Benchmark: trim loadsh vs native trim

HTML Preparation code:

<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.11/lodash.core.js"></script>

Script Preparation code:

var request = "abc a testing";

Tests:

lodash-trim
_.trim(request);
Native trim
request.trim()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash-trim
Native trim

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/121.0.0.0 Safari/537.36

Browser/OS: Chrome 121 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lodash-trim	0.0 Ops/sec
Native trim	25396212.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared, and the pros and cons of each approach.

**Benchmark Overview**

The benchmark compares the execution performance of two approaches: using Lodash (`lodash-trim`) and native JavaScript (`Native trim`). Both tests are designed to measure the time it takes to execute a string trimming operation.

**Options Compared**

Two options are being compared:

1. **Lodash**: A popular JavaScript utility library that provides a wide range of functions for tasks like string manipulation, array manipulation, and more.
2. **Native JavaScript**: The built-in JavaScript engine's native string trimming implementation.

**Pros and Cons**

**Lodash (`lodash-trim`)**

Pros:

* **Ease of use**: Lodash is a well-maintained library with a simple API for performing various tasks, including string manipulation.
* **Community support**: Lodash has an active community and a wide range of documentation resources available.

Cons:

* **Overhead**: Using an external library like Lodash may introduce some overhead due to the additional code execution and memory allocation required.
* **Size**: The Lodash library is larger than the native JavaScript implementation, which could impact performance in certain scenarios.

**Native JavaScript (`Native trim`)**

Pros:

* **Performance**: Native JavaScript implementations are typically optimized for speed and have less overhead compared to external libraries.
* **No additional dependencies**: No additional code needs to be executed or loaded to perform the trimming operation.

Cons:

* **Complexity**: The native JavaScript implementation may be more complex to use, especially for developers unfamiliar with its internal workings.
* **Less intuitive API**: Native JavaScript string manipulation APIs can be less intuitive than those in external libraries like Lodash.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of functions for tasks like string manipulation, array manipulation, and more. In this benchmark, the `_.trim()` function from Lodash is used to trim the input string.

**Special JS Feature/Syntax (None)**

There are no special JavaScript features or syntaxes being tested in this benchmark.

**Other Alternatives**

If you're interested in exploring other alternatives for string trimming, here are a few options:

* **String.prototype.trim()**: This method is built into the native JavaScript engine and can be used to trim strings.
* **Substring()**: You can use `substring()` with start and end indices to extract the trimmed substring from the original string.

Keep in mind that these alternatives may not offer significant performance improvements over Lodash or native JavaScript implementations, but they can provide different trade-offs in terms of complexity and usage.

Related benchmarks:

trim loadsh vs native trim (version: 0)

Comparing performance of: lodash-trim vs Native trim

Created: 6 years ago by: Guest

Jump to the latest result

lodash-trim

Native trim

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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