import pandas as pd import argparse import re import os import constants from utils import parse_string def check_file(filename): if not filename.lower().endswith('.csv'): raise ValueError("Only CSV files are allowed.") if not os.path.exists(filename): raise FileNotFoundError("Filepath: {} invalid or not found.".format(filename)) def sanity_check(test_filename, output_filename): check_file(test_filename) check_file(output_filename) try: test_df = pd.read_csv(test_filename) output_df = pd.read_csv(output_filename) except Exception as e: raise ValueError(f"Error reading the CSV files: {e}") if 'index' not in test_df.columns: raise ValueError("Test CSV file must contain the 'index' column.") if 'index' not in output_df.columns or 'prediction' not in output_df.columns: raise ValueError("Output CSV file must contain 'index' and 'prediction' columns.") missing_index = set(test_df['index']).difference(set(output_df['index'])) if len(missing_index) != 0: print("Missing index in test file: {}".format(missing_index)) extra_index = set(output_df['index']).difference(set(test_df['index'])) if len(extra_index) != 0: print("Extra index in test file: {}".format(extra_index)) output_df.apply(lambda x: parse_string(x['prediction']), axis=1) print("Parsing successfull for file: {}".format(output_filename)) if __name__ == "__main__": #Usage example: python sanity.py --test_filename sample_test.csv --output_filename sample_test_out.csv parser = argparse.ArgumentParser(description="Run sanity check on a CSV file.") parser.add_argument("--test_filename", type=str, required=True, help="The test CSV file name.") parser.add_argument("--output_filename", type=str, required=True, help="The output CSV file name to check.") args = parser.parse_args() try: sanity_check(args.test_filename, args.output_filename) except Exception as e: print('Error:', e)