Next.js website for Rocky Mountain Vending company featuring: - Product catalog with Stripe integration - Service areas and parts pages - Admin dashboard with Clerk authentication - SEO optimized pages with JSON-LD structured data Co-authored-by: Cursor <cursoragent@cursor.com>
99 lines
3.5 KiB
Text
99 lines
3.5 KiB
Text
/**
|
|
* @license
|
|
* Copyright 2019 Google LLC
|
|
* SPDX-License-Identifier: Apache-2.0
|
|
*/
|
|
|
|
import {Audit} from '../audit.js';
|
|
import * as i18n from '../../lib/i18n/i18n.js';
|
|
import {LargestContentfulPaint as ComputedLcp} from '../../computed/metrics/largest-contentful-paint.js';
|
|
|
|
const UIStrings = {
|
|
/** Description of the Largest Contentful Paint (LCP) metric, which marks the time at which the largest text or image is painted by the browser. This is displayed within a tooltip when the user hovers on the metric name to see more. No character length limits. The last sentence starting with 'Learn' becomes link text to additional documentation. */
|
|
description: 'Largest Contentful Paint marks the time at which the largest text or image is ' +
|
|
`painted. [Learn more about the Largest Contentful Paint metric](https://developer.chrome.com/docs/lighthouse/performance/lighthouse-largest-contentful-paint/)`,
|
|
};
|
|
|
|
const str_ = i18n.createIcuMessageFn(import.meta.url, UIStrings);
|
|
|
|
class LargestContentfulPaint extends Audit {
|
|
/**
|
|
* @return {LH.Audit.Meta}
|
|
*/
|
|
static get meta() {
|
|
return {
|
|
id: 'largest-contentful-paint',
|
|
title: str_(i18n.UIStrings.largestContentfulPaintMetric),
|
|
description: str_(UIStrings.description),
|
|
scoreDisplayMode: Audit.SCORING_MODES.NUMERIC,
|
|
supportedModes: ['navigation'],
|
|
requiredArtifacts: ['HostUserAgent', 'Trace', 'DevtoolsLog', 'GatherContext', 'URL',
|
|
'SourceMaps'],
|
|
};
|
|
}
|
|
|
|
/**
|
|
* @return {{mobile: {scoring: LH.Audit.ScoreOptions}, desktop: {scoring: LH.Audit.ScoreOptions}}}
|
|
*/
|
|
static get defaultOptions() {
|
|
return {
|
|
mobile: {
|
|
// 25th and 13th percentiles HTTPArchive -> median and p10 points.
|
|
// https://bigquery.cloud.google.com/table/httparchive:lighthouse.2020_02_01_mobile?pli=1
|
|
// https://web.dev/articles/lcp#what_is_a_good_lcp_score
|
|
// see https://www.desmos.com/calculator/1etesp32kt
|
|
scoring: {
|
|
p10: 2500,
|
|
median: 4000,
|
|
},
|
|
},
|
|
desktop: {
|
|
// 25th and 5th percentiles HTTPArchive -> median and p10 points.
|
|
// SELECT
|
|
// APPROX_QUANTILES(lcpValue, 100)[OFFSET(5)] AS p05_lcp,
|
|
// APPROX_QUANTILES(lcpValue, 100)[OFFSET(25)] AS p25_lcp
|
|
// FROM (
|
|
// SELECT CAST(JSON_EXTRACT_SCALAR(payload, "$['_chromeUserTiming.LargestContentfulPaint']") AS NUMERIC) AS lcpValue
|
|
// FROM `httparchive.pages.2020_04_01_desktop`
|
|
// )
|
|
scoring: {
|
|
p10: 1200,
|
|
median: 2400,
|
|
},
|
|
},
|
|
};
|
|
}
|
|
|
|
/**
|
|
* @param {LH.Artifacts} artifacts
|
|
* @param {LH.Audit.Context} context
|
|
* @return {Promise<LH.Audit.Product>}
|
|
*/
|
|
static async audit(artifacts, context) {
|
|
const trace = artifacts.Trace;
|
|
const devtoolsLog = artifacts.DevtoolsLog;
|
|
const gatherContext = artifacts.GatherContext;
|
|
const metricComputationData = {
|
|
trace, devtoolsLog, gatherContext,
|
|
settings: context.settings, URL: artifacts.URL,
|
|
SourceMaps: artifacts.SourceMaps, simulator: null,
|
|
};
|
|
|
|
const metricResult = await ComputedLcp.request(metricComputationData, context);
|
|
const options = context.options[context.settings.formFactor];
|
|
|
|
return {
|
|
score: Audit.computeLogNormalScore(
|
|
options.scoring,
|
|
metricResult.timing
|
|
),
|
|
scoringOptions: options.scoring,
|
|
numericValue: metricResult.timing,
|
|
numericUnit: 'millisecond',
|
|
displayValue: str_(i18n.UIStrings.seconds, {timeInMs: metricResult.timing}),
|
|
};
|
|
}
|
|
}
|
|
|
|
export default LargestContentfulPaint;
|
|
export {UIStrings};
|