gahusb
ace0339d33
- git mv stock-lab/ → stock/ - docker-compose.yml: 서비스 키 + container_name + build.context + frontend.depends_on + agent-office STOCK_LAB_URL → STOCK_URL - agent-office/app: config.py, service_proxy.py, agents/stock.py, tests/ STOCK_LAB_URL → STOCK_URL - nginx/default.conf: proxy_pass http://stock-lab → http://stock (3 lines) - CLAUDE.md / README.md / STATUS.md / scripts/ 문구 갱신 - stock/ 내부 자기 참조 갱신 lab 네이밍 정책 (feedback_lab_naming.md) graduation. API URL / Python import / DB 파일명 변경 없음.
31 lines
1.0 KiB
Python
31 lines
1.0 KiB
Python
"""52주 신고가 근접도 (룰 기반: 70% 미만 0점, 100% 도달 100점, 선형)."""
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import pandas as pd
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from .base import ScoreNode
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class High52WProximity(ScoreNode):
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name = "high52w"
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label = "52주 신고가 근접도"
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default_params = {"window_days": 252}
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param_schema = {
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"type": "object",
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"properties": {
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"window_days": {"type": "integer", "minimum": 60, "maximum": 504, "default": 252}
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},
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}
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def compute(self, ctx, params: dict) -> pd.Series:
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window = int(params.get("window_days", 252))
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prices = ctx.prices
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if prices.empty:
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return pd.Series(dtype=float)
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ordered = prices.sort_values("date")
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last = ordered.groupby("ticker").tail(window)
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agg = last.groupby("ticker").agg(close=("close", "last"), high=("high", "max"))
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proximity = (agg["close"] / agg["high"]).clip(upper=1.0)
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score = ((proximity - 0.7) / 0.3).clip(lower=0.0, upper=1.0) * 100.0
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return score.fillna(0.0)
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