Benchmark: Object.assign vs spread vs 1 dimensional loop

Tests:

Object.assign
var params = { b:"hello", c: true, d:7 }; var other = Object.assign({ a: 2 }, params);
spread operator
var params = { b:"hello", c: true, d:7 }; var other = { a: 2, ...params };
1 Dimensional loop
var params = { b:"hello", c: true, d:7 }; var other = {} for(var prop in params){ other[prop] = params[prop] }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Object.assign
spread operator
1 Dimensional loop

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 dive into the explanation of the provided benchmark.

**Benchmark Overview**

The benchmark compares three approaches to merge an object with existing properties: `Object.assign()`, spread operator (`...`), and a 1-dimensional loop. The benchmark aims to measure which approach is faster, more efficient, or has better performance in modern JavaScript engines.

**Options Compared**

1. **Object.assign()**: This method takes two objects as arguments and merges the second object into the first one, overwriting existing properties. It's a built-in JavaScript method that has been available since ECMAScript 5 (2011).
2. **Spread Operator (`...`)**: Introduced in ECMAScript 2018 (ES8), this operator allows you to merge an object with existing properties using the syntax `{ ...obj }`. This approach is more concise and readable but might incur a slight performance overhead due to its novelty.
3. **1-Dimensional Loop**: This approach uses a traditional loop to iterate over the properties of the second object and assigns each property value to the corresponding key in the first object.

**Pros and Cons**

* **Object.assign()**:
	+ Pros: Fast, widely supported, and well-optimized by modern JavaScript engines.
	+ Cons: Can be less readable due to its method call syntax.
* **Spread Operator (`...`)**:
	+ Pros: Concise, readable, and easy to understand.
	+ Cons: Might incur a small performance overhead due to its novelty.
* **1-Dimensional Loop**:
	+ Pros: Allows for fine-grained control over the merging process.
	+ Cons: Can be more verbose and error-prone due to manual property iteration.

**Library Usage**

None of these approaches rely on any external libraries. However, if we consider the spread operator's implementation in modern JavaScript engines, it might utilize some underlying library or optimized functions that are not explicitly exposed through the `...` syntax.

**Special JS Features/Syntax**

The benchmark uses a special ES8 feature (the spread operator) and assumes that the JavaScript engine supports it. If the target environment doesn't support this feature, the benchmark will fail to execute properly.

**Alternative Approaches**

Other approaches to merge objects include:

* Using the `lodash.merge()` function from the Lodash library
* Utilizing a custom implementation with object iteration and property assignment
* Leveraging a library like Immutable.js for immutable data structures

These alternative approaches might offer better performance, concurrency, or other benefits but are often more complex and less readable than the three options compared in this benchmark.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.77 Safari/537.36

Browser/OS: Chrome 91 on Mac OS X 10.14.1

View result in a separate tab

Test name	Executions per second
Object.assign	2847415.8 Ops/sec
spread operator	8784739.0 Ops/sec
1 Dimensional loop	8577439.0 Ops/sec

Related benchmarks:

Object.assign vs spread vs 1 dimensional loop (version: 0)

Comparing performance of: Object.assign vs spread operator vs 1 Dimensional loop

Created: 5 years ago by: Guest

Jump to the latest result

Object.assign

spread operator

1 Dimensional loop

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):