import os
import pandas as pd
from argparse import ArgumentParser

from src.grade import parse_grade_data, parse_final_grade_data
from src.execution import parse_execution_data
from src.assessment import parse_assessment_simple

def parse_args():
    """
    Parse command line arguments.
    """
    parser = ArgumentParser(description="Process CodeBench data.")
    parser.add_argument("--input", type=str, required=True, help="Input directory containing downloaded tar.")
    return parser.parse_args()


def process_data(BASE_PATH):

    assessment_data = []
    grade_data = []
    execution_data = []
    for root, dirs, files in os.walk(BASE_PATH):
        for d in dirs:
            full_path = os.path.join(root, d)
        if not len(dirs):
            # We are within a last level directory
            if root.split("/")[-1] == "assessments":
                for f in files:
                    full_path = os.path.join(root, f)
                    assessment_data.append(parse_assessment_simple(full_path))
            elif root.split("/")[-1] == "grades":
                for f in files:
                    if f.endswith(".data"): # Final grade
                        full_path = os.path.join(root, f)
                        grade_data.append(parse_final_grade_data(full_path))
                    else:
                        full_path = os.path.join(root, f)
                        grade_data.append(parse_grade_data(full_path)) 
            elif root.split("/")[-1] == "executions":
                for f in files:
                    full_path = os.path.join(root, f)
                    execution_data.append(parse_execution_data(full_path))
                    break 

    assessment_df = pd.concat(assessment_data)
    grade_df = pd.concat(grade_data)
    execution_df = pd.concat(execution_data)

    return assessment_df, grade_df, execution_df

def main():
    args = parse_args()
    # Load all provided dataframes
    subset = args.input.split("/")[-1]
    print(f"Processing data from {subset}...")
    assessment_df, grade_df, execution_df = process_data(args.input)

    # Save the dataframes to CSV files
    base_save_path = f"./data/{subset}/"
    os.makedirs(base_save_path, exist_ok=True)
    assessment_df.to_csv(os.path.join(base_save_path, f"assessment_{subset}.csv"), index=False)
    grade_df.to_csv(os.path.join(base_save_path, f"grade_{subset}.csv"), index=False)
    execution_df.to_csv(os.path.join(base_save_path, f"execution_{subset}.csv"), index=False)


if __name__ == "__main__":
    main()