Benchmark: Lodash merge/clone vs Objest.assign vs object spread

HTML Preparation code:

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

Script Preparation code:

var o1 = {
 a: {
   b: 1,
   c: 2,
   d: 3,
   j: {
     k: [1,2,3],
     l: [4,5,6]
   },
 },
 e: [1,2,3,4,5,6],
 f: 1,
 g: {
   h: 1,
 }
}

var o2 = {
  x: 'abc',
  y: true,
  z: 'last',
  w: [1,2,3]
}

Tests:

Lodash merge/clone
const a = _.merge(_.clone(o1), o2)
Objest.assign
const a = Object.assign({}, o1, o2)
object spread
const a = { ...o1, ...o2 }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash merge/clone
Objest.assign
object spread

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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 and explain what is tested, compared, and their pros and cons.

**Benchmark Definition**

The benchmark measures the performance of three different approaches to merge or clone objects:

1. **Lodash merge/clone**: Uses the `_.merge` function from Lodash library to merge two objects.
2. **Object.assign**: A built-in JavaScript method that merges properties of one object into another.
3. **Object spread (Destructuring)**: A syntax feature introduced in ECMAScript 2018, where an object is created by spreading the properties of another object.

**Options Compared**

The benchmark compares the performance of these three approaches:

* Lodash merge/clone
* Object.assign
* Object spread

**Pros and Cons of each approach**

1. **Lodash merge/clone**:
	* Pros: Provides a robust and feature-rich merging function.
	* Cons: Requires an additional library (Lodash) to be included, which may not be desirable for smaller projects or those with strict size constraints.
2. **Object.assign**:
	* Pros: Built-in method, no additional library required.
	* Cons: Can be slower than other approaches due to the overhead of property iteration and merging.
3. **Object spread (Destructuring)**:
	* Pros: Syntax is concise and easy to read, efficient in terms of overhead.
	* Cons: Requires modern JavaScript features (ECMAScript 2018) to work.

**Library: Lodash**

Lodash is a popular JavaScript library that provides various utility functions for tasks such as array manipulation, object merging, and more. The `_.merge` function used in the benchmark is part of this library.

**Special JS Feature or Syntax: Object spread (Destructuring)**

Object spread is a syntax feature introduced in ECMAScript 2018, which allows creating new objects by spreading properties from existing objects. It's used in the third test case (`const a = { ...o1, ...o2 }`).

**Other Alternatives**

For merging or cloning objects without using Lodash, alternative approaches could be:

* Using `Object.assign()` with `...` syntax for object spread (as shown in the benchmark).
* Implementing custom merging logic using loops and array properties.
* Utilizing a third-party library like `merge-objects` or `obj-util`.

For more advanced cases, consider using functional programming principles, such as immutability and pure functions.

In summary, the benchmark provides a useful comparison of three approaches to merge or clone objects in JavaScript. Understanding the pros and cons of each approach can help developers choose the best fit for their specific use case, considering factors like performance, maintainability, and compatibility with different versions of JavaScript.

Related benchmarks:

Lodash merge/clone vs Objest.assign vs object spread (version: 0)

Comparing performance of: Lodash merge/clone vs Objest.assign vs object spread

Created: 6 years ago by: Guest

Jump to the latest result

Lodash merge/clone

Objest.assign

object spread

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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