Benchmark: Object.fromEntries vs reduce vs Map (from Array)

Script Preparation code:

var data = [...Array(10000).keys()].map((elem) => ({ original: elem, edited: elem + 1 }));

Tests:

Object.fromEntries
Object.fromEntries(data.map((elem) => [elem.original, elem]));
Reduce (reuse object)
data.reduce((acc, elem) => { acc[elem.original] = elem; return acc; }, {});
Reduce (creating temporary objects)
data.reduce((acc, elem) => ({ ...acc, [elem.original]: elem }), {});
Map
data.reduce((acc, elem) => { acc.set(elem.original, elem) return acc; }, new Map());

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Object.fromEntries
Reduce (reuse object)
Reduce (creating temporary objects)
Map

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 provided benchmark and explain what's being tested.

**Benchmark Overview**

The benchmark compares three approaches to create an object from an array of key-value pairs:

1. `Object.fromEntries`: Creates an object from an iterable of key-value pairs.
2. `Reduce` (reuse object): Uses the `reduce` method to accumulate values into an object.
3. `Reduce` (creating temporary objects): Variants of the previous approach, but with a twist.

**Options Compared**

The three options are compared in terms of their performance and execution time.

Pros and Cons:

1. **Object.fromEntries**:
	* Pros: Elegant syntax, efficient creation of objects from iterables.
	* Cons: May incur additional overhead due to object creation.
2. **Reduce (reuse object)**:
	* Pros: Reuses the accumulator object, reducing memory allocation.
	* Cons: Can be slower than `Object.fromEntries` if the initial value is not optimized.
3. **Reduce (creating temporary objects)**:
	* Pros: Creates a new object for each iteration, potentially avoiding accumulation issues.
	* Cons: Inefficient due to unnecessary object creation and garbage collection.

**Library Used**

The benchmark uses two libraries:

1. `Map`: Used in the "Reduce (reuse object)" and "Reduce (creating temporary objects)" variants.
2. `reduce`: Used in all three options.

These libraries are part of the JavaScript standard library and provide efficient data structures and algorithms for manipulating objects.

**Special JS Feature/Syntax**

None mentioned in this benchmark, but it's worth noting that other benchmarks might use special features like:

* `async/await`
* `promises`
* `Generators`
* `Arrow functions`

However, in this specific case, the focus is on the performance comparison of three object creation approaches.

**Other Alternatives**

If you're interested in exploring alternative approaches for creating objects from iterables, consider the following options:

1. **Array.prototype.reduce()**: Similar to the "Reduce" variant, but with a more concise syntax.
2. **Object.assign()**: Creates an object by copying properties from source iterables.
3. **for...in** loop: A traditional approach for iterating over key-value pairs and creating objects.

Keep in mind that each of these alternatives has its own trade-offs in terms of performance, readability, and maintainability.

Latest run results:

Run details: (Test run date: 10 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36

Browser/OS: Chrome 120 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Object.fromEntries	2542.4 Ops/sec
Reduce (reuse object)	16679.3 Ops/sec
Reduce (creating temporary objects)	118.8 Ops/sec
Map	2417.9 Ops/sec

Related benchmarks:

Object.fromEntries vs reduce vs Map (from Array) (version: 0)

Comparing performance of: Object.fromEntries vs Reduce (reuse object) vs Reduce (creating temporary objects) vs Map

Created: 10 months ago by: Guest

Jump to the latest result

Object.fromEntries

Reduce (reuse object)

Reduce (creating temporary objects)

Map

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):