Benchmark: Lodash clone deep performance

HTML Preparation code:

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

Script Preparation code:

var MyObject = {
  description: 'Creates a deep copy of source, which should be an object or an array.',
  myNumber: 123456789,
  myBoolean: true,
  jayson: {
    stringify: 'JSON.stringify() method converts a JavaScript value to a JSON string....',
    parse: 'JSON.parse() method parses a JSON string...',
    more: {
    	less: {
        	msg: 'Benis'
        }
    }
  },
  penis: 'Benis'
};

Tests:

lodash clone
const clone = _.cloneDeep(MyObject)
Json parse stringify
const clone = JSON.parse(JSON.stringify(MyObject))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash clone
Json parse stringify

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/15.5 Safari/605.1.15

Browser/OS: Safari 15 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lodash clone	349790.5 Ops/sec
Json parse stringify	334347.4 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the benchmarking test cases and explain what's being tested, the pros and cons of each approach, and other considerations.

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark test case. It defines two benchmark definitions:

1. "Lodash clone deep performance"
2. "Json parse stringify"

**Lodash Clone Deep Performance**

This benchmark tests the performance of creating a deep copy of an object using Lodash's `cloneDeep` function.

**Test Preparation Code**
```javascript
var MyObject = {
  description: 'Creates a deep copy of source, which should be an object or an array.',
  myNumber: 123456789,
  myBoolean: true,
  jayson: {
    stringify: 'JSON.stringify() method converts a JavaScript value to a JSON string....',
    parse: 'JSON.parse() method parses a JSON string...',
    more: {
      less: {
        msg: 'Benis'
      }
    }
  },
  penis: 'Benis'
};
```
**Purpose**

The purpose of this benchmark is to measure the performance of creating a deep copy of an object using Lodash's `cloneDeep` function.

**Pros and Cons**

Using Lodash's `cloneDeep` function has several pros:

* It handles complex data structures, such as arrays and objects with nested properties.
* It provides a simple and concise way to create a deep copy of an object.

However, there are also some cons:

* Using a third-party library like Lodash may introduce additional overhead and dependencies.
* The performance benefits of using `cloneDeep` may not be significant for small datasets.

**Alternative Approach**

An alternative approach would be to implement a custom deep cloning function without using a third-party library. This could be done using a recursive function that iterates through the object's properties and creates new copies of each one.

```javascript
function cloneDeep(obj) {
  if (typeof obj !== 'object') return obj;
  const result = Array.isArray(obj) ? [] : {};
  for (const key in obj) {
    result[key] = cloneDeep(obj[key]);
  }
  return result;
}
```
This approach would eliminate the dependency on Lodash, but it may be less efficient and more error-prone.

**Json Parse Stringify**

The second benchmark tests the performance of parsing a JSON string using the `JSON.parse` function.

**Test Preparation Code**
```javascript
const MyObject = {
  description: 'Creates a deep copy of source, which should be an object or an array.',
  myNumber: 123456789,
  myBoolean: true,
  jayson: {
    stringify: 'JSON.stringify() method converts a JavaScript value to a JSON string....',
    parse: 'JSON.parse() method parses a JSON string...',
    more: {
      less: {
        msg: 'Benis'
      }
    }
  },
  penis: 'Benis'
};
```
**Purpose**

The purpose of this benchmark is to measure the performance of parsing a JSON string using the `JSON.parse` function.

**Pros and Cons**

Using `JSON.parse` has several pros:

* It is a widely supported and well-maintained function.
* It provides a simple way to parse JSON strings into JavaScript objects.

However, there are also some cons:

* Using `JSON.parse` may be slower than other parsing methods for large datasets.
* The function can throw errors if the input string is malformed or not valid JSON.

**Alternative Approach**

An alternative approach would be to use a custom parsing function that implements the JSON specification. This could be done using a recursive function that iterates through the JSON token stream and creates new objects based on each token type.

```javascript
function parseJson(jsonStr) {
  const tokens = jsonStr.split(' ');
  const result = {};
  for (const token of tokens) {
    if (token === 'object') {
      // Handle object literal creation
    } else if (token === 'array') {
      // Handle array literal creation
    } else if (token === '"') {
      // Handle string creation
    }
  }
  return result;
}
```
This approach would provide more control over the parsing process, but it may be less efficient and more error-prone.

**Libraries**

Both benchmarks use the Lodash library. Lodash is a popular JavaScript utility library that provides a wide range of functions for tasks such as array manipulation, object cloning, and string manipulation.

In this case, the `cloneDeep` function is used to create a deep copy of the `MyObject` instance.

**Special JS Features or Syntax**

There are no special JavaScript features or syntax used in these benchmarks. The code uses standard JavaScript syntax and constructs.

Related benchmarks:

Lodash clone deep performance (version: 0)

Comparing performance of: lodash clone vs Json parse stringify

Created: 4 years ago by: Guest

Jump to the latest result

lodash clone

Json parse stringify

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):