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https://github.com/LukeHagar/usage-statistics.git
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chore: streamline release workflows by adding version bump and built files commit step; remove redundant asset upload steps
This commit is contained in:
Luke Hagar
388
dist/summaries/pypi.js
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388
dist/summaries/pypi.js
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@@ -0,0 +1,388 @@
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import { mkdirSync, writeFileSync } from 'node:fs';
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import { Chart, registerables } from 'chart.js';
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import { Canvas } from 'skia-canvas';
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Chart.register(...registerables);
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export function formatPypiSummary(summary, platformMetrics) {
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summary += `| Package | Total Downloads | Monthly Downloads | Weekly Downloads | Daily Downloads | Version |\n`;
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summary += `| --- | --- | --- | --- | --- | --- |\n`;
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for (const metric of platformMetrics) {
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summary += `| ${metric.name} | ${metric.metrics?.downloadsTotal?.toLocaleString() || 0} | ${metric.metrics?.downloadsMonthly?.toLocaleString() || 0} | ${metric.metrics?.downloadsWeekly?.toLocaleString() || 0} | ${metric.metrics?.downloadsDaily?.toLocaleString() || 0} | ${metric.metrics?.version || 'N/A'} |\n`;
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}
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summary += `| **Total** | **${platformMetrics.reduce((sum, m) => sum + (m.metrics?.downloadsTotal || 0), 0).toLocaleString()}** | **${platformMetrics.reduce((sum, m) => sum + (m.metrics?.downloadsMonthly || 0), 0).toLocaleString()}** | **${platformMetrics.reduce((sum, m) => sum + (m.metrics?.downloadsWeekly || 0), 0).toLocaleString()}** | **${platformMetrics.reduce((sum, m) => sum + (m.metrics?.downloadsDaily || 0), 0).toLocaleString()}** | | |\n`;
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return summary;
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}
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function toIsoMonth(dateStr) {
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// input expected YYYY-MM-DD; fallback to Date parse if needed
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const iso = dateStr?.slice(0, 7);
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if (iso && /\d{4}-\d{2}/.test(iso))
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return iso;
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const d = new Date(dateStr);
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const y = d.getFullYear();
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const m = String(d.getMonth() + 1).padStart(2, '0');
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return `${y}-${m}`;
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}
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function displayMonthLabel(isoMonth) {
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const [y, m] = isoMonth.split('-');
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const d = new Date(Number(y), Number(m) - 1, 1);
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return d.toLocaleDateString('en-US', { month: 'short', year: '2-digit' });
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}
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function aggregateMonthlyTotals(points) {
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const totals = {};
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for (const p of points) {
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const iso = toIsoMonth(p.date);
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totals[iso] = (totals[iso] || 0) + p.downloads;
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}
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const labelsIso = Object.keys(totals).sort();
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const labels = labelsIso.map(displayMonthLabel);
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const data = labelsIso.map(l => totals[l]);
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return { labels, data };
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}
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function aggregateMonthlyByCategory(points) {
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const labelIsoSet = new Set();
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const categoryMap = {};
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for (const p of points) {
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const iso = toIsoMonth(p.date);
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labelIsoSet.add(iso);
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if (!categoryMap[p.category])
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categoryMap[p.category] = {};
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categoryMap[p.category][iso] = (categoryMap[p.category][iso] || 0) + p.downloads;
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}
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const labelsIso = Array.from(labelIsoSet).sort();
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const labels = labelsIso.map(displayMonthLabel);
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return { labelsIso, labels, categoryMap };
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}
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async function createOverallDownloadsChart(metric, outputPath) {
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// Prefer server-prepared chart JSON if present
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const server = metric.metrics?.overallChart;
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let labels;
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let datasets;
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if (server && server.labels && server.labels.length && server.datasets && server.datasets.length) {
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labels = server.labels;
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const colorFor = (label, idx) => {
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const l = (label || '').toLowerCase();
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if (l.includes('without'))
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return { stroke: '#2563eb', fill: '#2563eb33' }; // blue
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if (l.includes('with'))
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return { stroke: '#64748b', fill: '#64748b33' }; // slate
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const palette = ['#2563eb', '#16a34a', '#f59e0b', '#ef4444', '#7c3aed'];
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const i = idx ?? 0;
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return { stroke: palette[i % palette.length], fill: palette[i % palette.length] + '33' };
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};
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datasets = server.datasets.map((ds, i) => {
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const c = colorFor(ds.label, i);
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return {
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...ds,
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borderColor: c.stroke,
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backgroundColor: c.fill,
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borderWidth: 3,
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fill: true,
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tension: 0.1,
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};
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});
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}
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else {
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const series = metric.metrics?.overallSeries || [];
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const agg = aggregateMonthlyTotals(series.map(p => ({ date: p.date, downloads: p.downloads })));
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labels = agg.labels;
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datasets = [{
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label: `${metric.name} downloads per month`,
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data: agg.data,
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backgroundColor: 'rgba(54, 162, 235, 0.2)',
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borderColor: 'rgba(54, 162, 235, 1)',
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borderWidth: 3,
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fill: true,
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tension: 0.1
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}];
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}
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const canvas = new Canvas(1000, 800);
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const chart = new Chart(canvas, {
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type: 'line',
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data: { labels, datasets },
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options: {
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plugins: {
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legend: { display: true, position: 'bottom' },
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title: { display: true, text: `${metric.name} overall downloads` }
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},
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scales: {
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x: { title: { display: true, text: 'Month' } },
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y: { title: { display: true, text: 'Downloads' } }
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}
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}
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});
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const svgBuffer = await canvas.toBuffer('svg', { matte: 'white' });
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const svgPath = `${outputPath}/${metric.name}-pypi-overall.svg`;
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writeFileSync(svgPath, svgBuffer);
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chart.destroy();
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return svgPath;
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}
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// Time-series: Python major over time (line)
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async function createPythonMajorChart(metric, outputPath) {
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// Prefer server chart JSON if present
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const server = metric.metrics?.pythonMajorChart;
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let labels;
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let datasets;
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if (server && server.labels && server.labels.length && server.datasets && server.datasets.length) {
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const palette = ['#2563eb', '#16a34a', '#f59e0b', '#ef4444', '#7c3aed', '#0891b2', '#dc2626', '#0ea5e9'];
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labels = server.labels;
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datasets = server.datasets
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.filter(ds => !/unknown/i.test(ds.label))
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.map((ds, idx) => ({
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...ds,
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borderColor: palette[idx % palette.length],
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backgroundColor: palette[idx % palette.length] + '33',
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borderWidth: 2,
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fill: false,
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}));
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}
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else {
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const points = metric.metrics?.pythonMajorSeries || [];
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const { labelsIso, labels: lbls, categoryMap } = aggregateMonthlyByCategory(points);
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labels = lbls;
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const sortedCategories = Object.keys(categoryMap).filter(k => !/unknown/i.test(k)).sort((a, b) => Number(a) - Number(b));
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const palette = ['#2563eb', '#16a34a', '#f59e0b', '#ef4444', '#7c3aed', '#0891b2', '#dc2626', '#0ea5e9'];
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datasets = sortedCategories.map((category, idx) => ({
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label: `Python ${category}`,
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data: labelsIso.map(l => categoryMap[category][l] || 0),
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borderColor: palette[idx % palette.length],
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backgroundColor: palette[idx % palette.length] + '33',
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borderWidth: 2,
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fill: false,
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}));
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}
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const canvas = new Canvas(1000, 800);
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const chart = new Chart(canvas, {
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type: 'line',
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data: { labels, datasets },
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options: {
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plugins: {
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legend: { position: 'bottom' },
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title: { display: true, text: `${metric.name} downloads by Python major version` }
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},
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scales: {
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x: { title: { display: true, text: 'Month' } },
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y: { title: { display: true, text: 'Downloads' } }
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}
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}
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});
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const svgBuffer = await canvas.toBuffer('svg', { matte: 'white' });
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const svgPath = `${outputPath}/${metric.name}-pypi-python-major.svg`;
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writeFileSync(svgPath, svgBuffer);
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chart.destroy();
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return svgPath;
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}
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// Time-series: Python minor over time (line)
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async function createPythonMinorChart(metric, outputPath) {
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// Prefer server chart JSON if present
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const server = metric.metrics?.pythonMinorChart;
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let labels;
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let datasets;
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if (server && server.labels && server.labels.length && server.datasets && server.datasets.length) {
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const palette = ['#1d4ed8', '#059669', '#d97706', '#dc2626', '#6d28d9', '#0e7490', '#b91c1c', '#0284c7'];
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labels = server.labels;
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datasets = server.datasets
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.filter(ds => !/unknown/i.test(ds.label))
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.map((ds, idx) => ({
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...ds,
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borderColor: palette[idx % palette.length],
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backgroundColor: palette[idx % palette.length] + '33',
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borderWidth: 2,
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fill: false,
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}));
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}
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else {
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const points = metric.metrics?.pythonMinorSeries || [];
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const { labelsIso, labels: lbls, categoryMap } = aggregateMonthlyByCategory(points);
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labels = lbls;
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const sortedCategories = Object.keys(categoryMap).filter(k => !/unknown/i.test(k)).sort((a, b) => a.localeCompare(b, undefined, { numeric: true }));
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const palette = ['#1d4ed8', '#059669', '#d97706', '#dc2626', '#6d28d9', '#0e7490', '#b91c1c', '#0284c7'];
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datasets = sortedCategories.map((category, idx) => ({
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label: `Python ${category}`,
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data: labelsIso.map(l => categoryMap[category][l] || 0),
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borderColor: palette[idx % palette.length],
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backgroundColor: palette[idx % palette.length] + '33',
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borderWidth: 2,
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fill: false,
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}));
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}
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const canvas = new Canvas(1000, 800);
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const chart = new Chart(canvas, {
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type: 'line',
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data: { labels, datasets },
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options: {
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plugins: {
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legend: { position: 'bottom' },
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title: { display: true, text: `${metric.name} downloads by Python minor version` }
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},
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scales: {
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x: { title: { display: true, text: 'Month' } },
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y: { title: { display: true, text: 'Downloads' } }
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}
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}
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});
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const svgBuffer = await canvas.toBuffer('svg', { matte: 'white' });
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const svgPath = `${outputPath}/${metric.name}-pypi-python-minor.svg`;
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writeFileSync(svgPath, svgBuffer);
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chart.destroy();
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return svgPath;
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}
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// Time-series: Installer over time (line) - prefer server JSON
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async function createInstallerChart(metric, outputPath) {
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const server = metric.metrics?.installerChart;
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let labels;
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let datasets;
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if (server && server.labels && server.labels.length && server.datasets && server.datasets.length) {
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const palette = ['#3b82f6', '#10b981', '#f59e0b', '#ef4444', '#a78bfa', '#22d3ee'];
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labels = server.labels;
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datasets = server.datasets.map((ds, idx) => ({
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...ds,
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borderColor: palette[idx % palette.length],
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backgroundColor: palette[idx % palette.length] + '33',
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borderWidth: 2,
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fill: false,
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}));
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}
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else {
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const points = metric.metrics?.installerSeries || [];
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const { labelsIso, labels: lbls, categoryMap } = aggregateMonthlyByCategory(points);
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labels = lbls;
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const categories = Object.keys(categoryMap);
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const palette = ['#3b82f6', '#10b981', '#f59e0b', '#ef4444', '#a78bfa', '#22d3ee'];
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datasets = categories.map((category, idx) => ({
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label: category,
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data: labelsIso.map(l => categoryMap[category][l] || 0),
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borderColor: palette[idx % palette.length],
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backgroundColor: palette[idx % palette.length] + '33',
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borderWidth: 2,
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fill: false,
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}));
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}
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const canvas = new Canvas(1000, 800);
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const chart = new Chart(canvas, {
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type: 'line',
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data: { labels, datasets },
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options: {
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plugins: {
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legend: { position: 'bottom' },
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title: { display: true, text: `${metric.name} downloads by installer` }
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},
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scales: {
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x: { title: { display: true, text: 'Month' } },
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y: { title: { display: true, text: 'Downloads' } }
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}
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}
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});
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const svgBuffer = await canvas.toBuffer('svg', { matte: 'white' });
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const svgPath = `${outputPath}/${metric.name}-pypi-installer.svg`;
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writeFileSync(svgPath, svgBuffer);
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chart.destroy();
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return svgPath;
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}
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// Time-series: System over time (line) - prefer server JSON
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async function createSystemChart(metric, outputPath) {
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const server = metric.metrics?.systemChart;
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let labels;
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let datasets;
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if (server && server.labels && server.labels.length && server.datasets && server.datasets.length) {
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const palette = ['#0ea5e9', '#22c55e', '#f97316', '#e11d48', '#8b5cf6', '#06b6d4'];
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labels = server.labels;
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datasets = server.datasets.map((ds, idx) => ({
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...ds,
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borderColor: palette[idx % palette.length],
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backgroundColor: palette[idx % palette.length] + '33',
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borderWidth: 2,
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fill: false,
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}));
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}
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else {
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const points = metric.metrics?.systemSeries || [];
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const { labelsIso, labels: lbls, categoryMap } = aggregateMonthlyByCategory(points);
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labels = lbls;
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const sortedCategories = Object.keys(categoryMap).sort();
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const palette = ['#0ea5e9', '#22c55e', '#f97316', '#e11d48', '#8b5cf6', '#06b6d4'];
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datasets = sortedCategories.map((category, idx) => ({
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label: category,
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data: labelsIso.map(l => categoryMap[category][l] || 0),
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borderColor: palette[idx % palette.length],
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backgroundColor: palette[idx % palette.length] + '33',
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borderWidth: 2,
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fill: false,
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}));
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}
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const canvas = new Canvas(1000, 800);
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const chart = new Chart(canvas, {
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type: 'line',
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data: { labels, datasets },
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options: {
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plugins: {
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legend: { position: 'bottom' },
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title: { display: true, text: `${metric.name} downloads by OS` }
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},
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scales: {
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x: { title: { display: true, text: 'Month' } },
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y: { title: { display: true, text: 'Downloads' } }
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}
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}
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});
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const svgBuffer = await canvas.toBuffer('svg', { matte: 'white' });
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const svgPath = `${outputPath}/${metric.name}-pypi-system.svg`;
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writeFileSync(svgPath, svgBuffer);
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chart.destroy();
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return svgPath;
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}
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// Removed static bar chart generators per request
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async function createPypiCharts(metrics, basePath) {
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const outputPaths = [];
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for (const metric of metrics) {
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const packagePath = `${basePath}`;
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mkdirSync(packagePath, { recursive: true });
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const overall = await createOverallDownloadsChart(metric, packagePath);
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outputPaths.push(overall);
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const pythonMajor = await createPythonMajorChart(metric, packagePath);
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outputPaths.push(pythonMajor);
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const pythonMinor = await createPythonMinorChart(metric, packagePath);
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outputPaths.push(pythonMinor);
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const installer = await createInstallerChart(metric, packagePath);
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outputPaths.push(installer);
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const system = await createSystemChart(metric, packagePath);
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outputPaths.push(system);
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// static bar charts removed
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}
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return outputPaths;
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}
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export function addPypiDetails(summary, metrics) {
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summary += `#### Package Details:\n\n`;
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for (const metric of metrics) {
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summary += `**${metric.name}**:\n`;
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summary += `- Version: ${metric.metrics?.version || 'N/A'}\n`;
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if (metric.metrics?.latestReleaseDate)
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summary += `- Released: ${metric.metrics.latestReleaseDate}\n`;
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if (metric.metrics?.popularSystem)
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summary += `- Popular system: ${metric.metrics.popularSystem}\n`;
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if (metric.metrics?.popularInstaller)
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summary += `- Popular installer: ${metric.metrics.popularInstaller}\n`;
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summary += `- Releases: ${metric.metrics?.releases || 0}\n`;
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if (metric.metrics?.systemBreakdown) {
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summary += `- OS Usage Breakdown \n`;
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for (const [key, value] of Object.entries(metric.metrics?.systemBreakdown)) {
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summary += ` - ${key}: ${value}\n`;
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}
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}
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if (metric.metrics?.pythonVersionBreakdown) {
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summary += `- Python Version Breakdown \n`;
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for (const [key, value] of Object.entries(metric.metrics?.pythonVersionBreakdown)) {
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summary += ` - ${key}: ${value}\n`;
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}
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}
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}
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return summary;
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}
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export async function addPypiCharts(summary, platformMetrics) {
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const outputPath = './charts/pypi';
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mkdirSync(outputPath, { recursive: true });
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summary += `\n\n`;
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const svgPaths = await createPypiCharts(platformMetrics, outputPath);
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for (const p of svgPaths) {
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summary += `\n`;
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}
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return summary;
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}
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