Benchmark: Lodash merge vs mergedeep 1

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.min.js'></script>
<script src='https://unpkg.com/deepmerge@4.3.1/dist/umd.js'></script>

Script Preparation code:

var a = { a: 'oh', b: 'my', c: { a: 'a', b: { c: 'c' } } };
var b = { c: { b: { d: 'a'  }, c: { d: 'd' } } };

Tests:

Lodash.merge
var c = _.merge({}, a, b);
deepmerge
var c = deepmerge({}, a, b);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash.merge
deepmerge

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 benchmark and explain what is being tested.

**Benchmark Definition**

The benchmark is designed to compare the performance of two library functions: `_.merge` from Lodash and `deepmerge`. The test creates two objects, `a` and `b`, with nested structures. Then, it defines two benchmarking scripts:

1. One script uses `_.merge` to merge `a` and `b` into a new object `c`.
2. Another script uses the `deepmerge` library to achieve the same result.

**Options Compared**

The two libraries are being compared in terms of their performance when merging objects with nested structures. The test aims to determine which library is faster, more efficient, or perhaps has better performance characteristics for this specific use case.

**Pros and Cons of Different Approaches:**

1. **Lodash _.merge**: This function merges the source objects into a new object, preserving the structure of both input objects. It uses a recursive approach to handle nested properties.
	* Pros:
		+ Easy to use and understand.
		+ Provides a simple way to merge objects with similar structures.
	* Cons:
		+ May perform unnecessary work when dealing with deeply nested objects.
2. **Deepmerge**: This library is specifically designed for deep object merging, using a more efficient algorithm that avoids the recursive overhead of _.merge.
	* Pros:
		+ Optimized for performance and efficiency, especially with deeply nested objects.
		+ Can handle complex merge scenarios with ease.
	* Cons:
		+ May be less intuitive to use due to its focus on optimization.

**Library: Deepmerge**

Deepmerge is a JavaScript library that provides an efficient way to merge objects with deep structure. It's designed to optimize performance and avoid unnecessary work when merging large objects. The `deepmerge` function takes two or more objects as input and returns a new object containing the merged properties, while preserving the original structure.

**Special JS Feature/Syntax: None**

There are no special JavaScript features or syntaxes used in this benchmark. It's a straightforward comparison of two libraries using standard JavaScript code.

**Alternatives**

If you need to merge objects with deep structures, other alternatives to Lodash _.merge and Deepmerge include:

1. **Merge.js**: A lightweight library for merging objects with deep structures.
2. **Immer**: A state management library that provides a `merge` function for merging objects with immutable data structures.
3. **Object.assign()**: A built-in JavaScript method for merging objects, but it may not handle deeply nested structures efficiently.

Keep in mind that these alternatives might have different performance characteristics or usage scenarios compared to Lodash _.merge and Deepmerge.

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/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36

Browser/OS: Chrome 129 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Lodash.merge	514930.3 Ops/sec
deepmerge	1166416.0 Ops/sec

Related benchmarks:

Lodash merge vs mergedeep 1 (version: 0)

Comparing performance of: Lodash.merge vs deepmerge

Created: one month ago by: Guest

Jump to the latest result

Lodash.merge

deepmerge

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):