Benchmark: native slice vs lodash slice 1M

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: 1000000
}, () => Math.random())

Tests:

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

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
native
lodash

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):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks and explore what's tested on MeasureThat.net.

**Benchmark Definition JSON**

The provided JSON represents a benchmark definition for two test cases: `native` and `lodash`. The `Name`, `Description`, `Script Preparation Code`, and `Html Preparation Code` sections provide information about the benchmark.

*   **Script Preparation Code**: This code creates an array of 1 million random numbers, which is used as input for both test cases.
*   **Html Preparation Code**: This code includes a reference to the Lodash library (version 4.17.5) in the HTML header, making it available for use in the benchmark.

**Individual Test Cases**

The two test cases are:

1.  `native`: Tests the native JavaScript `slice()` method.
2.  `lodash`: Tests the `_.slice()` method from Lodash.

**Options Compared**

In this benchmark, two options are compared:

*   **Native Slice**: Uses the built-in JavaScript `slice()` method to extract a subset of the array.
*   **Lodash Slice**: Utilizes the `_` alias (short for underscore) and the `_.slice()` method from Lodash to achieve the same result.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

### Native Slice

Pros:

*   **Lightweight**: The native JavaScript `slice()` method is an optimized implementation that's typically very fast.
*   **No Dependencies**: This solution doesn't require any additional libraries or dependencies.

Cons:

*   **Browser Support**: The performance of the native slice might vary across browsers, depending on their engine and version.
*   **Error Handling**: Without explicit handling, native slices can be brittle if errors occur during execution.

### Lodash Slice

Pros:

*   **Reliable Results**: By using a well-maintained library like Lodash, developers can expect consistent results across different environments.
*   **Robust Error Handling**: Lodash provides robust error handling and logging capabilities to improve overall reliability.

Cons:

*   **Additional Dependencies**: This solution requires an additional dependency (Lodash) to be included in the benchmark.
*   **Overhead**: Including another library might introduce overhead due to loading time or memory usage.

**Special JavaScript Features/Syntax**

This benchmark doesn't explicitly test any special JavaScript features or syntax. However, it does demonstrate the use of arrays and slicing methods, which are fundamental concepts in JavaScript programming.

**Alternatives**

If you're looking for alternatives to MeasureThat.net, consider the following:

*   **jsperf**: A popular benchmarking platform specifically designed for testing JavaScript performance.
*   **Benchmark.js**: An open-source library that provides a simple way to write and run benchmarks in Node.js.
*   **Benchmarks.io**: A cloud-based benchmarking platform that supports multiple programming languages, including JavaScript.

Keep in mind that each of these alternatives might have their own strengths and weaknesses, so it's essential to evaluate them based on your specific needs and requirements.

Related benchmarks:

native slice vs lodash slice 1M (version: 0)

Comparing performance of: native vs lodash

Created: 5 years ago by: Guest

Jump to the latest result

native

lodash

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):