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lodash uniq vs set string custom
(version: 0)
Comparing performance of:
Set vs Array
Created:
3 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:
Set
var l = new Set(["a", "a","b","c", "englihs", "prey", "english", "b"]); return l;
Array
var l = ["a", "a","b","c", "englihs", "prey", "english", "b"]; return _.uniq(l);
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Set
Array
Fastest:
N/A
Slowest:
N/A
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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 those approaches, library usage, special JavaScript features, and other considerations. **Benchmark Overview** MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided benchmark compares two approaches for removing duplicates from an array: using the native `Set` data structure and using the popular utility library Lodash's `uniq` function. **Test Cases** There are two test cases: 1. **Set**: This test case uses a `Set` object to remove duplicates from an array containing multiple identical elements. 2. **Array**: This test case uses Lodash's `uniq` function to remove duplicates from the same array as in the previous test case. **Library Usage** The `uniq` function is part of the Lodash library, which provides a set of useful functions for working with arrays and objects. The `uniq` function takes an array as input and returns a new array containing only unique elements, preserving the original order of equal elements. In the context of this benchmark, the `Set` data structure is used to remove duplicates from the array because it automatically removes duplicates by storing each element as a key in a hash table. The `uniq` function from Lodash achieves the same result but uses an algorithmic approach to identify and remove duplicate elements. **Special JavaScript Features** There are no special JavaScript features or syntaxes being tested in this benchmark, apart from using the `Set` data structure which is a built-in feature of modern browsers. **Options Compared** The two options being compared are: 1. **Native Set Data Structure**: Using the native `Set` data structure to remove duplicates from an array. 2. **Lodash's uniq Function**: Using Lodash's `uniq` function to remove duplicates from the same array. **Pros and Cons of Each Approach** Here are some pros and cons of each approach: 1. **Native Set Data Structure**: * Pros: Fast, efficient, and widely supported by modern browsers. * Cons: May not work as expected in older browsers that do not support `Set`. 2. **Lodash's uniq Function**: * Pros: More comprehensive and flexible, can handle edge cases and complex scenarios. * Cons: Slower than the native `Set` data structure due to its algorithmic nature. **Other Considerations** * The benchmark measures the execution speed of each approach, which is an important factor for applications that require fast performance. * The test case uses a specific array with multiple identical elements to simulate real-world scenarios where duplicates need to be removed. * The use of Lodash's `uniq` function may not be necessary in all cases, and developers can opt for the native `Set` data structure instead. **Alternatives** Other alternatives for removing duplicates from an array include: 1. **Using a custom implementation**: Developers can write their own algorithm to remove duplicates from an array. 2. **Using other utility libraries**: Other libraries like jQuery or Underscore.js may provide similar functionality as Lodash's `uniq` function. In conclusion, the benchmark compares two approaches for removing duplicates from an array: using the native `Set` data structure and using Lodash's `uniq` function. The pros and cons of each approach are discussed, along with other considerations such as performance, compatibility, and custom implementation options.
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