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Lodash filter length vs sumby 20211125
(version: 0)
Comparing performance of:
Filter length vs Sum vs Manual
Created:
4 years ago
by:
Guest
Jump to the latest result
HTML Preparation code:
<script src="https://cdn.jsdelivr.net/lodash/4.17.15/lodash.min.js"></script>
Script Preparation code:
window.array = [1, 4, 3, 4, 2, 2, 1, 5, 3, 5, 1, 4, 3, 4, 2, 2, 1, 5, 3, 5, 1, 4, 3, 4, 2, 2, 1, 5, 3, 5, 1, 4, 3, 4, 2, 2, 1, 5, 3, 5, 1, 4, 3, 4, 2, 2, 1, 5, 3, 5];
Tests:
Filter length
const x = _.filter(window.array, i => i === 3).length; return x;
Sum
const x = _.sumBy(window.array, i => i === 3 ? 1 : 0); return x;
Manual
let x = 0; let array = window.array; let len = array.length; for (let i = 0; i < len; i++) { if (array[i] === 3) { x++; } } return x;
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (3)
Previous results
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Test case name
Result
Filter length
Sum
Manual
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided JSON and explain what is being tested. **Benchmark Definition** The benchmark definition provides information about the test case, including its name, description (which is null in this case), script preparation code, and HTML preparation code (which includes a reference to Lodash, a popular JavaScript utility library). **Test Cases** There are three individual test cases: 1. **Filter Length**: This test case uses Lodash's `filter()` function to create a new array with only the elements that match the condition (`i => i === 3`). The length of this filtered array is then returned. 2. **Sum**: This test case uses Lodash's `sumBy()` function to calculate the sum of all elements in the array where the value matches the condition (`i => i === 3 ? 1 : 0`). 3. **Manual**: This test case performs a manual iteration over the array using a for loop, incrementing a counter variable (`x`) whenever it encounters an element equal to `3`. **Options Compared** The three test cases compare different approaches to achieve the same result: * **Filter Length**: Uses Lodash's optimized implementation of filtering arrays. * **Sum**: Uses Lodash's optimized implementation of summing arrays with a custom condition. * **Manual**: Performs a manual iteration over the array, using a for loop and incrementing a counter variable. **Pros and Cons** Here are some pros and cons of each approach: * **Filter Length**: + Pros: Fast and efficient, as Lodash's implementation is optimized for performance. + Cons: Requires an external dependency (Lodash). * **Sum**: + Pros: Also fast and efficient, as Lodash's implementation is optimized for performance. + Cons: May require additional memory allocation or copying of data, depending on the specific implementation. * **Manual**: + Pros: No external dependencies required. + Cons: Can be slower and more error-prone due to manual iteration. **Lodash Library** Lodash (pronounced "lodash") is a popular JavaScript utility library that provides a comprehensive set of functional programming tools. The `filter()` and `sumBy()` functions are part of Lodash's core set of functions, which makes it easy for developers to perform common data transformations and aggregations. **Other Considerations** When writing benchmarks or performance tests, it's essential to consider factors such as: * **Memory allocation**: How much memory is allocated for each test case? * **Copying data**: Does the implementation involve copying or modifying data structures? * **Conditionals and loops**: Are there any unnecessary conditionals or loops that can be optimized? **Alternatives** If you're interested in exploring alternative approaches, here are some options: * Use a different filtering library, such as `Array.prototype.filter()` (native JavaScript) or `lodash-filter` (a lightweight wrapper around Lodash). * Implement your own manual filtering and summing logic using bitwise operations or other optimization techniques. * Experiment with other libraries or frameworks that provide similar functionality to Lodash. Keep in mind that the best approach will depend on the specific requirements of your project, including factors such as performance, memory usage, and development complexity.
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