import os
import argparse
import pandas as pd
from risk_manage_engine.risk_calculator import calculate_all_risks
from risk_manage_engine.risk_scorer import compute_risk_score
from risk_manage_engine.filter import filter_by_risk

def evaluate_predictions(prediction_file, cds_dir, output_path="risk_filtered_result.csv"):
    df = pd.read_csv(prediction_file)

    results = []
    for _, row in df.iterrows():
        symbol = row["symbol"]
        score = row["predicted_score"]
        cds_path = os.path.join(cds_dir, f"{symbol}_ohlcv.csv")
        if not os.path.exists(cds_path):
            continue
        try:
            df_cds = pd.read_csv(cds_path)
            risk_factors = calculate_all_risks(df_cds)
            risk_score = compute_risk_score(risk_factors)
            results.append({
                "symbol": symbol,
                "predicted_score": score,
                "risk_score": risk_score,
                "tradable": risk_score >= 60  # 기준점은 조정 가능
            })
        except Exception as e:
            print(f"❌ {symbol} 리스크 평가 중 오류 발생: {e}")
            continue

    result_df = pd.DataFrame(results)

    print("\n[리스크 평가 요약]")
    print(result_df)

    result_df.to_csv(output_path, index=False)
    print(f"\n결과가 다음 위치에 저장되었습니다: {output_path}")

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="SightRay 리스크 평가 실행")
    parser.add_argument('--cds_dir', type=str, required=True, help='CDS 디렉토리 경로')
    parser.add_argument('--prediction_file', type=str, required=True, help='예측 결과 CSV 파일 경로')
    parser.add_argument('--output_file', type=str, default='risk_filtered_result.csv', help='리스크 평가 결과 저장 경로')
    args = parser.parse_args()

    evaluate_predictions(
        prediction_file=args.prediction_file,
        cds_dir=args.cds_dir,
        output_path=args.output_file
    )