Benchmark: Lodash CloneDeep vs Immer Produce with heavy load

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 =  {
    data: {
      data1: {
        data2: 'test',
      },
      data3: Array.from({length: 1000}).map(() => document.createElement('div'))
    }
  };

Tests:

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

Historical Performance Data aggregated from 128 community runs

Desktop Results:

Chrome 109 runs

Produce

693K/s

CloneDeep

2K/s

Fastest: Produce (337.3x faster)

View exact numbers

✓ Produce: 693,109 ops/sec
• CloneDeep: 2,055 ops/sec

Firefox 8 runs

Produce

415K/s

CloneDeep

5K/s

Fastest: Produce (76.3x faster)

View exact numbers

✓ Produce: 414,555 ops/sec
• CloneDeep: 5,437 ops/sec

Safari 5 runs

Produce

769K/s

CloneDeep

8K/s

Fastest: Produce (96.7x faster)

View exact numbers

✓ Produce: 768,734 ops/sec
• CloneDeep: 7,951 ops/sec

Mobile Results:

Safari 6 runs

Produce

612K/s

CloneDeep

6K/s

Fastest: Produce (110.1x faster)

View exact numbers

✓ Produce: 612,034 ops/sec
• CloneDeep: 5,558 ops/sec

Results show median performance across all community submissions. Run this benchmark yourself to verify on your device.

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: 4 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/146.0.0.0 Safari/537.36

Browser/OS: Chrome 146 on Windows

View result in a separate tab

Produce

692K/s

CloneDeep

2K/s

View exact numbers

Test name	Executions per second
✓ Produce	691,593 Ops/sec
CloneDeep	2,114 Ops/sec

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

LLMs can make mistakes. Check important info.

The provided JSON represents a benchmark test case for measuring the performance of two different approaches: Immer's `produce` function and Lodash's `cloneDeep` function.

**What is being tested?**

In this benchmark, we have a complex data structure `state`, which consists of an object `data` with multiple nested objects and arrays. The goal is to update the value of `data.data1.data2` using two different approaches:

1. Immer's `produce` function: This function creates a new copy of the original data structure, allowing us to safely mutate it without affecting the original.
2. Lodash's `cloneDeep` function: This function creates a deep clone of the original data structure, which can be used to create a new independent copy.

**Options being compared**

We are comparing two options:

1. **Immer's produce**: Immer is a library that provides immutable data structures and functions for working with them. `produce` is a specific function that creates a new copy of the original data structure, allowing us to update it without affecting the original.
2. **Lodash's cloneDeep**: Lodash is a utility library that provides various functions for working with data, including cloning and mutating. `cloneDeep` is a specific function that creates a deep clone of the original data structure.

**Pros and Cons**

Here are some pros and cons of each approach:

**Immer's produce**

Pros:

* Immutability ensures thread-safety and prevents unexpected side effects.
* Can be more efficient than cloning, especially for large data structures.

Cons:

* Creates a new copy of the data structure, which can be memory-intensive.
* May not be suitable for very large or complex data structures due to performance overhead.

**Lodash's cloneDeep**

Pros:

* Provides a deep clone of the original data structure, allowing for independent updates.
* Can be more flexible than Immer's produce, as it allows for arbitrary mutations.

Cons:

* Cloning can be memory-intensive and slow for very large data structures.
* May not ensure immutability, leading to unexpected side effects if not used carefully.

**Other considerations**

When using either approach, consider the following:

* Make sure to use `produce` with caution when working with very large or complex data structures, as it can lead to performance issues.
* Use `cloneDeep` with care when updating large data structures, as it can consume a significant amount of memory.

**Library and its purpose**

Immer is a library that provides immutable data structures and functions for working with them. Its primary goal is to help developers write more predictable, reliable, and concurrent code.

Lodash is a utility library that provides various functions for working with data, including cloning, mutating, and transforming. Its primary goal is to provide a comprehensive set of tools for common data-related tasks.

**Special JS feature or syntax**

This benchmark does not use any special JavaScript features or syntax beyond the standard language features provided by the browsers and Node.js environments used to run it.

Lodash CloneDeep vs Immer Produce with heavy load (version: 0)

Comparing performance of: `Produce vs CloneDeep`

Created: 3 years ago by: Guest

Go to the latest result

Produce

CloneDeep

Historical Performance Data aggregated from 128 community runs

Desktop Results:

Chrome 109 runs

Firefox 8 runs

Safari 5 runs

Mobile Results:

Safari 6 runs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Lodash CloneDeep vs Immer Produce with heavy load (version: 0)

Comparing performance of: Produce vs CloneDeep

Created: 3 years ago by: Guest

Go to the latest result

Produce

CloneDeep

Historical Performance Data aggregated from 128 community runs

Desktop Results:

Chrome 109 runs

Firefox 8 runs

Safari 5 runs

Mobile Results:

Safari 6 runs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `Produce vs CloneDeep`