Benchmark: Array.prototype.map vs Lodash map

HTML Preparation code:

<script src="lodash.js"></script>

Script Preparation code:

var array = [...Array(100000).keys()];

Tests:

Array.prototype.map
array.map(n => n*2)
Lodash map
_.map(array,n => n*2)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array.prototype.map
Lodash map

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and understand what is being tested.

**Benchmark Overview**

The benchmark compares the performance of `Array.prototype.map` ( native JavaScript method) with `_map` from the popular utility library Lodash. The goal is to determine which approach provides better performance for mapping an array of numbers by doubling each value.

**Options Compared**

Two options are compared:

1. **Native JavaScript: Array.prototype.map**: This uses the built-in `Array.prototype.map()` method, which iterates over an array and applies a specified function to each element.
2. **Lodash: _.map()**: This uses the Lodash library's `_map()` function, which provides a similar functionality to the native JavaScript `map()` method but may optimize it for better performance.

**Pros and Cons**

**Native JavaScript (Array.prototype.map)**

Pros:

* Widespread support across modern browsers
* Low overhead in terms of code size and complexity
* Familiarity for developers already using JavaScript

Cons:

* May not provide optimal performance due to its native implementation
* Can be slower compared to specialized libraries like Lodash

**Lodash (.map())**

Pros:

* Optimized for better performance, especially in larger datasets
* Often includes additional features and utility methods
* Widespread adoption among developers who use JavaScript extensively

Cons:

* Requires an external library to include, which can add overhead
* May not be suitable for projects with strict code size or complexity constraints

**Other Considerations**

When deciding between these two approaches, consider the following factors:

* Project requirements: If you're working on a project that requires high performance and is targeting large datasets, Lodash might be a better choice. For smaller datasets or projects with low performance requirements, native JavaScript might suffice.
* Code complexity and size: If code size and complexity are important factors in your project, native JavaScript might be a more suitable option.

**Library Overview**

Lodash is a popular utility library for JavaScript that provides various functions to simplify common tasks. The `_map()` function is one of its most widely used features, which allows you to apply a specified function to each element of an array while preserving the original array structure.

**JavaScript Features and Syntax**

This benchmark doesn't use any special JavaScript features or syntax beyond what's required for basic JavaScript programming (e.g., arrow functions, template literals). If it did utilize advanced features like async/await, generators, or Promises, the explanation would focus on those aspects as well. In this case, that's not the case.

**Alternative Benchmarks**

If you're interested in exploring other alternatives to benchmark performance differences between `Array.prototype.map` and Lodash `_map()`, consider these options:

* Using the native JavaScript `forEach()` method instead of `map()`
* Implementing your own custom mapping function
* Testing with different input sizes or dataset distributions (e.g., arrays of objects, numbers)
* Comparing performance across multiple browsers or versions

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36

Browser/OS: Chrome 114 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Array.prototype.map	2233.3 Ops/sec
Lodash map	1557.7 Ops/sec

Related benchmarks:

Array.prototype.map vs Lodash map (version: 0)

Comparing performance of: Array.prototype.map vs Lodash map

Created: 5 years ago by: Guest

Jump to the latest result

Array.prototype.map

Lodash map

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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