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lodash
(version: 0)
Comparing performance of:
lodash vs js
Created:
7 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>
Tests:
lodash
const numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]; _.reduce(numbers, (sum, n) => sum + n, 0)
js
const numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]; numbers.reduce((sum, n) => sum + n, 0)
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
lodash
js
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's being tested, compared, and the pros/cons of each approach. **Benchmark Definition JSON** The benchmark definition is a JSON object that represents a JavaScript microbenchmark. The two test cases are: 1. **Lodash**: This test case uses the `lodash` library to perform a reduction operation on an array of numbers. 2. **js**: This test case is a bare-bones version of the same reduction operation, without any external library. **Options Compared** The main options being compared here are: * Using an external library (`lodash`) vs. not using an external library (`js`). * The implementation of the reduction operation: using `_.reduce()` from Lodash or writing a custom implementation with `numbers.reduce()`. **Pros and Cons of Each Approach** 1. **Using an external library (Lodash)**: * Pros: + Reduces boilerplate code and makes it easier to write correct logic. + Often provides optimized implementations for common data structures and operations. * Cons: + Adds dependency on the library, which may not be present in all environments. + May have performance overhead due to the additional layer of abstraction. 2. **Not using an external library (js)**: * Pros: + Eliminates dependencies and potential performance overhead. + Allows for more fine-grained control over implementation details. * Cons: + Requires manual implementation of common logic, which can be error-prone. + May not provide optimized implementations for specific data structures or operations. **Library: Lodash** Lodash is a popular JavaScript library that provides a comprehensive set of functional programming utilities. In this benchmark, it's used to perform the reduction operation on an array of numbers using `_.reduce()`. The purpose of Lodash is to simplify and optimize common data structure operations, such as reducing arrays or objects. **Special JS Feature/Syntax: None** There are no special JavaScript features or syntax being used in these test cases. The benchmark focuses solely on the comparison of two implementation approaches. **Other Alternatives** If you wanted to create a similar benchmark for other libraries or implementations, you could consider using different libraries (e.g., `underscore`, `ramda`) and comparing their performance with the `js` implementation. You could also explore alternative algorithms or data structures (e.g., iterative reductions, map-reduce combinations) and compare their performance. Keep in mind that creating a comprehensive benchmark like this one requires careful consideration of factors such as: * Hardware and software configurations * Data sizes and distributions * Algorithmic optimizations and trade-offs * Library dependencies and overhead If you're interested in creating similar benchmarks for other libraries or implementations, I'd be happy to provide more guidance on how to approach it!
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