const path = require('path');
const fs = require('fs');
const os = require('os'); // For detecting CPU cores

// Get the base directory (the directory containing the inventory-server folder)
const baseDir = path.resolve(__dirname, '../../..');

// Load environment variables from the inventory-server directory
require('dotenv').config({ path: path.resolve(__dirname, '../..', '.env') });

// Configure statement timeout (30 minutes)
const PG_STATEMENT_TIMEOUT_MS = 1800000;

// Add error handler for uncaught exceptions
process.on('uncaughtException', (error) => {
    console.error('Uncaught Exception:', error);
    process.exit(1);
});

// Add error handler for unhandled promise rejections
process.on('unhandledRejection', (reason, promise) => {
    console.error('Unhandled Rejection at:', promise, 'reason:', reason);
    process.exit(1);
});

// Load progress module
const progress = require('../utils/progress');

// Store progress functions in global scope to ensure availability
global.formatElapsedTime = progress.formatElapsedTime;
global.estimateRemaining = progress.estimateRemaining;
global.calculateRate = progress.calculateRate;
global.outputProgress = progress.outputProgress;
global.clearProgress = progress.clearProgress;
global.getProgress = progress.getProgress;
global.logError = progress.logError;

// Load database module
const { getConnection, closePool } = require('../utils/db');

// Add cancel handler
let isCancelled = false;
let runningQueryPromise = null;

function cancelCalculation() {
    if (!isCancelled) {
        isCancelled = true;
        console.log('Calculation has been cancelled by user');
        
        // Store the query promise to potentially cancel it
        const queryToCancel = runningQueryPromise;
        if (queryToCancel) {
            console.log('Attempting to cancel the running query...');
        }
        
        // Force-terminate any query that's been running for more than 5 seconds
        try {
            const connection = getConnection();
            connection.then(async (conn) => {
                try {
                    // Identify and terminate long-running queries from our application
                    await conn.query(`
                        SELECT pg_cancel_backend(pid) 
                        FROM pg_stat_activity 
                        WHERE query_start < now() - interval '5 seconds'
                        AND application_name = 'populate_metrics'
                        AND query NOT LIKE '%pg_cancel_backend%'
                    `);
                    
                    // Release connection
                    conn.release();
                } catch (err) {
                    console.error('Error during force cancellation:', err);
                    conn.release();
                }
            }).catch(err => {
                console.error('Could not get connection for cancellation:', err);
            });
        } catch (err) {
            console.error('Failed to terminate running queries:', err);
        }
    }
    
    return {
        success: true,
        message: 'Calculation has been cancelled'
    };
}

// Handle SIGTERM signal for cancellation
process.on('SIGTERM', cancelCalculation);
process.on('SIGINT', cancelCalculation);

const calculateInitialMetrics = (client, onProgress) => {
  return client.query(`
    -- Truncate the existing metrics tables to ensure clean data
    TRUNCATE TABLE public.daily_product_snapshots;
    TRUNCATE TABLE public.product_metrics;

    -- First let's create daily snapshots for all products with order activity
    WITH SalesData AS (
      SELECT
        p.pid,
        p.sku,
        o.date::date AS order_date,
        -- Count orders to ensure we only include products with real activity
        COUNT(o.id) as order_count,
        -- Aggregate Sales (Quantity > 0, Status not Canceled/Returned)
        COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.quantity ELSE 0 END), 0) AS units_sold,
        COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.price * o.quantity ELSE 0 END), 0.00) AS gross_revenue_unadjusted,
        COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.discount ELSE 0 END), 0.00) AS discounts,
        COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN COALESCE(o.costeach, p.landing_cost_price, p.cost_price) * o.quantity ELSE 0 END), 0.00) AS cogs,
        COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN p.regular_price * o.quantity ELSE 0 END), 0.00) AS gross_regular_revenue,

        -- Aggregate Returns (Quantity < 0 or Status = Returned)
        COALESCE(SUM(CASE WHEN o.quantity < 0 OR COALESCE(o.status, 'pending') = 'returned' THEN ABS(o.quantity) ELSE 0 END), 0) AS units_returned,
        COALESCE(SUM(CASE WHEN o.quantity < 0 OR COALESCE(o.status, 'pending') = 'returned' THEN o.price * ABS(o.quantity) ELSE 0 END), 0.00) AS returns_revenue
      FROM public.products p
      LEFT JOIN public.orders o ON p.pid = o.pid
      GROUP BY p.pid, p.sku, o.date::date
      HAVING COUNT(o.id) > 0 -- Only include products with actual orders
    ),
    ReceivingData AS (
      SELECT
        r.pid,
        r.received_date::date AS receiving_date,
        -- Count receiving documents to ensure we only include products with real activity
        COUNT(DISTINCT r.receiving_id) as receiving_count,
        -- Calculate received quantity for this day
        SUM(r.received_quantity) AS units_received,
        -- Calculate received cost for this day
        SUM(r.received_quantity * r.unit_cost) AS cost_received
      FROM public.receivings r
      GROUP BY r.pid, r.received_date::date
      HAVING COUNT(DISTINCT r.receiving_id) > 0 OR SUM(r.received_quantity) > 0
    ),
    -- Get current stock quantities
    StockData AS (
      SELECT
        p.pid,
        p.stock_quantity,
        COALESCE(p.landing_cost_price, p.cost_price, 0.00) as effective_cost_price,
        COALESCE(p.price, 0.00) as current_price,
        COALESCE(p.regular_price, 0.00) as current_regular_price
      FROM public.products p
    ),
    -- Combine sales and receiving dates to get all activity dates
    DatePidCombos AS (
      SELECT DISTINCT pid, order_date AS activity_date FROM SalesData
      UNION
      SELECT DISTINCT pid, receiving_date FROM ReceivingData
    ),
    -- Insert daily snapshots for all product-date combinations
    SnapshotInsert AS (
      INSERT INTO public.daily_product_snapshots (
        snapshot_date,
        pid,
        sku,
        eod_stock_quantity,
        eod_stock_cost,
        eod_stock_retail,
        eod_stock_gross,
        stockout_flag,
        units_sold,
        units_returned,
        gross_revenue,
        discounts,
        returns_revenue,
        net_revenue,
        cogs,
        gross_regular_revenue,
        profit,
        units_received,
        cost_received,
        calculation_timestamp
      )
      SELECT
        d.activity_date AS snapshot_date,
        d.pid,
        p.sku,
        -- Use current stock as approximation, since historical stock data is not available
        s.stock_quantity AS eod_stock_quantity,
        s.stock_quantity * s.effective_cost_price AS eod_stock_cost,
        s.stock_quantity * s.current_price AS eod_stock_retail,
        s.stock_quantity * s.current_regular_price AS eod_stock_gross,
        (s.stock_quantity <= 0) AS stockout_flag,
        -- Sales metrics
        COALESCE(sd.units_sold, 0),
        COALESCE(sd.units_returned, 0),
        COALESCE(sd.gross_revenue_unadjusted, 0.00),
        COALESCE(sd.discounts, 0.00),
        COALESCE(sd.returns_revenue, 0.00),
        COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00) AS net_revenue,
        COALESCE(sd.cogs, 0.00),
        COALESCE(sd.gross_regular_revenue, 0.00),
        (COALESCE(sd.gross_revenue_unadjusted, 0.00) - COALESCE(sd.discounts, 0.00)) - COALESCE(sd.cogs, 0.00) AS profit,
        -- Receiving metrics
        COALESCE(rd.units_received, 0),
        COALESCE(rd.cost_received, 0.00),
        now() -- calculation timestamp
      FROM DatePidCombos d
      JOIN public.products p ON d.pid = p.pid
      LEFT JOIN SalesData sd ON d.pid = sd.pid AND d.activity_date = sd.order_date
      LEFT JOIN ReceivingData rd ON d.pid = rd.pid AND d.activity_date = rd.receiving_date
      LEFT JOIN StockData s ON d.pid = s.pid
      RETURNING pid, snapshot_date
    ),
    -- Now build the aggregated product metrics from the daily snapshots
    MetricsInsert AS (
      INSERT INTO public.product_metrics (
        pid,
        sku,
        current_stock_quantity,
        current_stock_cost,
        current_stock_retail,
        current_stock_msrp,
        is_out_of_stock,
        total_units_sold,
        total_units_returned,
        return_rate,
        gross_revenue,
        total_discounts,
        total_returns,
        net_revenue,
        total_cogs,
        total_gross_revenue,
        total_profit,
        profit_margin,
        avg_daily_units,
        reorder_point,
        reorder_alert,
        days_of_supply,
        sales_velocity,
        sales_velocity_score,
        rank_by_revenue,
        rank_by_quantity,
        rank_by_profit,
        total_received_quantity,
        total_received_cost,
        last_sold_date,
        last_received_date,
        days_since_last_sale,
        days_since_last_received,
        calculation_timestamp
      )
      SELECT
        p.pid,
        p.sku,
        p.stock_quantity AS current_stock_quantity,
        p.stock_quantity * COALESCE(p.landing_cost_price, p.cost_price, 0) AS current_stock_cost,
        p.stock_quantity * COALESCE(p.price, 0) AS current_stock_retail,
        p.stock_quantity * COALESCE(p.regular_price, 0) AS current_stock_msrp,
        (p.stock_quantity <= 0) AS is_out_of_stock,
        -- Aggregate metrics
        COALESCE(SUM(ds.units_sold), 0) AS total_units_sold,
        COALESCE(SUM(ds.units_returned), 0) AS total_units_returned,
        CASE 
          WHEN COALESCE(SUM(ds.units_sold), 0) > 0 
          THEN COALESCE(SUM(ds.units_returned), 0)::float / NULLIF(COALESCE(SUM(ds.units_sold), 0), 0) 
          ELSE 0 
        END AS return_rate,
        COALESCE(SUM(ds.gross_revenue), 0) AS gross_revenue,
        COALESCE(SUM(ds.discounts), 0) AS total_discounts,
        COALESCE(SUM(ds.returns_revenue), 0) AS total_returns,
        COALESCE(SUM(ds.net_revenue), 0) AS net_revenue,
        COALESCE(SUM(ds.cogs), 0) AS total_cogs,
        COALESCE(SUM(ds.gross_regular_revenue), 0) AS total_gross_revenue,
        COALESCE(SUM(ds.profit), 0) AS total_profit,
        CASE 
          WHEN COALESCE(SUM(ds.net_revenue), 0) > 0 
          THEN COALESCE(SUM(ds.profit), 0) / NULLIF(COALESCE(SUM(ds.net_revenue), 0), 0) 
          ELSE 0 
        END AS profit_margin,
        -- Calculate average daily units
        COALESCE(AVG(ds.units_sold), 0) AS avg_daily_units,
        -- Calculate reorder point (simplified, can be enhanced with lead time and safety stock)
        CEILING(COALESCE(AVG(ds.units_sold) * 14, 0)) AS reorder_point,
        (p.stock_quantity <= CEILING(COALESCE(AVG(ds.units_sold) * 14, 0))) AS reorder_alert,
        -- Days of supply based on average daily sales
        CASE 
          WHEN COALESCE(AVG(ds.units_sold), 0) > 0 
          THEN p.stock_quantity / NULLIF(COALESCE(AVG(ds.units_sold), 0), 0) 
          ELSE NULL 
        END AS days_of_supply,
        -- Sales velocity (average units sold per day over last 30 days)
        (SELECT COALESCE(AVG(recent.units_sold), 0)
         FROM public.daily_product_snapshots recent
         WHERE recent.pid = p.pid
         AND recent.snapshot_date >= CURRENT_DATE - INTERVAL '30 days'
        ) AS sales_velocity,
        -- Placeholder for sales velocity score (can be calculated based on velocity)
        0 AS sales_velocity_score,
        -- Will be updated later by ranking procedure
        0 AS rank_by_revenue,
        0 AS rank_by_quantity,
        0 AS rank_by_profit,
        -- Receiving data
        COALESCE(SUM(ds.units_received), 0) AS total_received_quantity,
        COALESCE(SUM(ds.cost_received), 0) AS total_received_cost,
        -- Date metrics
        (SELECT MAX(sd.snapshot_date)
         FROM public.daily_product_snapshots sd
         WHERE sd.pid = p.pid AND sd.units_sold > 0
        ) AS last_sold_date,
        (SELECT MAX(rd.snapshot_date)
         FROM public.daily_product_snapshots rd
         WHERE rd.pid = p.pid AND rd.units_received > 0
        ) AS last_received_date,
        -- Calculate days since last sale/received
        CASE 
          WHEN (SELECT MAX(sd.snapshot_date)
                FROM public.daily_product_snapshots sd
                WHERE sd.pid = p.pid AND sd.units_sold > 0) IS NOT NULL
          THEN (CURRENT_DATE - (SELECT MAX(sd.snapshot_date)
                                FROM public.daily_product_snapshots sd
                                WHERE sd.pid = p.pid AND sd.units_sold > 0))::integer
          ELSE NULL
        END AS days_since_last_sale,
        CASE 
          WHEN (SELECT MAX(rd.snapshot_date)
                FROM public.daily_product_snapshots rd
                WHERE rd.pid = p.pid AND rd.units_received > 0) IS NOT NULL
          THEN (CURRENT_DATE - (SELECT MAX(rd.snapshot_date)
                               FROM public.daily_product_snapshots rd
                               WHERE rd.pid = p.pid AND rd.units_received > 0))::integer
          ELSE NULL
        END AS days_since_last_received,
        now() -- calculation timestamp
      FROM public.products p
      LEFT JOIN public.daily_product_snapshots ds ON p.pid = ds.pid
      GROUP BY p.pid, p.sku, p.stock_quantity, p.landing_cost_price, p.cost_price, p.price, p.regular_price
    )
    
    -- Update the calculate_status table
    INSERT INTO public.calculate_status (module_name, last_calculation_timestamp)
    VALUES 
      ('daily_snapshots', now()),
      ('product_metrics', now())
    ON CONFLICT (module_name) DO UPDATE 
    SET last_calculation_timestamp = now();
    
    -- Finally, update the ranks for products
    UPDATE public.product_metrics pm SET
      rank_by_revenue = rev_ranks.rank
    FROM (
      SELECT pid, RANK() OVER (ORDER BY net_revenue DESC) AS rank
      FROM public.product_metrics
      WHERE net_revenue > 0
    ) rev_ranks
    WHERE pm.pid = rev_ranks.pid;
    
    UPDATE public.product_metrics pm SET
      rank_by_quantity = qty_ranks.rank
    FROM (
      SELECT pid, RANK() OVER (ORDER BY total_units_sold DESC) AS rank
      FROM public.product_metrics
      WHERE total_units_sold > 0
    ) qty_ranks
    WHERE pm.pid = qty_ranks.pid;
    
    UPDATE public.product_metrics pm SET
      rank_by_profit = profit_ranks.rank
    FROM (
      SELECT pid, RANK() OVER (ORDER BY total_profit DESC) AS rank
      FROM public.product_metrics
      WHERE total_profit > 0
    ) profit_ranks
    WHERE pm.pid = profit_ranks.pid;
    
    -- Return count of products with metrics
    SELECT COUNT(*) AS product_count FROM public.product_metrics
  `);
};

async function populateInitialMetrics() {
    let connection;
    const startTime = Date.now();
    let calculateHistoryId;
    
    try {
        // Clean up any previously running calculations
        connection = await getConnection({
            // Add performance-related settings
            application_name: 'populate_metrics',
            statement_timeout: PG_STATEMENT_TIMEOUT_MS, // 30 min timeout per statement
        });
        
        // Ensure the calculate_status table exists and has the correct structure
        await connection.query(`
            CREATE TABLE IF NOT EXISTS calculate_status (
                module_name TEXT PRIMARY KEY,
                last_calculation_timestamp TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT CURRENT_TIMESTAMP
            )
        `);
        
        await connection.query(`
            UPDATE calculate_history 
            SET 
                status = 'cancelled',
                end_time = NOW(),
                duration_seconds = EXTRACT(EPOCH FROM (NOW() - start_time))::INTEGER,
                error_message = 'Previous calculation was not completed properly'
            WHERE status = 'running' AND additional_info->>'type' = 'populate_initial_metrics'
        `);

        // Create history record for this calculation
        const historyResult = await connection.query(`
            INSERT INTO calculate_history (
                start_time,
                status,
                additional_info
            ) VALUES (
                NOW(),
                'running',
                jsonb_build_object(
                    'type', 'populate_initial_metrics',
                    'sql_file', 'populate_initial_product_metrics.sql'
                )
            ) RETURNING id
        `);
        calculateHistoryId = historyResult.rows[0].id;

        // Initialize progress
        global.outputProgress({
            status: 'running',
            operation: 'Starting initial product metrics population',
            current: 0,
            total: 100,
            elapsed: '0s',
            remaining: 'Calculating... (this may take a while)',
            rate: 0,
            percentage: '0',
            timing: {
                start_time: new Date(startTime).toISOString(),
                end_time: new Date().toISOString(),
                elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
            },
            historyId: calculateHistoryId
        });

        // Prepare the database - analyze tables
        global.outputProgress({
            status: 'running',
            operation: 'Analyzing database tables for better query performance',
            current: 2,
            total: 100,
            elapsed: global.formatElapsedTime(startTime),
            remaining: 'Analyzing...',
            rate: 0,
            percentage: '2',
            timing: {
                start_time: new Date(startTime).toISOString(),
                end_time: new Date().toISOString(),
                elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
            },
            historyId: calculateHistoryId
        });
        
        // Enable better query planning and parallel operations
        await connection.query(`
            -- Analyze tables for better query planning
            ANALYZE public.products;
            ANALYZE public.purchase_orders;
            ANALYZE public.daily_product_snapshots;
            ANALYZE public.orders;
            
            -- Enable parallel operations
            SET LOCAL enable_parallel_append = on;
            SET LOCAL enable_parallel_hash = on;
            SET LOCAL max_parallel_workers_per_gather = 4;
            
            -- Larger work memory for complex sorts/joins
            SET LOCAL work_mem = '128MB';
        `).catch(err => {
            // Non-fatal if analyze fails
            console.warn('Failed to analyze tables (non-fatal):', err.message);
        });

        // Execute the SQL query
        global.outputProgress({
            status: 'running',
            operation: 'Executing initial metrics SQL query',
            current: 5,
            total: 100,
            elapsed: global.formatElapsedTime(startTime),
            remaining: 'Calculating... (this could take several hours with 150M+ records)',
            rate: 0,
            percentage: '5',
            timing: {
                start_time: new Date(startTime).toISOString(),
                end_time: new Date().toISOString(),
                elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
            },
            historyId: calculateHistoryId
        });

        // Read the SQL file
        const sqlFilePath = path.resolve(__dirname, 'populate_initial_product_metrics.sql');
        console.log('Base directory:', baseDir);
        console.log('Script directory:', __dirname);
        console.log('SQL file path:', sqlFilePath);
        console.log('Current working directory:', process.cwd());
        
        if (!fs.existsSync(sqlFilePath)) {
            throw new Error(`SQL file not found at ${sqlFilePath}`);
        }
        
        // Read and clean up the SQL (Slightly more robust cleaning)
        const sqlQuery = fs.readFileSync(sqlFilePath, 'utf8')
            .replace(/\r\n/g, '\n') // Handle Windows endings
            .replace(/\r/g, '\n')   // Handle old Mac endings
            .trim(); // Remove leading/trailing whitespace VERY IMPORTANT

        // Log details again AFTER cleaning
        console.log('SQL Query length (cleaned):', sqlQuery.length);
        console.log('SQL Query structure validation:');
        console.log('- Contains DO block:', sqlQuery.includes('DO $$') || sqlQuery.includes('DO $')); // Check both types of tag start
        console.log('- Contains BEGIN:', sqlQuery.includes('BEGIN'));
        console.log('- Contains END:', sqlQuery.includes('END $$;') || sqlQuery.includes('END $')); // Check both types of tag end
        console.log('- First 50 chars:', JSON.stringify(sqlQuery.slice(0, 50)));
        console.log('- Last 100 chars (cleaned):', JSON.stringify(sqlQuery.slice(-100)));
        
        // Final check to ensure clean SQL ending
        if (!sqlQuery.endsWith('END $$;')) {
            console.warn('WARNING: SQL does not end with "END $$;". This might cause issues.');
            console.log('Exact ending:', JSON.stringify(sqlQuery.slice(-20)));
        }
        
        // Execute the script
        console.log('Starting initial product metrics population...');
        
        // Track the query promise for potential cancellation
        runningQueryPromise = connection.query({
            text: sqlQuery,
            rowMode: 'array'
        });
        await runningQueryPromise;
        runningQueryPromise = null;

        // Update progress to 100%
        global.outputProgress({
            status: 'complete',
            operation: 'Initial product metrics population complete',
            current: 100,
            total: 100,
            elapsed: global.formatElapsedTime(startTime),
            remaining: '0s',
            rate: 0,
            percentage: '100',
            timing: {
                start_time: new Date(startTime).toISOString(),
                end_time: new Date().toISOString(),
                elapsed_seconds: Math.round((Date.now() - startTime) / 1000)
            },
            historyId: calculateHistoryId
        });

        // Update history with completion
        await connection.query(`
            UPDATE calculate_history 
            SET 
                end_time = NOW(),
                duration_seconds = $1,
                status = 'completed'
            WHERE id = $2
        `, [Math.round((Date.now() - startTime) / 1000), calculateHistoryId]);

        // Clear progress file on successful completion
        global.clearProgress();

        return {
            success: true,
            message: 'Initial product metrics population completed successfully',
            duration: Math.round((Date.now() - startTime) / 1000)
        };
    } catch (error) {
        const endTime = Date.now();
        const totalElapsedSeconds = Math.round((endTime - startTime) / 1000);

        // Enhanced error logging
        console.error('Error details:', {
            message: error.message,
            code: error.code,
            hint: error.hint,
            position: error.position,
            detail: error.detail,
            where: error.where ? error.where.substring(0, 500) + '...' : undefined, // Truncate to avoid huge logs
            severity: error.severity,
            file: error.file,
            line: error.line,
            routine: error.routine
        });

        // Update history with error
        if (connection && calculateHistoryId) {
            await connection.query(`
                UPDATE calculate_history 
                SET 
                    end_time = NOW(),
                    duration_seconds = $1,
                    status = $2,
                    error_message = $3
                WHERE id = $4
            `, [
                totalElapsedSeconds,
                isCancelled ? 'cancelled' : 'failed',
                error.message,
                calculateHistoryId
            ]);
        }

        if (isCancelled) {
            global.outputProgress({
                status: 'cancelled',
                operation: 'Calculation cancelled',
                current: 50,
                total: 100,
                elapsed: global.formatElapsedTime(startTime),
                remaining: null,
                rate: 0,
                percentage: '50',
                timing: {
                    start_time: new Date(startTime).toISOString(),
                    end_time: new Date().toISOString(),
                    elapsed_seconds: totalElapsedSeconds
                },
                historyId: calculateHistoryId
            });
        } else {
            global.outputProgress({
                status: 'error',
                operation: 'Error during initial product metrics population',
                message: error.message,
                current: 0,
                total: 100,
                elapsed: global.formatElapsedTime(startTime),
                remaining: null,
                rate: 0,
                percentage: '0',
                timing: {
                    start_time: new Date(startTime).toISOString(),
                    end_time: new Date().toISOString(),
                    elapsed_seconds: totalElapsedSeconds
                },
                historyId: calculateHistoryId
            });
        }

        console.error('Error during initial product metrics population:', error);
        return {
            success: false,
            error: error.message,
            duration: totalElapsedSeconds
        };
    } finally {
        if (connection) {
            connection.release();
        }
        await closePool();
    }
}

// Start population process
populateInitialMetrics()
    .then(result => {
        if (result.success) {
            console.log(`Initial product metrics population completed successfully in ${result.duration} seconds`);
            process.exit(0);
        } else {
            console.error(`Initial product metrics population failed: ${result.error}`);
            process.exit(1);
        }
    })
    .catch(err => {
        console.error('Unexpected error:', err);
        process.exit(1);
    });