feat: add L/S ratio collector service for top_acct and global ratios

Collect top trader account L/S ratio and global L/S ratio every 15 minutes
for XRP, BTC, ETH (6 API calls/cycle) and persist to per-symbol parquet files.
Deployed as a separate Docker service reusing the bot image.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

scripts/collect_ls_ratio.py

@@ -0,0 +1,121 @@
+"""
+Long/Short Ratio 장기 수집 스크립트.
+15분마다 cron 실행하여 Binance Trading Data API에서
+top_acct_ls_ratio, global_ls_ratio를 data/{symbol}/ls_ratio_15m.parquet에 누적한다.
+
+수집 대상:
+  - topLongShortAccountRatio × 3심볼 (XRPUSDT, BTCUSDT, ETHUSDT)
+  - globalLongShortAccountRatio × 3심볼 (XRPUSDT, BTCUSDT, ETHUSDT)
+  → 총 API 호출 6회/15분 (rate limit 무관)
+
+사용법:
+  python scripts/collect_ls_ratio.py
+  python scripts/collect_ls_ratio.py --symbols XRPUSDT BTCUSDT
+"""
+
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+import argparse
+import asyncio
+from datetime import datetime, timezone
+
+import aiohttp
+import pandas as pd
+
+BASE_URL = "https://fapi.binance.com"
+DEFAULT_SYMBOLS = ["XRPUSDT", "BTCUSDT", "ETHUSDT"]
+
+ENDPOINTS = {
+    "top_acct_ls_ratio": "/futures/data/topLongShortAccountRatio",
+    "global_ls_ratio": "/futures/data/globalLongShortAccountRatio",
+}
+
+
+async def fetch_latest(session: aiohttp.ClientSession, symbol: str) -> dict | None:
+    """심볼 하나에 대해 두 ratio의 최신 1건씩 가져온다."""
+    row = {"timestamp": None, "symbol": symbol}
+
+    for col_name, endpoint in ENDPOINTS.items():
+        url = f"{BASE_URL}{endpoint}"
+        params = {"symbol": symbol, "period": "15m", "limit": 1}
+        try:
+            async with session.get(url, params=params, timeout=aiohttp.ClientTimeout(total=10)) as resp:
+                data = await resp.json()
+                if isinstance(data, list) and data:
+                    row[col_name] = float(data[0]["longShortRatio"])
+                    # 타임스탬프는 첫 번째 응답에서 설정
+                    if row["timestamp"] is None:
+                        row["timestamp"] = pd.Timestamp(
+                            int(data[0]["timestamp"]), unit="ms", tz="UTC"
+                        )
+                else:
+                    print(f"[WARN] {symbol} {col_name}: unexpected response: {data}")
+                    return None
+        except Exception as e:
+            print(f"[ERROR] {symbol} {col_name}: {e}")
+            return None
+
+    return row
+
+
+async def collect(symbols: list[str]):
+    """모든 심볼 데이터를 수집하고 parquet에 추가한다."""
+    async with aiohttp.ClientSession() as session:
+        tasks = [fetch_latest(session, sym) for sym in symbols]
+        results = await asyncio.gather(*tasks)
+
+    now = datetime.now(timezone.utc)
+    collected = 0
+
+    for row in results:
+        if row is None:
+            continue
+
+        symbol = row["symbol"]
+        out_path = Path(f"data/{symbol.lower()}/ls_ratio_15m.parquet")
+        out_path.parent.mkdir(parents=True, exist_ok=True)
+
+        new_df = pd.DataFrame([{
+            "timestamp": row["timestamp"],
+            "top_acct_ls_ratio": row["top_acct_ls_ratio"],
+            "global_ls_ratio": row["global_ls_ratio"],
+        }])
+
+        if out_path.exists():
+            existing = pd.read_parquet(out_path)
+            # 중복 방지: 동일 timestamp가 이미 있으면 스킵
+            if row["timestamp"] in existing["timestamp"].values:
+                print(f"[SKIP] {symbol} ts={row['timestamp']} already exists")
+                continue
+            combined = pd.concat([existing, new_df], ignore_index=True)
+        else:
+            combined = new_df
+
+        combined.to_parquet(out_path, index=False)
+        collected += 1
+        print(
+            f"[{now.isoformat()}] {symbol}: "
+            f"top_acct={row['top_acct_ls_ratio']:.4f}, "
+            f"global={row['global_ls_ratio']:.4f} "
+            f"→ {out_path} ({len(combined)} rows)"
+        )
+
+    if collected == 0:
+        print(f"[{now.isoformat()}] No new data collected")
+
+
+def main():
+    parser = argparse.ArgumentParser(description="L/S Ratio 장기 수집")
+    parser.add_argument(
+        "--symbols", nargs="+", default=DEFAULT_SYMBOLS,
+        help="수집 대상 심볼 (기본: XRPUSDT BTCUSDT ETHUSDT)",
+    )
+    args = parser.parse_args()
+    asyncio.run(collect(args.symbols))
+
+
+if __name__ == "__main__":
+    main()