auto: 일일 백업 2026-06-09 02:00

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

agents/stock/workspace/sim/benchmark.py

@@ -0,0 +1,115 @@
+"""기준지수(KOSPI/KOSDAQ) 일별 종가 캐시 + 벤치마크 수익률·알파.
+
+네이버 m.stock 지수 일별시세 API에서 받아 state/sim/index_history.json 에 누적.
+sim/백테스트 수익률을 '같은 기간 지수 매수후보유' 대비(알파)로 평가하기 위한 데이터원.
+실패해도 raise 하지 않고 None 으로 흘려보낸다 (지표 부재 ≠ 엔진 중단).
+"""
+from __future__ import annotations
+
+import json
+import urllib.request
+
+from . import config
+
+INDEX_PATH = config.STATE_DIR / 'index_history.json'
+INDICES = ('KOSPI', 'KOSDAQ')
+INDEX_LABEL = {'KOSPI': '코스피', 'KOSDAQ': '코스닥'}
+
+
+def norm_date(d: str) -> str:
+    """'2026-06-09', '2026-06-09T...', '20260609' → 'YYYYMMDD'."""
+    return (d or '').replace('-', '')[:8]
+
+
+def _load() -> dict:
+    try:
+        return json.loads(INDEX_PATH.read_text())
+    except Exception:
+        return {}
+
+
+def _save(data: dict) -> None:
+    config.STATE_DIR.mkdir(parents=True, exist_ok=True)
+    INDEX_PATH.write_text(json.dumps(data, ensure_ascii=False))
+
+
+def _fetch_page(index: str, page: int, size: int) -> list[dict]:
+    url = f'https://m.stock.naver.com/api/index/{index}/price?pageSize={size}&page={page}'
+    req = urllib.request.Request(url, headers={'User-Agent': 'Mozilla/5.0'})
+    with urllib.request.urlopen(req, timeout=6.0) as r:
+        return json.loads(r.read().decode('utf-8', 'ignore')) or []
+
+
+def backfill(pages: int = 8, size: int = 50) -> dict:
+    """KOSPI/KOSDAQ 일별 종가를 pages×size 만큼 받아 캐시에 병합(idempotent). {index: 신규건수}."""
+    data = _load()
+    added: dict[str, int] = {}
+    for idx in INDICES:
+        store = data.setdefault(idx, {})
+        n0 = len(store)
+        for p in range(1, pages + 1):
+            try:
+                rows = _fetch_page(idx, p, size)
+            except Exception:
+                break
+            if not rows:
+                break
+            for row in rows:
+                d = norm_date(row.get('localTradedAt'))
+                c = row.get('closePrice')
+                if not d or not c:
+                    continue
+                try:
+                    store[d] = float(str(c).replace(',', ''))
+                except (ValueError, TypeError):
+                    pass
+        added[idx] = len(store) - n0
+    _save(data)
+    return added
+
+
+def update_today() -> None:
+    """최신 1페이지만 받아 오늘 종가 갱신 (스캔마다 저비용 호출, 실패 무시)."""
+    try:
+        backfill(pages=1, size=10)
+    except Exception:
+        pass
+
+
+def series(index: str) -> dict:
+    return _load().get(index, {})
+
+
+def _nearest(store: dict, date: str, after: bool):
+    """date 기준 on-or-after(after=True) / on-or-before 가장 가까운 (date, close). 없으면 None."""
+    if not store:
+        return None
+    d = norm_date(date)
+    keys = sorted(store)
+    if after:
+        cand = [k for k in keys if k >= d]
+        k = cand[0] if cand else None
+    else:
+        cand = [k for k in keys if k <= d]
+        k = cand[-1] if cand else None
+    return (k, store[k]) if k else None
+
+
+def benchmark_return(index: str, date_from: str, date_to: str):
+    """[from, to] 구간 지수 등락률(%). from=on-or-after, to=on-or-before 종가. 데이터 없으면 None."""
+    store = series(index)
+    a = _nearest(store, date_from, after=True)
+    b = _nearest(store, date_to, after=False)
+    if not a or not b or a[1] <= 0 or b[0] <= a[0]:
+        return None
+    return round((b[1] / a[1] - 1) * 100, 2)
+
+
+def compare(return_pct, date_from: str, date_to: str) -> dict:
+    """기간 수익률(return_pct)을 지수 대비로 비교. {index: {'pct':지수등락, 'alpha':초과}}."""
+    out: dict[str, dict] = {}
+    for idx in INDICES:
+        b = benchmark_return(idx, date_from, date_to)
+        alpha = round(return_pct - b, 2) if (b is not None and return_pct is not None) else None
+        out[idx] = {'pct': b, 'alpha': alpha}
+    return out