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date formatter libraries 2021
(version: 3)
Comparing performance of:
moment/moment vs taylorhakes/fecha
Created:
4 years ago
by:
Registered User
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HTML Preparation code:
<script src="https://unpkg.com/moment@2.29.1/moment.js"></script> <script src="https://unpkg.com/fecha@4.2.1/lib/fecha.umd.js"></script> <script src="https://unpkg.com/date-fns@2.23.0/index.js"></script> <script src="https://unpkg.com/dateformat@4.5.1/lib/dateformat.js"></script>
Script Preparation code:
window.__date__ = new Date(); window.__expected__ = '2000/01/06';
Tests:
moment/moment
var actual = moment(__date__).format('YYYY/MM/DD'); console.assert(actual === __expected__);
taylorhakes/fecha
var actual = fecha.format(__date__, 'YYYY/MM/DD'); console.assert(actual === __expected__);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
moment/moment
taylorhakes/fecha
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**Benchmark Overview** The provided JSON represents a JavaScript microbenchmarking test case hosted on MeasureThat.net. The goal of this benchmark is to compare the performance of two date formatting libraries: Moment.js and fecha. **Library Descriptions** 1. **Moment.js**: A popular JavaScript library for working with dates and times. It provides a wide range of features, including parsing, formatting, and manipulating dates. 2. **fecha**: Another date formatting library developed by Taylor Hakes. It aims to provide fast and efficient date formatting capabilities. **Benchmark Test Cases** The benchmark consists of two test cases: 1. **Moment.js** The script preparation code sets up a `window.__date__` variable with a predefined Date object, which is then passed to the Moment.js library for formatting using the `.format()` method. The expected output is hardcoded as `'2000/01/06'`. The test case compares the actual formatted date string with the expected value. 2. **fecha** The script preparation code sets up a `window.__date__` variable, similar to the first test case. However, this time, it passes the Date object to the fecha library using the `.format()` method with the same format string as before. The test case also compares the actual formatted date string with the expected value. **Comparison and Options** The benchmark is designed to measure the performance of each library by executing the formatting process multiple times. In this specific test, both libraries use a similar approach: * They take a Date object as input. * They format the date using a specific format string (YYYY/MM/DD). * They compare the formatted output with an expected value. The main options being compared are the performance of each library in terms of execution speed. **Pros and Cons** 1. **Moment.js**: Pros: * Highly feature-rich and widely adopted. * Well-maintained and actively supported. * Can handle complex date calculations and manipulations. However, it may have slower performance due to its extensive feature set. 2. **fecha**: Pros: * Designed specifically for fast and efficient date formatting. * Optimized for performance, making it suitable for real-time applications. Cons: * Smaller community support compared to Moment.js. * Fewer features than Moment.js, which might limit its use cases. **Special JS Features** Neither library uses any special JavaScript features or syntax in this test case. The focus is solely on the date formatting performance of each library. **Alternative Libraries and Approaches** If you're looking for alternative libraries for date formatting, some popular options include: 1. **Date-fns**: A modern and efficient date manipulation library that provides a wide range of features. 2. **date-format**: Another lightweight library designed specifically for fast and accurate date formatting. 3. **Luxon**: A powerful and feature-rich date and time library developed by Mozilla. In terms of approaches, the benchmark uses a simple and straightforward method to measure performance: executing the same test case multiple times to average out any variability. This approach is effective but might not capture all aspects of performance, especially for more complex libraries or use cases.
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