317 lines
11 KiB
Python
317 lines
11 KiB
Python
"""
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장중 미니배치: 매 10분마다 실행 (평일 09:00~15:30 KST)
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[흐름]
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1. 아침 배치(batch_daily_analysis.py)가 분석종목(watchlist)을 score 상위 50개로 초기화
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2. 장중 미니배치는 분석종목만 재분석하여 최신 지표로 stock_analysis 갱신
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3. 분석 결과를 watchlist_history에 시계열로 누적 저장
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4. score 기준으로 분석종목 진입(≥60) / 제거(<20) 자동 관리
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실행: python batch_intraday_analysis.py
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Cron: */10 9-15 * * 1-5 docker exec autostock-backend python /app/batch_intraday_analysis.py >> /logs/batch_intraday.log 2>&1
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"""
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import asyncio
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import sys
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from datetime import datetime, date
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent))
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from sqlalchemy import select, delete, update, func
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from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
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from sqlalchemy.orm import sessionmaker
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import logging
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from app.core.config import settings
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from app.core.market_schedule import is_market_open
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from app.models.models import StockAnalysis, WatchlistStock, WatchlistHistory
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from app.api.endpoints.recommendations import analyze_stock_for_batch
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from app.services.watchlist import (
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WATCHLIST_MAX_SIZE,
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WATCHLIST_ENTRY_SCORE,
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WATCHLIST_EXIT_SCORE,
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)
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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# 동시 처리 종목 수 (KIS API 세마포어가 추가로 속도 제어)
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BATCH_CONCURRENCY = 5
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# DB 연결
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database_url = settings.DATABASE_URL
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if database_url.startswith("postgresql://"):
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database_url = database_url.replace("postgresql://", "postgresql+asyncpg://", 1)
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engine = create_async_engine(
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database_url,
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echo=False,
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pool_pre_ping=True,
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pool_size=5,
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max_overflow=10,
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)
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AsyncSessionLocal = sessionmaker(
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engine,
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class_=AsyncSession,
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expire_on_commit=False,
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)
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async def get_active_watchlist() -> list[tuple[str, str]]:
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"""현재 활성 분석종목 목록 조회."""
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async with AsyncSessionLocal() as session:
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result = await session.execute(
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select(WatchlistStock.stock_code, WatchlistStock.stock_name)
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.where(WatchlistStock.is_active == True)
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)
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rows = result.all()
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if not rows:
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logger.warning(
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"⚠️ 분석종목이 없습니다. "
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"아침 배치(batch_daily_analysis.py)가 먼저 실행되었는지 확인하세요."
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)
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else:
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logger.info(f"📋 분석종목 {len(rows)}개 대상")
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return [(row.stock_code, row.stock_name) for row in rows]
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async def analyze_update_and_manage(
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stock_code: str,
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stock_name: str,
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analysis_date: date,
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) -> tuple[bool, int | None]:
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"""종목 재분석 → stock_analysis 갱신 → watchlist_history 저장 → watchlist 관리.
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Returns: (success, score)
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"""
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try:
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result = await analyze_stock_for_batch(stock_code, stock_name)
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if not result:
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logger.info(f"No result for {stock_code} (chart/price issue)")
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return False, None
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# 5,000원 이하 저가주 → watchlist에서도 제거
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if result.current_price and result.current_price < 5000:
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logger.debug(f"Skip {stock_code}: price={result.current_price:.0f}원 < 5,000원")
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async with AsyncSessionLocal() as session:
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await session.execute(
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update(WatchlistStock)
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.where(
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WatchlistStock.stock_code == stock_code,
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WatchlistStock.is_active == True,
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)
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.values(
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is_active=False,
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removed_at=datetime.now(),
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removed_reason="price_filter",
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)
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)
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await session.commit()
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return False, None
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now = datetime.now()
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score = result.score
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async with AsyncSessionLocal() as session:
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# 1. stock_analysis 갱신 (DELETE + INSERT)
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await session.execute(
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delete(StockAnalysis).where(
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StockAnalysis.stock_code == stock_code,
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StockAnalysis.analysis_date == analysis_date,
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)
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)
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session.add(StockAnalysis(
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stock_code=stock_code,
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stock_name=stock_name,
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analysis_date=analysis_date,
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current_price=result.current_price,
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change_rate=result.change_rate,
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volume=result.volume,
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rsi=result.rsi,
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ma5=result.ma5,
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ma20=result.ma20,
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ma60=result.ma60,
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stochastic_k=result.stochastic_k,
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stochastic_d=result.stochastic_d,
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bollinger_upper=result.bollinger_upper,
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bollinger_lower=result.bollinger_lower,
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bollinger_middle=result.bollinger_middle,
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signals=result.signals,
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score=score,
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ml_score=result.ml_score,
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ml_confidence=result.ml_confidence,
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ml_signal=result.ml_signal,
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atr_14=result.atr_14,
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adx_14=result.adx_14,
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))
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# 2. watchlist_history 시계열 기록
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session.add(WatchlistHistory(
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stock_code=stock_code,
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stock_name=stock_name,
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recorded_at=now,
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score=score,
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current_price=result.current_price,
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change_rate=result.change_rate,
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rsi=result.rsi,
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signals=result.signals,
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))
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# 3. score가 기준 이하면 분석종목에서 제거
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if score is not None and score < WATCHLIST_EXIT_SCORE:
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await session.execute(
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update(WatchlistStock)
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.where(
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WatchlistStock.stock_code == stock_code,
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WatchlistStock.is_active == True,
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)
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.values(
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is_active=False,
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removed_at=now,
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removed_reason="score_drop",
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)
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)
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logger.info(
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f"🚫 {stock_code} ({stock_name}) 분석종목 제거: "
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f"score={score} < {WATCHLIST_EXIT_SCORE}"
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)
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await session.commit()
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logger.info(f"✅ {stock_code} ({stock_name}): score={score}")
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return True, score
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except Exception as e:
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logger.error(f"❌ Failed {stock_code}: {e}")
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return False, None
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async def refresh_watchlist(analysis_date: date, current_codes: set[str]) -> int:
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"""분석종목에 없는 고점수 종목을 신규 추가.
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Args:
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analysis_date: 오늘 날짜 (stock_analysis 기준)
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current_codes: 이번 배치 시작 시점의 watchlist 코드 집합
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Returns: 추가된 종목 수
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"""
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async with AsyncSessionLocal() as session:
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# 현재 활성 종목 수 확인
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count_result = await session.execute(
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select(func.count())
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.select_from(WatchlistStock)
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.where(WatchlistStock.is_active == True)
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)
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active_count = count_result.scalar() or 0
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slots = WATCHLIST_MAX_SIZE - active_count
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if slots <= 0:
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logger.debug(f"Watchlist 최대치 도달 ({active_count}/{WATCHLIST_MAX_SIZE})")
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return 0
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# stock_analysis에서 고점수 종목 중 현재 watchlist에 없는 것 조회
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exclude_codes = list(current_codes) if current_codes else ["__none__"]
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result = await session.execute(
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select(
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StockAnalysis.stock_code,
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StockAnalysis.stock_name,
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StockAnalysis.score,
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)
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.where(
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StockAnalysis.analysis_date == analysis_date,
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StockAnalysis.score >= WATCHLIST_ENTRY_SCORE,
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StockAnalysis.stock_code.notin_(exclude_codes),
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)
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.order_by(StockAnalysis.score.desc())
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.limit(slots)
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)
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candidates = result.all()
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if not candidates:
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return 0
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now = datetime.now()
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for row in candidates:
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session.add(WatchlistStock(
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stock_code=row.stock_code,
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stock_name=row.stock_name,
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added_at=now,
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added_reason="score_rise",
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score_at_add=row.score,
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is_active=True,
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))
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await session.commit()
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logger.info(
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f"➕ 분석종목 {len(candidates)}개 신규 추가 "
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f"(score ≥ {WATCHLIST_ENTRY_SCORE}, 현재 {active_count + len(candidates)}개)"
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)
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return len(candidates)
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async def main():
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"""장중 미니배치 메인"""
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# 장중(09:00~15:30 KST 평일)이 아니면 즉시 종료
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if not is_market_open():
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logger.info("📴 장중이 아닙니다 (09:00~15:30 평일). 종료합니다.")
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return
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start_time = datetime.now()
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analysis_date = date.today()
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logger.info(
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f"⚡ [Intraday] {start_time.strftime('%H:%M:%S')} 시작 — "
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f"분석종목 재분석 (진입≥{WATCHLIST_ENTRY_SCORE}, 제거<{WATCHLIST_EXIT_SCORE})"
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)
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# 활성 분석종목 조회
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active_stocks = await get_active_watchlist()
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if not active_stocks:
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return
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# 이번 배치 시작 시점의 코드 집합 (신규 추가 시 중복 방지용)
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current_codes = {code for code, _ in active_stocks}
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total = len(active_stocks)
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# 병렬 재분석
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semaphore = asyncio.Semaphore(BATCH_CONCURRENCY)
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async def analyze_one(i: int, code: str, name: str) -> tuple[bool, int | None]:
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async with semaphore:
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logger.info(f"[{i}/{total}] {code} ({name})")
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return await analyze_update_and_manage(code, name, analysis_date)
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tasks = [
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analyze_one(i, code, name)
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for i, (code, name) in enumerate(active_stocks, 1)
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]
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results = await asyncio.gather(*tasks, return_exceptions=True)
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success = sum(1 for r in results if isinstance(r, tuple) and r[0] is True)
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removed = sum(
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1 for r in results
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if isinstance(r, tuple) and r[0] is True
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and r[1] is not None and r[1] < WATCHLIST_EXIT_SCORE
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)
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fail = sum(1 for r in results if isinstance(r, tuple) and r[0] is False)
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error = sum(1 for r in results if isinstance(r, Exception))
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# 고점수 신규 종목 추가
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added = await refresh_watchlist(analysis_date, current_codes)
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duration = (datetime.now() - start_time).total_seconds()
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logger.info(
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f"✅ [Intraday] 완료: {success}/{total} 성공, "
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f"{removed} 제거, +{added} 신규, "
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f"{fail} 실패, {error} 오류 — {duration:.1f}초"
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)
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if __name__ == "__main__":
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asyncio.run(main())
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