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Orchestrates and executes a comprehensive test suite for the Vice AI Data Analysis Integration, running multiple test functions, creating test datasets, and providing detailed pass/fail reporting.

Purpose

This function serves as the main entry point for testing the Vice AI data analysis integration system. It sequentially executes tests for model integration, data analysis service, and database schema, handles exceptions gracefully, creates test datasets, and provides a comprehensive summary of test results with actionable next steps for users.

Source Code

def main():
    """Run all tests"""
    print("🚀 Starting Vice AI Data Analysis Integration Tests\\n")
    
    tests = [
        ("Model Integration", test_models_integration),
        ("Data Analysis Service", test_data_analysis_service), 
        ("Database Schema", test_database_schema)
    ]
    
    results = []
    for test_name, test_func in tests:
        print(f"Running {test_name} test...")
        try:
            result = test_func()
            results.append((test_name, result))
            print(f"{'✅' if result else '❌'} {test_name} test {'PASSED' if result else 'FAILED'}\\n")
        except Exception as e:
            print(f"❌ {test_name} test FAILED with exception: {e}\\n")
            results.append((test_name, False))
    
    # Create test dataset
    print("Creating test dataset...")
    try:
        test_file = create_test_dataset()
        print(f"Test dataset available at: {test_file}")
    except Exception as e:
        print(f"❌ Failed to create test dataset: {e}")
    
    # Summary
    print("\\n" + "="*60)
    print("TEST SUMMARY")
    print("="*60)
    
    passed = sum(1 for _, result in results if result)
    total = len(results)
    
    for test_name, result in results:
        status = "PASSED" if result else "FAILED"
        icon = "✅" if result else "❌"
        print(f"{icon} {test_name}: {status}")
    
    print(f"\\nOverall: {passed}/{total} tests passed")
    
    if passed == total:
        print("\\n🎉 All tests passed! The data analysis integration is working correctly.")
        print("\\n📋 Next steps:")
        print("1. Start the Vice AI application: python new_app.py")
        print("2. Create a new document")
        print("3. Add a 'Data Analysis' section")
        print("4. Upload a CSV/Excel dataset")
        print("5. Interact with the statistical analysis agent")
        print("6. Export the analysis results to your document")
    else:
        print(f"\\n⚠️  {total - passed} tests failed. Please check the errors above.")
        
    return passed == total

Return Value

Returns a boolean value: True if all tests passed successfully, False if any test failed or raised an exception. This allows the function to be used in CI/CD pipelines or automated testing workflows.

Dependencies

• pandas
• pathlib
• tempfile
• datetime
• json
• sys
• os

Required Imports

import sys
import os
import json
import tempfile
from datetime import datetime
from pathlib import Path
import pandas as pd
from models import SectionType
from models import TextSection
from models import DataAnalysisSession
from models import AnalysisStatus
from models import DataSource
from models import DataSourceType
from data_analysis_service import DataAnalysisService
from models import DatabaseManager

Usage Example

# Assuming all required test functions and imports are available
# Run this as a standalone script or import and call

if __name__ == '__main__':
    # Execute the test suite
    success = main()
    
    # Exit with appropriate code for CI/CD integration
    import sys
    sys.exit(0 if success else 1)

# Or call directly in a test runner:
# from test_module import main
# test_passed = main()
# assert test_passed, 'Integration tests failed'

Best Practices

• Ensure all test functions (test_models_integration, test_data_analysis_service, test_database_schema) are properly defined before calling main()
• The function uses exception handling to prevent one failing test from stopping the entire suite
• Test results are collected and summarized at the end, providing clear visibility into which tests passed or failed
• The function provides actionable next steps when all tests pass, guiding users on how to use the system
• Use the boolean return value in CI/CD pipelines to determine build success/failure
• The create_test_dataset function should be implemented to generate appropriate test data for the analysis system
• Consider redirecting output to a log file for automated testing environments
• The function prints Unicode emoji characters; ensure the execution environment supports UTF-8 encoding

Tags

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