Benchmark: lodash10003 - MeasureThat.net

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

var peopleArr = [];
var peopLen = 10000000;
for (let i = 0; i < peopLen; i++) {
  var obj = {
    name: 'Alex',
    age: Math.floor(Math.random() * 100),
    gender: Math.floor(Math.random() * 2) === 1 ? 'male' : 'female',
    isProgrammer: Math.floor(Math.random() * 2) === 1
  }

  peopleArr[i] = obj;
}

Tests:

Native
peopleArr.map(item => item);
Lodash
_.map(peopleArr, item => item);

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 provided benchmark definition and test cases.

**Benchmark Definition**

The benchmark is designed to measure the performance of JavaScript arrays, specifically the `map()` function. The benchmark defines two test cases:

1. **Native**: This test case uses only built-in JavaScript features without any external libraries.
2. **Lodash**: This test case uses the popular JavaScript library Lodash.

**Script Preparation Code**

The script preparation code creates a large array of objects (`peopleArr`) with random properties (name, age, gender, and programmer status). The number of elements in the array is set to 10 million. This code is executed before each test case.

**Html Preparation Code**

The HTML preparation code includes a link to the Lodash library, which is loaded using the `script` tag.

**Individual Test Cases**

There are two test cases:

1. **Native**: This test case measures the performance of the built-in `map()` function without any external libraries.
2. **Lodash**: This test case measures the performance of the `_.map()` function from Lodash, which is a wrapper around the built-in `map()` function.

**Pros and Cons**

Here are some pros and cons of each approach:

**Native**

Pros:

* No additional library overhead
* Native JavaScript implementation may be optimized for the specific browser or platform

Cons:

* May not provide the same level of functionality as Lodash
* Can be slower due to the lack of optimization by the compiler

**Lodash**

Pros:

* Provides a higher-level interface that can abstract away the details of the `map()` function
* May offer better performance due to optimizations provided by the Lodash team

Cons:

* Adds an external library dependency
* May introduce overhead due to the creation and management of additional objects (the Lodash wrapper)

**Library Consideration**

Lodash is a popular JavaScript utility library that provides a wide range of functions for common tasks, such as array manipulation, string manipulation, and object iteration. In this case, the `_.map()` function is used to transform the array of objects.

**Special JS Feature or Syntax**

None are mentioned in the benchmark definition.

**Other Alternatives**

If you want to measure the performance of other JavaScript array functions, you could consider using different approaches:

* **ES6 Array.prototype.map()**: This would use the built-in `map()` function from ECMAScript 2015 (ES6) instead of the native implementation.
* **Other libraries**: There are many other JavaScript libraries that provide array manipulation functions, such as Ramda or Underscore.js. You could consider using one of these alternatives to compare with Lodash.

In summary, the benchmark is designed to measure the performance of JavaScript arrays and the `map()` function in two different scenarios: native (built-in) and with an external library (Lodash).

Related benchmarks:

lodash10003 (version: 0)

3

Comparing performance of: Native vs Lodash

Created: 3 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):