#!/usr/bin/env python3
"""Fetch OHLCV bars from HF Market Data into CSV or Parquet.

Examples:
  fetch_bars.py --asset stock --ticker AAPL --start 2020-01-01 --out aapl.csv
  fetch_bars.py --asset stock --ticker AAPL MSFT --timeframe 1hour --start 2025-08-01 --out both.csv
  fetch_bars.py --asset futures --ticker CL --adjustment contin_adj_ratio --out cl.parquet
"""
from __future__ import annotations

import argparse
import sys
from pathlib import Path

import pandas as pd

sys.path.insert(0, str(Path(__file__).parent))
import hfmd  # noqa: E402


def main() -> int:
    ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter)
    ap.add_argument("--asset", required=True, choices=["stock", "etf", "crypto", "index", "fx", "futures"])
    ap.add_argument("--ticker", required=True, nargs="+", help="one or more symbols")
    ap.add_argument("--timeframe", default="1day", help="1min 5min 30min 1hour 1day (aliases 1m 5m 30m 1h 1d)")
    ap.add_argument("--start")
    ap.add_argument("--end")
    ap.add_argument("--adjustment", help="stock/etf: UNADJUSTED adj_split adj_splitdiv · futures: contin_UNadj contin_adj_ratio contin_adj_absolute")
    ap.add_argument("--out", required=True, help=".csv or .parquet")
    a = ap.parse_args()

    frames = []
    for t in a.ticker:
        df = hfmd.bars(a.asset, t.upper(), a.timeframe, a.start, a.end, a.adjustment)
        if df.empty:
            hfmd.log(f"{t}: no rows returned")
            continue
        hfmd.log(f"{t}: {len(df):,} bars from {df['datetime'].iloc[0]} to {df['datetime'].iloc[-1]}")
        frames.append(df)
    if not frames:
        return 1
    out = pd.concat(frames, ignore_index=True)
    if a.out.endswith(".parquet"):
        out.to_parquet(a.out, index=False)
    else:
        out.to_csv(a.out, index=False)
    print(f"wrote {a.out}: {len(out):,} rows, {out['ticker'].nunique()} ticker(s), columns={list(out.columns)}")
    return 0


if __name__ == "__main__":
    sys.exit(main())