import sys
import os
import pandas as pd

def generate_delta_csv(csv_pcp, csv_ppcp, output_directory=None):
    # If output_directory is not provided, use the current directory
    if output_directory is None:
        output_directory = os.getcwd()

    # Load CSV data into Pandas DataFrames
    df_pcp = pd.read_csv(csv_pcp)
    df_ppcp = pd.read_csv(csv_ppcp)

    # Ensure the tasks are in the same order
    df_pcp = df_pcp.sort_values(by='task').reset_index(drop=True)
    df_ppcp = df_ppcp.sort_values(by='task').reset_index(drop=True)

    # Calculate the differences
    df_delta = df_pcp.copy()
    df_delta[['worst', 'best', 'average', 'missed']] = df_pcp[['worst', 'best', 'average', 'missed']] - df_ppcp[['worst', 'best', 'average', 'missed']]

    # Save the result as CSV
    output_delta_path = os.path.join(output_directory, f'{os.path.basename(csv_pcp).replace("_PCP_", "_DELTA_")}')
    df_delta.to_csv(output_delta_path, index=False)

if __name__ == "__main__":
    if len(sys.argv) != 4 and len(sys.argv) != 3:
        print("Usage: python script.py csv_pcp csv_ppcp [output_directory]")
        sys.exit(1)

    csv_pcp = sys.argv[1]
    csv_ppcp = sys.argv[2]

    output_directory = sys.argv[3] if len(sys.argv) == 4 else '.'
    
    generate_delta_csv(csv_pcp, csv_ppcp, output_directory)