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Lodash reduce vs native in for loop
(version: 0)
This test aims to compare lodash reduce function with the Javascript native reduce function, doing exactly the same operation, BUT inside a regular for loop
Comparing performance of:
Native reduce (in for loop) vs Lodash reduce (in for loop)
Created:
5 years ago
by:
Guest
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HTML Preparation code:
<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>
Script Preparation code:
var nbIterations = 100000 //100,000 var numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
Tests:
Native reduce (in for loop)
for (let i = 0; i < nbIterations; i++) { numbers.reduce((sum, n) => sum + n, 0) }
Lodash reduce (in for loop)
for (let i = 0; i < nbIterations; i++) { _.reduce(numbers, (sum, n) => sum + n, 0) }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
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Test case name
Result
Native reduce (in for loop)
Lodash reduce (in for loop)
Fastest:
N/A
Slowest:
N/A
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down what's being tested in this benchmark. **Benchmark Definition:** The test is designed to compare two approaches: 1. Native JavaScript `reduce()` function inside a `for` loop (Test Name: "Native reduce (in for loop)") 2. Lodash `reduce()` function, also inside a `for` loop, but using the Lodash library (Test Name: "Lodash reduce (in for loop)") **Options Compared:** The two approaches are being compared in terms of performance, specifically: * How many executions per second can be achieved by each approach * Whether the native JavaScript implementation is faster or slower than the Lodash version **Pros and Cons:** 1. **Native JavaScript `reduce()` function (in for loop)**: * Pros: + Typically optimized for performance, as it's a built-in function + May be more predictable and consistent in behavior * Cons: + Requires manual iteration over the array using a `for` loop, which can be error-prone + Might not leverage modern JavaScript features or optimizations (e.g., parallel processing) 2. **Lodash `reduce()` function (in for loop)**: * Pros: + Easier to write and maintain, as it's a standardized library function + May offer more flexibility in terms of customization and extension * Cons: + Introduces an external dependency (the Lodash library) + Might incur overhead due to the additional layer of abstraction **Library:** In this case, the Lodash library is being used for its `reduce()` function. Lodash is a popular utility library that provides a set of functional programming helpers and shortcuts for common tasks. **Special JS Feature/Syntax:** There doesn't appear to be any specific JavaScript features or syntax being tested in this benchmark. Both tests follow the standard syntax and structure for using the `reduce()` function. **Other Alternatives:** If you're considering alternative approaches, here are a few options: 1. **Using modern JavaScript features:** You could explore using modern JavaScript features like `Array.prototype.reduce()` with an arrow function (`numbers.reduce((sum, n) => sum + n, 0)`), which might offer better performance and readability. 2. **Native implementation without for loop:** Another approach would be to implement the reduction operation directly within a single line of code, avoiding the need for a `for` loop altogether (e.g., `numbers.reduce((sum, n) => sum + n, 0)`). 3. **Using parallel processing or concurrency:** Depending on the specific use case and requirements, you might consider using modern JavaScript features like Web Workers or async/await to leverage parallel processing or concurrency. Keep in mind that these alternatives may require additional setup, dependencies, or changes to your codebase. I hope this explanation helps!
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