Benchmark: Object.assign vs. JSON String/Parse vs deepclone

Tests:

deepclone
function deepClone(obj) { if (obj === null || typeof obj !== 'object') { return obj; } const clone = Array.isArray(obj) ? [] : {}; for (let key in obj) { if (obj.hasOwnProperty(key)) { clone[key] = deepClone(obj[key]); } } return clone; } var n = {foo: 'bar', hello: [{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'}]}; while (n.length < 1000) { n = deepClone(n); }
JSON Parse
var n = {foo: 'bar', hello: [{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'}]}; while(n.length < 1000) { n = JSON.parse(JSON.stringify(n)) }
Object.assign
var n = {foo: 'bar', hello: [{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'},{hello: 'world', foo: 'bar'}]}; while(n.length < 1000) { n = Object.assign({}, n); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
deepclone
JSON Parse
Object.assign

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 7 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36 Edg/143.0.0.0

Browser/OS: Chrome 143 on Windows

View result in a separate tab

Object.assign

97.9M/s

JSON Parse

64.6M/s

deepclone

38.5M/s

View exact numbers

Test name	Executions per second
✓ Object.assign	97,911,848 Ops/sec
JSON Parse	64,580,096 Ops/sec
deepclone	38,459,496 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks and explore what's being tested in this benchmark.

**Benchmark Definition**

The test is designed to compare three approaches for creating a new object reference:

1. `Object.assign()`
2. JSON string parsing
3. Deep cloning using a custom function (`deepClone()`)

The benchmark aims to measure which approach creates the most efficient and scalable way to create a large number of objects.

**Options being compared**

The options being compared are:

* `Object.assign()`: A method that creates a new object by copying properties from an existing object.
* JSON string parsing: This involves creating a new object from a JSON string.
* Deep cloning using a custom function (`deepClone()`): A recursive function that creates a deep copy of an object.

**Pros and Cons**

Here's a brief overview of each approach:

1. `Object.assign()`:
	* Pros: Fast, widely supported, and easy to use.
	* Cons: Creates a shallow copy of the original object, which may not be suitable for complex data structures like arrays or objects with nested properties.
2. JSON string parsing:
	* Pros: Can handle complex data structures like arrays and objects with nested properties.
	* Cons: Slower than `Object.assign()` due to the overhead of parsing the JSON string.
3. Deep cloning using a custom function (`deepClone()`):
	* Pros: Creates a deep copy of the original object, which is suitable for complex data structures.
	* Cons: Slow and may not be optimized for performance.

**Library usage**

The `JSON.parse()` function uses the built-in `JSON` library in JavaScript. This library provides methods for parsing JSON data from strings to JavaScript objects.

**Special JS feature or syntax**

There are no special JS features or syntaxes used in this benchmark that would require additional explanation.

**Other alternatives**

If you're looking for alternative approaches, consider:

1. Using the `JSON.parse()` method with a custom parser to handle complex data structures.
2. Implementing a custom deep cloning algorithm using recursive function calls.
3. Using a library like Lodash or Ramda to provide a deep clone function.

However, keep in mind that these alternatives may introduce additional overhead and complexity compared to the original benchmark.

**Benchmark result interpretation**

The latest benchmark results show that `Object.assign()` is the fastest approach, followed closely by JSON string parsing and then deep cloning using the custom `deepClone()` function. This suggests that for this specific use case, `Object.assign()` is the most efficient way to create a new object reference.

Object.assign vs. JSON String/Parse vs deepclone (version: 0)

Creating a "new" object reference every time

Comparing performance of: `deepclone vs JSON Parse vs Object.assign`

Created: 2 years ago by: Guest

Go to the latest result

deepclone

JSON Parse

Object.assign

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Object.assign vs. JSON String/Parse vs deepclone (version: 0)

Creating a "new" object reference every time

Comparing performance of: deepclone vs JSON Parse vs Object.assign

Created: 2 years ago by: Guest

Go to the latest result

deepclone

JSON Parse

Object.assign

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: `deepclone vs JSON Parse vs Object.assign`