inventory/inventory-server/scripts/metrics/brand-metrics.js

const { outputProgress } = require('../utils/progress');
const { getConnection } = require('../utils/db');

async function calculateBrandMetrics(startTime, totalProducts, processedCount) {
    const connection = await getConnection();
    try {
        outputProgress({
            status: 'running',
            operation: 'Calculating brand metrics',
            current: Math.floor(totalProducts * 0.95),
            total: totalProducts,
            elapsed: formatElapsedTime(startTime),
            remaining: estimateRemaining(startTime, Math.floor(totalProducts * 0.95), totalProducts),
            rate: calculateRate(startTime, Math.floor(totalProducts * 0.95)),
            percentage: '95'
        });

        // Calculate brand metrics
        await connection.query(`
            INSERT INTO brand_metrics (
                brand,
                product_count,
                active_products,
                total_stock_units,
                total_stock_cost,
                total_stock_retail,
                total_revenue,
                avg_margin,
                growth_rate
            )
            WITH brand_data AS (
                SELECT 
                    p.brand,
                    COUNT(DISTINCT p.product_id) as product_count,
                    COUNT(DISTINCT CASE WHEN p.visible = true THEN p.product_id END) as active_products,
                    SUM(p.stock_quantity) as total_stock_units,
                    SUM(p.stock_quantity * p.cost_price) as total_stock_cost,
                    SUM(p.stock_quantity * p.price) as total_stock_retail,
                    SUM(o.price * o.quantity) as total_revenue,
                    CASE 
                        WHEN SUM(o.price * o.quantity) > 0 THEN 
                            (SUM((o.price - p.cost_price) * o.quantity) * 100.0) / SUM(o.price * o.quantity)
                        ELSE 0 
                    END as avg_margin,
                    -- Current period (last 3 months)
                    SUM(CASE 
                        WHEN o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 3 MONTH) 
                        THEN COALESCE(o.quantity * o.price, 0) 
                        ELSE 0 
                    END) as current_period_sales,
                    -- Previous year same period
                    SUM(CASE 
                        WHEN o.date BETWEEN DATE_SUB(CURRENT_DATE, INTERVAL 15 MONTH) AND DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
                        THEN COALESCE(o.quantity * o.price, 0) 
                        ELSE 0 
                    END) as previous_year_period_sales
                FROM products p
                LEFT JOIN orders o ON p.product_id = o.product_id AND o.canceled = false
                WHERE p.brand IS NOT NULL
                GROUP BY p.brand
            )
            SELECT 
                brand,
                product_count,
                active_products,
                total_stock_units,
                total_stock_cost,
                total_stock_retail,
                total_revenue,
                avg_margin,
                CASE
                    WHEN previous_year_period_sales = 0 AND current_period_sales > 0 THEN 100.0
                    WHEN previous_year_period_sales = 0 THEN 0.0
                    ELSE LEAST(
                        GREATEST(
                            ((current_period_sales - previous_year_period_sales) / 
                            NULLIF(previous_year_period_sales, 0)) * 100.0,
                            -100.0
                        ),
                        999.99
                    )
                END as growth_rate
            FROM brand_data
            ON DUPLICATE KEY UPDATE
                product_count = VALUES(product_count),
                active_products = VALUES(active_products),
                total_stock_units = VALUES(total_stock_units),
                total_stock_cost = VALUES(total_stock_cost),
                total_stock_retail = VALUES(total_stock_retail),
                total_revenue = VALUES(total_revenue),
                avg_margin = VALUES(avg_margin),
                growth_rate = VALUES(growth_rate),
                last_calculated_at = CURRENT_TIMESTAMP
        `);

        // Calculate brand time-based metrics
        await connection.query(`
            INSERT INTO brand_time_metrics (
                brand,
                year,
                month,
                product_count,
                active_products,
                total_stock_units,
                total_stock_cost,
                total_stock_retail,
                total_revenue,
                avg_margin
            )
            SELECT 
                p.brand,
                YEAR(o.date) as year,
                MONTH(o.date) as month,
                COUNT(DISTINCT p.product_id) as product_count,
                COUNT(DISTINCT CASE WHEN p.visible = true THEN p.product_id END) as active_products,
                SUM(p.stock_quantity) as total_stock_units,
                SUM(p.stock_quantity * p.cost_price) as total_stock_cost,
                SUM(p.stock_quantity * p.price) as total_stock_retail,
                SUM(o.price * o.quantity) as total_revenue,
                CASE 
                    WHEN SUM(o.price * o.quantity) > 0 THEN 
                        (SUM((o.price - p.cost_price) * o.quantity) * 100.0) / SUM(o.price * o.quantity)
                    ELSE 0 
                END as avg_margin
            FROM products p
            LEFT JOIN orders o ON p.product_id = o.product_id AND o.canceled = false
            WHERE p.brand IS NOT NULL
                AND o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
            GROUP BY p.brand, YEAR(o.date), MONTH(o.date)
            ON DUPLICATE KEY UPDATE
                product_count = VALUES(product_count),
                active_products = VALUES(active_products),
                total_stock_units = VALUES(total_stock_units),
                total_stock_cost = VALUES(total_stock_cost),
                total_stock_retail = VALUES(total_stock_retail),
                total_revenue = VALUES(total_revenue),
                avg_margin = VALUES(avg_margin)
        `);

        return Math.floor(totalProducts * 0.98);
    } finally {
        connection.release();
    }
}

module.exports = calculateBrandMetrics;