Benchmark: lodash merge vs object.assign vs spread with deep values

HTML Preparation code:

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

Tests:

lodash merge
var a = { a: 'oh', b: 'my', deep: {a:'a',b:'b'} }; var b = { c: 'goddess' , deep: {c: 'c', b: 'b2'}}; var c = _.merge(a, b);
object.assign
var a = { a: 'oh', b: 'my', deep: {a:'a',b:'b'} }; var b = { c: 'goddess' , deep: {c: 'c', b: 'b2'}}; var c = Object.assign(a, b, {deep: Object.assign(a.deep, b.deep)});
spread
var a = { a: 'oh', b: 'my', deep: {a:'a',b:'b'} }; var b = { c: 'goddess' , deep: {c: 'c', b: 'b2'}}; var c = { ...a, ...b, deep:{...a.deep, ...b.deep} };

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash merge
object.assign
spread

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

**Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks, comparing different approaches for merging objects with nested properties.

**Benchmark Definition JSON**

The provided benchmark definition JSON consists of three test cases:

1. `lodash merge`: Tests the performance of Lodash's `merge` function.
2. `object.assign`: Tests the performance of the built-in `Object.assign` method.
3. `spread`: Tests the performance of the spread operator (`...`) for merging objects.

**Options Compared**

The three options compared are:

1. **Lodash merge**: Uses the `merge` function from Lodash to merge two objects, including nested properties.
2. **Object.assign**: Uses the built-in `Object.assign` method to merge two objects, including nested properties.
3. **Spread operator**: Uses the spread operator (`...`) to merge two objects, including nested properties.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

1. **Lodash merge**:
	* Pros: Efficiently handles deep object merges with recursion.
	* Cons: Requires Lodash to be included in the scope (adds overhead).
2. **Object.assign**:
	* Pros: Built-in method, efficient for shallow merges.
	* Cons: Can lead to recursive function calls for deep merges, potentially causing performance issues.
3. **Spread operator**:
	* Pros: Simple, efficient, and does not require any additional libraries.
	* Cons: Limited control over merge behavior (e.g., handling nested arrays).

**Library and Purpose**

The `lodash` library is a popular JavaScript utility library that provides a wide range of functions for manipulating data. In this benchmark, Lodash's `merge` function is used to merge objects with nested properties.

**Special JS Feature or Syntax**

There is no special feature or syntax mentioned in the benchmark definition. However, it's worth noting that older browsers may not support the spread operator (`...`) or `Object.assign`.

**Other Alternatives**

If you'd like to explore alternative approaches, here are a few options:

1. **JSON merge**: Uses a custom JSON merge function (not shown in this example) to compare the behavior of different merge libraries.
2. **Iterative merge**: Implements an iterative merge algorithm that uses loops and conditional statements instead of recursion or built-in methods.

These alternatives may offer different trade-offs in terms of performance, complexity, and control over the merge behavior.

Latest run results:

Run details: (Test run date: 4 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36

Browser/OS: Chrome 126 on Windows

View result in a separate tab

Test name	Executions per second
lodash merge	1801719.6 Ops/sec
object.assign	6141901.0 Ops/sec
spread	17041934.0 Ops/sec

Related benchmarks:

lodash merge vs object.assign vs spread with deep values (version: 0)

Comparing performance of: lodash merge vs object.assign vs spread

Created: 3 years ago by: Guest

Jump to the latest result

lodash merge

object.assign

spread

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):