import csv import argparse import json from datetime import datetime import os def validate_fake_companies(file_path, expected_num_companies=5, result_file=None): if not file_path.lower().endswith('.csv'): msg = f"Error: File {file_path} is not a CSV file." print(msg) if result_file: record_result(result_file, False, msg, process_success=False) return False try: with open(file_path, 'r', encoding='utf-8') as file: reader = csv.DictReader(file) rows = list(reader) except Exception as e: msg = f"Error: Unable to read file {file_path}, reason: {str(e)}" print(msg) if result_file: record_result(result_file, False, msg, process_success=False) return False if not rows: msg = "Error: CSV file is empty or contains no valid data rows." print(msg) if result_file: record_result(result_file, False, msg, process_success=True) return False if len(rows) != expected_num_companies: msg = f"Error: Expected {expected_num_companies} records, but got {len(rows)}." print(msg) if result_file: record_result(result_file, False, msg, process_success=True) return False required_fields = ['company name', 'address', 'phone'] for idx, row in enumerate(rows, 1): normalized_row = {k.lower().strip(): v.strip() for k, v in row.items()} for field in required_fields: if field not in normalized_row: msg = f"Error: Row {idx} is missing field '{field}'." print(msg) if result_file: record_result(result_file, False, msg, process_success=True) return False value = normalized_row[field] if not value: msg = f"Error: Row {idx} has empty value for field '{field}'." print(msg) if result_file: record_result(result_file, False, msg, process_success=True) return False # Basic content checks if field == "phone" and not any(char.isdigit() for char in value): msg = f"Error: Row {idx} field 'Phone' should contain digits." print(msg) if result_file: record_result(result_file, False, msg, process_success=True) return False if field == "company name" and value.isdigit(): msg = f"Error: Row {idx} field 'Company Name' should not be all digits." print(msg) if result_file: record_result(result_file, False, msg, process_success=True) return False if field == "address" and len(value) < 5: msg = f"Error: Row {idx} field 'Address' seems too short to be valid." print(msg) if result_file: record_result(result_file, False, msg, process_success=True) return False success_msg = f"All {expected_num_companies} company records passed structural and content checks." print(success_msg) if result_file: record_result(result_file, True, success_msg, process_success=True) return True def record_result(result_file, result, comments, process_success=True): # Get current timestamp time_point = datetime.now().strftime('%Y-%m-%dT%H:%M:%S') # Build result dictionary result_data = { "Process": process_success, "Result": result, "TimePoint": time_point, "comments": comments } # Write to jsonl file try: # Create file if it doesn't exist and append result with open(result_file, 'a', encoding='utf-8') as file: json.dump(result_data, file, ensure_ascii=False, default=str) file.write('\n') # Write each result on new line except Exception as e: print(f"Error: Unable to write to result file {result_file}, reason: {str(e)}") if __name__ == "__main__": parser = argparse.ArgumentParser(description="Validate generated fake company data") parser.add_argument('--output', type=str, required=True, help="Path to generated CSV file") parser.add_argument('--result', type=str, required=False, help="Path to save results in jsonl format", default="test_results.jsonl") args = parser.parse_args() # Execute validation validate_fake_companies(args.output, result_file=args.result)