b86c88a8d6
- Created README.md to document project features, structure, and setup instructions. - Updated fetch_history.py to include path adjustments for module imports. - Enhanced train_model.py for parallel processing of dataset generation and added command-line argument for specifying worker count. Made-with: Cursor
74 lines
2.4 KiB
Python
74 lines
2.4 KiB
Python
"""
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바이낸스 선물 REST API로 과거 캔들 데이터를 수집해 parquet으로 저장한다.
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사용법: python scripts/fetch_history.py --symbol XRPUSDT --interval 1m --days 90
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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 asyncio
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import argparse
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from datetime import datetime, timedelta
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import pandas as pd
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from binance import AsyncClient
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from dotenv import load_dotenv
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import os
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load_dotenv()
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async def fetch_klines(symbol: str, interval: str, days: int) -> pd.DataFrame:
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client = await AsyncClient.create(
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api_key=os.getenv("BINANCE_API_KEY", ""),
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api_secret=os.getenv("BINANCE_API_SECRET", ""),
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)
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try:
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start_ts = int((datetime.utcnow() - timedelta(days=days)).timestamp() * 1000)
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all_klines = []
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while True:
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klines = await client.futures_klines(
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symbol=symbol,
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interval=interval,
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startTime=start_ts,
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limit=1500,
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)
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if not klines:
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break
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all_klines.extend(klines)
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last_ts = klines[-1][0]
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if last_ts >= int(datetime.utcnow().timestamp() * 1000):
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break
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start_ts = last_ts + 1
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print(f"수집 중... {len(all_klines)}개")
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finally:
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await client.close_connection()
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df = pd.DataFrame(all_klines, columns=[
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"timestamp", "open", "high", "low", "close", "volume",
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"close_time", "quote_volume", "trades",
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"taker_buy_base", "taker_buy_quote", "ignore",
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])
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df = df[["timestamp", "open", "high", "low", "close", "volume"]].copy()
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for col in ["open", "high", "low", "close", "volume"]:
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df[col] = df[col].astype(float)
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df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms")
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df.set_index("timestamp", inplace=True)
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return df
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--symbol", default="XRPUSDT")
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parser.add_argument("--interval", default="1m")
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parser.add_argument("--days", type=int, default=90)
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parser.add_argument("--output", default="data/xrpusdt_1m.parquet")
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args = parser.parse_args()
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df = asyncio.run(fetch_klines(args.symbol, args.interval, args.days))
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df.to_parquet(args.output)
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print(f"저장 완료: {args.output} ({len(df)}행)")
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if __name__ == "__main__":
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main()
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