Benchmark: lodash map vs native map

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var data = Array(1000000).fill({ a: 'a', b: 1 });

Tests:

lodash
_.map(data, x => `${x.a}_${x.b}`)
native
data.map(x => `${x.a}_${x.b}`)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash
native

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/26.3.1 Safari/605.1.15

Browser/OS: Safari 26 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lodash	81.1 Ops/sec
native	77.3 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down what's being tested in this benchmark and the pros and cons of each approach.

**What is being tested?**

The benchmark is comparing the performance of two approaches to create a new array with transformed values:

1. Using Lodash (`_.map(data, x => `${x.a}_${x.b}`)`): This uses the `lodash` library to define the `map` function.
2. Without any additional library (`data.map(x => `${x.a}_${x.b}`)`): This is a native JavaScript implementation using the built-in `Array.prototype.map()` method.

**Options being compared**

The two options being compared are:

* Using Lodash for array transformation
* Not using any additional library (native JavaScript implementation)

**Pros and Cons of each approach:**

1. **Using Lodash:**
	* Pros:
		+ Easier to read and write code, especially for complex transformations.
		+ Provides a more robust and maintainable solution.
		+ Can be used across multiple platforms and browsers.
	* Cons:
		+ Adds an extra dependency (the `lodash` library).
		+ May not be optimized for performance in all scenarios.
2. **Native JavaScript implementation:**
	* Pros:
		+ Eliminates the need to include an additional library, reducing page load times.
		+ Can provide better performance optimization since it's native code.
	* Cons:
		+ Requires more expertise and familiarity with JavaScript implementation details.
		+ May be harder to read and maintain, especially for complex transformations.

**Library used:**

In this benchmark, the `lodash` library is being used. Lodash is a popular utility library that provides various functions for working with arrays, objects, and other data structures. In this case, it's being used to define the `map` function that transforms each object in the array into a new string.

**Special JS feature or syntax:**

There doesn't seem to be any special JavaScript features or syntax being tested in this benchmark. The focus is on comparing two approaches to perform an array transformation using either Lodash or native JavaScript implementation.

**Other alternatives:**

If you're looking for alternative libraries to implement the `map` function, some popular options include:

* `Array.prototype.forEach()`: This method iterates over each element in the array and provides a way to execute a callback function for each element.
* `Array.prototype.reduce()`: This method applies a reduction function to each element in the array, accumulating a value from all elements.
* `Underscore.js` or other utility libraries: These libraries provide alternative implementations of various functions, including `map`, that might offer better performance or more concise code.

Keep in mind that using a library like Lodash or Underscore.js can add additional dependencies and potential overhead. In some cases, native JavaScript implementation might be the best choice for optimal performance.

Related benchmarks:

lodash map vs native map (version: 0)

Comparing performance of: lodash vs native

Created: 5 years ago by: Guest

Jump to the latest result

lodash

native

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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