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Test moment.js
(version: 0)
Comparing performance of:
1 vs 2
Created:
one year ago
by:
Guest
Go to the latest result
HTML Preparation code:
<script src='https://cdnjs.cloudflare.com/ajax/libs/moment.js/2.22.0/moment.min.js'></script>
Tests:
1
let entries = []; for (let i = 0; i < 10000; ++i) { entries.push(moment().utc()); }
2
let entries = []; for (let i = 0; i < 1000; ++i) { entries.push(moment().utc()); }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
1
2
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
one year ago
)
User agent:
Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36
Browser/OS:
Chrome 127 on Android
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Embed Benchmark Result
<iframe src="https://measurethat.net/Embed?id=556647" width="100%" height="500px"></iframe>
2
1K/s
1
107/s
View exact numbers
Test name
Executions per second
✓
2
1,113 Ops/sec
1
107 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
I'd be happy to explain the benchmark and its options. **Benchmark Overview** The provided JSON represents a JavaScript microbenchmark, specifically testing the performance of Moment.js, a popular library for working with dates in JavaScript. **Script Preparation Code** The script preparation code is empty, which means that no additional setup or initialization is required before running the benchmarks. This allows the focus to be solely on the execution time of the Moment.js library. **Html Preparation Code** The html preparation code includes a reference to the Moment.js library from a CDN (Content Delivery Network), specifically version 2.22.0. This ensures that the benchmark runs with the latest stable release of Moment.js. **Test Cases** There are two test cases: 1. **Test Case 1**: This benchmark creates an array `entries` and pushes 10,000 UTC timestamps from Moment.js into it using a for loop. 2. **Test Case 2**: Similar to Test Case 1, but with only 1,000 UTC timestamps. **Options Compared** The two test cases compare the execution time of Moment.js when dealing with different quantities of dates: * **Small Array Size (1000)**: This benchmark tests the performance of Moment.js when working with a relatively small dataset. * **Large Array Size (10,000)**: This benchmark tests the performance of Moment.js when working with a larger dataset. **Pros and Cons** The choice of array size depends on the specific use case: * **Small Array Size**: More suitable for situations where you need to work with a limited number of dates, such as in real-time analytics or reporting applications. + Pros: Faster execution time due to fewer operations. + Cons: May not be representative of larger-scale datasets. * **Large Array Size**: More suitable for situations where you need to process large amounts of data, such as in big data analytics or machine learning applications. + Pros: Representative of real-world scenarios where larger datasets are common. + Cons: May result in slower execution times due to more operations. **Other Considerations** * **Language and Platform**: The benchmark is running on JavaScript (specifically ES5 syntax) on a Linux-based Android device, which may affect the results. * **Moment.js Library**: As mentioned earlier, Moment.js is used as the library for working with dates in this benchmark. Its performance characteristics are likely to be influenced by factors such as cache efficiency, parallel processing, and algorithmic complexity. **Alternatives** Other libraries or approaches could be considered for date manipulation tasks: * **Internationalized Date and Time (IDT)**: A JavaScript API that provides a standardized way of handling dates and times across different cultures and locales. * **Lux**: A lightweight library for working with dates and times, designed to be fast and efficient while still providing features like locale awareness and formatting support. However, the choice of alternative library or approach would depend on specific requirements such as performance needs, feature set, and compatibility issues.
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