"""
Пример оптимизации с сырым SQL для самых медленных запросов.
Использовать только если ORM оптимизация недостаточна.
"""
from django.db import connection
from django.db.models import Count, Sum, Avg, Q
from decimal import Decimal


def get_detailed_lesson_stats_raw_sql(mentor, start_date, end_date):
    """
    Оптимизированная версия с сырым SQL.
    Использовать только если get_detailed_lesson_stats все еще медленный.
    
    Выигрыш: ~30-50% быстрее за счет одного сложного запроса вместо множественных.
    """
    with connection.cursor() as cursor:
        # Один большой запрос вместо множественных
        cursor.execute("""
            WITH lesson_stats AS (
                SELECT 
                    COUNT(*) as total,
                    COUNT(*) FILTER (WHERE status = 'completed') as completed,
                    COUNT(*) FILTER (WHERE status = 'cancelled') as cancelled,
                    SUM(duration) FILTER (WHERE status = 'completed') as total_duration,
                    AVG(duration) FILTER (WHERE status = 'completed') as avg_duration,
                    SUM(price) FILTER (WHERE status = 'completed' AND price IS NOT NULL) as total_revenue,
                    AVG(price) FILTER (WHERE status = 'completed' AND price IS NOT NULL) as avg_price,
                    AVG(mentor_grade) FILTER (WHERE status = 'completed' AND mentor_grade IS NOT NULL) as avg_grade,
                    MAX(mentor_grade) FILTER (WHERE status = 'completed' AND mentor_grade IS NOT NULL) as max_grade,
                    MIN(mentor_grade) FILTER (WHERE status = 'completed' AND mentor_grade IS NOT NULL) as min_grade,
                    SUM(price) FILTER (WHERE status = 'cancelled' AND price IS NOT NULL) as cancelled_revenue,
                    COUNT(*) FILTER (WHERE status = 'completed' AND mentor_grade IS NOT NULL) as graded_count
                FROM lessons
                WHERE mentor_id = %s 
                    AND start_time >= %s 
                    AND start_time <= %s
            ),
            by_hour_stats AS (
                SELECT 
                    EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC')::int as hour,
                    COUNT(*) as count
                FROM lessons
                WHERE mentor_id = %s 
                    AND start_time >= %s 
                    AND start_time <= %s
                    AND status = 'completed'
                GROUP BY hour
            ),
            time_of_day_stats AS (
                SELECT 
                    COUNT(*) FILTER (WHERE EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC') >= 6 AND EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC') < 12) as morning,
                    COUNT(*) FILTER (WHERE EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC') >= 12 AND EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC') < 18) as afternoon,
                    COUNT(*) FILTER (WHERE EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC') >= 18 AND EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC') < 24) as evening,
                    COUNT(*) FILTER (WHERE EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC') >= 0 AND EXTRACT(HOUR FROM start_time AT TIME ZONE 'UTC') < 6) as night
                FROM lessons
                WHERE mentor_id = %s 
                    AND start_time >= %s 
                    AND start_time <= %s
                    AND status = 'completed'
            ),
            top_clients_stats AS (
                SELECT 
                    c.id as client_id,
                    u.first_name,
                    u.last_name,
                    u.email,
                    COUNT(l.id) as lessons_count,
                    COUNT(l.id) FILTER (WHERE l.status = 'completed') as completed_count,
                    SUM(l.price) FILTER (WHERE l.status = 'completed' AND l.price IS NOT NULL) as total_revenue,
                    AVG(l.mentor_grade) FILTER (WHERE l.status = 'completed' AND l.mentor_grade IS NOT NULL) as avg_grade
                FROM lessons l
                JOIN clients c ON l.client_id = c.id
                JOIN users u ON c.user_id = u.id
                WHERE l.mentor_id = %s 
                    AND l.start_time >= %s 
                    AND l.start_time <= %s
                GROUP BY c.id, u.first_name, u.last_name, u.email
                ORDER BY lessons_count DESC
                LIMIT 10
            )
            SELECT 
                (SELECT row_to_json(s) FROM lesson_stats s) as stats,
                (SELECT json_agg(row_to_json(b)) FROM by_hour_stats b) as by_hour,
                (SELECT row_to_json(t) FROM time_of_day_stats t) as time_of_day,
                (SELECT json_agg(row_to_json(tc)) FROM top_clients_stats tc) as top_clients
        """, [
            mentor.id, start_date, end_date,  # lesson_stats
            mentor.id, start_date, end_date,  # by_hour_stats
            mentor.id, start_date, end_date,  # time_of_day_stats
            mentor.id, start_date, end_date,  # top_clients_stats
        ])
        
        row = cursor.fetchone()
        stats_data = row[0]
        by_hour_data = row[1] or []
        time_of_day_data = row[2] or {}
        top_clients_data = row[3] or []
        
        # Форматируем результат
        stats = stats_data.get('stats', {})
        by_hour_dict = {item['hour']: item['count'] for item in by_hour_data}
        
        return {
            'summary': {
                'total_lessons': stats.get('total', 0),
                'completed': stats.get('completed', 0),
                'cancelled': stats.get('cancelled', 0),
                'completion_rate': round(
                    (stats.get('completed', 0) / stats.get('total', 1) * 100) if stats.get('total', 0) > 0 else 0, 
                    1
                ),
            },
            'time': {
                'total_duration_minutes': stats.get('total_duration', 0) or 0,
                'total_duration_hours': round((stats.get('total_duration', 0) or 0) / 60, 1),
                'average_duration_minutes': round(stats.get('avg_duration', 0) or 0, 1),
                'by_hour': [
                    {'hour': hour, 'count': by_hour_dict.get(hour, 0)}
                    for hour in range(24)
                ],
                'by_time_of_day': {
                    'morning': time_of_day_data.get('morning', 0) or 0,
                    'afternoon': time_of_day_data.get('afternoon', 0) or 0,
                    'evening': time_of_day_data.get('evening', 0) or 0,
                    'night': time_of_day_data.get('night', 0) or 0,
                },
            },
            'revenue': {
                'total': float(stats.get('total_revenue', 0) or 0),
                'average_per_lesson': float(stats.get('avg_price', 0) or 0),
                'potential_revenue': float(stats.get('cancelled_revenue', 0) or 0),
            },
            'grades': {
                'average': round(stats.get('avg_grade', 0) or 0, 1),
                'max': stats.get('max_grade', 0) or 0,
                'min': stats.get('min_grade', 0) or 0,
                'graded_count': stats.get('graded_count', 0) or 0,
            },
            'top_clients': [
                {
                    'name': f"{item['first_name']} {item['last_name']}".strip() or item['email'],
                    'email': item['email'],
                    'lessons_count': item['lessons_count'],
                    'completed_count': item['completed_count'],
                    'total_revenue': float(item['total_revenue'] or 0),
                    'average_grade': round(item['avg_grade'] or 0, 1),
                }
                for item in top_clients_data
            ],
        }


# ВАЖНО: Использовать только после измерения производительности!
# Сначала убедитесь, что оптимизация ORM недостаточна.