fix: DB 타임스탬프 KST 통일 + KIS 토큰 캐시 영속화

시간대 혼재: 모델 기본값은 datetime.utcnow(UTC), 수동 매매 등 일부 경로는 _get_kst_now(KST)로
저장해 같은 테이블에 9시간 차가 섞였다(화면 매매시각 02:14 등). 조회 구간(utcnow - days)도
KST 저장분과 비교돼 어긋났고, 추가매수 쿨다운은 (UTC now - KST created_at)이 음수라 상시
발동했다. app.core.timeutil.now_kst() 도입 후 모델 기본값 27곳과 app/ 전역 utcnow() 호출을
모두 KST 기준으로 통일(잔존 0건, 테스트로 고정).

KIS 토큰 캐시(~/.cache/auto-stock)가 컨테이너에만 있어 배포마다 사라지고 토큰을 새로
발급받다 KIS가 EGW00103(유효하지 않은 AppKey)로 거부 → 502·잔고 0 유발. 볼륨 마운트로
재배포 후에도 재사용.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

backend/app/services/db_worker.py

@@ -38,6 +38,7 @@ from sqlalchemy import select
 
 from app.core.database import AsyncSessionLocal
 from app.models.models import TradeHistory
+from app.core.timeutil import now_kst
 
 logger = logging.getLogger(__name__)
 
@@ -291,7 +292,7 @@ async def enqueue_trade_journal(trade, content: str) -> None:
             "trade_id": trade.id,
             "stock_code": trade.stock_code,
             "stock_name": trade.stock_name,
-            "journal_date": trade.executed_at or trade.created_at or datetime.utcnow(),
+            "journal_date": trade.executed_at or trade.created_at or now_kst(),
             "content": content,
             "strategy_name": strategy,
             "mood": mood,
@@ -450,7 +451,7 @@ async def db_writer_worker() -> None:
                         set_={
                             "consecutive_losses": stmt.excluded.consecutive_losses,
                             "ban_until": stmt.excluded.ban_until,
-                            "updated_at": datetime.utcnow(),
+                            "updated_at": now_kst(),
                         },
                     )
                     await session.execute(stmt)
@@ -612,7 +613,7 @@ async def db_writer_worker() -> None:
 
                     if record:
                         record.status = "closed"
-                        record.updated_at = _dt.utcnow()
+                        record.updated_at = now_kst()
                         await session.commit()
                         logger.debug(
                             "✅ [Worker] ActiveTrade closed: %s (strategy=%s)",

backend/app/services/ml_retrain_pipeline.py

@@ -33,6 +33,7 @@ import pytz
 
 from app.core.config import settings
 from app.core.database import AsyncSessionLocal
+from app.core.timeutil import now_kst
 from app.services.feature_engineering import (
     extract_features,
     db_data_to_dataframe,
@@ -397,11 +398,11 @@ async def _load_trade_history(
     from sqlalchemy import select, and_
     from app.models.models import TradeHistory
 
-    # [FIX] TradeHistory.created_at은 timestamp WITHOUT time zone(naive UTC, datetime.utcnow
+    # [2026-09-23] TradeHistory.created_at 은 KST naive (app.core.timeutil.now_kst)
     # 저장)이므로, tz-aware인 datetime.now(KST)로 비교하면 asyncpg가
     # "can't subtract offset-naive and offset-aware datetimes" DataError를 낸다.
     # 컬럼과 동일하게 naive UTC로 맞춘다.
-    cutoff = datetime.utcnow() - timedelta(days=months * 30)
+    cutoff = now_kst() - timedelta(days=months * 30)
 
     async with AsyncSessionLocal() as session:
         stmt = (

backend/app/services/news_sentiment.py

@@ -24,6 +24,7 @@ from bs4 import BeautifulSoup
 from app.core.config import settings
 from app.core.redis import setex_json, get_json
 from app.services.db_worker import db_task_queue
+from app.core.timeutil import now_kst
 
 logger = logging.getLogger(__name__)
 
@@ -168,7 +169,7 @@ def _compute_aggregate_score(articles: List[Dict[str, Any]]) -> float:
     if not articles:
         return 0.0
 
-    now = datetime.utcnow()
+    now = now_kst()
     weighted_sum = 0.0
     weight_total = 0.0
 
@@ -327,7 +328,7 @@ async def collect_market_news(limit: int = 0) -> List[Dict[str, Any]]:
                     "stock_codes": [],  # 시장 뉴스는 특정 종목 없음
                     "sentiment": label,
                     "sentiment_score": score,
-                    "published_at": datetime.utcnow(),  # 파싱 불가 시 현재 시간
+                    "published_at": now_kst(),  # 파싱 불가 시 현재 시간
                 })
 
                 if len(articles) >= limit:
@@ -392,7 +393,7 @@ async def collect_newsapi_news(
             try:
                 published_at = datetime.fromisoformat(pub_str.replace("Z", "+00:00"))
             except Exception:
-                published_at = datetime.utcnow()
+                published_at = now_kst()
 
             score, label = analyze_sentiment_keyword(title, content)
 
@@ -567,7 +568,7 @@ def _parse_naver_date(date_str: str) -> datetime:
     형식: "2026.03.24 09:15" 또는 "2026.03.24"
     """
     if not date_str:
-        return datetime.utcnow()
+        return now_kst()
 
     date_str = date_str.strip()
     for fmt in ("%Y.%m.%d %H:%M", "%Y.%m.%d"):
@@ -576,7 +577,7 @@ def _parse_naver_date(date_str: str) -> datetime:
         except ValueError:
             continue
 
-    return datetime.utcnow()
+    return now_kst()
 
 
 # ═════════════════════════════════════════════════════════════════════════════

backend/app/services/schedulers.py

@@ -13,6 +13,7 @@ from datetime import datetime as _dt, date as _date, timedelta as _td
 
 from app.core.config import settings
 from app.core.database import AsyncSessionLocal
+from app.core.timeutil import now_kst
 from app.core.market_schedule import (
     is_market_open, seconds_until_market_open, is_pre_market_window,
 )
@@ -224,7 +225,6 @@ async def post_market_analyzer_scheduler():
                 )
                 from app.models.models import TradeHistory
                 from sqlalchemy import select, func, and_
-                from datetime import datetime as _utcnow_dt
 
                 async with AsyncSessionLocal() as db:
                     uncovered = await get_uncovered_trades(db, days=7)
@@ -246,7 +246,7 @@ async def post_market_analyzer_scheduler():
                     try:
                         from app.services.telegram_notifier import telegram_notifier
                         # 당일 SELL 체결 내역으로 PnL 계산
-                        _today_start = _utcnow_dt.utcnow().replace(hour=0, minute=0, second=0, microsecond=0)
+                        _today_start = now_kst().replace(hour=0, minute=0, second=0, microsecond=0)
                         _today_sells = await db.execute(
                             select(TradeHistory).where(
                                 and_(
@@ -282,7 +282,7 @@ async def post_market_analyzer_scheduler():
                     except Exception as _tg_err:
                         logger.debug(f"[PostMarket] Telegram 리포트 전송 실패: {_tg_err}")
 
-                    since_7d = _utcnow_dt.utcnow() - _td(days=7)
+                    since_7d = now_kst() - _td(days=7)
                     trade_count_result = await db.execute(
                         select(func.count(TradeHistory.id)).where(
                             and_(

backend/app/services/stock_pattern_memory.py

@@ -27,6 +27,7 @@ from datetime import datetime, date, timedelta
 from typing import Optional, List, Dict, Tuple
 
 from app.core.config import settings
+from app.core.timeutil import now_kst
 
 logger = logging.getLogger(__name__)
 
@@ -791,7 +792,7 @@ async def build_stock_profile(stock_code: str) -> Optional[StockProfile]:
         total_trades=trade_stats["total_trades"],
         beta=beta,
         sector="",  # 별도 섹터 DB 필요 시 확장
-        last_updated=datetime.utcnow().isoformat(),
+        last_updated=now_kst().isoformat(),
     )
     return profile
 
@@ -899,7 +900,7 @@ async def refresh_all_profiles_with_percentile(stock_codes: List[str]) -> int:
         # 해당 종목의 순위 → 백분위
         rank = sorted_ranges.index(p.avg_daily_range_pct)
         p.volatility_percentile = round(rank / n * 100, 1) if n > 1 else 50.0
-        p.last_updated = datetime.utcnow().isoformat()
+        p.last_updated = now_kst().isoformat()
 
     # 3단계: 캐시 저장
     success = 0

backend/app/services/strategy_config_service.py

@@ -29,6 +29,7 @@ from sqlalchemy.dialects.postgresql import insert as pg_insert
 
 from app.core.database import AsyncSessionLocal
 from app.models.models import StrategyConfig
+from app.core.timeutil import now_kst
 
 logger = logging.getLogger(__name__)
 
@@ -219,7 +220,7 @@ class StrategyConfigService:
 
                 cfg.value = value
                 cfg.updated_by = updated_by
-                cfg.updated_at = __import__("datetime").datetime.utcnow()
+                cfg.updated_at = __import__("datetime").now_kst()
                 await session.commit()
                 await session.refresh(cfg)
 

backend/app/services/strategy_optimizer.py

@@ -27,6 +27,7 @@ from app.core.database import AsyncSessionLocal
 from app.models.models import StrategyOptimizationLog, StockDailyPrice
 from app.services.strategy_config_service import strategy_cfg
 from app.services.backtest_engine import BacktestEngine, BacktestConfig
+from app.core.timeutil import now_kst
 
 logger = logging.getLogger(__name__)
 
@@ -193,7 +194,7 @@ async def _get_representative_stocks(period_days: int = 90) -> List[str]:
     from sqlalchemy import func, and_
     from datetime import datetime, timedelta
 
-    since = datetime.utcnow() - timedelta(days=period_days)
+    since = now_kst() - timedelta(days=period_days)
 
     async with AsyncSessionLocal() as db:
         stmt = (

backend/app/services/trade_analyzer.py

@@ -20,6 +20,7 @@ from sqlalchemy import select, and_, func
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.models.models import TradeHistory, TradeJournal
+from app.core.timeutil import now_kst
 
 logger = logging.getLogger(__name__)
 
@@ -380,7 +381,7 @@ async def analyze_performance(db: AsyncSession, days: int = 30) -> Dict[str, Any
           "generated_at": ISO 문자열
         }
     """
-    since = datetime.utcnow() - timedelta(days=days)
+    since = now_kst() - timedelta(days=days)
 
     stmt = select(TradeHistory).where(
         and_(
@@ -408,7 +409,7 @@ async def analyze_performance(db: AsyncSession, days: int = 30) -> Dict[str, Any
             "drift_alerts": [],
             "period_days": days,
             "total_trades": 0,
-            "generated_at": datetime.utcnow().isoformat(),
+            "generated_at": now_kst().isoformat(),
         }
 
     # ── 전체 통계 ──────────────────────────────────────────────────────────
@@ -526,7 +527,7 @@ async def analyze_performance(db: AsyncSession, days: int = 30) -> Dict[str, Any
         "drift_alerts": drift_alerts,
         "period_days": days,
         "total_trades": len(trades),
-        "generated_at": datetime.utcnow().isoformat(),
+        "generated_at": now_kst().isoformat(),
     }
 
 
@@ -637,7 +638,7 @@ def build_insights(perf: Dict[str, Any]) -> List[Dict[str, str]]:
 
 async def get_uncovered_trades(db: AsyncSession, days: int = 7) -> List[TradeHistory]:
     """일지가 아직 없는 완료 SELL 거래 목록을 반환."""
-    since = datetime.utcnow() - timedelta(days=days)
+    since = now_kst() - timedelta(days=days)
 
     # 이미 일지가 있는 trade_id 목록
     covered_stmt = select(TradeJournal.trade_id).where(TradeJournal.trade_id.is_not(None))
@@ -753,7 +754,7 @@ async def create_journal_record(
         trade_id=trade.id,
         stock_code=trade.stock_code,
         stock_name=trade.stock_name,
-        journal_date=trade.executed_at or trade.created_at or datetime.utcnow(),
+        journal_date=trade.executed_at or trade.created_at or now_kst(),
         content=content,
         strategy_name=strategy,
         mood=mood,

backend/app/services/trade_executor.py

@@ -32,6 +32,7 @@ from app.services.technical_indicators import (
 from app.services.signal_types import BUY_KEYWORDS, SELL_KEYWORDS, STRONG_BUY_KEYWORDS, BLOCK_KEYWORDS
 from app.services.correlation_filter import validate_correlation_filter
 from app.services.exchange_detector import is_us_stock, detect_exchange, get_market_info
+from app.core.timeutil import now_kst
 from app.services.trade_helpers import (
     check_opening_range_volatility, check_surge_prevention, check_trend_filter,
     calculate_cooldown_minutes, get_daily_cutoff_utc, get_leverage_check_keywords,
@@ -725,7 +726,7 @@ async def _execute_buy(
         if available_cash > 0:
             _set_account_cache(available_cash, total_assets)
 
-    # [이슈1 수정] TradeHistory.created_at은 UTC 저장(datetime.utcnow)이므로
+    # [2026-09-23] TradeHistory.created_at 은 KST 저장(now_kst)이므로
     # daily_cutoff도 UTC 기준으로 계산해야 9시간 오차가 없음.
     daily_cutoff = get_daily_cutoff_utc()  # 오늘 00:00:00 UTC
 
@@ -770,9 +771,9 @@ async def _execute_buy(
     )
     recent_buys = cooldown_check.scalars().all()
     # 마지막 매수 이후 쿨다운 시간이 지나지 않았으면 HOLD
-    # [이슈1 수정] created_at은 UTC이므로 현재 시각도 UTC로 비교
-    from datetime import datetime as _dt_utc2
-    if recent_buys and (_dt_utc2.utcnow() - recent_buys[0].created_at).total_seconds() < cooldown_min * 60:
+    # created_at·현재시각 모두 KST naive 기준 (예전에는 UTC now 와 KST created_at 을
+    # 비교해 차이가 음수가 되어 쿨다운이 항상 발동했다)
+    if recent_buys and (now_kst() - recent_buys[0].created_at).total_seconds() < cooldown_min * 60:
         return {"action": "HOLD", "stock": stock_name, "reason": "cooldown"}
 
     # ── 6.5. 상관관계 필터 (CLAUDE.md 섹션 5.4) ──────────────────────────────────

backend/app/services/trade_helpers.py

@@ -19,6 +19,7 @@ from app.services.technical_indicators import (
 from app.core.market_schedule import is_opening_range_period
 from app.services.market_analyzer import _get_kst_now
 from app.services.exchange_detector import get_market_info
+from app.core.timeutil import now_kst
 
 logger = logging.getLogger(__name__)
 
@@ -214,7 +215,7 @@ def get_daily_cutoff_utc() -> _dt_utc:
     Returns:
         datetime: Today's 00:00:00 UTC
     """
-    return _dt_utc.utcnow().replace(hour=0, minute=0, second=0, microsecond=0)
+    return now_kst().replace(hour=0, minute=0, second=0, microsecond=0)
 
 
 def get_leverage_check_keywords() -> set: