Benchmark: Lodash vs Native Filters : BabbleTech 01

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.11/lodash.min.js"></script>

Script Preparation code:

var data = Array(1000000).fill({ random: Math.random() });

Tests:

Native filter-map
data.filter(x => { return x.random > 0.5})
Lodash filter-map
_.filter(data, x => { return x.random > 0.5})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native filter-map
Lodash filter-map

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 6 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36

Browser/OS: Chrome 71 on Linux

View result in a separate tab

Test name	Executions per second
Native filter-map	81.9 Ops/sec
Lodash filter-map	85.2 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Overview**

The benchmark, "Lodash vs Native Filters : BabbleTech 01", is designed to compare the performance of two approaches: using native JavaScript filters and using Lodash's filter function. The benchmark aims to determine which approach is faster for filtering a large dataset.

**Script Preparation Code**

The script preparation code creates an array `data` with 1 million elements, each containing a random property `random`. This data will be used as the input for the benchmark.

**Html Preparation Code**

The HTML preparation code includes a reference to Lodash's minified version (4.17.11) via a CDN link. This is necessary because some browsers may not execute native JavaScript functions directly, but instead rely on external libraries like Lodash.

**Individual Test Cases**

There are two test cases:

1. **Native filter-map**: This test case uses the `filter` method with an arrow function to create a new array containing only elements where `x.random > 0.5`.
2. **Lodash filter-map**: This test case uses the `_.filter` function from Lodash, which is equivalent to the native `filter` method but leverages the external library.

**Libraries and Features**

* **Lodash**: A popular JavaScript utility library that provides a variety of functions for tasks like filtering, mapping, reducing, and more. In this benchmark, Lodash's `_.filter` function is used.
* **Native JavaScript filters**: The native JavaScript `filter` method is used in the first test case.

**Pros and Cons**

**Native JavaScript Filters:**
Pros:

* Faster execution, as no external library is required
* More control over the filtering process

Cons:

* May not be compatible with older browsers that don't support this method
* Requires manual implementation of the filter logic

**Lodash Filter Function:**
Pros:

* More concise and readable code for complex filtering tasks
* Compatible with a wide range of browsers, as Lodash is included via a CDN link
* Reduces the need for manual implementation of the filter logic

Cons:

* Slower execution due to the overhead of loading an external library
* Less control over the filtering process, as it relies on Lodash's implementation

**Other Considerations**

* The benchmark only compares the performance of these two approaches and doesn't account for other factors that might affect performance, such as memory usage or caching.
* The dataset size (1 million elements) is relatively small compared to typical real-world datasets. Increasing the dataset size would likely demonstrate a more significant impact on performance.

**Alternatives**

Other libraries like underscore.js, moment.js, or Ramda could potentially be used in place of Lodash for filtering tasks. However, it's essential to note that each library has its own strengths and weaknesses, and the choice ultimately depends on the specific requirements of the project.

Related benchmarks:

Lodash vs Native Filters : BabbleTech 01 (version: 0)

Comparing performance of: Native filter-map vs Lodash filter-map

Created: 6 years ago by: Guest

Jump to the latest result

Native filter-map

Lodash filter-map

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):