🔍 Code Extractor

function test_models_integration

Maturity: 42

Integration test function that validates the import and instantiation of data models including SectionType, TextSection, DataAnalysisSession, AnalysisStatus, DataSource, and DataSourceType.

File:
/tf/active/vicechatdev/vice_ai/test_integration.py
Lines:
17 - 54
Complexity:
simple

Purpose

This function serves as an integration test to ensure all required models from the models module can be successfully imported and instantiated with test data. It verifies the basic functionality of creating TextSection objects with DATA_ANALYSIS type and DataAnalysisSession objects, providing early detection of import errors or model initialization issues in the codebase.

Source Code

def test_models_integration():
    """Test that all models can be imported and created"""
    print("Testing model imports...")
    
    try:
        from models import (
            SectionType, TextSection, DataAnalysisSession, 
            AnalysisStatus, DataSource, DataSourceType
        )
        print("✅ All models imported successfully")
        
        # Test creating a data analysis section
        section = TextSection(
            id="test-section",
            owner="test@example.com", 
            title="Test Analysis Section",
            section_type=SectionType.DATA_ANALYSIS
        )
        print("✅ Data analysis TextSection created successfully")
        
        # Test creating analysis session
        analysis_session = DataAnalysisSession(
            session_id="test-analysis",
            section_id="test-section",
            document_id="test-doc",
            user_id="test@example.com",
            title="Test Analysis"
        )
        print("✅ DataAnalysisSession created successfully")
        
        return True
        
    except ImportError as e:
        print(f"❌ Import error: {e}")
        return False
    except Exception as e:
        print(f"❌ Model creation error: {e}")
        return False

Return Value

Returns a boolean value: True if all models are successfully imported and instantiated without errors, False if any ImportError or Exception occurs during the test process. The function also prints status messages to stdout indicating success (✅) or failure (❌) for each test step.

Dependencies

  • models

Required Imports

from models import SectionType
from models import TextSection
from models import DataAnalysisSession
from models import AnalysisStatus
from models import DataSource
from models import DataSourceType

Conditional/Optional Imports

These imports are only needed under specific conditions:

from models import SectionType, TextSection, DataAnalysisSession, AnalysisStatus, DataSource, DataSourceType

Condition: imported within try-except block to catch ImportError during testing

Required (conditional)

Usage Example

# Run the integration test
result = test_models_integration()

if result:
    print("All model integration tests passed")
else:
    print("Model integration tests failed")

# Expected output:
# Testing model imports...
# ✅ All models imported successfully
# ✅ Data analysis TextSection created successfully
# ✅ DataAnalysisSession created successfully

Best Practices

  • This function should be run as part of a test suite to verify model availability before running the main application
  • The function uses print statements for output; consider using a proper logging framework for production test suites
  • The function catches broad Exception types; consider more specific exception handling for better error diagnosis
  • Test data uses hardcoded values (e.g., 'test@example.com'); ensure these don't conflict with actual data in production environments
  • This is a basic smoke test; more comprehensive unit tests should be created for individual model validation
  • The function returns boolean for success/failure but also prints messages; consider separating concerns for better testability

Tags

testing integration-test models validation import-test data-analysis model-instantiation error-handling

Similar Components

AI-powered semantic similarity - components with related functionality:

  • function test_data_analysis_service 67.4% similar

    A test function that validates the functionality of the DataAnalysisService by creating, initializing, and retrieving analysis sessions.

    From: /tf/active/vicechatdev/vice_ai/test_integration.py

  • function test_imports 60.5% similar

    A diagnostic function that tests the availability and correct import of all critical project modules including configuration, logging utilities, and email forwarding components.

    From: /tf/active/vicechatdev/email-forwarder/test_imports.py

  • function test_database_schema 58.0% similar

    A test function that validates database schema updates, specifically testing the storage and retrieval of TextSection objects with analysis_session_id fields using an in-memory SQLite database.

    From: /tf/active/vicechatdev/vice_ai/test_integration.py

  • function main_v25 56.5% similar

    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.

    From: /tf/active/vicechatdev/vice_ai/test_integration.py

  • function test_enhanced_workflow 55.3% similar

    A comprehensive test function that validates the EnhancedSQLWorkflow system by testing component initialization, request parsing, and data assessment capabilities.

    From: /tf/active/vicechatdev/full_smartstat/test_enhanced_workflow.py
← Back to Browse