#!/usr/bin/env python3
import json

with open('/home/mdares/.node-red/flows.json', 'r') as f:
    flows = json.load(f)

# New Format Graph Data function that handles KPI history data
new_format_func = '''// Format Graph Data for KPI charts

// Check if we have KPI history data (from global context)
if (msg.topic === "kpiHistory" && msg.payload) {
    const kpiData = msg.payload;

    // Extract arrays
    const oeeHist = kpiData.oee || [];
    const availHist = kpiData.availability || [];
    const perfHist = kpiData.performance || [];
    const qualHist = kpiData.quality || [];

    // Build labels and data arrays
    const labels = [];
    const oeeData = [];
    const availData = [];
    const perfData = [];
    const qualData = [];

    // Use OEE timestamps as primary (they should all be the same length)
    oeeHist.forEach((point, index) => {
        const timestamp = new Date(point.timestamp);
        labels.push(timestamp.toLocaleString());

        oeeData.push(point.value || 0);
        availData.push(availHist[index]?.value || 0);
        perfData.push(perfHist[index]?.value || 0);
        qualData.push(qualHist[index]?.value || 0);
    });

    msg.graphData = {
        labels: labels,
        datasets: [
            { label: 'OEE %', data: oeeData },
            { label: 'Availability %', data: availData },
            { label: 'Performance %', data: perfData },
            { label: 'Quality %', data: qualData }
        ]
    };

    node.warn(`[GRAPH DATA] Formatted ${labels.length} KPI history points`);

    delete msg.topic;
    delete msg.payload;
    return msg;
}

// Legacy support: work_orders query data (if needed)
const rows = msg.payload || [];

if (!Array.isArray(rows) || rows.length === 0) {
    msg.graphData = {
        labels: [],
        datasets: [
            { label: 'OEE %', data: [] },
            { label: 'Availability %', data: [] },
            { label: 'Performance %', data: [] },
            { label: 'Quality %', data: [] }
        ]
    };
    delete msg.topic;
    delete msg.payload;
    return msg;
}

// If we have work_orders data, format it (though we won't use this path anymore)
const labels = [];
const goodData = [];
const scrapData = [];
const efficiencyData = [];
const qualityData = [];

rows.forEach(row => {
    const timestamp = new Date(row.updated_at);
    labels.push(timestamp.toLocaleString());

    const good = Number(row.good_parts) || 0;
    const scrap = Number(row.scrap_parts) || 0;
    const target = Number(row.target_quantity) || 0;

    goodData.push(good);
    scrapData.push(scrap);

    let eff = (row.progress_percent != null)
        ? Number(row.progress_percent)
        : (target > 0 ? (good / target) * 100 : 0);
    efficiencyData.push(Math.min(eff, 100));

    const total = good + scrap;
    const quality = total > 0 ? (good / total) * 100 : 100;
    qualityData.push(quality);
});

msg.graphData = {
    labels: labels,
    datasets: [
        { label: 'OEE %', data: efficiencyData },  // Use efficiency as fallback
        { label: 'Availability %', data: [] },
        { label: 'Performance %', data: [] },
        { label: 'Quality %', data: qualityData }
    ]
};

delete msg.topic;
delete msg.payload;

return msg;'''

# Update Format Graph Data function
for node in flows:
    if node.get('id') == 'format_graph_data_node_id':
        node['func'] = new_format_func
        print("✓ Updated Format Graph Data function to handle KPI data")
        break

with open('/home/mdares/.node-red/flows.json', 'w') as f:
    json.dump(flows, f, indent=4)

print("✓ flows.json updated")