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Ramda vs native vs loop
(version: 0)
Comparing performance of:
R.reduce vs Native reduce vs loop
Created:
6 years ago
by:
Guest
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HTML Preparation code:
<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>
Script Preparation code:
var a = []; a.length = 10000; a.fill(1,0,10000);
Tests:
R.reduce
var ram = R.reduce( (a,v) => a+v, 0, a)
Native reduce
var nat = a.reduce( (a,v) => a+v, 0)
loop
var loop for(let i=0; i<a.length; i++) { loop += a[i] }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (3)
Previous results
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Test case name
Result
R.reduce
Native reduce
loop
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**Benchmark Overview** The provided benchmark is designed to compare the performance of three approaches for performing a reduction operation on an array: using Ramda's `R.reduce()` function, native JavaScript's `reduce()` method, and a manual loop-based approach. **Approaches Compared** 1. **Ramda's R.reduce()**: This approach uses the Ramda library, which provides a functional programming API for JavaScript. 2. **Native reduce()**: This is the built-in JavaScript method that performs reduction operations on arrays. 3. **loop**: This is a manual loop-based approach where the developer writes the code to iterate over the array and accumulate the values. **Pros and Cons of Each Approach** 1. **Ramda's R.reduce()**: * Pros: Provides a concise and expressive way to perform reduction operations, eliminates the need for explicit loop handling. * Cons: Requires including an external library (Ramda), may have performance overhead due to library loading and function invocation. 2. **Native reduce()**: * Pros: Built-in method with minimal overhead, no external libraries required. * Cons: May require additional setup or configuration, less readable than Ramda's approach for some developers. 3. **loop**: * Pros: No external dependencies, full control over implementation. * Cons: Requires manual loop handling, which can be error-prone and verbose. **Library Used (Ramda)** Ramda is a popular functional programming library for JavaScript that provides a concise way to perform common operations such as reduction, filtering, mapping, etc. In this benchmark, Ramda's `R.reduce()` function is used to reduce an array of 10,000 elements by accumulating the values. **Special JS Feature/Syntax** None mentioned in the provided code or benchmark results. **Other Considerations** * The test cases are designed to compare the performance of each approach on a specific use case (reduction operation on an array). * The benchmark results are reported as executions per second, which provides a measure of performance. * The test environment is specified as Chrome 78 on Windows Desktop. **Alternatives** Other alternatives for performing reduction operations on arrays include: 1. Lodash: A popular utility library that provides a `reduce()` function similar to Ramda's approach. 2. Array.prototype.reduce(): This built-in method can be used instead of native reduce() or Ramda's R.reduce(). 3. Custom implementation using iterative techniques (e.g., accumulator-based approach). These alternatives may have different trade-offs in terms of performance, readability, and dependencies required.
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