run_backtest_universe.py

from pathlib import Path
import pandas as pd

from strategy_engine import scan_symbol_for_day, OUTPUT_COLUMNS

BASE_DIR = Path(__file__).resolve().parent
UNIVERSE_PATH = BASE_DIR / "option_stock_universe.csv"
OUT_DIR = BASE_DIR / "outputs"

TRADE_DATE = "2026-02-26"

MODE = "priority"   # "priority" or "all"

# MODE = "all"


def load_universe():
    df = pd.read_csv(UNIVERSE_PATH)
    df["symbol"] = df["symbol"].astype(str).str.upper()
    df["sector"] = df["sector"].fillna("").astype(str)
    df["priority_rank"] = pd.to_numeric(df["priority_rank"], errors="coerce").fillna(999)
    return df


def pick_universe(df, mode):
    if mode == "priority":
        return df[df["priority_rank"] == 1].copy()
    if mode == "all":
        return df.copy()
    raise ValueError("MODE must be 'priority' or 'all'")


def main():
    OUT_DIR.mkdir(exist_ok=True)

    universe = load_universe()
    universe = pick_universe(universe, MODE)

    print(f"Universe mode: {MODE}")
    print(f"Symbols to scan: {len(universe)}")

    for variant in ["v1", "v2"]:
        print(f"\nRunning {variant} ...")
        option_cache = {}
        frames = []

        for _, row in universe.iterrows():
            symbol = row["symbol"]
            sector = row["sector"]

            print(f"Scanning {symbol} ...")
            try:
                df = scan_symbol_for_day(
                    stock_symbol=symbol,
                    sector=sector,
                    trade_date=TRADE_DATE,
                    variant=variant,
                    option_cache=option_cache,
                )

                if not df.empty:
                    frames.append(df)
                    print(f"  Trades found: {len(df)}")
                else:
                    print("  No trades")
            except Exception as e:
                print(f"  Error: {e}")

        if frames:
            result = pd.concat(frames, ignore_index=True)
        else:
            result = pd.DataFrame(columns=OUTPUT_COLUMNS)

        out_path = OUT_DIR / f"paper_trades_{TRADE_DATE}_{MODE}_{variant}.csv"
        result.to_csv(out_path, index=False)

        print(f"\nSaved: {out_path}")
        print(f"Total rows: {len(result)}")


if __name__ == "__main__":
    main()