479 lines
19 KiB
JavaScript
479 lines
19 KiB
JavaScript
const mysql = require('mysql2/promise');
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const path = require('path');
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require('dotenv').config({ path: path.resolve(__dirname, '..', '.env') });
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// Helper function to format elapsed time
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function formatElapsedTime(startTime) {
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const elapsed = Date.now() - startTime;
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const seconds = Math.floor(elapsed / 1000);
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const minutes = Math.floor(seconds / 60);
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const hours = Math.floor(minutes / 60);
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if (hours > 0) {
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return `${hours}h ${minutes % 60}m`;
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} else if (minutes > 0) {
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return `${minutes}m ${seconds % 60}s`;
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} else {
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return `${seconds}s`;
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}
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}
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// Helper function to estimate remaining time
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function estimateRemaining(startTime, current, total) {
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if (current === 0) return null;
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const elapsed = Date.now() - startTime;
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const rate = current / elapsed;
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const remaining = (total - current) / rate;
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const minutes = Math.floor(remaining / 60000);
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const seconds = Math.floor((remaining % 60000) / 1000);
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if (minutes > 0) {
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return `${minutes}m ${seconds}s`;
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} else {
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return `${seconds}s`;
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}
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}
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// Helper function to calculate rate
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function calculateRate(startTime, current) {
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const elapsed = (Date.now() - startTime) / 1000; // Convert to seconds
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return elapsed > 0 ? Math.round(current / elapsed) : 0;
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}
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// Helper function to output progress
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function outputProgress(data) {
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process.stdout.write(JSON.stringify(data) + '\n');
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}
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// Helper function to log errors
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function logError(error, context) {
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console.error(JSON.stringify({
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status: 'error',
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error: error.message || error,
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context
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}));
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}
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// Database configuration
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const dbConfig = {
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host: process.env.DB_HOST,
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user: process.env.DB_USER,
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password: process.env.DB_PASSWORD,
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database: process.env.DB_NAME,
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waitForConnections: true,
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connectionLimit: 10,
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queueLimit: 0
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};
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// Add cancel handler
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let isCancelled = false;
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function cancelCalculation() {
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isCancelled = true;
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process.stdout.write(JSON.stringify({
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status: 'cancelled',
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operation: 'Calculation cancelled',
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current: 0,
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total: 0,
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elapsed: null,
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remaining: null,
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rate: 0
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}) + '\n');
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process.exit(0);
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}
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async function calculateMetrics() {
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let pool;
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const startTime = Date.now();
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let processedCount = 0;
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let totalProducts = 0; // Initialize at the top
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try {
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isCancelled = false;
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pool = mysql.createPool(dbConfig);
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const connection = await pool.getConnection();
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try {
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// Get total number of products
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const [countResult] = await connection.query('SELECT COUNT(*) as total FROM products');
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totalProducts = countResult[0].total;
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// Initial progress
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outputProgress({
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status: 'running',
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operation: 'Processing products',
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current: processedCount,
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total: totalProducts,
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elapsed: '0s',
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remaining: 'Calculating...',
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rate: 0
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});
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// Process in batches of 100
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const batchSize = 100;
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for (let offset = 0; offset < totalProducts; offset += batchSize) {
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if (isCancelled) {
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throw new Error('Operation cancelled');
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}
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const [products] = await connection.query('SELECT product_id FROM products LIMIT ? OFFSET ?', [batchSize, offset]);
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processedCount += products.length;
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// Update progress after each batch
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outputProgress({
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status: 'running',
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operation: 'Processing products',
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current: processedCount,
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total: totalProducts,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, processedCount, totalProducts),
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rate: calculateRate(startTime, processedCount)
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});
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// Process the batch
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for (const product of products) {
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// Calculate sales metrics
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const [salesMetrics] = await connection.query(`
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SELECT
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SUM(o.quantity) as total_quantity_sold,
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SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) as total_revenue,
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SUM(COALESCE(p.cost_price, 0) * o.quantity) as total_cost,
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MAX(o.date) as last_sale_date
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FROM orders o
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JOIN products p ON o.product_id = p.product_id
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WHERE o.canceled = 0 AND o.product_id = ?
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GROUP BY o.product_id
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`, [product.product_id]);
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// Calculate purchase metrics
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const [purchaseMetrics] = await connection.query(`
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SELECT
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SUM(received) as total_quantity_purchased,
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SUM(cost_price * received) as total_cost,
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MAX(date) as last_purchase_date,
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MAX(received_date) as last_received_date,
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AVG(DATEDIFF(received_date, date)) as avg_lead_time_days
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FROM purchase_orders
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WHERE status = 'closed' AND received > 0 AND product_id = ?
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GROUP BY product_id
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`, [product.product_id]);
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// Get current stock
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const [stockInfo] = await connection.query(`
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SELECT stock_quantity, cost_price
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FROM products
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WHERE product_id = ?
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`, [product.product_id]);
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// Calculate metrics
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const metrics = salesMetrics[0] || {};
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const purchases = purchaseMetrics[0] || {};
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const stock = stockInfo[0] || {};
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const daily_sales_avg = metrics.total_quantity_sold ? metrics.total_quantity_sold / 30 : 0;
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const weekly_sales_avg = metrics.total_quantity_sold ? metrics.total_quantity_sold / 4 : 0;
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const monthly_sales_avg = metrics.total_quantity_sold || 0;
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// Update product metrics
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await connection.query(`
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INSERT INTO product_metrics (
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product_id,
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last_calculated_at,
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daily_sales_avg,
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weekly_sales_avg,
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monthly_sales_avg,
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days_of_inventory,
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weeks_of_inventory,
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reorder_point,
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safety_stock,
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avg_margin_percent,
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total_revenue,
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avg_lead_time_days,
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last_purchase_date,
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last_received_date,
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abc_class,
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stock_status
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) VALUES (
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?,
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NOW(),
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?,
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?,
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?,
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?,
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?,
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?,
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?,
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?,
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?,
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?,
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?,
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?,
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NULL,
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?
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)
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ON DUPLICATE KEY UPDATE
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last_calculated_at = VALUES(last_calculated_at),
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daily_sales_avg = VALUES(daily_sales_avg),
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weekly_sales_avg = VALUES(weekly_sales_avg),
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monthly_sales_avg = VALUES(monthly_sales_avg),
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days_of_inventory = VALUES(days_of_inventory),
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weeks_of_inventory = VALUES(weeks_of_inventory),
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reorder_point = VALUES(reorder_point),
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safety_stock = VALUES(safety_stock),
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avg_margin_percent = VALUES(avg_margin_percent),
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total_revenue = VALUES(total_revenue),
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avg_lead_time_days = VALUES(avg_lead_time_days),
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last_purchase_date = VALUES(last_purchase_date),
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last_received_date = VALUES(last_received_date),
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stock_status = VALUES(stock_status)
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`, [
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product.product_id,
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daily_sales_avg,
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weekly_sales_avg,
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monthly_sales_avg,
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daily_sales_avg ? stock.stock_quantity / daily_sales_avg : null,
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weekly_sales_avg ? stock.stock_quantity / weekly_sales_avg : null,
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Math.ceil(daily_sales_avg * 14), // 14 days reorder point
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Math.ceil(daily_sales_avg * 7), // 7 days safety stock
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metrics.total_revenue ? ((metrics.total_revenue - metrics.total_cost) / metrics.total_revenue) * 100 : 0,
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metrics.total_revenue || 0,
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purchases.avg_lead_time_days || 0,
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purchases.last_purchase_date,
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purchases.last_received_date,
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daily_sales_avg === 0 ? 'New' :
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stock.stock_quantity <= Math.ceil(daily_sales_avg * 7) ? 'Critical' :
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stock.stock_quantity <= Math.ceil(daily_sales_avg * 14) ? 'Reorder' :
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stock.stock_quantity > (daily_sales_avg * 90) ? 'Overstocked' : 'Healthy'
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]);
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}
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}
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// Update progress for ABC classification
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outputProgress({
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status: 'running',
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operation: 'Calculating ABC classification',
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current: totalProducts,
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total: totalProducts,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, totalProducts, totalProducts),
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rate: calculateRate(startTime, totalProducts)
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});
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// Calculate ABC classification
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await connection.query(`
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WITH revenue_percentiles AS (
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SELECT
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product_id,
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total_revenue,
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PERCENT_RANK() OVER (ORDER BY total_revenue DESC) as revenue_percentile
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FROM product_metrics
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WHERE total_revenue > 0
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)
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UPDATE product_metrics pm
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JOIN revenue_percentiles rp ON pm.product_id = rp.product_id
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SET pm.abc_class =
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CASE
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WHEN rp.revenue_percentile < 0.2 THEN 'A'
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WHEN rp.revenue_percentile < 0.5 THEN 'B'
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ELSE 'C'
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END;
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`);
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// Update progress for time-based aggregates
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outputProgress({
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status: 'running',
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operation: 'Calculating time-based aggregates',
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current: totalProducts,
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total: totalProducts,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, totalProducts, totalProducts),
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rate: calculateRate(startTime, totalProducts)
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});
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// Calculate time-based aggregates
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await connection.query('TRUNCATE TABLE product_time_aggregates;');
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await connection.query(`
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INSERT INTO product_time_aggregates (
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product_id,
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year,
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month,
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total_quantity_sold,
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total_revenue,
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total_cost,
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order_count,
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stock_received,
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stock_ordered,
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avg_price,
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profit_margin
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)
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WITH sales_data AS (
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SELECT
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o.product_id,
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YEAR(o.date) as year,
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MONTH(o.date) as month,
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SUM(o.quantity) as total_quantity_sold,
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SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) as total_revenue,
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SUM(COALESCE(p.cost_price, 0) * o.quantity) as total_cost,
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COUNT(DISTINCT o.order_number) as order_count,
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AVG(o.price - COALESCE(o.discount, 0)) as avg_price,
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CASE
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WHEN SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) = 0 THEN 0
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ELSE ((SUM((o.price - COALESCE(o.discount, 0)) * o.quantity) -
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SUM(COALESCE(p.cost_price, 0) * o.quantity)) /
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SUM((o.price - COALESCE(o.discount, 0)) * o.quantity)) * 100
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END as profit_margin
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FROM orders o
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JOIN products p ON o.product_id = p.product_id
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WHERE o.canceled = 0
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GROUP BY o.product_id, YEAR(o.date), MONTH(o.date)
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),
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purchase_data AS (
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SELECT
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product_id,
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YEAR(date) as year,
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MONTH(date) as month,
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SUM(received) as stock_received,
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SUM(ordered) as stock_ordered
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FROM purchase_orders
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WHERE status = 'closed'
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GROUP BY product_id, YEAR(date), MONTH(date)
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)
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SELECT
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s.product_id,
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s.year,
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s.month,
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s.total_quantity_sold,
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s.total_revenue,
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s.total_cost,
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s.order_count,
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COALESCE(p.stock_received, 0) as stock_received,
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COALESCE(p.stock_ordered, 0) as stock_ordered,
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s.avg_price,
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s.profit_margin
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FROM sales_data s
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LEFT JOIN purchase_data p
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ON s.product_id = p.product_id
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AND s.year = p.year
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AND s.month = p.month
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UNION
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SELECT
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p.product_id,
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p.year,
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p.month,
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0 as total_quantity_sold,
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0 as total_revenue,
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0 as total_cost,
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0 as order_count,
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p.stock_received,
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p.stock_ordered,
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0 as avg_price,
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0 as profit_margin
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FROM purchase_data p
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LEFT JOIN sales_data s
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ON p.product_id = s.product_id
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AND p.year = s.year
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AND p.month = s.month
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WHERE s.product_id IS NULL
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`);
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// Update progress for vendor metrics
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outputProgress({
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status: 'running',
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operation: 'Calculating vendor metrics',
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current: totalProducts,
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total: totalProducts,
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elapsed: formatElapsedTime(startTime),
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remaining: estimateRemaining(startTime, totalProducts, totalProducts),
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rate: calculateRate(startTime, totalProducts)
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});
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// Calculate vendor metrics
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await connection.query(`
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INSERT INTO vendor_metrics (
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vendor,
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last_calculated_at,
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avg_lead_time_days,
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on_time_delivery_rate,
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order_fill_rate,
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total_orders,
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total_late_orders
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)
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SELECT
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vendor,
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NOW() as last_calculated_at,
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COALESCE(AVG(DATEDIFF(received_date, date)), 0) as avg_lead_time_days,
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COALESCE((COUNT(CASE WHEN DATEDIFF(received_date, date) <= 14 THEN 1 END) * 100.0 / NULLIF(COUNT(*), 0)), 0) as on_time_delivery_rate,
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COALESCE((SUM(received) * 100.0 / NULLIF(SUM(ordered), 0)), 0) as order_fill_rate,
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COUNT(DISTINCT po_id) as total_orders,
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COUNT(CASE WHEN DATEDIFF(received_date, date) > 14 THEN 1 END) as total_late_orders
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FROM purchase_orders
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WHERE status = 'closed'
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GROUP BY vendor
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ON DUPLICATE KEY UPDATE
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last_calculated_at = VALUES(last_calculated_at),
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avg_lead_time_days = VALUES(avg_lead_time_days),
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on_time_delivery_rate = VALUES(on_time_delivery_rate),
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order_fill_rate = VALUES(order_fill_rate),
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total_orders = VALUES(total_orders),
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total_late_orders = VALUES(total_late_orders)
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`);
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// Final success message
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outputProgress({
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status: 'complete',
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operation: 'Metrics calculation complete',
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current: totalProducts,
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total: totalProducts,
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elapsed: formatElapsedTime(startTime),
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remaining: '0s',
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rate: calculateRate(startTime, totalProducts)
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});
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} catch (error) {
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if (isCancelled) {
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outputProgress({
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status: 'cancelled',
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operation: 'Calculation cancelled',
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current: processedCount,
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total: totalProducts || 0, // Use 0 if not yet defined
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elapsed: formatElapsedTime(startTime),
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remaining: null,
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rate: calculateRate(startTime, processedCount)
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});
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} else {
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outputProgress({
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status: 'error',
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operation: 'Error: ' + error.message,
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current: processedCount,
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total: totalProducts || 0, // Use 0 if not yet defined
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elapsed: formatElapsedTime(startTime),
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remaining: null,
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rate: calculateRate(startTime, processedCount)
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});
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}
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throw error;
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} finally {
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connection.release();
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}
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} finally {
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if (pool) {
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await pool.end();
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}
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}
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}
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// Export both functions
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module.exports = calculateMetrics;
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module.exports.cancelCalculation = cancelCalculation;
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// Run directly if called from command line
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if (require.main === module) {
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calculateMetrics().catch(error => {
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if (!error.message.includes('Operation cancelled')) {
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console.error('Error:', error);
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}
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process.exit(1);
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});
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}
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