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A test function that validates collection processing logic, specifically testing how collections are handled when selected, deselected, or missing, with focus on data clearing behavior.

Purpose

This function serves as a unit test to verify the correct behavior of collection deactivation logic. It tests three scenarios: when collections are selected, when an empty list is provided, and when collections config is missing. The test demonstrates a bug fix where data_handles.clear_data() should always be called when data_handles exists, regardless of whether collections are present. This ensures that unchecking all collections properly clears data sources.

Source Code

def test_collection_logic():
    """Test the collection processing logic"""
    
    print("🧪 Testing Collection Deactivation Logic")
    print("=" * 50)
    
    # Test scenarios
    test_cases = [
        {
            "name": "Collections selected",
            "collections": ["collection1", "collection2"],
            "expected": "Should clear data and add collections"
        },
        {
            "name": "No collections selected (empty list)",
            "collections": [],
            "expected": "Should clear data and add no collections"
        },
        {
            "name": "Collections config missing",
            "collections": None,
            "expected": "Should clear data and add no collections"
        }
    ]
    
    for i, test_case in enumerate(test_cases, 1):
        print(f"\n📋 Test Case {i}: {test_case['name']}")
        print(f"   Input: {test_case['collections']}")
        print(f"   Expected: {test_case['expected']}")
        
        # Simulate the fixed logic
        collections = test_case['collections'] or []
        print(f"   Collections after processing: {collections}")
        
        # Check if data_handles would be processed
        has_data_handles = True  # Simulate having data_handles
        
        if has_data_handles:
            print("   ✅ Would clear existing data sources")
            
            if collections:
                print(f"   ✅ Would add {len(collections)} collections")
                for collection in collections:
                    print(f"      - {collection}")
            else:
                print("   ✅ Would add no collections (data sources cleared)")
        else:
            print("   ❌ No data_handles available")
    
    print("\n" + "=" * 50)
    print("🎯 Summary of Fix:")
    print("   Before: data_handles.clear_data() only called when collections exist")
    print("   After:  data_handles.clear_data() always called when data_handles exists")
    print("   Result: Unchecking all collections now properly clears data sources")

Return Value

This function does not return any value (implicitly returns None). It outputs test results directly to stdout via print statements, showing test case execution, expected behavior, and a summary of the logic fix being validated.

Usage Example

# Simply call the function to run the test suite
test_collection_logic()

# Expected output:
# 🧪 Testing Collection Deactivation Logic
# ==================================================
# 
# 📋 Test Case 1: Collections selected
#    Input: ['collection1', 'collection2']
#    Expected: Should clear data and add collections
#    Collections after processing: ['collection1', 'collection2']
#    ✅ Would clear existing data sources
#    ✅ Would add 2 collections
#       - collection1
#       - collection2
# ...
# 🎯 Summary of Fix:
#    Before: data_handles.clear_data() only called when collections exist
#    After:  data_handles.clear_data() always called when data_handles exists
#    Result: Unchecking all collections now properly clears data sources

Best Practices

• This is a demonstration/test function that simulates logic rather than executing actual operations
• The function uses print statements for output rather than assertions, making it more of a visual verification tool than an automated test
• The test cases cover edge cases including empty lists and None values, which is good practice for defensive programming
• For production use, consider converting this to proper unit tests using pytest or unittest framework with actual assertions
• The function hardcodes has_data_handles=True; in real implementation this should be dynamically determined
• Consider adding actual integration with the data_handles object to make this a true functional test rather than a simulation

Tags

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