Benchmark: JavaScript spread operator vs Object.assign performance (larger)

Tests:

Using the spread operator
const firstObject = { sampleData: 'Hello world', someMoreData: 'gooby pls' } const secondObject = { moreData: 'foo bar', evenMoreData: 'ok' } const finalObject = { ...firstObject, ...secondObject };
Using Object.assign
const firstObject = { sampleData: 'Hello world', someMoreData: 'gooby pls' } const secondObject = { moreData: 'foo bar', evenMoreData: 'ok' } const finalObject = Object.assign(firstObject, secondObject);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Using the spread operator
Using Object.assign

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark and explain what's being tested, compared, and their pros/cons.

**Benchmark Overview**

The benchmark compares two ways to merge objects in JavaScript: using the spread operator (`...`) and `Object.assign`. The test case uses two example objects: `firstObject` and `secondObject`, which are then merged into a single object `finalObject`.

**Options Compared**

1. **Spread Operator (`...`)**:
	* This method was introduced in ECMAScript 2018 (ES2018) as a shorthand for creating a new object with spreadable properties from an existing object.
	* It uses the syntax `{ ...existingObject, ...newObject }`, where `existingObject` and `newObject` are objects that may contain nested objects.
2. **Object.assign()**:
	* This method is used to create a shallow copy of an object by merging one or more source objects into a target object.
	* It uses the syntax `targetObject = Object.assign(targetObject, sourceObject);`, where `targetObject` and `sourceObject` are objects that may contain nested objects.

**Pros/Cons**

1. **Spread Operator (`...`)**:
	* Pros:
		+ More concise and readable code
		+ Works with nested objects without requiring explicit merging
		+ Can be faster, as it avoids the overhead of function calls
	* Cons:
		+ May have performance issues due to the creation of a new object
		+ Not supported in older browsers or environments (pre-ES2018)
2. **Object.assign()**:
	* Pros:
		+ Widely supported across browsers and environments (since ES5)
		+ Allows for shallow merging, which can be useful for specific use cases
	* Cons:
		+ More verbose code compared to the spread operator
		+ May have performance issues due to function call overhead

**Library/Functionality Used**

In this benchmark, `Object.assign()` is used as a library function to merge objects. `Object.assign()` is a built-in JavaScript method that has been part of the language since ES5.

**Special JS Feature/Syntax**

There are no special JS features or syntaxes mentioned in the provided benchmark code.

**Alternatives**

Other alternatives for merging objects in JavaScript include:

1. **Array.prototype.reduce()**: This method can be used to merge objects by creating a new object and iterating over the properties of one of the source objects.
2. **Object.assign() with spread operator**: Some modern browsers and environments support using `Object.assign()` with spread operators, which allows for more concise merging: `const finalObject = Object.assign({}, firstObject, secondObject);`
3. **Library functions like Lodash's _merge()**: Libraries like Lodash provide optimized implementations of object merging, which can be useful in performance-critical applications.

Overall, the choice between using the spread operator and `Object.assign()` depends on the specific requirements of your use case, such as performance considerations or code readability.

Related benchmarks:

JavaScript spread operator vs Object.assign performance (larger) (version: 0)

Comparing performance of: Using the spread operator vs Using Object.assign

Created: 7 years ago by: Guest

Jump to the latest result

Using the spread operator

Using Object.assign

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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