feat: 리밸런싱 엔진 V1 + GAS 버그 수정 (2026-06-13)

주요 변경: - tools/build_rebalance_engine_v1.py: REBALANCE_ENGINE_V1 신규 * account_snapshot 직접 합산(_build_snap_position_map) → 소수주 분리 행 병합 * 레짐 소스 macro.REGIME_PRELIM 최우선 (GAS 와 동일) - src/gas_adapter_parts/gdf_06_rebalance.gs: runRebalanceSheet_() 신규 * Logger.log / getSpreadsheet_() 로 run_all 연동 수정 - src/gas_adapter_parts/gdc_01_fetch_fundamentals.gs * _mergePositionRecord_(): 소수주 중복 행 합산 신규 * parseInt → parseFloat (qty, availQty) - src/gas_adapter_parts/gdf_01_price_metrics.gs * 미보유 종목 SELL_READY → WATCH_EXIT_SIGNAL - spec/41_release_dag.yaml: build_rebalance_sheet 노드 추가 (step_count 63) - spec/51_formula_lifecycle_registry.yaml: REBALANCE_ENGINE_V1 등록 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-13 13:20:14 +09:00
commit ee3e799de1
1474 changed files with 176087 additions and 0 deletions
@@ -0,0 +1,234 @@
+from __future__ import annotations
+
+import argparse
+import csv
+import datetime as dt
+import re
+from pathlib import Path
+from typing import Any
+
+import openpyxl
+
+
+ROOT = Path(__file__).resolve().parents[2]
+DEFAULT_XLSX = ROOT / "GatherTradingData.xlsx"
+
+OUTPUT_HEADERS = [
+    "ETF_Ticker",
+    "ETF_Name",
+    "Close",
+    "NAV",
+    "iNAV",
+    "Premium_Discount_Pct",
+    "Tracking_Error",
+    "AUM",
+    "Source_Date",
+    "Source",
+    "Enabled",
+    "Note",
+]
+
+COLUMN_ALIASES = {
+    "ticker": ["ETF_Ticker", "종목코드", "단축코드", "표준코드", "code", "ticker"],
+    "name": ["ETF_Name", "종목명", "한글종목명", "Name", "name"],
+    "close": ["Close", "종가", "현재가", "시장가격", "TDD_CLSPRC", "close"],
+    "nav": ["NAV", "순자산가치", "기준가격", "기준가", "NAV(원)", "nav"],
+    "inav": ["iNAV", "추정순자산가치", "실시간기준가", "iNAV(원)", "inav"],
+    "premium_discount_pct": ["Premium_Discount_Pct", "괴리율", "괴리율(%)", "가격괴리율", "premium_discount_pct"],
+    "tracking_error": ["Tracking_Error", "추적오차율", "추적오차", "추적오차율(%)", "tracking_error"],
+    "aum": ["AUM", "순자산총액", "순자산총액(원)", "상장좌수", "aum"],
+    "source_date": ["Source_Date", "기준일", "일자", "거래일자", "Date", "date"],
+}
+
+
+def normalize_header(value: Any) -> str:
+    return re.sub(r"\s+", "", str(value or "").strip()).lower()
+
+
+def normalize_ticker(value: Any) -> str:
+    text = str(value or "").strip()
+    if text.endswith(".0"):
+        text = text[:-2]
+    text = re.sub(r"[^0-9A-Za-z]", "", text)
+    if text.isdigit():
+        return text.zfill(6)
+    if re.fullmatch(r"[0-9A-Za-z]{1,6}", text):
+        return text.zfill(6)
+    return text
+
+
+def parse_number(value: Any) -> float | None:
+    if value in (None, ""):
+        return None
+    if isinstance(value, (int, float)) and not isinstance(value, bool):
+        return float(value)
+    text = str(value).strip()
+    if not text or text in {"-", "N/A", "nan"}:
+        return None
+    text = text.replace(",", "").replace("%", "")
+    try:
+        return float(text)
+    except ValueError:
+        return None
+
+
+def parse_date(value: Any) -> str:
+    if value in (None, ""):
+        return ""
+    if isinstance(value, (dt.datetime, dt.date)):
+        return value.strftime("%Y-%m-%d")
+    text = str(value).strip()
+    match = re.search(r"(\d{4})[./-]?(\d{1,2})[./-]?(\d{1,2})", text)
+    if not match:
+        return ""
+    y, m, d = match.groups()
+    return f"{y}-{int(m):02d}-{int(d):02d}"
+
+
+def read_source_table(path: Path) -> list[dict[str, Any]]:
+    if path.suffix.lower() in {".xlsx", ".xlsm"}:
+        wb = openpyxl.load_workbook(path, data_only=True, read_only=True)
+        ws = wb[wb.sheetnames[0]]
+        rows = list(ws.iter_rows(values_only=True))
+        header_row_idx = 0
+        best_score = -1
+        alias_tokens = {normalize_header(a) for aliases in COLUMN_ALIASES.values() for a in aliases}
+        for i, row in enumerate(rows[:20]):
+            score = sum(1 for cell in row if normalize_header(cell) in alias_tokens)
+            if score > best_score:
+                best_score = score
+                header_row_idx = i
+        headers = [str(v or "").strip() for v in rows[header_row_idx]]
+        return [
+            dict(zip(headers, row))
+            for row in rows[header_row_idx + 1 :]
+            if row and any(v not in (None, "") for v in row)
+        ]
+
+    encoding_candidates = ["utf-8-sig", "cp949", "euc-kr"]
+    last_error: Exception | None = None
+    for encoding in encoding_candidates:
+        try:
+            with path.open("r", encoding=encoding, newline="") as f:
+                sample = f.read(4096)
+                f.seek(0)
+                dialect = csv.Sniffer().sniff(sample, delimiters=",\t;")
+                return list(csv.DictReader(f, dialect=dialect))
+        except Exception as exc:
+            last_error = exc
+    raise RuntimeError(f"failed to read source file {path}: {last_error}")
+
+
+def resolve_columns(rows: list[dict[str, Any]]) -> dict[str, str]:
+    if not rows:
+        return {}
+    source_headers = list(rows[0].keys())
+    normalized = {normalize_header(h): h for h in source_headers}
+    resolved: dict[str, str] = {}
+    for field, aliases in COLUMN_ALIASES.items():
+        for alias in aliases:
+            key = normalize_header(alias)
+            if key in normalized:
+                resolved[field] = normalized[key]
+                break
+    return resolved
+
+
+def existing_etfs(wb: openpyxl.Workbook) -> dict[str, str]:
+    result: dict[str, str] = {}
+    if "etf_raw" in wb.sheetnames:
+        ws = wb["etf_raw"]
+        headers = [ws.cell(2, c).value for c in range(1, ws.max_column + 1)]
+        idx = {h: i + 1 for i, h in enumerate(headers) if h}
+        if "ETF_Ticker" in idx:
+            for r in range(3, ws.max_row + 1):
+                ticker = normalize_ticker(ws.cell(r, idx["ETF_Ticker"]).value)
+                if ticker:
+                    result[ticker] = str(ws.cell(r, idx.get("ETF_Name", idx["ETF_Ticker"])).value or "")
+    return result
+
+
+def update_workbook(workbook_path: Path, source_path: Path, enable: bool) -> tuple[int, int]:
+    rows = read_source_table(source_path)
+    columns = resolve_columns(rows)
+    if "ticker" not in columns:
+        raise RuntimeError(f"source file has no ticker/code column. resolved={columns}")
+
+    wb = openpyxl.load_workbook(workbook_path)
+    targets = existing_etfs(wb)
+    if "etf_nav_manual" in wb.sheetnames:
+        del wb["etf_nav_manual"]
+    insert_at = wb.sheetnames.index("etf_raw") + 1 if "etf_raw" in wb.sheetnames else 1
+    ws = wb.create_sheet("etf_nav_manual", insert_at)
+    ws.append([f"updated: imported from {source_path.name}"])
+    ws.append(OUTPUT_HEADERS)
+
+    imported = 0
+    matched = 0
+    seen: set[str] = set()
+    for row in rows:
+        ticker = normalize_ticker(row.get(columns["ticker"]))
+        if not ticker or ticker in seen:
+            continue
+        seen.add(ticker)
+        name = str(row.get(columns.get("name", ""), "") or targets.get(ticker, "")).strip()
+        close = parse_number(row.get(columns.get("close", "")))
+        nav = parse_number(row.get(columns.get("nav", "")))
+        inav = parse_number(row.get(columns.get("inav", "")))
+        premium = parse_number(row.get(columns.get("premium_discount_pct", "")))
+        if premium is None:
+            basis_nav = nav if nav and nav > 0 else inav
+            if close is not None and basis_nav and basis_nav > 0:
+                premium = ((close / basis_nav) - 1) * 100
+        tracking_error = parse_number(row.get(columns.get("tracking_error", "")))
+        aum = parse_number(row.get(columns.get("aum", "")))
+        source_date = parse_date(row.get(columns.get("source_date", "")))
+        is_match = not targets or ticker in targets
+        if is_match:
+            matched += 1
+        row_enable = "Y" if enable and is_match and (nav is not None or inav is not None) else "N"
+        ws.append([
+            ticker,
+            name,
+            close,
+            nav,
+            inav,
+            premium,
+            tracking_error,
+            aum,
+            source_date,
+            f"import:{source_path.name}",
+            row_enable,
+            "matched_etf_raw" if is_match else "not_in_etf_raw_review_before_enable",
+        ])
+        imported += 1
+
+    for row in ws.iter_rows(min_row=1, max_row=ws.max_row):
+        row[0].number_format = "@"
+    for cell in ws[2]:
+        cell.font = openpyxl.styles.Font(bold=True, color="FFFFFF")
+        cell.fill = openpyxl.styles.PatternFill("solid", fgColor="7030A0")
+    ws.freeze_panes = "A3"
+    ws.auto_filter.ref = f"A2:L{ws.max_row}"
+    widths = [14, 34, 14, 14, 14, 20, 16, 16, 16, 28, 10, 42]
+    for i, width in enumerate(widths, 1):
+        ws.column_dimensions[openpyxl.utils.get_column_letter(i)].width = width
+
+    wb.save(workbook_path)
+    return imported, matched
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Import official ETF NAV/iNAV data into etf_nav_manual sheet.")
+    parser.add_argument("source", type=Path, help="KRX/KIND/issuer CSV or XLSX export")
+    parser.add_argument("--workbook", type=Path, default=DEFAULT_XLSX)
+    parser.add_argument("--enable", action="store_true", help="Set Enabled=Y for matched rows with NAV or iNAV")
+    args = parser.parse_args()
+
+    imported, matched = update_workbook(args.workbook, args.source, args.enable)
+    print(f"ETF NAV IMPORT OK: imported={imported} matched_etf_raw={matched} workbook={args.workbook.name}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())