Benchmark: spread vs Object.assign for reduce callback

Tests:

with spread operator
const range = (from, to) => { const output = [] for(var x = from; x < to; x++){ output.push(x) } return output } range(0, 10).reduce((acc, num) => { return { ...acc, [num]: num } }, {})
with object assign
const range = (from, to) => { const output = [] for(var x = from; x < to; x++){ output.push(x) } return output } range(0, 10).reduce((acc, num) => { return Object.assign(acc, {[num]: num}) }, {})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
with spread operator
with object assign

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

Let's dive into explaining the provided benchmark.

**Benchmark Purpose**

The goal of this benchmark is to compare the performance of two approaches: using the spread operator (`...`) and `Object.assign()` in JavaScript when reducing an array with an object as the accumulator.

**Options Compared**

There are only two options being compared:

1. **Spread Operator (`...`)**: This approach uses the spread operator to merge the accumulator object with a new key-value pair, where the key is the current element from the array and the value is the same as the current element.
2. **Object.assign()**: This approach uses the `Object.assign()` method to merge the accumulator object with a new key-value pair.

**Pros and Cons**

**Spread Operator (`...`)**:

Pros:

* More concise and readable code
* Less boilerplate code

Cons:

* Performance might be slower due to the creation of a new object for each iteration

**Object.assign()**:

Pros:

* May be faster because it avoids creating a new object on each iteration, as it modifies the existing accumulator object directly.

Cons:

* More verbose and less readable code
* Can lead to errors if not used carefully (e.g., when merging objects with different structures)

**Other Considerations**

* The benchmark does not account for edge cases such as empty accumulators or null/undefined values.
* It only compares the performance of these two approaches in reducing an array, without exploring other use cases where they might differ.

**Library Usage**

In the provided benchmark definition and test cases, there is no explicit library usage. However, it's worth noting that `Object.assign()` is a built-in JavaScript method, while the spread operator (`...`) was introduced in ECMAScript 2015 (ES6).

**Special JS Features/Syntax**

There are no special JS features or syntax used in this benchmark, but it does utilize the `const` keyword for variable declarations and the arrow function syntax.

**Alternative Approaches**

Other approaches to achieve similar results could include:

1. **Using a library like Lodash**: Instead of using the spread operator or `Object.assign()`, you could use a library like Lodash's `merge()` method, which provides a more concise way to merge objects.
2. **Using a custom implementation**: Depending on the specific requirements and performance considerations, you might choose to implement your own merging logic using a custom function or a different data structure.

Overall, this benchmark provides a good starting point for understanding the performance differences between two common approaches in JavaScript when reducing an array with an object as the accumulator.

Latest run results:

Run details: (Test run date: 6 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 YaBrowser/18.9.0.3363 Yowser/2.5 Safari/537.36

Browser/OS: Yandex Browser 18 on Mac OS X 10.13.6

View result in a separate tab

Test name	Executions per second
with spread operator	80670.3 Ops/sec
with object assign	114876.9 Ops/sec

Related benchmarks:

spread vs Object.assign for reduce callback (version: 0)

Comparing performance of: with spread operator vs with object assign

Created: 6 years ago by: Guest

Jump to the latest result

with spread operator

with object assign

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):