Benchmark: native slice vs lodash slice

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var test = Array.from({
    length: 100000
}, () => Math.random())

Tests:

native slice
test.slice(0,5000)
lodash slice
_.slice(test, 0, 5000)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
native slice
lodash slice

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 5 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:145.0) Gecko/20100101 Firefox/145.0

Browser/OS: Firefox 145 on Windows

View result in a separate tab

Test name	Executions per second
native slice	105577.1 Ops/sec
lodash slice	125104.7 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

The provided JSON represents a benchmark test between native JavaScript slicing (using `Array.prototype.slice`) and the popular library, Lodash's `slice` function. Here's what's being tested:

**Native Slice**

* The first test case measures the execution time of the native JavaScript slice method (`test.slice(0, 5000)`) on a large array created using `Array.from({ length: 100000 }, () => Math.random())`. This is the built-in way to extract a subset of elements from an array in JavaScript.
* The test prepares the script by defining the `test` variable as an array with 100,000 random elements.

**Lodash Slice**

* The second test case measures the execution time of Lodash's `slice` function (`_.slice(test, 0, 5000)`) on the same large array created earlier.
* The test prepares the HTML by including the Lodash library (version 4.17.5) via a CDN.

Now, let's discuss the options being compared:

**Native Slice vs. Lodash Slice**

Pros of Native Slice:

1. **Performance**: Native JavaScript methods are generally faster since they don't rely on external libraries.
2. **Efficiency**: The native slice method is optimized for performance and doesn't require any additional computations.

Cons of Native Slice:

1. **Browser Support**: Not all browsers support the `Array.prototype.slice` method, especially older versions.
2. **Compatibility**: Some browsers might have different implementation details, leading to potential performance differences.

Pros of Lodash Slice:

1. **Cross-Browser Compatibility**: Lodash's `slice` function is widely supported across various browsers and versions.
2. **Standardization**: Using a library like Lodash ensures that the behavior is standardized, making it easier to maintain and debug code.

Cons of Lodash Slice:

1. **Overhead**: Including an external library adds overhead due to loading time and potential size differences.
2. **Performance Overhead**: The Lodash library may introduce performance overhead compared to native JavaScript methods.

**Other Considerations**

* The test measures the execution time per second (`ExecutionsPerSecond`) for each test case, which gives a better understanding of the relative performance between native slice and Lodash slice.
* The test is run on multiple devices (Desktop) with Firefox 130 as the browser, providing a more comprehensive view of the results.

**Alternatives**

If you need to compare other JavaScript slicing methods or libraries, you might consider:

1. **Array.prototype.slice**: As mentioned earlier, this is the native JavaScript method being compared in the benchmark.
2. **Slice from Es6 Arrays**: If your target browsers support ES6+ features, you can use `slice` from the new Array prototype.
3. **Array.prototype.subarray**: Another native JavaScript method for slicing arrays that might be faster or more efficient than `slice`.
4. **Other libraries**: Other popular libraries like jQuery or Ramda might have their own slice functions that could be compared in a benchmark.

Keep in mind that benchmarking different JavaScript methods and libraries can help identify performance differences, but it's essential to consider the specific use case, target audience, and trade-offs between factors like performance, compatibility, and maintainability.

Related benchmarks:

native slice vs lodash slice (version: 1)

Comparing performance of: native slice vs lodash slice

Created: 5 years ago by: Registered User

Jump to the latest result

native slice

lodash slice

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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