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foofooo
(version: 0)
fooo
Comparing performance of:
Keys vs Entries
Created:
5 years ago
by:
Registered User
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Tests:
Keys
const BREAKPOINTS = { desktop: 1024, desktopMedium: 1280, desktopWide: 1600, mobile: 320, mobileMedium: 375, mobileWide: 425, tablet: 768, } const size = 1100 const keys = Object.keys(BREAKPOINTS) keys.reduce((previous, current) => { const currentWidth = BREAKPOINTS[current] const previousWidth = BREAKPOINTS[previous] return Math.abs(size - previousWidth) < Math.abs(size - currentWidth) ? previous : current }, 'desktop')
Entries
const BREAKPOINTS = { desktop: 1024, desktopMedium: 1280, desktopWide: 1600, mobile: 320, mobileMedium: 375, mobileWide: 425, tablet: 768, } const size = 1100 const entries = Object.entries(BREAKPOINTS) entries.sort(([, widthA], [_, widthB]) => { return Math.abs(widthA - size) - Math.abs(widthB - size) })[0][0]
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Suite status:
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Result
Keys
Entries
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'll break down the provided benchmark and explain what's being tested, compared options, pros and cons of each approach, and other considerations. **Benchmark Overview** The benchmark is testing two different methods for finding the desktop breakpoint from a predefined `BREAKPOINTS` object. The object contains various breakpoints (e.g., `desktop`, `mobile`, `tablet`) with corresponding widths. **Test Cases** There are two test cases: 1. **Keys**: This test case uses the `Object.keys()` method to iterate over the `BREAKPOINTS` object's keys and find the one that is closest to a predefined size (`size = 1100`). The test compares the absolute difference between the size and each key's width. 2. **Entries**: This test case uses the `Object.entries()` method to iterate over the `BREAKPOINTS` object's entries (key-value pairs) and sort them based on the absolute difference between each entry's width and the predefined size. The test then extracts the first sorted entry's key, which is assumed to be the closest breakpoint. **Comparison of Approaches** 1. **Keys**: * Pros: Simple, straightforward approach using a well-known method (`Object.keys()`). * Cons: May not work correctly if the `BREAKPOINTS` object has an empty or null value for a particular key. 2. **Entries**: * Pros: More efficient and accurate than the `Keys` approach, as it uses a stable sorting algorithm (e.g., Timsort in V8). * Cons: Requires more memory to store the temporary sorted array, and may have higher overhead due to the sorting process. **Other Considerations** * **Library:** No external libraries are used in this benchmark. * **Special JS Features/Syntax:** None mentioned or applicable. **Alternatives** Some alternative approaches could be: 1. Using `Array.prototype.indexOf()` instead of `Object.keys()`: This would provide a more direct way to find the closest breakpoint, but may not work correctly if the object has an empty or null value for a particular key. 2. Using a custom sorting function with `Object.entries()`: Instead of using the default comparison function, you could define a custom function that takes into account additional factors, such as the breakpoint's name or other properties in the object. 3. Using a different data structure, such as an array or a trie, to store and query breakpoints. Keep in mind that these alternatives may introduce additional complexity or performance overhead, depending on your specific use case and requirements. In summary, the `Keys` approach is simple and easy to understand, while the `Entries` approach provides more efficiency and accuracy. The choice of which one to use ultimately depends on your priorities and the specific characteristics of your use case.
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