359 lines
16 KiB
JavaScript
359 lines
16 KiB
JavaScript
const { outputProgress, formatElapsedTime, estimateRemaining, calculateRate, logError } = require('./utils/progress');
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const { getConnection } = require('./utils/db');
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// Helper function to handle NaN and undefined values
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function sanitizeValue(value) {
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if (value === undefined || value === null || Number.isNaN(value)) {
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return null;
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}
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return value;
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}
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async function calculateProductMetrics(startTime, totalProducts, processedCount = 0, isCancelled = false) {
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const connection = await getConnection();
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try {
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// Skip flags are inherited from the parent scope
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const SKIP_PRODUCT_BASE_METRICS = 0;
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const SKIP_PRODUCT_TIME_AGGREGATES = 0;
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if (isCancelled) {
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outputProgress({
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status: 'cancelled',
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operation: 'Product metrics calculation cancelled',
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current: processedCount,
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total: totalProducts,
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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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percentage: ((processedCount / totalProducts) * 100).toFixed(1),
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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return processedCount;
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}
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// Calculate base product metrics
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if (!SKIP_PRODUCT_BASE_METRICS) {
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outputProgress({
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status: 'running',
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operation: 'Starting base product metrics calculation',
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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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percentage: ((processedCount / totalProducts) * 100).toFixed(1),
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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// Calculate base metrics
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await connection.query(`
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UPDATE product_metrics pm
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JOIN (
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SELECT
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p.pid,
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p.cost_price * p.stock_quantity as inventory_value,
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SUM(o.quantity) as total_quantity,
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COUNT(DISTINCT o.order_number) as number_of_orders,
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SUM(o.quantity * o.price) as total_revenue,
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SUM(o.quantity * p.cost_price) as cost_of_goods_sold,
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AVG(o.price) as avg_price,
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STDDEV(o.price) as price_std,
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MIN(o.date) as first_sale_date,
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MAX(o.date) as last_sale_date,
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COUNT(DISTINCT DATE(o.date)) as active_days
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FROM products p
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LEFT JOIN orders o ON p.pid = o.pid AND o.canceled = false
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GROUP BY p.pid
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) stats ON pm.pid = stats.pid
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SET
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pm.inventory_value = COALESCE(stats.inventory_value, 0),
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pm.avg_quantity_per_order = COALESCE(stats.total_quantity / NULLIF(stats.number_of_orders, 0), 0),
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pm.number_of_orders = COALESCE(stats.number_of_orders, 0),
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pm.total_revenue = COALESCE(stats.total_revenue, 0),
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pm.cost_of_goods_sold = COALESCE(stats.cost_of_goods_sold, 0),
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pm.gross_profit = COALESCE(stats.total_revenue - stats.cost_of_goods_sold, 0),
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pm.avg_margin_percent = CASE
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WHEN COALESCE(stats.total_revenue, 0) > 0
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THEN ((stats.total_revenue - stats.cost_of_goods_sold) / stats.total_revenue) * 100
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ELSE 0
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END,
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pm.first_sale_date = stats.first_sale_date,
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pm.last_sale_date = stats.last_sale_date,
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pm.days_of_inventory = CASE
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WHEN COALESCE(stats.total_quantity / NULLIF(stats.active_days, 0), 0) > 0
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THEN FLOOR(p.stock_quantity / (stats.total_quantity / stats.active_days))
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ELSE NULL
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END,
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pm.weeks_of_inventory = CASE
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WHEN COALESCE(stats.total_quantity / NULLIF(stats.active_days, 0), 0) > 0
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THEN FLOOR(p.stock_quantity / (stats.total_quantity / stats.active_days) / 7)
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ELSE NULL
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END,
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pm.gmroi = CASE
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WHEN COALESCE(stats.inventory_value, 0) > 0
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THEN (stats.total_revenue - stats.cost_of_goods_sold) / stats.inventory_value
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ELSE 0
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END,
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pm.last_calculated_at = NOW()
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`);
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// Calculate forecast accuracy and bias
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await connection.query(`
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WITH forecast_accuracy AS (
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SELECT
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sf.pid,
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AVG(CASE
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WHEN o.quantity > 0
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THEN ABS(sf.forecast_units - o.quantity) / o.quantity * 100
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ELSE 100
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END) as avg_forecast_error,
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AVG(CASE
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WHEN o.quantity > 0
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THEN (sf.forecast_units - o.quantity) / o.quantity * 100
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ELSE 0
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END) as avg_forecast_bias,
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MAX(sf.forecast_date) as last_forecast_date
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FROM sales_forecasts sf
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JOIN orders o ON sf.pid = o.pid
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AND DATE(o.date) = sf.forecast_date
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WHERE o.canceled = false
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AND sf.forecast_date >= DATE_SUB(CURRENT_DATE, INTERVAL 90 DAY)
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GROUP BY sf.pid
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)
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UPDATE product_metrics pm
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JOIN forecast_accuracy fa ON pm.pid = fa.pid
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SET
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pm.forecast_accuracy = GREATEST(0, 100 - LEAST(fa.avg_forecast_error, 100)),
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pm.forecast_bias = GREATEST(-100, LEAST(fa.avg_forecast_bias, 100)),
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pm.last_forecast_date = fa.last_forecast_date,
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pm.last_calculated_at = NOW()
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`);
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processedCount = Math.floor(totalProducts * 0.4);
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outputProgress({
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status: 'running',
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operation: 'Base product metrics calculated',
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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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percentage: ((processedCount / totalProducts) * 100).toFixed(1),
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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} else {
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processedCount = Math.floor(totalProducts * 0.4);
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outputProgress({
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status: 'running',
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operation: 'Skipping base product metrics calculation',
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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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percentage: ((processedCount / totalProducts) * 100).toFixed(1),
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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}
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if (isCancelled) return processedCount;
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// Calculate product time aggregates
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if (!SKIP_PRODUCT_TIME_AGGREGATES) {
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outputProgress({
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status: 'running',
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operation: 'Starting product time aggregates calculation',
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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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percentage: ((processedCount / totalProducts) * 100).toFixed(1),
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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// Calculate time-based aggregates
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await connection.query(`
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INSERT INTO product_time_aggregates (
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pid,
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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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avg_price,
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profit_margin,
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inventory_value,
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gmroi
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)
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SELECT
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p.pid,
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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.quantity * o.price) as total_revenue,
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SUM(o.quantity * p.cost_price) as total_cost,
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COUNT(DISTINCT o.order_number) as order_count,
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AVG(o.price) as avg_price,
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CASE
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WHEN SUM(o.quantity * o.price) > 0
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THEN ((SUM(o.quantity * o.price) - SUM(o.quantity * p.cost_price)) / SUM(o.quantity * o.price)) * 100
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ELSE 0
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END as profit_margin,
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p.cost_price * p.stock_quantity as inventory_value,
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CASE
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WHEN p.cost_price * p.stock_quantity > 0
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THEN (SUM(o.quantity * (o.price - p.cost_price))) / (p.cost_price * p.stock_quantity)
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ELSE 0
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END as gmroi
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FROM products p
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LEFT JOIN orders o ON p.pid = o.pid AND o.canceled = false
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WHERE o.date >= DATE_SUB(CURRENT_DATE, INTERVAL 12 MONTH)
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GROUP BY p.pid, YEAR(o.date), MONTH(o.date)
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ON DUPLICATE KEY UPDATE
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total_quantity_sold = VALUES(total_quantity_sold),
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total_revenue = VALUES(total_revenue),
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total_cost = VALUES(total_cost),
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order_count = VALUES(order_count),
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avg_price = VALUES(avg_price),
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profit_margin = VALUES(profit_margin),
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inventory_value = VALUES(inventory_value),
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gmroi = VALUES(gmroi),
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last_calculated_at = CURRENT_TIMESTAMP
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`);
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processedCount = Math.floor(totalProducts * 0.6);
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outputProgress({
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status: 'running',
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operation: 'Product time aggregates calculated',
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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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percentage: ((processedCount / totalProducts) * 100).toFixed(1),
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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} else {
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processedCount = Math.floor(totalProducts * 0.6);
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outputProgress({
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status: 'running',
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operation: 'Skipping product time aggregates calculation',
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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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percentage: ((processedCount / totalProducts) * 100).toFixed(1),
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timing: {
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start_time: new Date(startTime).toISOString(),
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end_time: new Date().toISOString(),
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elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
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}
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});
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}
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return processedCount;
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} catch (error) {
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logError(error, 'Error calculating product metrics');
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throw error;
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} finally {
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if (connection) {
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connection.release();
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}
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}
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}
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function calculateStockStatus(stock, config, daily_sales_avg, weekly_sales_avg, monthly_sales_avg) {
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if (stock <= 0) {
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return 'Out of Stock';
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}
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// Use the most appropriate sales average based on data quality
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let sales_avg = daily_sales_avg;
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if (sales_avg === 0) {
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sales_avg = weekly_sales_avg / 7;
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}
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if (sales_avg === 0) {
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sales_avg = monthly_sales_avg / 30;
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}
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if (sales_avg === 0) {
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return stock <= config.low_stock_threshold ? 'Low Stock' : 'In Stock';
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}
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const days_of_stock = stock / sales_avg;
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if (days_of_stock <= config.critical_days) {
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return 'Critical';
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} else if (days_of_stock <= config.reorder_days) {
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return 'Reorder';
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} else if (days_of_stock > config.overstock_days) {
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return 'Overstocked';
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}
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return 'Healthy';
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}
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function calculateReorderQuantities(stock, stock_status, daily_sales_avg, avg_lead_time, config) {
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// Calculate safety stock based on service level and lead time
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const z_score = 1.96; // 95% service level
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const lead_time = avg_lead_time || config.target_days;
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const safety_stock = Math.ceil(daily_sales_avg * Math.sqrt(lead_time) * z_score);
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// Calculate reorder point
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const lead_time_demand = daily_sales_avg * lead_time;
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const reorder_point = Math.ceil(lead_time_demand + safety_stock);
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// Calculate reorder quantity using EOQ formula if we have the necessary data
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let reorder_qty = 0;
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if (daily_sales_avg > 0) {
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const annual_demand = daily_sales_avg * 365;
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const order_cost = 25; // Fixed cost per order
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const holding_cost_percent = 0.25; // 25% annual holding cost
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reorder_qty = Math.ceil(Math.sqrt((2 * annual_demand * order_cost) / holding_cost_percent));
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} else {
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// If no sales data, use a basic calculation
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reorder_qty = Math.max(safety_stock, config.low_stock_threshold);
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}
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// Calculate overstocked amount
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const overstocked_amt = stock_status === 'Overstocked' ?
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stock - Math.ceil(daily_sales_avg * config.overstock_days) :
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0;
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return {
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safety_stock,
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reorder_point,
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reorder_qty,
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overstocked_amt
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};
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}
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module.exports = calculateProductMetrics;
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