⚡ Optimize Navbar rendering by memoizing derived collection data#63
⚡ Optimize Navbar rendering by memoizing derived collection data#63
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- Wrapped the calculation of `collectionsWithProducts` inside `useMemo` to prevent unnecessary re-renders. - Optimized the grouping logic from an $O(N \times M)$ operation (using `map` and `filter`) to an $O(N + M)$ operation using a `Map` to group products by `collectionId`. - Updated `fetchCollectionsAndProducts` to store raw `collections` and `products` instead of doing the calculation synchronously. Co-authored-by: AJFrio <20246916+AJFrio@users.noreply.github.com>
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| <meta name="viewport" content="width=device-width, initial-scale=1.0" /> | ||
| <title>OpenShop</title> | ||
| <script type="module" crossorigin src="/assets/index-BYJaIYQ8.js"></script> | ||
| <script type="module" crossorigin src="/assets/index-ENYPUJjh.js"></script> |
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Include referenced dist JS bundle
dist/index.html now points to /assets/index-ENYPUJjh.js, but this commit does not add that file to dist/assets (and removes the previously tracked bundle), so the checked-in dist/ snapshot cannot boot the app because the entry script 404s. This breaks any workflow that serves repository dist contents directly without a rebuild step.
Useful? React with 👍 / 👎.
| @@ -0,0 +1,22 @@ | |||
| import React, { useMemo, useState } from 'react'; | |||
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Remove lint-failing unused symbols in benchmarks
This new benchmark file introduces unused imports (useMemo, useState) and an unused local result, which violates the repo’s no-unused-vars rule for **/*.{js,jsx} and causes lint failures (the same pattern appears in benchmark2.js and benchmark3.js). As committed, these added scripts break standard lint runs.
Useful? React with 👍 / 👎.
💡 What:
Navbar.jsxthat grouped products into their respective collections has been refactored.useMemohook, and the algorithm has been improved from a nested.map()and.filter()approach (which is $O(N \times M)$) to a single-passMaplookup approach (which is $O(N + M)$).🎯 Why:
filteriterated over all products for every single collection, this operation scaled poorly with larger catalogs.📊 Measured Improvement:
I created a synthetic benchmark to measure the execution time of grouping 1000 products into 100 collections over 10,000 iterations:
PR created automatically by Jules for task 8750007747577903858 started by @AJFrio