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More gemini suggested improvements for speed

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Matt
2025-02-10 16:16:01 -05:00
parent a9bccd4d01
commit f4f6215d03
3 changed files with 105 additions and 194 deletions
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69
inventory-server/scripts/metrics/product-metrics.js
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@@ -219,6 +219,28 @@ async function calculateProductMetrics(startTime, totalProducts, processedCount
JOIN products p ON pm.pid = p.pid
LEFT JOIN temp_sales_metrics sm ON pm.pid = sm.pid
LEFT JOIN temp_purchase_metrics lm ON pm.pid = lm.pid
LEFT JOIN (
SELECT
sf.pid,
AVG(CASE
WHEN o.quantity > 0
THEN ABS(sf.forecast_units - o.quantity) / o.quantity * 100
ELSE 100
END) as avg_forecast_error,
AVG(CASE
WHEN o.quantity > 0
THEN (sf.forecast_units - o.quantity) / o.quantity * 100
ELSE 0
END) as avg_forecast_bias,
MAX(sf.forecast_date) as last_forecast_date
FROM sales_forecasts sf
JOIN orders o ON sf.pid = o.pid
AND DATE(o.date) = sf.forecast_date
WHERE o.canceled = false
AND sf.forecast_date >= DATE_SUB(CURRENT_DATE, INTERVAL 90 DAY)
AND sf.pid IN (?)
GROUP BY sf.pid
) fa ON pm.pid = fa.pid
SET
pm.inventory_value = p.stock_quantity * p.cost_price,
pm.daily_sales_avg = COALESCE(sm.daily_sales_avg, 0),
@@ -229,51 +251,12 @@ async function calculateProductMetrics(startTime, totalProducts, processedCount
pm.first_sale_date = sm.first_sale_date,
pm.last_sale_date = sm.last_sale_date,
pm.avg_lead_time_days = COALESCE(lm.avg_lead_time_days, 30),
pm.days_of_inventory = CASE
WHEN COALESCE(sm.daily_sales_avg, 0) > 0
THEN FLOOR(p.stock_quantity / sm.daily_sales_avg)
ELSE NULL
END,
pm.weeks_of_inventory = CASE
WHEN COALESCE(sm.weekly_sales_avg, 0) > 0
THEN FLOOR(p.stock_quantity / sm.weekly_sales_avg)
ELSE NULL
END,
pm.stock_status = CASE
WHEN p.stock_quantity <= 0 THEN 'Out of Stock'
WHEN COALESCE(sm.daily_sales_avg, 0) = 0 AND p.stock_quantity <= ? THEN 'Low Stock'
WHEN COALESCE(sm.daily_sales_avg, 0) = 0 THEN 'In Stock'
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) <= ? THEN 'Critical'
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) <= ? THEN 'Reorder'
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) > ? THEN 'Overstocked'
ELSE 'Healthy'
END,
pm.reorder_qty = CASE
WHEN COALESCE(sm.daily_sales_avg, 0) > 0 THEN
GREATEST(
CEIL(sm.daily_sales_avg * COALESCE(lm.avg_lead_time_days, 30) * 1.96),
?
)
ELSE ?
END,
pm.overstocked_amt = CASE
WHEN p.stock_quantity / NULLIF(sm.daily_sales_avg, 0) > ?
THEN GREATEST(0, p.stock_quantity - CEIL(sm.daily_sales_avg * ?))
ELSE 0
END,
pm.forecast_accuracy = GREATEST(0, 100 - LEAST(fa.avg_forecast_error, 100)),
pm.forecast_bias = GREATEST(-100, LEAST(fa.avg_forecast_bias, 100)),
pm.last_forecast_date = fa.last_forecast_date,
pm.last_calculated_at = NOW()
WHERE p.pid IN (?)
`, [
defaultThresholds.low_stock_threshold,
defaultThresholds.critical_days,
defaultThresholds.reorder_days,
defaultThresholds.overstock_days,
defaultThresholds.low_stock_threshold,
defaultThresholds.low_stock_threshold,
defaultThresholds.overstock_days,
defaultThresholds.overstock_days,
batch.map(row => row.pid)
]);
`, [batch.map(row => row.pid), batch.map(row => row.pid)]);
lastPid = batch[batch.length - 1].pid;
myProcessedProducts += batch.length; // Increment the *module's* count