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sdsadasd
(version: 0)
sd
Comparing performance of:
lodash vs object
Created:
2 years ago
by:
Guest
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HTML Preparation code:
<script src='https://cdn.jsdelivr.net/npm/lodash@4.17.10/lodash.min.js'></script>
Tests:
lodash
return _.uniq([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]);
object
const map = {}; return [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7].filter(item => { if (!map[item]) { map[item] = true; return true; } return false; });
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
lodash
object
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
2 years ago
)
User agent:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36
Browser/OS:
Chrome 120 on Mac OS X 10.15.7
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Test name
Executions per second
lodash
10184539.0 Ops/sec
object
8844717.0 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided JSON data and explain what is tested, compared options, pros and cons, and other considerations. **Benchmark Definition** The benchmark definition represents a single JavaScript microbenchmark. It has the following properties: * `Name`: A human-readable name for the benchmark (in this case, "sdsadasd"). * `Description`: A brief description of the benchmark (in this case, "sd"). * `Script Preparation Code` and `Html Preparation Code`: These fields are not used in this example. In a typical benchmark definition, you would provide code that sets up the environment for your benchmark. **Individual Test Cases** There are two individual test cases defined: 1. **Lodash Benchmark** The benchmark definition is: `return _.uniq([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]);` This test case uses the Lodash library, specifically the `uniq` function. The purpose of this benchmark is to measure the performance of the `uniq` function in removing duplicate elements from an array. The `_.uniq` function returns a new array with unique elements from the original array, preserving the order of the original elements. **Object Benchmark** The benchmark definition is: ` const map = {};\r\n return [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7].filter(item => {\r\n if (!map[item]) {\r\n map[item] = true;\r\n return true;\r\n }\r\n return false;\r\n });` This test case simulates a scenario where you need to remove duplicate elements from an array while preserving the order of unique elements. The benchmark measures the performance of this custom filtering approach. **Comparison** The two benchmarks are designed to compare the performance of: * Lodash's `uniq` function vs. * A custom filtering approach that uses an object to keep track of unique elements. **Pros and Cons** Lodash's `uniq` function is likely to be faster than the custom filtering approach because it is implemented in C++ and optimized for performance. However, the custom filtering approach can be easier to understand and maintain, especially if you're not familiar with Lodash or its ecosystem. The pros of using Lodash are: * Faster execution times * Easier to implement complex logic The cons of using Lodash are: * Additional dependency on an external library * Potential performance overhead due to the library's size and complexity **Other Considerations** When benchmarking JavaScript code, it's essential to consider factors such as: * **Device platform**: The test results were recorded on a Macintosh (Intel Mac OS X 10.15.7) with Chrome 120. * **Browser version**: The test was run in Chrome 120. * **Operating system**: The test was run on Mac OS X 10.15.7. **Alternatives** If you're looking for alternatives to Lodash or custom filtering approaches, consider the following options: * Other library functions that provide similar functionality (e.g., `Set` in JavaScript) * In-place filtering algorithms (e.g., using a single array and indices) * Custom implementations using native JavaScript features (e.g., `Map` or `Set` objects) Keep in mind that the choice of implementation depends on your specific use case, performance requirements, and personal preferences.
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