Benchmark: lodash map vs Object.keys map 1234

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/lodash/4.16.0/lodash.min.js"></script>

Script Preparation code:

  var list = [];
  for (var i = 0; i<100; i++) {
  	list.push(i);
  }
  
  var add1 = function(element){return element + 1;};

Tests:

lodash.map
_.map(list, add1)
native
list.map(add1)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash.map
native

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

Let's break down what's being tested in the provided JSON.

**Benchmark Test**

The test is comparing two approaches to iterate over an array and perform a simple operation on each element:

1. Using Lodash's `_.map()` function
2. Using native JavaScript's `map()` function

In both cases, we have a list of numbers generated using a loop (`var list = []; for (var i = 0; i<100; i++) { list.push(i); }`), and an add-one function (`var add1 = function(element){return element + 1;};`). The goal is to measure the performance of each approach.

**Options Compared**

The options being compared are:

* Lodash's `_.map()` function
* Native JavaScript's `map()` function

Both functions will iterate over the array and apply the `add1` function to each element, but they do so in different ways. The main difference is that Lodash's implementation is likely more optimized for performance, as it's a specialized library designed for functional programming.

**Pros and Cons**

* **Lodash's _.map()**: Pros:
	+ Likely optimized for performance
	+ Simplifies code by providing a reusable function
	+ May provide additional functionality or options
* Cons:
	+ Adds an external dependency (the Lodash library)
	+ May introduce overhead due to the library's initialization and setup
* **Native JavaScript's map()**: Pros:
	+ No external dependencies
	+ Lightweight and simple implementation
	+ Built-in language support makes it easy to use
* Cons:
	+ May not be as optimized for performance as Lodash's implementation

**Library: Lodash**

Lodash is a popular JavaScript library that provides a wide range of utility functions, including `map()`. Its purpose is to simplify code and make common tasks easier by providing reusable, high-quality functions. In this benchmark, Lodash's `_.map()` function is used to iterate over the array and apply the `add1` function to each element.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntax being tested in this benchmark. The code is straightforward and uses standard language constructs.

**Alternative Approaches**

Other approaches to iterate over an array and perform a simple operation on each element might include:

* Using `forEach()`: This method executes the provided callback function once for each element in the array.
* Using a traditional loop (`for (var i = 0; i<array.length; i++) { ... }`): This approach is more explicit but can be slower and less concise than the `map()` or `forEach()` methods.

Keep in mind that these alternative approaches might not be directly comparable to Lodash's `_.map()` function or native JavaScript's `map()` function, as they may have different performance characteristics or use cases.

Latest run results:

Run details: (Test run date: 6 years ago)

User agent: Mozilla/5.0 (Linux; Android 8.0.0; SM-G965F Build/R16NW) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.91 Mobile Safari/537.36

Browser/OS: Chrome Mobile 68 on Android 8.0.0

View result in a separate tab

Test name	Executions per second
lodash.map	395585.1 Ops/sec
native	177195.3 Ops/sec

Related benchmarks:

lodash map vs Object.keys map 1234 (version: 0)

lodash map vs Object.keys map

Comparing performance of: lodash.map vs native

Created: 6 years ago by: Guest

Jump to the latest result

lodash.map

native

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):