Benchmark: lodash chain map join vs native map join

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
_.chain(data).map(x => `${x.a}_${x.b}`).join(',').value()
native
data.map(x => `${x.a}_${x.b}`).join(',')

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: 11 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/137.0.0.0 Safari/537.36

Browser/OS: Chrome 137 on Windows

View result in a separate tab

Test name	Executions per second
lodash	17.3 Ops/sec
native	15.3 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases to understand what is being tested.

**What is being tested?**

The website MeasureThat.net provides a platform for users to create and run JavaScript microbenchmarks. In this case, we have two individual test cases: "lodash" and "native". These test cases compare the performance of using Lodash's `chain` method with its `map` function versus using native JavaScript methods.

**Options compared**

The options being compared are:

1. **Lodash's `chain` method**: This method is part of the Lodash library, which allows for functional programming in JavaScript.
2. **Native JavaScript `map` function**: This is a built-in JavaScript function that applies a transformation to each element in an array.

**Pros and cons**

Using Lodash's `chain` method has some pros:

* It provides a more concise and readable way of performing complex operations, especially for those familiar with functional programming.
* It can help avoid bugs caused by incorrect variable scoping or asynchronous execution.

However, there are also some cons:

* Performance overhead due to the addition of extra layers in the call stack.
* Potential memory consumption if the chained methods require creating new arrays or objects.

On the other hand, using native JavaScript `map` function has its own pros and cons:

Pros:

* No performance overhead or additional memory consumption compared to Lodash's `chain` method.
* Built-in functionality means less chance of bugs related to external library usage.

Cons:

* Less concise and potentially more verbose code for complex operations.
* Requires manual handling of scope, asynchronous execution, and potential side effects.

**Library and purpose**

The used library is Lodash.js, a popular utility library for JavaScript. Its primary purpose is to provide functional programming functions, such as `chain`, `map`, `reduce`, and many others, to simplify common tasks and improve code readability.

**Special JS feature or syntax**

In this benchmark, there are no special features or syntax being tested beyond the standard JavaScript language itself. The focus is on comparing performance between using a library (Lodash) and native implementation of array operations.

**Other alternatives**

If you're looking for alternative libraries or methods to improve your code's performance:

* **Underscore.js**: Similar to Lodash, but with fewer features.
* **Ramda**: Another popular functional programming library that might be used instead of Lodash in some cases.
* **ES6 array methods**: Using modern JavaScript language features like `map`, `filter`, and `reduce` directly in your code without any additional libraries.

Keep in mind that benchmarking performance should always consider the specific use case, project requirements, and personal preference when choosing a library or method.

Related benchmarks:

lodash chain map join vs native map join (version: 0)

Comparing performance of: lodash vs native

Created: 6 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):