Benchmark: Lodash vs. Native

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.15/lodash.min.js'></script>

Script Preparation code:

var data = [];
var data2 = [];
for(let id = 0; id<  100; id++) {
  data.push({id});
  data2.push({id});
}

Tests:

Test lodash
const lodash = _.intersectionBy(data, data2, 'id');
Test native
data.map(q => { var matched = data2.find(x => x.id === q.id); return matched ? { ...q, ...matched } : q; })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Test lodash
Test native

Fastest: N/A

Slowest: N/A

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

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Let's break down the provided JSON and explain what's being tested.

**Benchmark Definition**

The benchmark is designed to compare the performance of Lodash, a popular JavaScript utility library, with native JavaScript functions for performing an intersection-by-id operation on two arrays, `data` and `data2`. The goal is to see which approach is faster.

**Options Compared**

There are two options being compared:

1. **Lodash**: Using the `lodash.intersectionBy` function to perform the intersection-by-id operation.
2. **Native JavaScript**: Writing a custom native JavaScript function to achieve the same result.

**Pros and Cons of Each Approach**

### Lodash

Pros:

* **Convenience**: Lodash provides a convenient way to perform common array operations, making it easy to write efficient code.
* **Reusability**: The `intersectionBy` function is reusable and can be used in other parts of the application.

Cons:

* **Overhead**: Using an external library like Lodash adds overhead due to the need for loading and parsing the library, as well as potential conflicts with other libraries or frameworks.
* **Bloat**: Depending on the size of the dataset, using Lodash might result in unnecessary memory allocation and deallocation, leading to slower performance.

### Native JavaScript

Pros:

* **Performance**: Writing native code can lead to better performance since there are no overheads associated with loading an external library.
* **Control**: Having direct control over the implementation allows for more fine-grained optimization.

Cons:

* **Code Complexity**: Writing efficient native code requires a good understanding of JavaScript internals and can be challenging, especially for complex operations like intersection-by-id.
* **Error Handling**: Without the safety net of Lodash's error handling mechanisms, native code may not handle errors as well.

**Library Used**

In this benchmark, the `lodash` library is used. Lodash is a popular utility library that provides a wide range of functions for working with arrays, objects, and other data structures. The `intersectionBy` function is specifically designed to find the intersection of two arrays based on a common key (in this case, `id`).

**Special JS Feature or Syntax**

The benchmark uses JavaScript's **arrow functions**, which are concise syntax for creating small anonymous functions. In the native test case, an arrow function is used to create a closure that captures the outer scope's variables.

**Other Alternatives**

If you're interested in exploring alternative approaches, here are some options:

* **Underscore.js**: Similar to Lodash, but with fewer features and less overhead.
* **Native implementation using `Set` data structure**: Using native JavaScript's built-in `Set` data structure can provide efficient lookup and intersection operations without the need for a library.
* **Other libraries**: Depending on your specific use case, you might find other libraries (e.g., Moment.js for date-related tasks) that offer similar functionality to Lodash but with different trade-offs.

Related benchmarks:

Lodash vs. Native (version: 0)

Testing lodash vs native function

Comparing performance of: Test lodash vs Test native

Created: 6 years ago by: Guest

Jump to the latest result

Test lodash

Test 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):