Benchmark: EGO Intersection lodash vs underscore vs manual

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/underscore@1.13.1/underscore-min.js"></script>

Script Preparation code:

var underscore = _.noConflict();

var objectArrays = [
  ['bedroom', 'kitchen', 'bathroom', 'living room', 'indoors', 'outdoors', 'city', 'urban', 'villa', 'hotel'],
  ['bed', 'kitchen island', 'bath', 'room', 'city'],
  ['bed', 'bathroom', 'bath', 'room', 'city']
];

Tests:

manual lodash
let shared = []; objectArrays.forEach((array, i) => { if (i === 0) { shared.push(...array); } else { _.intersection(shared, array); } });
manual underscore
let shared = []; objectArrays.forEach((array, i) => { if (i === 0) { shared.push(...array); } else { underscore.intersection(shared, array); } });
Lodash
const arrayLodash = _.intersection(...objectArrays);
Underscore
const arrayUnderscore = underscore.intersection(...objectArrays);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
manual lodash
manual underscore
Lodash
Underscore

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.127 Safari/537.36

Browser/OS: Chrome 100 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
manual lodash	447775.0 Ops/sec
manual underscore	624814.6 Ops/sec
Lodash	866699.6 Ops/sec
Underscore	1333295.5 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks and explore what's being tested on this provided JSON.

**Benchmark Overview**

The benchmark compares the performance of three approaches to find the intersection of two arrays:

1. **Manual**: Implementing the `intersection` operation from scratch without using any libraries.
2. **Lodash**: Using the popular `lodash` library, which provides a robust set of utility functions for JavaScript development.
3. **Underscore**: Using the `underscore` library, which is similar to `lodash` but has some differences in its API.

**Options Compared**

The benchmark compares the performance of each approach on two identical sets of input arrays:

* `objectArrays`: An array of two arrays, each containing a mix of strings and numbers.

The comparison is done using the same test case with different implementations: one for manual implementation, one for Lodash, one for Underscore, and another for manual implementation again (with a slight variation).

**Pros and Cons**

* **Manual**:
	+ Pros: Can be optimized for specific use cases, has no external dependencies.
	+ Cons: Requires more code to implement, may have performance issues if not implemented correctly.
* **Lodash**:
	+ Pros: Robust library with extensive testing, easy to use and integrate.
	+ Cons: Adds an external dependency, may have a higher overhead due to the extra abstraction layer.
* **Underscore**:
	+ Pros: Similar to Lodash but with some differences in its API, still a popular choice.
	+ Cons: Also adds an external dependency, similar to Lodash.

**Library Descriptions**

* **Lodash**: A widely used JavaScript library that provides a comprehensive set of utility functions for tasks like array manipulation, object transformation, and more. It's known for its robust testing and extensive documentation.
* **Underscore**: Another popular JavaScript library that provides a smaller set of functional programming helpers than Lodash. While similar to Lodash, Underscore has some differences in its API and is often preferred by developers who want a lighter weight alternative.

**Special JS Features or Syntax**

There are no special JavaScript features or syntax used in this benchmark. The code only uses standard JavaScript features like arrays, loops, and function calls.

**Other Alternatives**

If you're interested in exploring other approaches to find the intersection of two arrays, here are some alternatives:

* Using `Set` objects: You can convert both arrays to sets and then use the `intersection` method to find the common elements.
* Implementing a custom algorithm: There are several algorithms available that can be used to find the intersection of two arrays, such as the **Cartesian product** or the **Squeeze** algorithm.

I hope this explanation helps you understand what's being tested in this benchmark!

Related benchmarks:

EGO Intersection lodash vs underscore vs manual (version: 0)

Comparing performance of: manual lodash vs manual underscore vs Lodash vs Underscore

Created: 3 years ago by: Registered User

Jump to the latest result

manual lodash

manual underscore

Lodash

Underscore

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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