Benchmark: Lodash vs Ramda vs Native fromPairs

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.28.0/ramda.min.js"></script>
<script src='//cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.min.js'></script>

Script Preparation code:

var a = [['a', 1], ['b', 2], ['c', 3]];

Tests:

Ramda
var b = R.fromPairs(a);
Lodash
var b = _.fromPairs(a);
Native
var b = Object.fromEntries(a);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
Lodash
Native

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

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Let's dive into the details of what is tested on MeasureThat.net.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks, comparing different approaches for various tasks. The benchmark provided in this example tests three approaches: Ramda, Lodash, and Native (using the built-in `Object.fromEntries` method).

**Test Cases**

The test cases are defined in the "Individual Test Cases" section of the benchmark definition:

1. **Ramda**: `var b = R.fromPairs(a);`
	* This test case uses the Ramda library, a functional programming library for JavaScript.
	* The purpose of this library is to provide a set of immutable data structures and operations that can be used to manipulate and transform data in a predictable way.
2. **Lodash**: `var b = _.fromPairs(a);`
	* This test case uses the Lodash library, a utility library for JavaScript that provides a wide range of functions for tasks such as array manipulation, string manipulation, and more.
3. **Native (Object.fromEntries)**: `var b = Object.fromEntries(a);`
	* This test case uses the built-in `Object.fromEntries` method, which is a part of the ECMAScript standard since ECMAScript 2017.

**Comparison**

The benchmark compares the performance of these three approaches:

1. Ramda's `fromPairs` function
2. Lodash's `fromPairs` function (although it's worth noting that this function has been deprecated in recent versions of Lodash and replaced with `fromEntries`)
3. The built-in `Object.fromEntries` method

**Pros and Cons**

Here are some general pros and cons for each approach:

1. **Ramda**: Pros - provides a predictable and immutable way to work with data, can be used for more complex transformations. Cons - has a learning curve due to its functional programming style.
2. **Lodash**: Pros - widely adopted and well-documented, provides a wide range of utility functions. Cons - has become bloated and verbose in recent versions, can lead to performance issues if not used judiciously.
3. **Native (Object.fromEntries)**: Pros - built-in method, highly optimized for performance. Cons - requires support for ECMAScript 2017 or later.

**Other Considerations**

When choosing an approach, consider the following:

* Do you need a predictable and immutable way to work with data? Ramda might be a good choice.
* Are you looking for a utility library that provides a wide range of functions? Lodash might be a good choice... but only if you're willing to deal with its potential performance issues.
* Do you want to use a built-in method that is highly optimized for performance? Object.fromEntries is a good choice.

**Alternatives**

If you don't like the results from this benchmark, or if none of these approaches work for your specific use case, there are other alternatives:

* Other functional programming libraries such as Immutable.js or FSA.
* Other utility libraries such as Looptest or Fastify.
* Custom implementation using vanilla JavaScript.

Keep in mind that each approach has its trade-offs and considerations. It's essential to evaluate the specific requirements of your project and choose the best fit for your needs.

Related benchmarks:

Lodash vs Ramda vs Native fromPairs (version: 1)

Comparing performance of: Ramda vs Lodash vs Native

Created: 4 years ago by: Registered User

Jump to the latest result

Ramda

Lodash

Native

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):