e2b0454825
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>
122 lines
4.0 KiB
Python
122 lines
4.0 KiB
Python
"""
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Long/Short Ratio 장기 수집 스크립트.
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15분마다 cron 실행하여 Binance Trading Data API에서
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top_acct_ls_ratio, global_ls_ratio를 data/{symbol}/ls_ratio_15m.parquet에 누적한다.
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수집 대상:
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- topLongShortAccountRatio × 3심볼 (XRPUSDT, BTCUSDT, ETHUSDT)
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- globalLongShortAccountRatio × 3심볼 (XRPUSDT, BTCUSDT, ETHUSDT)
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→ 총 API 호출 6회/15분 (rate limit 무관)
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사용법:
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python scripts/collect_ls_ratio.py
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python scripts/collect_ls_ratio.py --symbols XRPUSDT BTCUSDT
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"""
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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import argparse
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import asyncio
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from datetime import datetime, timezone
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import aiohttp
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import pandas as pd
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BASE_URL = "https://fapi.binance.com"
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DEFAULT_SYMBOLS = ["XRPUSDT", "BTCUSDT", "ETHUSDT"]
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ENDPOINTS = {
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"top_acct_ls_ratio": "/futures/data/topLongShortAccountRatio",
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"global_ls_ratio": "/futures/data/globalLongShortAccountRatio",
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}
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async def fetch_latest(session: aiohttp.ClientSession, symbol: str) -> dict | None:
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"""심볼 하나에 대해 두 ratio의 최신 1건씩 가져온다."""
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row = {"timestamp": None, "symbol": symbol}
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for col_name, endpoint in ENDPOINTS.items():
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url = f"{BASE_URL}{endpoint}"
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params = {"symbol": symbol, "period": "15m", "limit": 1}
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try:
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async with session.get(url, params=params, timeout=aiohttp.ClientTimeout(total=10)) as resp:
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data = await resp.json()
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if isinstance(data, list) and data:
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row[col_name] = float(data[0]["longShortRatio"])
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# 타임스탬프는 첫 번째 응답에서 설정
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if row["timestamp"] is None:
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row["timestamp"] = pd.Timestamp(
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int(data[0]["timestamp"]), unit="ms", tz="UTC"
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)
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else:
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print(f"[WARN] {symbol} {col_name}: unexpected response: {data}")
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return None
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except Exception as e:
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print(f"[ERROR] {symbol} {col_name}: {e}")
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return None
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return row
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async def collect(symbols: list[str]):
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"""모든 심볼 데이터를 수집하고 parquet에 추가한다."""
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async with aiohttp.ClientSession() as session:
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tasks = [fetch_latest(session, sym) for sym in symbols]
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results = await asyncio.gather(*tasks)
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now = datetime.now(timezone.utc)
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collected = 0
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for row in results:
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if row is None:
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continue
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symbol = row["symbol"]
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out_path = Path(f"data/{symbol.lower()}/ls_ratio_15m.parquet")
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out_path.parent.mkdir(parents=True, exist_ok=True)
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new_df = pd.DataFrame([{
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"timestamp": row["timestamp"],
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"top_acct_ls_ratio": row["top_acct_ls_ratio"],
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"global_ls_ratio": row["global_ls_ratio"],
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}])
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if out_path.exists():
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existing = pd.read_parquet(out_path)
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# 중복 방지: 동일 timestamp가 이미 있으면 스킵
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if row["timestamp"] in existing["timestamp"].values:
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print(f"[SKIP] {symbol} ts={row['timestamp']} already exists")
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continue
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combined = pd.concat([existing, new_df], ignore_index=True)
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else:
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combined = new_df
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combined.to_parquet(out_path, index=False)
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collected += 1
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print(
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f"[{now.isoformat()}] {symbol}: "
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f"top_acct={row['top_acct_ls_ratio']:.4f}, "
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f"global={row['global_ls_ratio']:.4f} "
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f"→ {out_path} ({len(combined)} rows)"
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)
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if collected == 0:
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print(f"[{now.isoformat()}] No new data collected")
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def main():
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parser = argparse.ArgumentParser(description="L/S Ratio 장기 수집")
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parser.add_argument(
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"--symbols", nargs="+", default=DEFAULT_SYMBOLS,
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help="수집 대상 심볼 (기본: XRPUSDT BTCUSDT ETHUSDT)",
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)
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args = parser.parse_args()
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asyncio.run(collect(args.symbols))
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if __name__ == "__main__":
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main()
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