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- KOSPIMarketStateDetector: KOSPI MA 기반 시장 상태 판단 (bull/neutral/bear/crash) - VolumeScreener: 거래대금 2000억+ 스크리닝 (상한가 우선, 희소성 체크, 대형주 예외) - SectorPortfolioManager: 섹터 기반 비중 배분 - KJBScreeningSignalGenerator: 눌림목 진입, 5MA 손절, 단계적 익절 - KISTradeExecutor: KIS API 자동 매수/매도 (기본값 모의투자) - ScreeningSignal / AutoOrder DB 모델 추가 - screening API 엔드포인트 추가 - 스케줄러 잡 3종 추가 (08:30/5분/15:35) - Price.trading_value 컬럼 추가 - MarketIndex 테이블 추가 (KOSPI/KOSDAQ 지수 일봉) - IndexCollector 추가 (일일 수집 잡 등록) - intraday_exit_check 시간 필터 추가 (09:05~15:20 KST) - 드라이런 스크립트 추가 (scripts/screening_dryrun.py)
72 lines
1.8 KiB
Python
72 lines
1.8 KiB
Python
from datetime import date, datetime
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from decimal import Decimal
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from typing import List, Optional
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from pydantic import BaseModel
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from app.schemas.portfolio import FloatDecimal
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class ScreeningSignalResponse(BaseModel):
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id: int
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screen_date: date
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ticker: str
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name: Optional[str] = None
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sector: Optional[str] = None
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market_cap: Optional[int] = None
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trading_value: Optional[int] = None
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is_limit_up: bool = False
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daily_return: Optional[FloatDecimal] = None
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trigger_low: Optional[FloatDecimal] = None
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market_state: Optional[str] = None
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status: str
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entry_date: Optional[date] = None
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entry_price: Optional[FloatDecimal] = None
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exit_date: Optional[date] = None
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exit_price: Optional[FloatDecimal] = None
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created_at: datetime
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class Config:
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from_attributes = True
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class AutoOrderResponse(BaseModel):
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id: int
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order_date: datetime
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ticker: str
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order_type: Optional[str] = None
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qty: Optional[int] = None
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price: Optional[FloatDecimal] = None
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order_no: Optional[str] = None
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status: Optional[str] = None
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screening_signal_id: Optional[int] = None
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created_at: datetime
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class Config:
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from_attributes = True
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class WatchlistItem(BaseModel):
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ticker: str
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name: Optional[str] = None
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sector: Optional[str] = None
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screen_date: date
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trading_value: Optional[int] = None
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is_limit_up: bool = False
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daily_return: Optional[FloatDecimal] = None
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trigger_low: Optional[FloatDecimal] = None
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market_state: Optional[str] = None
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status: str
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class Config:
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from_attributes = True
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class ScreeningSummary(BaseModel):
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date: date
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market_state: str
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total_screened: int
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limit_up_count: int
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watchlist_count: int
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signals: List[ScreeningSignalResponse]
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