48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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import pandas as pd
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from qfr.data.tushare_client import fetch_fund_daily, load_tushare_config
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def main() -> None:
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p = argparse.ArgumentParser()
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p.add_argument("--env", default=None, help="Path to .env")
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p.add_argument("--config", default="configs/etf_universe.json")
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p.add_argument("--start", dest="start_date", default=None, help="YYYYMMDD")
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p.add_argument("--end", dest="end_date", default=None, help="YYYYMMDD")
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p.add_argument("--outdir", default="data/raw")
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args = p.parse_args()
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cfg = load_tushare_config(args.env)
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conf = json.loads(Path(args.config).read_text(encoding="utf-8"))
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assets = conf["assets"]
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outdir = Path(args.outdir)
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outdir.mkdir(parents=True, exist_ok=True)
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for a in assets:
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ts_code = a["ts_code"]
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df = fetch_fund_daily(cfg, ts_code=ts_code, start_date=args.start_date, end_date=args.end_date)
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if df is None or df.empty:
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print(f"skip {ts_code}: empty")
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continue
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# standardize columns expected by backtest
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# fund_daily provides: ts_code, trade_date, open, high, low, close, vol, amount
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keep = [c for c in ["ts_code", "trade_date", "open", "high", "low", "close", "vol", "amount"] if c in df.columns]
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df = df[keep].copy()
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df = df.sort_values("trade_date")
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out = outdir / f"{ts_code.replace('.', '')}.parquet"
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df.to_parquet(out, index=False)
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print(f"wrote {ts_code}: {len(df)} rows -> {out}")
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if __name__ == "__main__":
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main()
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