src/main.py - main - angels/learning-path-analyzer

src/main.py
73 строки2 KB
angelinagal1
update3
28 дек 2025, 19:20
28 дек 2025, 19:2050ad947
#!/usr/bin/env python3
"""
Learning Path Analyzer - Main entry point
Command line interface for analyzing LMS logs
"""
import argparse
import sys
import os
import sys

# Добавьте src в путь Python
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

try:
    from analyzer import LearningPathAnalyzer
except ImportError:
    print("Error: Could not import analyzer module")
    sys.exit(1)

def main():
    parser = argparse.ArgumentParser(description='Analyze student learning paths from LMS logs')
    parser.add_argument('--data', type=str, default='data/raw/sample_logs.csv',
                       help='Path to CSV file with LMS logs')
    parser.add_argument('--output', type=str, default='results',
                       help='Output directory for results')
    parser.add_argument('--visualize', action='store_true',
                       help='Generate visualizations')
    
    args = parser.parse_args()
    
    print("=" * 50)
    print("Learning Path Analyzer")
    print("=" * 50)
    
    # Create output directory
    os.makedirs(args.output, exist_ok=True)
    
    # Initialize analyzer
    analyzer = LearningPathAnalyzer()
    
    # Load data
    data = analyzer.load_data(args.data)
    if data.empty:
        print("Error: Could not load data. Exiting.")
        sys.exit(1)
    
    # Perform analysis
    print("\n🔍 Analyzing learning activities...")
    stats = analyzer.analyze_activities()
    print(f"   Total students: {stats.get('total_students', 0)}")
    print(f"   Total activities: {stats.get('total_activities', 0)}")
    
    print("\n📊 Calculating correlations...")
    correlations = analyzer.calculate_correlations()
    for key, value in correlations.items():
        print(f"   {key}: {value:.3f}")
    
    # Generate recommendations
    print("\n💡 Generating recommendations...")
    recommendations = analyzer.generate_recommendations()
    for i, rec in enumerate(recommendations, 1):
        print(f"   {i}. {rec}")
    
    # Visualize if requested
    if args.visualize:
        print("\n🎨 Creating visualizations...")
        analyzer.visualize(save_path=f"{args.output}/visualization.png")
    
    print("\n✅ Analysis complete!")
    print("=" * 50)

if __name__ == "__main__":
    main()