DMleadgen
46d973904b
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>
69 lines
No EOL
3.2 KiB
Text
69 lines
No EOL
3.2 KiB
Text
// Copyright 2024 The Chromium Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file.
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import * as Core from '../core/core.js';
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import * as Graph from '../graph/graph.js';
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class Metric {
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static getScriptUrls(dependencyGraph, treatNodeAsRenderBlocking) {
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const scriptUrls = new Set();
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dependencyGraph.traverse(node => {
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if (node.type !== Graph.BaseNode.types.NETWORK) {
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return;
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}
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if (node.request.resourceType !== 'Script') {
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return;
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}
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if (treatNodeAsRenderBlocking?.(node)) {
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scriptUrls.add(node.request.url);
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}
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});
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return scriptUrls;
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}
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static get coefficients() {
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throw new Core.LanternError('coefficients unimplemented!');
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}
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/**
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* Returns the coefficients, scaled by the throttling settings if needed by the metric.
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* Some lantern metrics (speed-index) use components in their estimate that are not
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* from the simulator. In this case, we need to adjust the coefficients as the target throttling
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* settings change.
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*/
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static getScaledCoefficients(_rttMs) {
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return this.coefficients;
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}
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static getOptimisticGraph(_dependencyGraph, _processedNavigation) {
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throw new Core.LanternError('Optimistic graph unimplemented!');
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}
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static getPessimisticGraph(_dependencyGraph, _processedNavigation) {
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throw new Core.LanternError('Pessmistic graph unimplemented!');
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}
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static getEstimateFromSimulation(simulationResult, _extras) {
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return simulationResult;
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}
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static compute(data, extras) {
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const { simulator, graph, processedNavigation } = data;
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const metricName = this.name.replace('Lantern', '');
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const optimisticGraph = this.getOptimisticGraph(graph, processedNavigation);
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const pessimisticGraph = this.getPessimisticGraph(graph, processedNavigation);
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let simulateOptions = { label: `optimistic${metricName}` };
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const optimisticSimulation = simulator.simulate(optimisticGraph, simulateOptions);
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simulateOptions = { label: `pessimistic${metricName}` };
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const pessimisticSimulation = simulator.simulate(pessimisticGraph, simulateOptions);
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const optimisticEstimate = this.getEstimateFromSimulation(optimisticSimulation, { ...extras, optimistic: true });
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const pessimisticEstimate = this.getEstimateFromSimulation(pessimisticSimulation, { ...extras, optimistic: false });
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const coefficients = this.getScaledCoefficients(simulator.rtt);
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// Estimates under 1s don't really follow the normal curve fit, minimize the impact of the intercept
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const interceptMultiplier = coefficients.intercept > 0 ? Math.min(1, optimisticEstimate.timeInMs / 1000) : 1;
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const timing = coefficients.intercept * interceptMultiplier +
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coefficients.optimistic * optimisticEstimate.timeInMs + coefficients.pessimistic * pessimisticEstimate.timeInMs;
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return {
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timing,
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optimisticEstimate,
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pessimisticEstimate,
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optimisticGraph,
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pessimisticGraph,
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};
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}
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}
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export { Metric };
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//# sourceMappingURL=Metric.js.map |