Benchmark: object.assign vs forin

HTML Preparation code:

<script>
  const state1 = {}
  const state2 = {}
  const data = {
    foo: 'foo',
    bar: 'bar',
    baz: 'baz',
    qux: 'qux'
  }
</script>

Tests:

Object.assign
Object.assign(state1, data)
forin
for (const key in data) { state2[key] = data[key] }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Object.assign
forin

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_6) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/14.0.3 Safari/605.1.15

Browser/OS: Safari 14 on Mac OS X 10.15.6

View result in a separate tab

Test name	Executions per second
Object.assign	1378398.0 Ops/sec
forin	525785.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what's being tested.

**What is being tested?**

The benchmark is comparing two approaches to merge data into an existing object:

1. **Object.assign**: A built-in JavaScript method that takes two or more objects as arguments and merges their properties into a new object.
2. **for...in loop**: A traditional way of iterating over the properties of an object using a loop.

**What options are compared?**

In this benchmark, we have two test cases:

* `Object.assign(state1, data)`
* `for (const key in data) { state2[key] = data[key] }`

Both approaches aim to merge the `data` object into the `state1` and `state2` objects. The difference lies in how they achieve this merging.

**Pros and Cons of each approach:**

**Object.assign**

Pros:

* More concise and expressive
* Built-in method, so it's likely to be implemented efficiently by most browsers
* Easy to understand and maintain

Cons:

* Requires two separate object literals (`state1` and `data`)
* Might not work as expected if the source data is not an object (e.g., a JSON string)

**for...in loop**

Pros:

* Works with any data type, not just objects
* Can be more flexible when dealing with complex merge logic

Cons:

* Less concise and less expressive than `Object.assign`
* Requires explicit looping over properties, which can lead to boilerplate code
* Might perform slower due to the overhead of the loop

**Other considerations:**

* In modern JavaScript, you might also consider using methods like `Object.create()` or the spread operator (`{ ... }`) for merging objects.
* The choice between `Object.assign` and a `for...in` loop ultimately depends on the specific requirements of your project and your personal preference.

Now, let's look at some individual test cases:

**Test Case 1: Object.assign**

The benchmark script creates two empty object literals (`state1` and `data`) and then calls `Object.assign()` to merge `data` into `state1`. The resulting object is stored in `state2`.

```javascript
const state1 = {};
const data = { foo: 'foo', bar: 'bar', baz: 'baz' };
Object.assign(state1, data);
```

**Test Case 2: for...in loop**

The benchmark script creates two empty object literals (`state1` and `data`) and then uses a `for...in` loop to iterate over the properties of `data`, assigning each value to the corresponding property in `state1`.

```javascript
const state1 = {};
const data = { foo: 'foo', bar: 'bar', baz: 'baz' };
for (const key in data) {
  state1[key] = data[key];
}
```

**Library/Libraries**

There are no explicit libraries mentioned in the benchmark script. However, if you were to use a library like Lodash or Ramda for merging objects, it would likely be a more concise and efficient solution.

**Special JS feature/Syntax**

There is no special JavaScript feature or syntax used in this benchmark that's not already explained above.

Related benchmarks:

object.assign vs forin (version: 0)

Comparing performance of: Object.assign vs forin

Created: 3 years ago by: Guest

Jump to the latest result

Object.assign

forin

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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