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Ramda sort vs JS native sort
(version: 0)
Comparing performance of:
Ramda vs Native
Created:
6 years ago
by:
Guest
Jump to the latest result
HTML Preparation code:
<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>
Script Preparation code:
var diff = (a, b) => (a - b); var bigArray = (new Array(1000)).fill(null).map(() => Math.floor(Math.random() * 200) );
Tests:
Ramda
R.sort(diff, bigArray)
Native
bigArray.sort(diff)
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Ramda
Native
Fastest:
N/A
Slowest:
N/A
Latest run results:
Run details:
(Test run date:
6 months ago
)
User agent:
Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/141.0.0.0 Safari/537.36
Browser/OS:
Chrome 141 on Windows
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Embed Benchmark Result
Test name
Executions per second
Ramda
9760.0 Ops/sec
Native
83774.6 Ops/sec
Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the benchmark and explain what's being tested. **What is being tested?** The benchmark compares two sorting algorithms: 1. **Native JavaScript sort**: This is the built-in sorting algorithm provided by JavaScript, which uses the Timsort algorithm (a hybrid of merge sort and insertion sort). 2. **Ramda sort**: Ramda is a functional programming library that provides a `R.sort` function for sorting arrays. **Options compared** The benchmark compares two options: * Native JavaScript sort: This option uses the built-in `sort` method provided by JavaScript. * Ramda sort: This option uses the `R.sort` function from the Ramda library. **Pros and cons of each approach** **Native JavaScript sort:** Pros: * Fast execution, as it's implemented in native code * Low overhead, as it only requires a single call to the `sort` method Cons: * May not perform well on certain data sets or edge cases * Can be slower than Ramda sort for smaller data sets due to the overhead of the `R.sort` function **Ramda sort:** Pros: * More readable and maintainable code, as it uses a functional programming approach * Can handle edge cases and irregularly shaped data sets more effectively Cons: * Slower execution compared to Native JavaScript sort, due to the overhead of the Ramda library * May require additional memory allocation for the Ramda library **Other considerations** The benchmark also considers the following factors: * **DevicePlatform**: The test is run on a desktop environment with Chrome 129. * **OperatingSystem**: The test is run on Mac OS X 10.15.7. These factors can affect the performance of the sorting algorithms, as some operating systems or devices may have different performance characteristics. **Library and syntax** The benchmark uses the Ramda library for the `R.sort` function. Ramda is a functional programming library that provides a set of functions for working with arrays, objects, and other data structures. There are no special JavaScript features or syntax used in this benchmark. **Alternatives** Other alternatives for sorting algorithms include: * **Lodash sort**: Lodash is another popular functional programming library that provides a `_.sort` function. * **Browser native sort**: Some browsers, such as Internet Explorer, provide their own custom sorting algorithm. However, these algorithms may not be as performant or efficient as Native JavaScript sort or Ramda sort. * **External sorting libraries**: There are also external libraries available, such as [quick.js](https://github.com/MatthewHalford/quickjs), that provide optimized sorting algorithms for use in web applications. I hope this explanation helps! Let me know if you have any further questions.
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