utils/test_data_layer.py

"""
Test script to validate data layer integration with actual JSON report.
"""

from results_loader import (
    find_latest_full_report,
    load_full_results,
    summarize_users,
    get_layer_details,
    get_report_metadata
)
from alert_config import (
    load_alert_config,
    evaluate_alerts,
    format_alert_summary
)


def test_full_integration():
    """Test complete data layer with actual report."""
    
    print("="*70)
    print("DATA LAYER INTEGRATION TEST")
    print("="*70)
    
    # Step 1: Find and load report
    print("\n1. Loading Report...")
    report_path = find_latest_full_report()
    if not report_path:
        print("❌ No report found")
        return False
    
    print(f"   ✅ Found: {report_path.name}")
    
    results = load_full_results(report_path)
    print(f"   ✅ Loaded {len(results)} sections")
    
    # Step 2: Get metadata
    print("\n2. Report Metadata...")
    metadata = get_report_metadata(report_path, results)
    print(f"   • File size: {metadata['file_size_mb']:.1f} MB")
    print(f"   • Users: {metadata['user_count']}")
    print(f"   • Modified: {metadata['modified_time']}")
    
    # Step 3: Summarize users
    print("\n3. User Summaries...")
    summaries = summarize_users(results)
    print(f"   ✅ Processed {len(summaries)} users")
    
    # Show quality distribution
    quality_bands = {'Excellent (>0.9)': 0, 'Good (0.8-0.9)': 0, 
                    'Fair (0.7-0.8)': 0, 'Poor (<0.7)': 0}
    
    for summary in summaries:
        score = summary['overall_mean_score']
        if score:
            if score > 0.9:
                quality_bands['Excellent (>0.9)'] += 1
            elif score > 0.8:
                quality_bands['Good (0.8-0.9)'] += 1
            elif score > 0.7:
                quality_bands['Fair (0.7-0.8)'] += 1
            else:
                quality_bands['Poor (<0.7)'] += 1
    
    print("\n   Quality Distribution:")
    for band, count in quality_bands.items():
        print(f"   • {band}: {count} users")
    
    # Step 4: Load alert config
    print("\n4. Alert Configuration...")
    config = load_alert_config()
    print(f"   ✅ Loaded thresholds for {len(config)} sections")
    
    # Step 5: Evaluate alerts for all users
    print("\n5. Alert Evaluation...")
    all_alerts = []
    
    # Get layer details once
    layer1_details = get_layer_details(results, 1)
    layer2_details = get_layer_details(results, 2)
    layer3_details = get_layer_details(results, 3)
    
    combined_details = {
        'layer1': layer1_details,
        'layer2': layer2_details,
        'layer3': layer3_details
    }
    
    for summary in summaries:
        user_alerts = evaluate_alerts(summary, combined_details, config)
        all_alerts.extend(user_alerts)
    
    print(f"   ✅ Evaluated {len(summaries)} users")
    print(f"   ⚠️ Found {len(all_alerts)} total alerts")
    
    # Show alert breakdown
    if all_alerts:
        severity_counts = {'HIGH': 0, 'MEDIUM': 0, 'LOW': 0}
        layer_counts = {'Global': 0, 'Layer 1': 0, 'Layer 2': 0, 'Layer 3': 0}
        
        for alert in all_alerts:
            severity_counts[alert['severity']] += 1
            layer_counts[alert['layer']] += 1
        
        print("\n   Alert Severity:")
        for severity, count in severity_counts.items():
            if count > 0:
                print(f"   • {severity}: {count} alerts")
        
        print("\n   Alerts by Layer:")
        for layer, count in layer_counts.items():
            if count > 0:
                print(f"   • {layer}: {count} alerts")
    
    # Step 6: Sample alert output
    if all_alerts:
        print("\n6. Sample Alerts (first 3)...")
        for alert in all_alerts[:3]:
            print(f"   • [{alert['severity']}] {alert['user_id']}: {alert['message']}")
    
    print("\n" + "="*70)
    print("✅ DATA LAYER TEST COMPLETE - ALL SYSTEMS OPERATIONAL")
    print("="*70)
    
    return True


if __name__ == "__main__":
    success = test_full_integration()
    exit(0 if success else 1)