import csv
import sys

def filter_csv(input_csv, columns_file, output_csv):
    # Read the columns of interest from the text file
    with open(columns_file, 'r') as f:
        columns_of_interest = [line.strip() for line in f]

    # Read the input CSV file and filter based on the columns of interest
    with open(input_csv, 'r') as f:
        reader = csv.DictReader(f)  # Read the CSV as a dictionary
        
        # Identify which columns exist in the original CSV
        all_columns = reader.fieldnames
        columns_to_keep = ['id'] + [col for col in columns_of_interest if col in all_columns]

        # Prepare to write the filtered data to a new CSV
        with open(output_csv, 'w', newline='') as out_f:
            writer = csv.DictWriter(out_f, fieldnames=columns_to_keep)
            writer.writeheader()  # Write header to the output file
            
            for row in reader:
                # Keep only the columns of interest
                filtered_row = {col: row[col] for col in columns_to_keep}

                # Check if all values (except 'id') are zero, and skip such rows
                if all(int(filtered_row[col]) == 0 for col in columns_to_keep[1:]):
                    continue  # Skip rows where all selected columns (except 'id') are 0
                
                # Write the filtered row to the output file
                writer.writerow(filtered_row)

    print(f"Filtered data saved to {output_csv}")

# Main block to handle command line arguments
if __name__ == "__main__":
    if len(sys.argv) != 4:
        print("Usage: python filter_csv.py <input_file.csv> <columns_of_interest.txt> <filtered_output.csv>")
        sys.exit(1)

    input_csv = sys.argv[1]
    columns_file = sys.argv[2]
    output_csv = sys.argv[3]

    filter_csv(input_csv, columns_file, output_csv)