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Lodash.js vs Nativemmlk
(version: 0)
Comparing performance of:
Native vs Lodash.js filter
Created:
one year ago
by:
Guest
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HTML Preparation code:
<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>
Script Preparation code:
var max1 = 100000; // 100,000 (100 Thousand) var max2 = 10000000; // 10,000,000 (10 Million) var max3 = 100000000; // 100,000,000 (100 Million) var arr1 = []; //for (var i = 0; i <= max1; i++) { arr1.push(i); } var arr2 = []; for (var i = 0; i <= max2; i++) { arr2.push(i); } var arr3 = []; //for (var i = 0; i <= max3; i++) { arr3.push(i); }
Tests:
Native
arr2.map(function (element, index) { return {id: element}; });
Lodash.js filter
_.map(arr2, function (element, index) { return {id: element}; });
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
Fork
Test case name
Result
Native
Lodash.js filter
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
one year ago
)
User agent:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36
Browser/OS:
Chrome 127 on Mac OS X 10.15.7
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Embed Benchmark Result
Test name
Executions per second
Native
12.1 Ops/sec
Lodash.js filter
27.7 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided JSON data for the JavaScript microbenchmarking test. **Benchmark Definition** The benchmark is designed to compare the performance of two approaches: native JavaScript and Lodash.js. The script preparation code generates three large arrays (`arr1`, `arr2`, and `arr3`) with different sizes (100,000, 10,000,000, and 100,000,000 elements, respectively). The benchmark then defines two test cases: 1. **Native**: This test case uses the native JavaScript `map()` function to transform an array into a new array with objects containing only the element's value. 2. **Lodash.js filter**: This test case uses the Lodash.js library (`_`) and its `filter()` function to achieve the same result as the native `map()` function. **Options Compared** The benchmark compares two options: 1. **Native JavaScript (map())**: Uses the built-in JavaScript `map()` function to transform an array into a new array. 2. **Lodash.js filter**: Uses the Lodash.js library and its `filter()` function to achieve the same result as the native `map()` function. **Pros and Cons of Each Approach** 1. **Native JavaScript (map())**: * Pros: No additional dependencies, lightweight, and highly optimized for performance. * Cons: May not be as readable or maintainable, especially for complex transformations. 2. **Lodash.js filter**: * Pros: More readable and maintainable code, easy to understand the intent behind the transformation. * Cons: Requires an external library dependency, which may add overhead. **Library Used** The Lodash.js library is used in this benchmark. Lodash.js is a popular JavaScript utility library that provides a wide range of functions for common tasks such as array manipulation, string manipulation, and more. In this case, the `filter()` function is used to transform an array into a new array. **Special JS Feature or Syntax** None mentioned explicitly, but the use of arrow functions (`function (element, index) { ... }`) is a relatively modern JavaScript feature introduced in ECMAScript 2015. **Other Considerations** The benchmark also considers the execution speed of each approach, measured in executions per second. This allows users to compare the performance of both options and make informed decisions about which one to use depending on their specific requirements. As an alternative to this benchmark, users might consider running other JavaScript benchmarks that focus on different aspects, such as: * V8 vs SpiderMonkey: A comparison between two popular JavaScript engines used in Google Chrome and Mozilla Firefox. * Async operations: A benchmark comparing the performance of different async programming approaches, such as callbacks, promises, or async/await. * WebAssembly: A benchmark evaluating the performance of JavaScript code compiled to WebAssembly (WASM) compared to native code.
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