Benchmark: Lodash CloneDeep vs Immer Produce on larger array

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/immer@3.1.3/dist/immer.umd.min.js"></script>
<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

state =  [
    {data1: {data2: 'test'}},
   {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}},
    {data1: {data2: 'test'}}
  ];

Tests:

Produce
const result = immer.produce(state, draft => { draft[5].data1.data2 = 'updated' })
CloneDeep
const result = _.cloneDeep(state); result[5].data1.data2 = 'updated';

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Produce
CloneDeep

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Safari/537.36

Browser/OS: Chrome 136 on Windows

View result in a separate tab

Test name	Executions per second
Produce	153362.0 Ops/sec
CloneDeep	30993.9 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 JSON benchmark definition and explain what's being tested, compared, and their pros and cons.

**Benchmark Definition:**

The benchmark is comparing two functions: `immer.produce` from the Immer library and `_cloneDeep` from Lodash. Both functions aim to create a deep copy of an object (in this case, an array of objects).

**What's being tested?**

* `immer.produce`: This function creates a new copy of the original state by modifying a draft version of it. The purpose is to detect when changes are made to the original state.
* `_cloneDeep`: This function creates a deep clone of the original state, which means creating an entirely new object with identical properties and structure.

**Options being compared:**

1. **Immer's `produce`**: Creates a new copy of the original state by modifying a draft version of it.
2. **Lodash's `_cloneDeep`**: Creates a deep clone of the original state.

**Pros and Cons:**

* **Immer's `produce`**:
	+ Pros:
		- More efficient, as it only modifies the draft copy and not the entire object tree.
		- Can be faster for larger objects due to less overhead.
	+ Cons:
		- May not work correctly if the original state is modified concurrently with the produce operation.
		- Requires a separate draft version of the state, which can add complexity.
* **Lodash's `_cloneDeep`**:
	+ Pros:
		- Guaranteed to create an exact copy of the original state, regardless of concurrent modifications.
		- Simple and straightforward implementation.
	+ Cons:
		- Can be slower than Immer's `produce`, as it needs to recursively clone the entire object tree.

**Other considerations:**

* The benchmark is comparing the performance of these two functions on a large array of objects. This is relevant for use cases where data needs to be cloned or updated frequently.
* The Immer library is designed specifically for working with immutable state, making `produce` an efficient choice for managing state changes.

**Library and syntax:**

* **Immer**: A library for building and managing immutable state. It provides a range of functions for creating, updating, and manipulating state objects.
	+ Purpose: To simplify the management of complex, interconnected data structures while ensuring immutability.
* **Lodash**: A utility library providing functional programming helpers, including cloning functions.
	+ Purpose: To provide a set of reusable functions for common tasks, such as array manipulation and object creation.

In summary, this benchmark compares two approaches to creating deep copies of objects: Immer's `produce` (modifying a draft copy) and Lodash's `_cloneDeep` (creating an exact clone). The choice between these options depends on the specific use case and performance requirements.

Related benchmarks:

Lodash CloneDeep vs Immer Produce on larger array (version: 0)

Comparing performance of: Produce vs CloneDeep

Created: 5 years ago by: Guest

Jump to the latest result

Produce

CloneDeep

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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