Benchmark: asdasjid - MeasureThat.net

HTML Preparation code:

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

Script Preparation code:

var max1 = 100000; // 100,000 (100 Thousand)
var max2 = 10000000; // 10,000,000 (10 Million)
var max3 = 100000000; // 100,000,000 (100 Million)

var arr1 = [];
//for (var i = 0; i <= max1; i++) { arr1.push(i); }

var arr2 = [];
for (var i = 0; i <= max2; i++) { arr2.push(i); }

var arr3 = [];
//for (var i = 0; i <= max3; i++) { arr3.push(i); }
var obj = {};

Tests:

Native
arr2.forEach(function(e) { obj[e] = false; });
Lodash.js filter
_.zipObject(arr2);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native
Lodash.js filter

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 break down the benchmark and explain what is being tested.

**Benchmark Overview**

The benchmark measures the performance of two approaches: using JavaScript's native `forEach` loop to iterate over an array, and using the Lodash library's `_zipObject` function to merge two arrays into a single object.

**Test Case 1: Native (JavaScript's forEach)**

* In this test case, a large array (`arr2`) is created with 10 million elements.
* The `forEach` loop iterates over the array and assigns each element to an empty object (`obj`). This creates a new property in the object for each iteration.

**Test Case 2: Lodash.js filter (using _zipObject)**

* In this test case, the same large array (`arr2`) is used.
* The `_zipObject` function from Lodash takes two arrays as input and returns a new object with merged properties. In this case, it merges the elements of `arr2` into an empty object.

**Comparison**

The benchmark tests which approach is faster:

1. Using JavaScript's native `forEach` loop to iterate over the array.
2. Using Lodash.js `_zipObject` function to merge the two arrays.

**Pros and Cons of Each Approach**

* **Native (JavaScript's forEach)**:
	+ Pros: Simple, lightweight, and easy to implement.
	+ Cons: Can be slower due to the overhead of iterating over the array with `forEach`.
* **Lodash.js _zipObject**:
	+ Pros: Faster and more efficient than the native approach, especially for large datasets. Lodash provides optimized functions for common tasks like merging arrays into objects.
	+ Cons: Requires importing an external library (Lodash) and may have a slight overhead due to the additional function call.

**Library: Lodash.js**

Lodash is a popular JavaScript utility library that provides a wide range of functional programming helpers, including array manipulation functions like `_zipObject`. The `_zipObject` function merges two arrays into a single object with merged properties. In this benchmark, it's used to compare the performance of using Lodash against the native `forEach` loop.

**Special JS Feature: No special features are mentioned in this benchmark.**

**Alternatives**

If you're interested in exploring alternative approaches, here are some options:

1. **Using other array methods**: Instead of `forEach`, you could use other array methods like `map()`, `reduce()`, or `for...of` loop.
2. **Using a custom implementation**: You could write your own optimized algorithm for merging arrays into objects.
3. **Testing with different input sizes**: The benchmark only tests with a large dataset (10 million elements). Testing with smaller datasets and varying input sizes can help identify performance characteristics.

Keep in mind that the choice of approach depends on the specific requirements of your project, such as performance, code simplicity, or library dependencies.

Related benchmarks:

asdasjid (version: 0)

Comparing performance of: Native vs Lodash.js filter

Created: 6 years ago by: Guest

Jump to the latest result

Native

Lodash.js filter

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):