewer
from src.evolution.optimizer import EvolutionOptimizer
from src.logging.decision_logger import DecisionLogger
from src.logging_config import setup_logging
from src.markets.schedule import MarketInfo, get_next_market_open, get_open_markets
from src.markets.schedule import MARKETS, MarketInfo, get_next_market_open, get_open_markets
from src.notifications.telegram_client import NotificationFilter, TelegramClient, TelegramCommandHandler
from src.strategy.models import DayPlaybook, MarketOutlook
from src.strategy.playbook_store import PlaybookStore
@@ -88,6 +88,129 @@ DAILY_TRADE_SESSIONS = 4 # Number of trading sessions per day
TRADE_SESSION_INTERVAL_HOURS = 6 # Hours between sessions
async def _retry_connection(coro_factory: Any, *args: Any, label: str = "", **kwargs: Any) -> Any:
"""Call an async function retrying on ConnectionError with exponential backoff.
Retries up to MAX_CONNECTION_RETRIES times (exclusive of the first attempt),
sleeping 2^attempt seconds between attempts. Use only for idempotent read
operations — never for order submission.
Args:
coro_factory: Async callable (method or function) to invoke.
*args: Positional arguments forwarded to coro_factory.
label: Human-readable label for log messages.
**kwargs: Keyword arguments forwarded to coro_factory.
Raises:
ConnectionError: If all retries are exhausted.
"""
for attempt in range(1, MAX_CONNECTION_RETRIES + 1):
try:
return await coro_factory(*args, **kwargs)
except ConnectionError as exc:
if attempt < MAX_CONNECTION_RETRIES:
wait_secs = 2 ** attempt
logger.warning(
"Connection error %s (attempt %d/%d), retrying in %ds: %s",
label,
attempt,
MAX_CONNECTION_RETRIES,
wait_secs,
exc,
)
await asyncio.sleep(wait_secs)
else:
logger.error(
"Connection error %s — all %d retries exhausted: %s",
label,
MAX_CONNECTION_RETRIES,
exc,
)
raise
async def sync_positions_from_broker(
broker: Any,
overseas_broker: Any,
db_conn: Any,
settings: "Settings",
) -> int:
"""Sync open positions from the live broker into the local DB at startup.
Fetches current holdings from the broker for all configured markets and
inserts a synthetic BUY record for any position that the DB does not
already know about. This prevents double-buy when positions were opened
in a previous session or entered manually outside the system.
Returns:
Number of new positions synced.
"""
synced = 0
seen_exchange_codes: set[str] = set()
for market_code in settings.enabled_market_list:
market = MARKETS.get(market_code)
if market is None:
continue
try:
if market.is_domestic:
balance_data = await broker.get_balance()
log_market = market_code # "KR"
else:
if market.exchange_code in seen_exchange_codes:
continue
seen_exchange_codes.add(market.exchange_code)
balance_data = await overseas_broker.get_overseas_balance(
market.exchange_code
)
log_market = market_code # e.g. "US_NASDAQ"
except ConnectionError as exc:
logger.warning(
"Startup sync: balance fetch failed for %s — skipping: %s",
market_code,
exc,
)
continue
held_codes = _extract_held_codes_from_balance(
balance_data, is_domestic=market.is_domestic
)
for stock_code in held_codes:
if get_open_position(db_conn, stock_code, log_market):
continue # already tracked
qty = _extract_held_qty_from_balance(
balance_data, stock_code, is_domestic=market.is_domestic
)
log_trade(
conn=db_conn,
stock_code=stock_code,
action="BUY",
confidence=0,
rationale="[startup-sync] Position detected from broker at startup",
quantity=qty,
price=0.0,
market=log_market,
exchange_code=market.exchange_code,
mode=settings.MODE,
)
logger.info(
"Startup sync: %s/%s recorded as open position (qty=%d)",
log_market,
stock_code,
qty,
)
synced += 1
if synced:
logger.info(
"Startup sync complete: %d position(s) synced from broker", synced
)
else:
logger.info("Startup sync: no new positions to sync from broker")
return synced
def _extract_symbol_from_holding(item: dict[str, Any]) -> str:
"""Extract symbol from overseas holding payload variants."""
for key in (
@@ -340,7 +463,13 @@ async def trading_cycle(
purchase_total = safe_float(balance_info.get("frcr_buy_amt_smtl", "0") or "0")
# Paper mode fallback: VTS overseas balance API often fails for many accounts.
if total_cash <= 0 and settings and settings.PAPER_OVERSEAS_CASH > 0:
# Only activate in paper mode — live mode must use real balance from KIS.
if (
total_cash <= 0
and settings
and settings.MODE == "paper"
and settings.PAPER_OVERSEAS_CASH > 0
):
logger.debug(
"Overseas cash balance is 0 for %s; using paper fallback %.2f USD",
market.exchange_code,
@@ -524,11 +653,11 @@ async def trading_cycle(
# BUY 결정 전 기존 포지션 체크 (중복 매수 방지)
if decision.action == "BUY":
existing_position = get_open_position(db_conn, stock_code, market.code)
if not existing_position and not market.is_domestic:
if not existing_position:
# SELL 지정가 접수 후 미체결 시 DB는 종료로 기록되나 브로커는 여전히 보유 중.
# 이중 매수 방지를 위해 라이브 브로커 잔고를 authoritative source로 사용.
# 국내/해외 모두 라이브 브로커 잔고를 authoritative source로 사용.
broker_qty = _extract_held_qty_from_balance(
balance_data, stock_code, is_domestic=False
balance_data, stock_code, is_domestic=market.is_domestic
)
if broker_qty > 0:
existing_position = {"price": 0.0, "quantity": broker_qty}
@@ -822,6 +951,7 @@ async def trading_cycle(
exchange_code=market.exchange_code,
selection_context=selection_context,
decision_id=decision_id,
mode=settings.MODE if settings else "paper",
)
# 7. Latency monitoring
@@ -860,18 +990,30 @@ async def run_daily_session(
telegram: TelegramClient,
settings: Settings,
smart_scanner: SmartVolatilityScanner | None = None,
) -> None:
daily_start_eval: float = 0.0,
) -> float:
"""Execute one daily trading session.
V2 proactive strategy: 1 Gemini call for playbook generation,
then local scenario evaluation per stock (0 API calls).
Args:
daily_start_eval: Portfolio evaluation at the start of the trading day.
Used to compute intra-day P&L for the Circuit Breaker.
Pass 0.0 on the first session of each day; the function will set
it from the first balance query and return it for subsequent
sessions.
Returns:
The daily_start_eval value that should be forwarded to the next
session of the same trading day.
"""
# Get currently open markets
open_markets = get_open_markets(settings.enabled_market_list)
if not open_markets:
logger.info("No markets open for this session")
return
return daily_start_eval
logger.info("Starting daily trading session for %d markets", len(open_markets))
@@ -957,11 +1099,18 @@ async def run_daily_session(
try:
if market.is_domestic:
current_price, price_change_pct, foreigner_net = (
await broker.get_current_price(stock_code)
await _retry_connection(
broker.get_current_price,
stock_code,
label=stock_code,
)
)
else:
price_data = await overseas_broker.get_overseas_price(
market.exchange_code, stock_code
price_data = await _retry_connection(
overseas_broker.get_overseas_price,
market.exchange_code,
stock_code,
label=f"{stock_code}@{market.exchange_code}",
)
current_price = safe_float(
price_data.get("output", {}).get("last", "0")
@@ -1012,9 +1161,27 @@ async def run_daily_session(
logger.warning("No valid stock data for market %s", market.code)
continue
# Get balance data once for the market
# Get balance data once for the market (read-only — safe to retry)
try:
if market.is_domestic:
balance_data = await _retry_connection(
broker.get_balance, label=f"balance:{market.code}"
)
else:
balance_data = await _retry_connection(
overseas_broker.get_overseas_balance,
market.exchange_code,
label=f"overseas_balance:{market.exchange_code}",
)
except ConnectionError as exc:
logger.error(
"Balance fetch failed for market %s after all retries — skipping market: %s",
market.code,
exc,
)
continue
if market.is_domestic:
balance_data = await broker.get_balance()
output2 = balance_data.get("output2", [{}])
total_eval = safe_float(
output2[0].get("tot_evlu_amt", "0")
@@ -1026,7 +1193,6 @@ async def run_daily_session(
output2[0].get("pchs_amt_smtl_amt", "0")
) if output2 else 0
else:
balance_data = await overseas_broker.get_overseas_balance(market.exchange_code)
output2 = balance_data.get("output2", [{}])
if isinstance(output2, list) and output2:
balance_info = output2[0]
@@ -1041,19 +1207,35 @@ async def run_daily_session(
balance_info.get("frcr_buy_amt_smtl", "0") or "0"
)
# Paper mode fallback: VTS overseas balance API often fails for many accounts.
if total_cash <= 0 and settings.PAPER_OVERSEAS_CASH > 0:
# Only activate in paper mode — live mode must use real balance from KIS.
if (
total_cash <= 0
and settings.MODE == "paper"
and settings.PAPER_OVERSEAS_CASH > 0
):
total_cash = settings.PAPER_OVERSEAS_CASH
# VTS overseas balance API often returns 0; use paper fallback.
if total_cash <= 0 and settings.PAPER_OVERSEAS_CASH > 0:
total_cash = settings.PAPER_OVERSEAS_CASH
# Capture the day's opening portfolio value on the first market processed
# in this session. Used to compute intra-day P&L for the CB instead of
# the cumulative purchase_total which spans the entire account history.
if daily_start_eval <= 0 and total_eval > 0:
daily_start_eval = total_eval
logger.info(
"Daily CB baseline set: total_eval=%.2f (first balance of the day)",
daily_start_eval,
)
# Calculate daily P&L %
pnl_pct = (
((total_eval - purchase_total) / purchase_total * 100)
if purchase_total > 0
else 0.0
)
# Daily P&L: compare current eval vs start-of-day eval.
# Falls back to purchase_total if daily_start_eval is unavailable (e.g. paper
# mode where balance API returns 0 for all values).
if daily_start_eval > 0:
pnl_pct = (total_eval - daily_start_eval) / daily_start_eval * 100
else:
pnl_pct = (
((total_eval - purchase_total) / purchase_total * 100)
if purchase_total > 0
else 0.0
)
portfolio_data = {
"portfolio_pnl_pct": pnl_pct,
"total_cash": total_cash,
@@ -1087,11 +1269,11 @@ async def run_daily_session(
# BUY 중복 방지: 브로커 잔고 기반 (미체결 SELL 리밋 주문 보호)
if decision.action == "BUY":
daily_existing = get_open_position(db_conn, stock_code, market.code)
if not daily_existing and not market.is_domestic:
if not daily_existing:
# SELL 지정가 접수 후 미체결 시 DB는 종료로 기록되나 브로커는 여전히 보유 중.
# 이중 매수 방지를 위해 라이브 브로커 잔고를 authoritative source로 사용.
# 국내/해외 모두 라이브 브로커 잔고를 authoritative source로 사용.
broker_qty = _extract_held_qty_from_balance(
balance_data, stock_code, is_domestic=False
balance_data, stock_code, is_domestic=market.is_domestic
)
if broker_qty > 0:
daily_existing = {"price": 0.0, "quantity": broker_qty}
@@ -1318,9 +1500,11 @@ async def run_daily_session(
market=market.code,
exchange_code=market.exchange_code,
decision_id=decision_id,
mode=settings.MODE,
)
logger.info("Daily trading session completed")
return daily_start_eval
async def _handle_market_close(
@@ -1938,6 +2122,12 @@ async def run(settings: Settings) -> None:
except Exception as exc:
logger.warning("System startup notification failed: %s", exc)
# Sync broker positions → DB to prevent double-buy on restart
try:
await sync_positions_from_broker(broker, overseas_broker, db_conn, settings)
except Exception as exc:
logger.warning("Startup position sync failed (non-fatal): %s", exc)
# Start command handler
try:
await command_handler.start_polling()
@@ -1956,13 +2146,26 @@ async def run(settings: Settings) -> None:
session_interval = settings.SESSION_INTERVAL_HOURS * 3600 # Convert to seconds
# daily_start_eval: portfolio eval captured at the first session of each
# trading day. Reset on calendar-date change so the CB measures only
# today's drawdown, not cumulative account history.
_cb_daily_start_eval: float = 0.0
_cb_last_date: str = ""
while not shutdown.is_set():
# Wait for trading to be unpaused
await pause_trading.wait()
_run_context_scheduler(context_scheduler, now=datetime.now(UTC))
# Reset intra-day CB baseline on a new calendar date
today_str = datetime.now(UTC).date().isoformat()
if today_str != _cb_last_date:
_cb_last_date = today_str
_cb_daily_start_eval = 0.0
logger.info("New trading day %s — daily CB baseline reset", today_str)
try:
await run_daily_session(
_cb_daily_start_eval = await run_daily_session(
broker,
overseas_broker,
scenario_engine,
@@ -1976,9 +2179,14 @@ async def run(settings: Settings) -> None:
telegram,
settings,
smart_scanner=smart_scanner,
daily_start_eval=_cb_daily_start_eval,
)
except CircuitBreakerTripped:
logger.critical("Circuit breaker tripped — shutting down")
await telegram.notify_circuit_breaker(
pnl_pct=settings.CIRCUIT_BREAKER_PCT,
threshold=settings.CIRCUIT_BREAKER_PCT,
)
shutdown.set()
break
except Exception as exc:
@@ -2296,6 +2504,8 @@ async def run(settings: Settings) -> None:
except TimeoutError:
pass # Normal — timeout means it's time for next cycle
finally:
# Notify shutdown before closing resources
await telegram.notify_system_shutdown("Normal shutdown")
# Clean up resources
await command_handler.stop_polling()
await broker.close()

View File

@@ -0,0 +1,114 @@
"""Auto-generated strategy: v20260220_210124
Generated at: 2026-02-20T21:01:24.706847+00:00
Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
"""
from __future__ import annotations
from typing import Any
from src.strategies.base import BaseStrategy
class Strategy_v20260220_210124(BaseStrategy):
"""Strategy: v20260220_210124"""
def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
import datetime
# --- Strategy Constants ---
# Minimum price for a stock to be considered for trading (avoids penny stocks)
MIN_PRICE = 5.0
# Momentum signal thresholds (stricter than previous failures)
MOMENTUM_PRICE_CHANGE_THRESHOLD = 7.0 # % price change
MOMENTUM_VOLUME_RATIO_THRESHOLD = 4.0 # X times average volume
# Oversold signal thresholds (more conservative)
OVERSOLD_RSI_THRESHOLD = 25.0 # RSI value (lower means more oversold)
# Confidence levels
CONFIDENCE_HOLD = 30
CONFIDENCE_BUY_OVERSOLD = 65
CONFIDENCE_BUY_MOMENTUM = 85
CONFIDENCE_BUY_STRONG_MOMENTUM = 90 # For higher-priced stocks with strong momentum
# Market hours in UTC (9:30 AM ET to 4:00 PM ET)
MARKET_OPEN_UTC = datetime.time(14, 30)
MARKET_CLOSE_UTC = datetime.time(21, 0)
# Volatile periods within market hours (UTC) to avoid
# First hour after open (14:30 UTC - 15:30 UTC)
VOLATILE_OPEN_END_UTC = datetime.time(15, 30)
# Last 30 minutes before close (20:30 UTC - 21:00 UTC)
VOLATILE_CLOSE_START_UTC = datetime.time(20, 30)
current_price = market_data.get('current_price')
price_change_pct = market_data.get('price_change_pct')
volume_ratio = market_data.get('volume_ratio') # Assumed pre-computed indicator
rsi = market_data.get('rsi') # Assumed pre-computed indicator
timestamp_str = market_data.get('timestamp')
action = "HOLD"
confidence = CONFIDENCE_HOLD
rationale = "Initial HOLD: No clear signal or conditions not met."
# --- 1. Basic Data Validation ---
if current_price is None or price_change_pct is None:
return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
"rationale": "Insufficient core data (price or price change) to evaluate."}
# --- 2. Price Filter: Avoid low-priced/penny stocks ---
if current_price < MIN_PRICE:
return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
"rationale": f"Avoiding low-priced stock (${current_price:.2f} < ${MIN_PRICE:.2f})."}
# --- 3. Time Filter: Only trade during core market hours ---
if timestamp_str:
try:
dt_object = datetime.datetime.fromisoformat(timestamp_str)
current_time_utc = dt_object.time()
if not (MARKET_OPEN_UTC <= current_time_utc < MARKET_CLOSE_UTC):
return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
"rationale": f"Avoiding trade outside core market hours ({current_time_utc} UTC)."}
if (MARKET_OPEN_UTC <= current_time_utc < VOLATILE_OPEN_END_UTC) or \
(VOLATILE_CLOSE_START_UTC <= current_time_utc < MARKET_CLOSE_UTC):
return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
"rationale": f"Avoiding trade during volatile market open/close periods ({current_time_utc} UTC)."}
except ValueError:
rationale += " (Warning: Malformed timestamp, time filters skipped)"
# --- Initialize signal states ---
has_momentum_buy_signal = False
has_oversold_buy_signal = False
# --- 4. Evaluate Enhanced Buy Signals ---
# Momentum Buy Signal
if volume_ratio is not None and \
price_change_pct > MOMENTUM_PRICE_CHANGE_THRESHOLD and \
volume_ratio > MOMENTUM_VOLUME_RATIO_THRESHOLD:
has_momentum_buy_signal = True
rationale = f"Momentum BUY: Price change {price_change_pct:.2f}%, Volume {volume_ratio:.2f}x."
confidence = CONFIDENCE_BUY_MOMENTUM
if current_price >= 10.0:
confidence = CONFIDENCE_BUY_STRONG_MOMENTUM
# Oversold Buy Signal
if rsi is not None and rsi < OVERSOLD_RSI_THRESHOLD:
has_oversold_buy_signal = True
if not has_momentum_buy_signal:
rationale = f"Oversold BUY: RSI {rsi:.2f}."
confidence = CONFIDENCE_BUY_OVERSOLD
if current_price >= 10.0:
confidence = min(CONFIDENCE_BUY_OVERSOLD + 5, 80)
# --- 5. Decision Logic ---
if has_momentum_buy_signal:
action = "BUY"
elif has_oversold_buy_signal:
action = "BUY"
return {"action": action, "confidence": confidence, "rationale": rationale}

View File

@@ -0,0 +1,97 @@
"""Auto-generated strategy: v20260220_210159
Generated at: 2026-02-20T21:01:59.391523+00:00
Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
"""
from __future__ import annotations
from typing import Any
from src.strategies.base import BaseStrategy
class Strategy_v20260220_210159(BaseStrategy):
"""Strategy: v20260220_210159"""
def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
import datetime
current_price = market_data.get('current_price')
price_change_pct = market_data.get('price_change_pct')
volume_ratio = market_data.get('volume_ratio')
rsi = market_data.get('rsi')
timestamp_str = market_data.get('timestamp')
market_name = market_data.get('market')
# Default action
action = "HOLD"
confidence = 0
rationale = "No strong signal or conditions not met."
# --- FAILURE PATTERN AVOIDANCE ---
# 1. Avoid low-priced/penny stocks
MIN_PRICE_THRESHOLD = 5.0 # USD
if current_price is not None and current_price < MIN_PRICE_THRESHOLD:
rationale = (
f"HOLD: Stock price (${current_price:.2f}) is below minimum threshold "
f"(${MIN_PRICE_THRESHOLD:.2f}). Past failures consistently involved low-priced stocks."
)
return {"action": action, "confidence": confidence, "rationale": rationale}
# 2. Avoid early market hour volatility
if timestamp_str:
try:
dt_obj = datetime.datetime.fromisoformat(timestamp_str)
utc_hour = dt_obj.hour
utc_minute = dt_obj.minute
if (utc_hour == 14 and utc_minute < 45) or (utc_hour == 13 and utc_minute >= 30):
rationale = (
f"HOLD: Trading during early market hours (UTC {utc_hour}:{utc_minute}), "
f"a period identified with past failures due to high volatility."
)
return {"action": action, "confidence": confidence, "rationale": rationale}
except ValueError:
pass
# --- IMPROVED BUY STRATEGY ---
# Momentum BUY signal
if volume_ratio is not None and price_change_pct is not None:
if price_change_pct > 7.0 and volume_ratio > 3.0:
action = "BUY"
confidence = 70
rationale = "Improved BUY: Momentum signal with high volume and above price threshold."
if market_name == 'US_AMEX':
confidence = max(55, confidence - 5)
rationale += " (Adjusted lower for AMEX market's higher risk profile)."
elif market_name == 'US_NASDAQ' and price_change_pct > 20:
confidence = max(50, confidence - 10)
rationale += " (Adjusted lower for aggressive NASDAQ momentum volatility)."
if price_change_pct > 15.0:
confidence = max(50, confidence - 5)
rationale += " (Caution: Very high daily price change, potential for reversal)."
return {"action": action, "confidence": confidence, "rationale": rationale}
# Oversold BUY signal
if rsi is not None and price_change_pct is not None:
if rsi < 30 and price_change_pct < -3.0:
action = "BUY"
confidence = 65
rationale = "Improved BUY: Oversold signal with recent decline and above price threshold."
if market_name == 'US_AMEX':
confidence = max(50, confidence - 5)
rationale += " (Adjusted lower for AMEX market's higher risk on oversold assets)."
if price_change_pct < -10.0:
confidence = max(45, confidence - 10)
rationale += " (Caution: Very steep decline, potential falling knife)."
return {"action": action, "confidence": confidence, "rationale": rationale}
# If no specific BUY signal, default to HOLD
return {"action": action, "confidence": confidence, "rationale": rationale}

View File

@@ -0,0 +1,88 @@
"""Auto-generated strategy: v20260220_210244
Generated at: 2026-02-20T21:02:44.387355+00:00
Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
"""
from __future__ import annotations
from typing import Any
from src.strategies.base import BaseStrategy
class Strategy_v20260220_210244(BaseStrategy):
"""Strategy: v20260220_210244"""
def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
from datetime import datetime
# Extract required data points safely
current_price = market_data.get("current_price")
price_change_pct = market_data.get("price_change_pct")
volume_ratio = market_data.get("volume_ratio")
rsi = market_data.get("rsi")
timestamp_str = market_data.get("timestamp")
market_name = market_data.get("market")
stock_code = market_data.get("stock_code", "UNKNOWN")
# Default action is HOLD with conservative confidence and rationale
action = "HOLD"
confidence = 50
rationale = f"No strong BUY signal for {stock_code} or awaiting more favorable conditions after avoiding known failure patterns."
# --- 1. Failure Pattern Avoidance Filters ---
# A. Avoid low-priced (penny) stocks
if current_price is not None and current_price < 5.0:
return {
"action": "HOLD",
"confidence": 50,
"rationale": f"AVOID {stock_code}: Stock price (${current_price:.2f}) is below minimum threshold ($5.00) for BUY action. Identified past failures on highly volatile, low-priced stocks."
}
# B. Avoid initiating BUY trades during identified high-volatility hours
if timestamp_str:
try:
trade_hour = datetime.fromisoformat(timestamp_str).hour
if trade_hour in [14, 20]:
return {
"action": "HOLD",
"confidence": 50,
"rationale": f"AVOID {stock_code}: Trading during historically volatile hour ({trade_hour} UTC) where previous BUYs resulted in losses. Prefer to observe market stability."
}
except ValueError:
pass
# C. Be cautious with extreme momentum spikes
if volume_ratio is not None and price_change_pct is not None:
if volume_ratio >= 9.0 and price_change_pct >= 15.0:
return {
"action": "HOLD",
"confidence": 50,
"rationale": f"AVOID {stock_code}: Extreme short-term momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Historical failures indicate buying into such rapid spikes often leads to reversals."
}
# D. Be cautious with "oversold" signals without further confirmation
if rsi is not None and rsi < 30:
return {
"action": "HOLD",
"confidence": 50,
"rationale": f"AVOID {stock_code}: Oversold signal (RSI={rsi:.1f}) detected. While often a BUY signal, historical failures on similar 'oversold' trades suggest waiting for stronger confirmation."
}
# --- 2. Improved BUY Signal Generation ---
if volume_ratio is not None and 2.0 <= volume_ratio < 9.0 and \
price_change_pct is not None and 2.0 <= price_change_pct < 15.0:
action = "BUY"
confidence = 70
rationale = f"BUY {stock_code}: Moderate momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Passed filters for price and extreme momentum, avoiding past failure patterns."
if market_name in ["US_AMEX", "US_NASDAQ"]:
confidence = max(60, confidence - 5)
rationale += f" Adjusted confidence for {market_name} market characteristics."
elif market_name == "US_NYSE":
confidence = max(65, confidence)
confidence = max(50, min(85, confidence))
return {"action": action, "confidence": confidence, "rationale": rationale}

View File

@@ -3,9 +3,11 @@
from __future__ import annotations
import sqlite3
import sys
import tempfile
from datetime import UTC, datetime, timedelta
from pathlib import Path
from unittest.mock import MagicMock, patch
import pytest
@@ -363,3 +365,435 @@ class TestHealthMonitor:
assert "timestamp" in report
assert "checks" in report
assert len(report["checks"]) == 3
# ---------------------------------------------------------------------------
# BackupExporter — additional coverage for previously uncovered branches
# ---------------------------------------------------------------------------
@pytest.fixture
def empty_db(tmp_path: Path) -> Path:
"""Create a temporary database with NO trade records."""
db_path = tmp_path / "empty_trades.db"
conn = sqlite3.connect(str(db_path))
conn.execute(
"""CREATE TABLE trades (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp TEXT NOT NULL,
stock_code TEXT NOT NULL,
action TEXT NOT NULL,
quantity INTEGER NOT NULL,
price REAL NOT NULL,
confidence INTEGER NOT NULL,
rationale TEXT,
pnl REAL DEFAULT 0.0
)"""
)
conn.commit()
conn.close()
return db_path
class TestBackupExporterAdditional:
"""Cover branches missed in the original TestBackupExporter suite."""
def test_export_all_default_formats(self, temp_db: Path, tmp_path: Path) -> None:
"""export_all with formats=None must default to JSON+CSV+Parquet path."""
exporter = BackupExporter(str(temp_db))
# formats=None triggers the default list assignment (line 62)
results = exporter.export_all(tmp_path / "out", formats=None, compress=False)
# JSON and CSV must always succeed; Parquet needs pyarrow
assert ExportFormat.JSON in results
assert ExportFormat.CSV in results
def test_export_all_logs_error_on_failure(
self, temp_db: Path, tmp_path: Path
) -> None:
"""export_all must log an error and continue when one format fails."""
exporter = BackupExporter(str(temp_db))
# Patch _export_format to raise on JSON, succeed on CSV
original = exporter._export_format
def failing_export(fmt, *args, **kwargs): # type: ignore[no-untyped-def]
if fmt == ExportFormat.JSON:
raise RuntimeError("simulated failure")
return original(fmt, *args, **kwargs)
exporter._export_format = failing_export # type: ignore[method-assign]
results = exporter.export_all(
tmp_path / "out",
formats=[ExportFormat.JSON, ExportFormat.CSV],
compress=False,
)
# JSON failed → not in results; CSV succeeded → in results
assert ExportFormat.JSON not in results
assert ExportFormat.CSV in results
def test_export_csv_empty_trades_no_compress(
self, empty_db: Path, tmp_path: Path
) -> None:
"""CSV export with no trades and compress=False must write header row only."""
exporter = BackupExporter(str(empty_db))
results = exporter.export_all(
tmp_path / "out",
formats=[ExportFormat.CSV],
compress=False,
)
assert ExportFormat.CSV in results
out = results[ExportFormat.CSV]
assert out.exists()
content = out.read_text()
assert "timestamp" in content
def test_export_csv_empty_trades_compressed(
self, empty_db: Path, tmp_path: Path
) -> None:
"""CSV export with no trades and compress=True must write gzipped header."""
import gzip
exporter = BackupExporter(str(empty_db))
results = exporter.export_all(
tmp_path / "out",
formats=[ExportFormat.CSV],
compress=True,
)
assert ExportFormat.CSV in results
out = results[ExportFormat.CSV]
assert out.suffix == ".gz"
with gzip.open(out, "rt", encoding="utf-8") as f:
content = f.read()
assert "timestamp" in content
def test_export_csv_with_data_compressed(
self, temp_db: Path, tmp_path: Path
) -> None:
"""CSV export with data and compress=True must write gzipped rows."""
import gzip
exporter = BackupExporter(str(temp_db))
results = exporter.export_all(
tmp_path / "out",
formats=[ExportFormat.CSV],
compress=True,
)
assert ExportFormat.CSV in results
out = results[ExportFormat.CSV]
with gzip.open(out, "rt", encoding="utf-8") as f:
lines = f.readlines()
# Header + 3 data rows
assert len(lines) == 4
def test_export_parquet_raises_import_error_without_pyarrow(
self, temp_db: Path, tmp_path: Path
) -> None:
"""Parquet export must raise ImportError when pyarrow is not installed."""
exporter = BackupExporter(str(temp_db))
with patch.dict(sys.modules, {"pyarrow": None, "pyarrow.parquet": None}):
try:
import pyarrow # noqa: F401
pytest.skip("pyarrow is installed; cannot test ImportError path")
except ImportError:
pass
results = exporter.export_all(
tmp_path / "out",
formats=[ExportFormat.PARQUET],
compress=False,
)
# Parquet export fails gracefully; result dict should not contain it
assert ExportFormat.PARQUET not in results
# ---------------------------------------------------------------------------
# CloudStorage — mocked boto3 tests
# ---------------------------------------------------------------------------
@pytest.fixture
def mock_boto3_module():
"""Inject a fake boto3 into sys.modules for the duration of the test."""
mock = MagicMock()
with patch.dict(sys.modules, {"boto3": mock}):
yield mock
@pytest.fixture
def s3_config():
"""Minimal S3Config for tests."""
from src.backup.cloud_storage import S3Config
return S3Config(
endpoint_url="http://localhost:9000",
access_key="minioadmin",
secret_key="minioadmin",
bucket_name="test-bucket",
region="us-east-1",
)
class TestCloudStorage:
"""Test CloudStorage using mocked boto3."""
def test_init_creates_s3_client(self, mock_boto3_module, s3_config) -> None:
"""CloudStorage.__init__ must call boto3.client with the correct args."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
mock_boto3_module.client.assert_called_once()
call_kwargs = mock_boto3_module.client.call_args[1]
assert call_kwargs["aws_access_key_id"] == "minioadmin"
assert call_kwargs["aws_secret_access_key"] == "minioadmin"
assert storage.config == s3_config
def test_init_raises_if_boto3_missing(self, s3_config) -> None:
"""CloudStorage.__init__ must raise ImportError when boto3 is absent."""
with patch.dict(sys.modules, {"boto3": None}): # type: ignore[dict-item]
with pytest.raises((ImportError, TypeError)):
# Re-import to trigger the try/except inside __init__
import importlib
import src.backup.cloud_storage as m
importlib.reload(m)
m.CloudStorage(s3_config)
def test_upload_file_success(
self, mock_boto3_module, s3_config, tmp_path: Path
) -> None:
"""upload_file must call client.upload_file and return the object key."""
from src.backup.cloud_storage import CloudStorage
test_file = tmp_path / "backup.json.gz"
test_file.write_bytes(b"data")
storage = CloudStorage(s3_config)
key = storage.upload_file(test_file, object_key="backups/backup.json.gz")
assert key == "backups/backup.json.gz"
storage.client.upload_file.assert_called_once()
def test_upload_file_default_key(
self, mock_boto3_module, s3_config, tmp_path: Path
) -> None:
"""upload_file without object_key must use the filename as key."""
from src.backup.cloud_storage import CloudStorage
test_file = tmp_path / "myfile.gz"
test_file.write_bytes(b"data")
storage = CloudStorage(s3_config)
key = storage.upload_file(test_file)
assert key == "myfile.gz"
def test_upload_file_not_found(
self, mock_boto3_module, s3_config, tmp_path: Path
) -> None:
"""upload_file must raise FileNotFoundError for missing files."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
with pytest.raises(FileNotFoundError):
storage.upload_file(tmp_path / "nonexistent.gz")
def test_upload_file_propagates_client_error(
self, mock_boto3_module, s3_config, tmp_path: Path
) -> None:
"""upload_file must re-raise exceptions from the boto3 client."""
from src.backup.cloud_storage import CloudStorage
test_file = tmp_path / "backup.gz"
test_file.write_bytes(b"data")
storage = CloudStorage(s3_config)
storage.client.upload_file.side_effect = RuntimeError("network error")
with pytest.raises(RuntimeError, match="network error"):
storage.upload_file(test_file)
def test_download_file_success(
self, mock_boto3_module, s3_config, tmp_path: Path
) -> None:
"""download_file must call client.download_file and return local path."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
dest = tmp_path / "downloads" / "backup.gz"
result = storage.download_file("backups/backup.gz", dest)
assert result == dest
storage.client.download_file.assert_called_once()
def test_download_file_propagates_error(
self, mock_boto3_module, s3_config, tmp_path: Path
) -> None:
"""download_file must re-raise exceptions from the boto3 client."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.download_file.side_effect = RuntimeError("timeout")
with pytest.raises(RuntimeError, match="timeout"):
storage.download_file("key", tmp_path / "dest.gz")
def test_list_files_returns_objects(
self, mock_boto3_module, s3_config
) -> None:
"""list_files must return parsed file metadata from S3 response."""
from datetime import timezone
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.list_objects_v2.return_value = {
"Contents": [
{
"Key": "backups/a.gz",
"Size": 1024,
"LastModified": datetime(2026, 1, 1, tzinfo=timezone.utc),
"ETag": '"abc123"',
}
]
}
files = storage.list_files(prefix="backups/")
assert len(files) == 1
assert files[0]["key"] == "backups/a.gz"
assert files[0]["size_bytes"] == 1024
def test_list_files_empty_bucket(
self, mock_boto3_module, s3_config
) -> None:
"""list_files must return empty list when bucket has no objects."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.list_objects_v2.return_value = {}
files = storage.list_files()
assert files == []
def test_list_files_propagates_error(
self, mock_boto3_module, s3_config
) -> None:
"""list_files must re-raise exceptions from the boto3 client."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.list_objects_v2.side_effect = RuntimeError("auth error")
with pytest.raises(RuntimeError):
storage.list_files()
def test_delete_file_success(
self, mock_boto3_module, s3_config
) -> None:
"""delete_file must call client.delete_object with the correct key."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.delete_file("backups/old.gz")
storage.client.delete_object.assert_called_once_with(
Bucket="test-bucket", Key="backups/old.gz"
)
def test_delete_file_propagates_error(
self, mock_boto3_module, s3_config
) -> None:
"""delete_file must re-raise exceptions from the boto3 client."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.delete_object.side_effect = RuntimeError("permission denied")
with pytest.raises(RuntimeError):
storage.delete_file("backups/old.gz")
def test_get_storage_stats_success(
self, mock_boto3_module, s3_config
) -> None:
"""get_storage_stats must aggregate file sizes correctly."""
from datetime import timezone
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.list_objects_v2.return_value = {
"Contents": [
{
"Key": "a.gz",
"Size": 1024 * 1024,
"LastModified": datetime(2026, 1, 1, tzinfo=timezone.utc),
"ETag": '"x"',
},
{
"Key": "b.gz",
"Size": 1024 * 1024,
"LastModified": datetime(2026, 1, 2, tzinfo=timezone.utc),
"ETag": '"y"',
},
]
}
stats = storage.get_storage_stats()
assert stats["total_files"] == 2
assert stats["total_size_bytes"] == 2 * 1024 * 1024
assert stats["total_size_mb"] == pytest.approx(2.0)
def test_get_storage_stats_on_error(
self, mock_boto3_module, s3_config
) -> None:
"""get_storage_stats must return error dict without raising on failure."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.list_objects_v2.side_effect = RuntimeError("no connection")
stats = storage.get_storage_stats()
assert "error" in stats
assert stats["total_files"] == 0
def test_verify_connection_success(
self, mock_boto3_module, s3_config
) -> None:
"""verify_connection must return True when head_bucket succeeds."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
result = storage.verify_connection()
assert result is True
def test_verify_connection_failure(
self, mock_boto3_module, s3_config
) -> None:
"""verify_connection must return False when head_bucket raises."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.head_bucket.side_effect = RuntimeError("no such bucket")
result = storage.verify_connection()
assert result is False
def test_enable_versioning(
self, mock_boto3_module, s3_config
) -> None:
"""enable_versioning must call put_bucket_versioning."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.enable_versioning()
storage.client.put_bucket_versioning.assert_called_once()
def test_enable_versioning_propagates_error(
self, mock_boto3_module, s3_config
) -> None:
"""enable_versioning must re-raise exceptions from the boto3 client."""
from src.backup.cloud_storage import CloudStorage
storage = CloudStorage(s3_config)
storage.client.put_bucket_versioning.side_effect = RuntimeError("denied")
with pytest.raises(RuntimeError):
storage.enable_versioning()

View File

@@ -572,4 +572,156 @@ class TestSendOrderTickRounding:
order_call = mock_post.call_args_list[1]
body = order_call[1].get("json", {})
assert body["ORD_DVSN"] == "01"
assert body["ORD_UNPR"] == "0"
# ---------------------------------------------------------------------------
# TR_ID live/paper branching (issues #201, #202, #203)
# ---------------------------------------------------------------------------
class TestTRIDBranchingDomestic:
"""get_balance and send_order must use correct TR_ID for live vs paper mode."""
def _make_broker(self, settings, mode: str) -> KISBroker:
from src.config import Settings
s = Settings(
KIS_APP_KEY=settings.KIS_APP_KEY,
KIS_APP_SECRET=settings.KIS_APP_SECRET,
KIS_ACCOUNT_NO=settings.KIS_ACCOUNT_NO,
GEMINI_API_KEY=settings.GEMINI_API_KEY,
DB_PATH=":memory:",
ENABLED_MARKETS="KR",
MODE=mode,
)
b = KISBroker(s)
b._access_token = "tok"
b._token_expires_at = float("inf")
b._rate_limiter.acquire = AsyncMock()
return b
@pytest.mark.asyncio
async def test_get_balance_paper_uses_vttc8434r(self, settings) -> None:
broker = self._make_broker(settings, "paper")
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(
return_value={"output1": [], "output2": {}}
)
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
await broker.get_balance()
headers = mock_get.call_args[1].get("headers", {})
assert headers["tr_id"] == "VTTC8434R"
@pytest.mark.asyncio
async def test_get_balance_live_uses_tttc8434r(self, settings) -> None:
broker = self._make_broker(settings, "live")
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(
return_value={"output1": [], "output2": {}}
)
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
await broker.get_balance()
headers = mock_get.call_args[1].get("headers", {})
assert headers["tr_id"] == "TTTC8434R"
@pytest.mark.asyncio
async def test_send_order_buy_paper_uses_vttc0012u(self, settings) -> None:
broker = self._make_broker(settings, "paper")
mock_hash = AsyncMock()
mock_hash.status = 200
mock_hash.json = AsyncMock(return_value={"HASH": "h"})
mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
mock_hash.__aexit__ = AsyncMock(return_value=False)
mock_order = AsyncMock()
mock_order.status = 200
mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
mock_order.__aenter__ = AsyncMock(return_value=mock_order)
mock_order.__aexit__ = AsyncMock(return_value=False)
with patch(
"aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
) as mock_post:
await broker.send_order("005930", "BUY", 1)
order_headers = mock_post.call_args_list[1][1].get("headers", {})
assert order_headers["tr_id"] == "VTTC0012U"
@pytest.mark.asyncio
async def test_send_order_buy_live_uses_tttc0012u(self, settings) -> None:
broker = self._make_broker(settings, "live")
mock_hash = AsyncMock()
mock_hash.status = 200
mock_hash.json = AsyncMock(return_value={"HASH": "h"})
mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
mock_hash.__aexit__ = AsyncMock(return_value=False)
mock_order = AsyncMock()
mock_order.status = 200
mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
mock_order.__aenter__ = AsyncMock(return_value=mock_order)
mock_order.__aexit__ = AsyncMock(return_value=False)
with patch(
"aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
) as mock_post:
await broker.send_order("005930", "BUY", 1)
order_headers = mock_post.call_args_list[1][1].get("headers", {})
assert order_headers["tr_id"] == "TTTC0012U"
@pytest.mark.asyncio
async def test_send_order_sell_paper_uses_vttc0011u(self, settings) -> None:
broker = self._make_broker(settings, "paper")
mock_hash = AsyncMock()
mock_hash.status = 200
mock_hash.json = AsyncMock(return_value={"HASH": "h"})
mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
mock_hash.__aexit__ = AsyncMock(return_value=False)
mock_order = AsyncMock()
mock_order.status = 200
mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
mock_order.__aenter__ = AsyncMock(return_value=mock_order)
mock_order.__aexit__ = AsyncMock(return_value=False)
with patch(
"aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
) as mock_post:
await broker.send_order("005930", "SELL", 1)
order_headers = mock_post.call_args_list[1][1].get("headers", {})
assert order_headers["tr_id"] == "VTTC0011U"
@pytest.mark.asyncio
async def test_send_order_sell_live_uses_tttc0011u(self, settings) -> None:
broker = self._make_broker(settings, "live")
mock_hash = AsyncMock()
mock_hash.status = 200
mock_hash.json = AsyncMock(return_value={"HASH": "h"})
mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
mock_hash.__aexit__ = AsyncMock(return_value=False)
mock_order = AsyncMock()
mock_order.status = 200
mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
mock_order.__aenter__ = AsyncMock(return_value=mock_order)
mock_order.__aexit__ = AsyncMock(return_value=False)
with patch(
"aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
) as mock_post:
await broker.send_order("005930", "SELL", 1)
order_headers = mock_post.call_args_list[1][1].get("headers", {})
assert order_headers["tr_id"] == "TTTC0011U"

View File

@@ -10,6 +10,7 @@ import pytest
from src.context.aggregator import ContextAggregator
from src.context.layer import LAYER_CONFIG, ContextLayer
from src.context.store import ContextStore
from src.context.summarizer import ContextSummarizer
from src.db import init_db, log_trade
@@ -370,3 +371,259 @@ class TestLayerMetadata:
# L1 aggregates from L2
assert LAYER_CONFIG[ContextLayer.L1_LEGACY].aggregation_source == ContextLayer.L2_ANNUAL
# ---------------------------------------------------------------------------
# ContextSummarizer tests
# ---------------------------------------------------------------------------
@pytest.fixture
def summarizer(db_conn: sqlite3.Connection) -> ContextSummarizer:
"""Provide a ContextSummarizer backed by an in-memory store."""
return ContextSummarizer(ContextStore(db_conn))
class TestContextSummarizer:
"""Test suite for ContextSummarizer."""
# ------------------------------------------------------------------
# summarize_numeric_values
# ------------------------------------------------------------------
def test_summarize_empty_values(self, summarizer: ContextSummarizer) -> None:
"""Empty list must return SummaryStats with count=0 and no other fields."""
stats = summarizer.summarize_numeric_values([])
assert stats.count == 0
assert stats.mean is None
assert stats.min is None
assert stats.max is None
def test_summarize_single_value(self, summarizer: ContextSummarizer) -> None:
"""Single-element list must return correct stats with std=0 and trend=flat."""
stats = summarizer.summarize_numeric_values([42.0])
assert stats.count == 1
assert stats.mean == 42.0
assert stats.std == 0.0
assert stats.trend == "flat"
def test_summarize_upward_trend(self, summarizer: ContextSummarizer) -> None:
"""Increasing values must produce trend='up'."""
values = [1.0, 2.0, 3.0, 10.0, 20.0, 30.0]
stats = summarizer.summarize_numeric_values(values)
assert stats.trend == "up"
def test_summarize_downward_trend(self, summarizer: ContextSummarizer) -> None:
"""Decreasing values must produce trend='down'."""
values = [30.0, 20.0, 10.0, 3.0, 2.0, 1.0]
stats = summarizer.summarize_numeric_values(values)
assert stats.trend == "down"
def test_summarize_flat_trend(self, summarizer: ContextSummarizer) -> None:
"""Stable values must produce trend='flat'."""
values = [100.0, 100.1, 99.9, 100.0, 100.2, 99.8]
stats = summarizer.summarize_numeric_values(values)
assert stats.trend == "flat"
# ------------------------------------------------------------------
# summarize_layer
# ------------------------------------------------------------------
def test_summarize_layer_no_data(
self, summarizer: ContextSummarizer
) -> None:
"""summarize_layer with no data must return the 'No data' sentinel."""
result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
assert result["count"] == 0
assert "No data" in result["summary"]
def test_summarize_layer_numeric(
self, summarizer: ContextSummarizer, db_conn: sqlite3.Connection
) -> None:
"""summarize_layer must collect numeric values and produce stats."""
store = summarizer.store
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "total_pnl", 100.0)
store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "total_pnl", 200.0)
result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
assert "total_entries" in result
def test_summarize_layer_with_dict_values(
self, summarizer: ContextSummarizer
) -> None:
"""summarize_layer must handle dict values by extracting numeric subkeys."""
store = summarizer.store
# set_context serialises the value as JSON, so passing a dict works
store.set_context(
ContextLayer.L6_DAILY, "2026-02-01", "metrics",
{"win_rate": 65.0, "label": "good"}
)
result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
assert "total_entries" in result
# numeric subkey "win_rate" should appear as "metrics.win_rate"
assert "metrics.win_rate" in result
def test_summarize_layer_with_string_values(
self, summarizer: ContextSummarizer
) -> None:
"""summarize_layer must count string values separately."""
store = summarizer.store
# set_context stores string values as JSON-encoded strings
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "outlook", "BULLISH")
result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
# String fields contribute a `<key>_count` entry
assert "outlook_count" in result
# ------------------------------------------------------------------
# rolling_window_summary
# ------------------------------------------------------------------
def test_rolling_window_summary_basic(
self, summarizer: ContextSummarizer
) -> None:
"""rolling_window_summary must return the expected structure."""
store = summarizer.store
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 500.0)
result = summarizer.rolling_window_summary(ContextLayer.L6_DAILY)
assert "window_days" in result
assert "recent_data" in result
assert "historical_summary" in result
def test_rolling_window_summary_no_older_data(
self, summarizer: ContextSummarizer
) -> None:
"""rolling_window_summary with summarize_older=False skips history."""
result = summarizer.rolling_window_summary(
ContextLayer.L6_DAILY, summarize_older=False
)
assert result["historical_summary"] == {}
# ------------------------------------------------------------------
# aggregate_to_higher_layer
# ------------------------------------------------------------------
def test_aggregate_to_higher_layer_mean(
self, summarizer: ContextSummarizer
) -> None:
"""aggregate_to_higher_layer with 'mean' via dict subkeys returns average."""
store = summarizer.store
# Use different outer keys but same inner metric key so get_all_contexts
# returns multiple rows with the target subkey.
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
result = summarizer.aggregate_to_higher_layer(
ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "mean"
)
assert result == pytest.approx(150.0)
def test_aggregate_to_higher_layer_sum(
self, summarizer: ContextSummarizer
) -> None:
"""aggregate_to_higher_layer with 'sum' must return the total."""
store = summarizer.store
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
result = summarizer.aggregate_to_higher_layer(
ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "sum"
)
assert result == pytest.approx(300.0)
def test_aggregate_to_higher_layer_max(
self, summarizer: ContextSummarizer
) -> None:
"""aggregate_to_higher_layer with 'max' must return the maximum."""
store = summarizer.store
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
result = summarizer.aggregate_to_higher_layer(
ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "max"
)
assert result == pytest.approx(200.0)
def test_aggregate_to_higher_layer_min(
self, summarizer: ContextSummarizer
) -> None:
"""aggregate_to_higher_layer with 'min' must return the minimum."""
store = summarizer.store
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
result = summarizer.aggregate_to_higher_layer(
ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "min"
)
assert result == pytest.approx(100.0)
def test_aggregate_to_higher_layer_no_data(
self, summarizer: ContextSummarizer
) -> None:
"""aggregate_to_higher_layer with no matching key must return None."""
result = summarizer.aggregate_to_higher_layer(
ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "nonexistent", "mean"
)
assert result is None
def test_aggregate_to_higher_layer_unknown_func_defaults_to_mean(
self, summarizer: ContextSummarizer
) -> None:
"""Unknown aggregation function must fall back to mean."""
store = summarizer.store
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
result = summarizer.aggregate_to_higher_layer(
ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "unknown_func"
)
assert result == pytest.approx(150.0)
# ------------------------------------------------------------------
# create_compact_summary + format_summary_for_prompt
# ------------------------------------------------------------------
def test_create_compact_summary(
self, summarizer: ContextSummarizer
) -> None:
"""create_compact_summary must produce a dict keyed by layer value."""
store = summarizer.store
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 100.0)
result = summarizer.create_compact_summary([ContextLayer.L6_DAILY])
assert ContextLayer.L6_DAILY.value in result
def test_format_summary_for_prompt_with_numeric_metrics(
self, summarizer: ContextSummarizer
) -> None:
"""format_summary_for_prompt must render avg/trend fields."""
store = summarizer.store
store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 100.0)
store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "pnl", 200.0)
compact = summarizer.create_compact_summary([ContextLayer.L6_DAILY])
text = summarizer.format_summary_for_prompt(compact)
assert isinstance(text, str)
def test_format_summary_for_prompt_skips_empty_layers(
self, summarizer: ContextSummarizer
) -> None:
"""format_summary_for_prompt must skip layers with no metrics."""
summary = {ContextLayer.L6_DAILY.value: {}}
text = summarizer.format_summary_for_prompt(summary)
assert text == ""
def test_format_summary_non_dict_value(
self, summarizer: ContextSummarizer
) -> None:
"""format_summary_for_prompt must render non-dict values as plain text."""
summary = {
"daily": {
"plain_count": 42,
}
}
text = summarizer.format_summary_for_prompt(summary)
assert "plain_count" in text
assert "42" in text

View File

@@ -95,3 +95,101 @@ def test_wal_mode_not_applied_to_memory_db() -> None:
# In-memory DBs default to 'memory' journal mode
assert mode != "wal", "WAL should not be set on in-memory database"
conn.close()
# ---------------------------------------------------------------------------
# mode column tests (issue #212)
# ---------------------------------------------------------------------------
def test_log_trade_stores_mode_paper() -> None:
"""log_trade must persist mode='paper' in the trades table."""
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="005930",
action="BUY",
confidence=85,
rationale="test",
mode="paper",
)
row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
assert row is not None
assert row[0] == "paper"
def test_log_trade_stores_mode_live() -> None:
"""log_trade must persist mode='live' in the trades table."""
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="005930",
action="BUY",
confidence=85,
rationale="test",
mode="live",
)
row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
assert row is not None
assert row[0] == "live"
def test_log_trade_default_mode_is_paper() -> None:
"""log_trade without explicit mode must default to 'paper'."""
conn = init_db(":memory:")
log_trade(
conn=conn,
stock_code="005930",
action="HOLD",
confidence=50,
rationale="test",
)
row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
assert row is not None
assert row[0] == "paper"
def test_mode_column_exists_in_schema() -> None:
"""trades table must have a mode column after init_db."""
conn = init_db(":memory:")
cursor = conn.execute("PRAGMA table_info(trades)")
columns = {row[1] for row in cursor.fetchall()}
assert "mode" in columns
def test_mode_migration_adds_column_to_existing_db() -> None:
"""init_db must add mode column to existing DBs that lack it (migration)."""
import sqlite3
with tempfile.NamedTemporaryFile(suffix=".db", delete=False) as f:
db_path = f.name
try:
# Create DB without mode column (simulate old schema)
old_conn = sqlite3.connect(db_path)
old_conn.execute(
"""CREATE TABLE trades (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp TEXT NOT NULL,
stock_code TEXT NOT NULL,
action TEXT NOT NULL,
confidence INTEGER NOT NULL,
rationale TEXT,
quantity INTEGER,
price REAL,
pnl REAL DEFAULT 0.0,
market TEXT DEFAULT 'KR',
exchange_code TEXT DEFAULT 'KRX',
decision_id TEXT
)"""
)
old_conn.commit()
old_conn.close()
# Run init_db — should add mode column via migration
conn = init_db(db_path)
cursor = conn.execute("PRAGMA table_info(trades)")
columns = {row[1] for row in cursor.fetchall()}
assert "mode" in columns
conn.close()
finally:
os.unlink(db_path)

View File

@@ -0,0 +1,117 @@
"""Tests for JSON structured logging configuration."""
from __future__ import annotations
import json
import logging
import sys
from src.logging_config import JSONFormatter, setup_logging
class TestJSONFormatter:
"""Test JSONFormatter output."""
def test_basic_log_record(self) -> None:
"""JSONFormatter must emit valid JSON with required fields."""
formatter = JSONFormatter()
record = logging.LogRecord(
name="test.logger",
level=logging.INFO,
pathname="",
lineno=0,
msg="Hello %s",
args=("world",),
exc_info=None,
)
output = formatter.format(record)
data = json.loads(output)
assert data["level"] == "INFO"
assert data["logger"] == "test.logger"
assert data["message"] == "Hello world"
assert "timestamp" in data
def test_includes_exception_info(self) -> None:
"""JSONFormatter must include exception info when present."""
formatter = JSONFormatter()
try:
raise ValueError("test error")
except ValueError:
exc_info = sys.exc_info()
record = logging.LogRecord(
name="test",
level=logging.ERROR,
pathname="",
lineno=0,
msg="oops",
args=(),
exc_info=exc_info,
)
output = formatter.format(record)
data = json.loads(output)
assert "exception" in data
assert "ValueError" in data["exception"]
def test_extra_trading_fields_included(self) -> None:
"""Extra trading fields attached to the record must appear in JSON."""
formatter = JSONFormatter()
record = logging.LogRecord(
name="test",
level=logging.INFO,
pathname="",
lineno=0,
msg="trade",
args=(),
exc_info=None,
)
record.stock_code = "005930" # type: ignore[attr-defined]
record.action = "BUY" # type: ignore[attr-defined]
record.confidence = 85 # type: ignore[attr-defined]
record.pnl_pct = -1.5 # type: ignore[attr-defined]
record.order_amount = 1_000_000 # type: ignore[attr-defined]
output = formatter.format(record)
data = json.loads(output)
assert data["stock_code"] == "005930"
assert data["action"] == "BUY"
assert data["confidence"] == 85
assert data["pnl_pct"] == -1.5
assert data["order_amount"] == 1_000_000
def test_none_extra_fields_excluded(self) -> None:
"""Extra fields that are None must not appear in JSON output."""
formatter = JSONFormatter()
record = logging.LogRecord(
name="test",
level=logging.INFO,
pathname="",
lineno=0,
msg="no extras",
args=(),
exc_info=None,
)
output = formatter.format(record)
data = json.loads(output)
assert "stock_code" not in data
assert "action" not in data
assert "confidence" not in data
class TestSetupLogging:
"""Test setup_logging function."""
def test_configures_root_logger(self) -> None:
"""setup_logging must attach a JSON handler to the root logger."""
setup_logging(level=logging.DEBUG)
root = logging.getLogger()
json_handlers = [
h for h in root.handlers if isinstance(h.formatter, JSONFormatter)
]
assert len(json_handlers) == 1
assert root.level == logging.DEBUG
def test_avoids_duplicate_handlers(self) -> None:
"""Calling setup_logging twice must not add duplicate handlers."""
setup_logging()
setup_logging()
root = logging.getLogger()
assert len(root.handlers) == 1

View File

@@ -18,10 +18,13 @@ from src.main import (
_extract_held_codes_from_balance,
_extract_held_qty_from_balance,
_handle_market_close,
_retry_connection,
_run_context_scheduler,
_run_evolution_loop,
_start_dashboard_server,
run_daily_session,
safe_float,
sync_positions_from_broker,
trading_cycle,
)
from src.strategy.models import (
@@ -3183,3 +3186,609 @@ class TestOverseasBrokerIntegration:
# DB도 브로커도 보유 없음 → BUY 주문이 실행되어야 함 (회귀 테스트)
overseas_broker.send_overseas_order.assert_called_once()
# ---------------------------------------------------------------------------
# _retry_connection — unit tests (issue #209)
# ---------------------------------------------------------------------------
class TestRetryConnection:
"""Unit tests for the _retry_connection helper (issue #209)."""
@pytest.mark.asyncio
async def test_success_on_first_attempt(self) -> None:
"""Returns the result immediately when the first call succeeds."""
async def ok() -> str:
return "data"
result = await _retry_connection(ok, label="test")
assert result == "data"
@pytest.mark.asyncio
async def test_succeeds_after_one_connection_error(self) -> None:
"""Retries once on ConnectionError and returns result on 2nd attempt."""
call_count = 0
async def flaky() -> str:
nonlocal call_count
call_count += 1
if call_count < 2:
raise ConnectionError("timeout")
return "ok"
with patch("src.main.asyncio.sleep") as mock_sleep:
mock_sleep.return_value = None
result = await _retry_connection(flaky, label="flaky")
assert result == "ok"
assert call_count == 2
mock_sleep.assert_called_once()
@pytest.mark.asyncio
async def test_raises_after_all_retries_exhausted(self) -> None:
"""Raises ConnectionError after MAX_CONNECTION_RETRIES attempts."""
from src.main import MAX_CONNECTION_RETRIES
call_count = 0
async def always_fail() -> None:
nonlocal call_count
call_count += 1
raise ConnectionError("unreachable")
with patch("src.main.asyncio.sleep") as mock_sleep:
mock_sleep.return_value = None
with pytest.raises(ConnectionError, match="unreachable"):
await _retry_connection(always_fail, label="always_fail")
assert call_count == MAX_CONNECTION_RETRIES
@pytest.mark.asyncio
async def test_passes_args_and_kwargs_to_factory(self) -> None:
"""Forwards positional and keyword arguments to the callable."""
received: dict = {}
async def capture(a: int, b: int, *, key: str) -> str:
received["a"] = a
received["b"] = b
received["key"] = key
return "captured"
result = await _retry_connection(capture, 1, 2, key="val", label="test")
assert result == "captured"
assert received == {"a": 1, "b": 2, "key": "val"}
@pytest.mark.asyncio
async def test_non_connection_error_not_retried(self) -> None:
"""Non-ConnectionError exceptions propagate immediately without retry."""
call_count = 0
async def bad_input() -> None:
nonlocal call_count
call_count += 1
raise ValueError("bad data")
with pytest.raises(ValueError, match="bad data"):
await _retry_connection(bad_input, label="bad")
assert call_count == 1 # No retry for non-ConnectionError
# run_daily_session — daily CB baseline (daily_start_eval) tests (issue #207)
# ---------------------------------------------------------------------------
class TestDailyCBBaseline:
"""Tests for run_daily_session's daily_start_eval (CB baseline) behaviour.
Issue #207: CB P&L should be computed relative to the portfolio value at
the start of each trading day, not the cumulative purchase_total.
"""
def _make_settings(self) -> Settings:
return Settings(
KIS_APP_KEY="test-key",
KIS_APP_SECRET="test-secret",
KIS_ACCOUNT_NO="12345678-01",
GEMINI_API_KEY="test-gemini",
MODE="paper",
PAPER_OVERSEAS_CASH=0,
)
def _make_domestic_balance(
self, tot_evlu_amt: float = 0.0, dnca_tot_amt: float = 50000.0
) -> dict:
return {
"output1": [],
"output2": [
{
"tot_evlu_amt": str(tot_evlu_amt),
"dnca_tot_amt": str(dnca_tot_amt),
"pchs_amt_smtl_amt": "40000.0",
}
],
}
@pytest.mark.asyncio
async def test_returns_daily_start_eval_when_no_markets_open(self) -> None:
"""run_daily_session returns the unchanged daily_start_eval when no markets are open."""
with patch("src.main.get_open_markets", return_value=[]):
result = await run_daily_session(
broker=MagicMock(),
overseas_broker=MagicMock(),
scenario_engine=MagicMock(),
playbook_store=MagicMock(),
pre_market_planner=MagicMock(),
risk=MagicMock(),
db_conn=init_db(":memory:"),
decision_logger=MagicMock(),
context_store=MagicMock(),
criticality_assessor=MagicMock(),
telegram=MagicMock(),
settings=self._make_settings(),
smart_scanner=None,
daily_start_eval=12345.0,
)
assert result == 12345.0
@pytest.mark.asyncio
async def test_returns_zero_when_no_markets_and_no_baseline(self) -> None:
"""run_daily_session returns 0.0 when no markets are open and daily_start_eval=0."""
with patch("src.main.get_open_markets", return_value=[]):
result = await run_daily_session(
broker=MagicMock(),
overseas_broker=MagicMock(),
scenario_engine=MagicMock(),
playbook_store=MagicMock(),
pre_market_planner=MagicMock(),
risk=MagicMock(),
db_conn=init_db(":memory:"),
decision_logger=MagicMock(),
context_store=MagicMock(),
criticality_assessor=MagicMock(),
telegram=MagicMock(),
settings=self._make_settings(),
smart_scanner=None,
daily_start_eval=0.0,
)
assert result == 0.0
@pytest.mark.asyncio
async def test_captures_total_eval_as_baseline_on_first_session(self) -> None:
"""When daily_start_eval=0 and balance returns a positive total_eval, the returned
value equals total_eval (the captured baseline for the day)."""
from src.analysis.smart_scanner import ScanCandidate
settings = self._make_settings()
broker = MagicMock()
# Domestic balance: tot_evlu_amt=55000
broker.get_balance = AsyncMock(
return_value=self._make_domestic_balance(tot_evlu_amt=55000.0)
)
# Price data for the stock
broker.get_current_price = AsyncMock(
return_value=(100.0, 1.5, 100.0)
)
market = MagicMock()
market.name = "KR"
market.code = "KR"
market.exchange_code = "KRX"
market.is_domestic = True
market.timezone = __import__("zoneinfo").ZoneInfo("Asia/Seoul")
smart_scanner = MagicMock()
smart_scanner.scan = AsyncMock(
return_value=[
ScanCandidate(
stock_code="005930",
name="Samsung",
price=100.0,
volume=1_000_000.0,
volume_ratio=2.5,
rsi=45.0,
signal="momentum",
score=80.0,
)
]
)
playbook_store = MagicMock()
playbook_store.load = MagicMock(return_value=_make_playbook("KR"))
scenario_engine = MagicMock(spec=ScenarioEngine)
scenario_engine.evaluate = MagicMock(return_value=_make_hold_match("005930"))
risk = MagicMock()
risk.check_circuit_breaker = MagicMock()
risk.check_fat_finger = MagicMock()
telegram = MagicMock()
telegram.notify_trade_execution = AsyncMock()
telegram.notify_scenario_matched = AsyncMock()
decision_logger = MagicMock()
decision_logger.log_decision = MagicMock(return_value="d1")
async def _passthrough(fn, *a, label: str = "", **kw): # type: ignore[override]
return await fn(*a, **kw)
with patch("src.main.get_open_markets", return_value=[market]), \
patch("src.main._retry_connection", new=_passthrough):
result = await run_daily_session(
broker=broker,
overseas_broker=MagicMock(),
scenario_engine=scenario_engine,
playbook_store=playbook_store,
pre_market_planner=MagicMock(),
risk=risk,
db_conn=init_db(":memory:"),
decision_logger=decision_logger,
context_store=MagicMock(),
criticality_assessor=MagicMock(),
telegram=telegram,
settings=settings,
smart_scanner=smart_scanner,
daily_start_eval=0.0,
)
assert result == 55000.0 # captured from tot_evlu_amt
@pytest.mark.asyncio
async def test_does_not_overwrite_existing_baseline(self) -> None:
"""When daily_start_eval > 0, it must not be overwritten even if balance returns
a different value (baseline is fixed at the start of each trading day)."""
from src.analysis.smart_scanner import ScanCandidate
settings = self._make_settings()
broker = MagicMock()
# Balance reports a different eval value (market moved during the day)
broker.get_balance = AsyncMock(
return_value=self._make_domestic_balance(tot_evlu_amt=58000.0)
)
broker.get_current_price = AsyncMock(return_value=(100.0, 1.5, 100.0))
market = MagicMock()
market.name = "KR"
market.code = "KR"
market.exchange_code = "KRX"
market.is_domestic = True
market.timezone = __import__("zoneinfo").ZoneInfo("Asia/Seoul")
smart_scanner = MagicMock()
smart_scanner.scan = AsyncMock(
return_value=[
ScanCandidate(
stock_code="005930",
name="Samsung",
price=100.0,
volume=1_000_000.0,
volume_ratio=2.5,
rsi=45.0,
signal="momentum",
score=80.0,
)
]
)
playbook_store = MagicMock()
playbook_store.load = MagicMock(return_value=_make_playbook("KR"))
scenario_engine = MagicMock(spec=ScenarioEngine)
scenario_engine.evaluate = MagicMock(return_value=_make_hold_match("005930"))
risk = MagicMock()
risk.check_circuit_breaker = MagicMock()
telegram = MagicMock()
telegram.notify_trade_execution = AsyncMock()
telegram.notify_scenario_matched = AsyncMock()
decision_logger = MagicMock()
decision_logger.log_decision = MagicMock(return_value="d1")
async def _passthrough(fn, *a, label: str = "", **kw): # type: ignore[override]
return await fn(*a, **kw)
with patch("src.main.get_open_markets", return_value=[market]), \
patch("src.main._retry_connection", new=_passthrough):
result = await run_daily_session(
broker=broker,
overseas_broker=MagicMock(),
scenario_engine=scenario_engine,
playbook_store=playbook_store,
pre_market_planner=MagicMock(),
risk=risk,
db_conn=init_db(":memory:"),
decision_logger=decision_logger,
context_store=MagicMock(),
criticality_assessor=MagicMock(),
telegram=telegram,
settings=settings,
smart_scanner=smart_scanner,
daily_start_eval=55000.0, # existing baseline
)
# Must return the original baseline, NOT the new total_eval (58000)
assert result == 55000.0
# ---------------------------------------------------------------------------
# sync_positions_from_broker — startup DB sync tests (issue #206)
# ---------------------------------------------------------------------------
class TestSyncPositionsFromBroker:
"""Tests for sync_positions_from_broker() startup position sync (issue #206).
The function queries broker balances at startup and inserts synthetic BUY
records for any holdings that the local DB is unaware of, preventing
double-buy when positions were opened in a previous session or manually.
"""
def _make_settings(self, enabled_markets: str = "KR") -> Settings:
return Settings(
KIS_APP_KEY="k",
KIS_APP_SECRET="s",
KIS_ACCOUNT_NO="12345678-01",
GEMINI_API_KEY="g",
ENABLED_MARKETS=enabled_markets,
MODE="paper",
)
def _domestic_balance(
self,
stock_code: str = "005930",
qty: int = 5,
) -> dict:
return {
"output1": [{"pdno": stock_code, "ord_psbl_qty": str(qty)}],
"output2": [
{
"tot_evlu_amt": "1000000",
"dnca_tot_amt": "500000",
"pchs_amt_smtl_amt": "500000",
}
],
}
def _overseas_balance(
self,
stock_code: str = "AAPL",
qty: int = 10,
) -> dict:
return {
"output1": [{"ovrs_pdno": stock_code, "ovrs_cblc_qty": str(qty)}],
"output2": [
{
"frcr_evlu_tota": "50000",
"frcr_dncl_amt_2": "10000",
"frcr_buy_amt_smtl": "40000",
}
],
}
@pytest.mark.asyncio
async def test_syncs_domestic_position_not_in_db(self) -> None:
"""A domestic holding found in broker but absent from DB is inserted."""
settings = self._make_settings("KR")
db_conn = init_db(":memory:")
broker = MagicMock()
broker.get_balance = AsyncMock(
return_value=self._domestic_balance("005930", qty=7)
)
overseas_broker = MagicMock()
synced = await sync_positions_from_broker(
broker, overseas_broker, db_conn, settings
)
assert synced == 1
from src.db import get_open_position
pos = get_open_position(db_conn, "005930", "KR")
assert pos is not None
assert pos["quantity"] == 7
@pytest.mark.asyncio
async def test_skips_position_already_in_db(self) -> None:
"""No duplicate record is created when the position already exists in DB."""
settings = self._make_settings("KR")
db_conn = init_db(":memory:")
# Pre-insert a BUY record
log_trade(
conn=db_conn,
stock_code="005930",
action="BUY",
confidence=85,
rationale="existing position",
quantity=5,
price=70000.0,
market="KR",
exchange_code="KRX",
)
broker = MagicMock()
broker.get_balance = AsyncMock(
return_value=self._domestic_balance("005930", qty=5)
)
overseas_broker = MagicMock()
synced = await sync_positions_from_broker(
broker, overseas_broker, db_conn, settings
)
assert synced == 0
@pytest.mark.asyncio
async def test_syncs_overseas_position_not_in_db(self) -> None:
"""An overseas holding found in broker but absent from DB is inserted."""
settings = self._make_settings("US_NASDAQ")
db_conn = init_db(":memory:")
broker = MagicMock()
overseas_broker = MagicMock()
overseas_broker.get_overseas_balance = AsyncMock(
return_value=self._overseas_balance("AAPL", qty=10)
)
synced = await sync_positions_from_broker(
broker, overseas_broker, db_conn, settings
)
assert synced == 1
from src.db import get_open_position
pos = get_open_position(db_conn, "AAPL", "US_NASDAQ")
assert pos is not None
assert pos["quantity"] == 10
@pytest.mark.asyncio
async def test_returns_zero_when_broker_has_no_holdings(self) -> None:
"""Returns 0 when broker reports empty holdings."""
settings = self._make_settings("KR")
db_conn = init_db(":memory:")
broker = MagicMock()
broker.get_balance = AsyncMock(
return_value={"output1": [], "output2": [{}]}
)
overseas_broker = MagicMock()
synced = await sync_positions_from_broker(
broker, overseas_broker, db_conn, settings
)
assert synced == 0
@pytest.mark.asyncio
async def test_handles_connection_error_gracefully(self) -> None:
"""ConnectionError during balance fetch is logged but does not raise."""
settings = self._make_settings("KR")
db_conn = init_db(":memory:")
broker = MagicMock()
broker.get_balance = AsyncMock(
side_effect=ConnectionError("KIS unreachable")
)
overseas_broker = MagicMock()
synced = await sync_positions_from_broker(
broker, overseas_broker, db_conn, settings
)
assert synced == 0 # Failure treated as no-op
@pytest.mark.asyncio
async def test_deduplicates_exchange_codes_for_overseas(self) -> None:
"""Each exchange code is queried at most once even if multiple market
codes share the same exchange (defensive deduplication)."""
# Both US_NASDAQ and a hypothetical duplicate would share "NASD"
# Use two DIFFERENT overseas markets (NASD vs NYSE) to verify each is
# queried separately.
settings = self._make_settings("US_NASDAQ,US_NYSE")
db_conn = init_db(":memory:")
broker = MagicMock()
overseas_broker = MagicMock()
overseas_broker.get_overseas_balance = AsyncMock(
return_value={"output1": [], "output2": [{}]}
)
await sync_positions_from_broker(
broker, overseas_broker, db_conn, settings
)
# Two distinct exchange codes (NASD, NYSE) → 2 calls
assert overseas_broker.get_overseas_balance.call_count == 2
# ---------------------------------------------------------------------------
# Domestic BUY double-prevention (issue #206) — trading_cycle integration
# ---------------------------------------------------------------------------
class TestDomesticBuyDoublePreventionTradingCycle:
"""Verify domestic BUY suppression using broker balance in trading_cycle.
Issue #206: the broker-balance check was overseas-only; domestic stocks
were not protected against double-buy caused by untracked positions.
"""
@pytest.mark.asyncio
async def test_domestic_buy_suppressed_when_broker_holds_stock(
self,
) -> None:
"""BUY for a domestic stock must be suppressed when broker holds it,
even if the DB shows no open position."""
db_conn = init_db(":memory:")
# DB: no open position for 005930
broker = MagicMock()
broker.get_current_price = AsyncMock(return_value=(70000.0, 1.0, 0.0))
# Broker balance: holds 5 shares of 005930
broker.get_balance = AsyncMock(
return_value={
"output1": [{"pdno": "005930", "ord_psbl_qty": "5"}],
"output2": [
{
"tot_evlu_amt": "1000000",
"dnca_tot_amt": "500000",
"pchs_amt_smtl_amt": "500000",
}
],
}
)
broker.send_order = AsyncMock(return_value={"msg1": "주문접수"})
market = MagicMock()
market.name = "KR"
market.code = "KR"
market.exchange_code = "KRX"
market.is_domestic = True
engine = MagicMock(spec=ScenarioEngine)
engine.evaluate = MagicMock(return_value=_make_buy_match("005930"))
telegram = MagicMock()
telegram.notify_trade_execution = AsyncMock()
telegram.notify_fat_finger = AsyncMock()
telegram.notify_circuit_breaker = AsyncMock()
telegram.notify_scenario_matched = AsyncMock()
decision_logger = MagicMock()
decision_logger.log_decision = MagicMock(return_value="d1")
settings = Settings(
KIS_APP_KEY="k",
KIS_APP_SECRET="s",
KIS_ACCOUNT_NO="12345678-01",
GEMINI_API_KEY="g",
MODE="paper",
)
await trading_cycle(
broker=broker,
overseas_broker=MagicMock(),
scenario_engine=engine,
playbook=_make_playbook(market="KR"),
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,
settings=settings,
market=market,
stock_code="005930",
scan_candidates={"KR": {}},
)
# BUY must NOT have been executed because broker still holds the stock
broker.send_order.assert_not_called()

View File

@@ -640,4 +640,176 @@ class TestPaperOverseasCash:
GEMINI_API_KEY="g",
)
assert settings.PAPER_OVERSEAS_CASH == 0.0
del os.environ["PAPER_OVERSEAS_CASH"]
# ---------------------------------------------------------------------------
# TR_ID live/paper branching — overseas (issues #201, #203)
# ---------------------------------------------------------------------------
def _make_overseas_broker_with_mode(mode: str) -> OverseasBroker:
s = Settings(
KIS_APP_KEY="k",
KIS_APP_SECRET="s",
KIS_ACCOUNT_NO="12345678-01",
GEMINI_API_KEY="g",
DB_PATH=":memory:",
MODE=mode,
)
kis = KISBroker(s)
kis._access_token = "tok"
kis._token_expires_at = float("inf")
kis._rate_limiter.acquire = AsyncMock()
return OverseasBroker(kis)
class TestOverseasTRIDBranching:
"""get_overseas_balance and send_overseas_order must use correct TR_ID."""
@pytest.mark.asyncio
async def test_get_overseas_balance_paper_uses_vtts3012r(self) -> None:
broker = _make_overseas_broker_with_mode("paper")
captured: list[str] = []
async def mock_auth_headers(tr_id: str) -> dict:
captured.append(tr_id)
return {"tr_id": tr_id, "authorization": "Bearer tok"}
broker._broker._auth_headers = mock_auth_headers # type: ignore[method-assign]
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(return_value={"output1": [], "output2": []})
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
mock_session = MagicMock()
mock_session.get = MagicMock(return_value=mock_resp)
broker._broker._get_session = MagicMock(return_value=mock_session)
await broker.get_overseas_balance("NASD")
assert "VTTS3012R" in captured
@pytest.mark.asyncio
async def test_get_overseas_balance_live_uses_ttts3012r(self) -> None:
broker = _make_overseas_broker_with_mode("live")
captured: list[str] = []
async def mock_auth_headers(tr_id: str) -> dict:
captured.append(tr_id)
return {"tr_id": tr_id, "authorization": "Bearer tok"}
broker._broker._auth_headers = mock_auth_headers # type: ignore[method-assign]
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(return_value={"output1": [], "output2": []})
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
mock_session = MagicMock()
mock_session.get = MagicMock(return_value=mock_resp)
broker._broker._get_session = MagicMock(return_value=mock_session)
await broker.get_overseas_balance("NASD")
assert "TTTS3012R" in captured
@pytest.mark.asyncio
async def test_send_overseas_order_buy_paper_uses_vttt1002u(self) -> None:
broker = _make_overseas_broker_with_mode("paper")
captured: list[str] = []
async def mock_auth_headers(tr_id: str) -> dict:
captured.append(tr_id)
return {"tr_id": tr_id, "authorization": "Bearer tok"}
broker._broker._auth_headers = mock_auth_headers # type: ignore[method-assign]
broker._broker._get_hash_key = AsyncMock(return_value="h") # type: ignore[method-assign]
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "OK"})
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
mock_session = MagicMock()
mock_session.post = MagicMock(return_value=mock_resp)
broker._broker._get_session = MagicMock(return_value=mock_session)
await broker.send_overseas_order("NASD", "AAPL", "BUY", 1)
assert "VTTT1002U" in captured
@pytest.mark.asyncio
async def test_send_overseas_order_buy_live_uses_tttt1002u(self) -> None:
broker = _make_overseas_broker_with_mode("live")
captured: list[str] = []
async def mock_auth_headers(tr_id: str) -> dict:
captured.append(tr_id)
return {"tr_id": tr_id, "authorization": "Bearer tok"}
broker._broker._auth_headers = mock_auth_headers # type: ignore[method-assign]
broker._broker._get_hash_key = AsyncMock(return_value="h") # type: ignore[method-assign]
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "OK"})
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
mock_session = MagicMock()
mock_session.post = MagicMock(return_value=mock_resp)
broker._broker._get_session = MagicMock(return_value=mock_session)
await broker.send_overseas_order("NASD", "AAPL", "BUY", 1)
assert "TTTT1002U" in captured
@pytest.mark.asyncio
async def test_send_overseas_order_sell_paper_uses_vttt1001u(self) -> None:
broker = _make_overseas_broker_with_mode("paper")
captured: list[str] = []
async def mock_auth_headers(tr_id: str) -> dict:
captured.append(tr_id)
return {"tr_id": tr_id, "authorization": "Bearer tok"}
broker._broker._auth_headers = mock_auth_headers # type: ignore[method-assign]
broker._broker._get_hash_key = AsyncMock(return_value="h") # type: ignore[method-assign]
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "OK"})
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
mock_session = MagicMock()
mock_session.post = MagicMock(return_value=mock_resp)
broker._broker._get_session = MagicMock(return_value=mock_session)
await broker.send_overseas_order("NASD", "AAPL", "SELL", 1)
assert "VTTT1001U" in captured
@pytest.mark.asyncio
async def test_send_overseas_order_sell_live_uses_tttt1006u(self) -> None:
broker = _make_overseas_broker_with_mode("live")
captured: list[str] = []
async def mock_auth_headers(tr_id: str) -> dict:
captured.append(tr_id)
return {"tr_id": tr_id, "authorization": "Bearer tok"}
broker._broker._auth_headers = mock_auth_headers # type: ignore[method-assign]
broker._broker._get_hash_key = AsyncMock(return_value="h") # type: ignore[method-assign]
mock_resp = AsyncMock()
mock_resp.status = 200
mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "OK"})
mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
mock_resp.__aexit__ = AsyncMock(return_value=False)
mock_session = MagicMock()
mock_session.post = MagicMock(return_value=mock_resp)
broker._broker._get_session = MagicMock(return_value=mock_session)
await broker.send_overseas_order("NASD", "AAPL", "SELL", 1)
assert "TTTT1006U" in captured

View File

@@ -0,0 +1,32 @@
"""Tests for BaseStrategy abstract class."""
from __future__ import annotations
from typing import Any
import pytest
from src.strategies.base import BaseStrategy
class ConcreteStrategy(BaseStrategy):
"""Minimal concrete strategy for testing."""
def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
return {"action": "HOLD", "confidence": 50, "rationale": "test"}
def test_base_strategy_cannot_be_instantiated() -> None:
"""BaseStrategy cannot be instantiated directly (it's abstract)."""
with pytest.raises(TypeError):
BaseStrategy() # type: ignore[abstract]
def test_concrete_strategy_evaluate_returns_decision() -> None:
"""Concrete subclass must implement evaluate and return a dict."""
strategy = ConcreteStrategy()
result = strategy.evaluate({"close": [100.0, 101.0]})
assert isinstance(result, dict)
assert result["action"] == "HOLD"
assert result["confidence"] == 50
assert "rationale" in result