Benchmark: asasasasasa - MeasureThat.net

Tests:

for-in
const List = [ { id: '111', Count: 2 }, { id: '222', Count: 2 }, { id: '333', Count: 2 }, { id: '323333', Count: 1 }, { id: '555111', Count: 1 }, { id: '700000', Count: 1 }, { id: '700001', Count: 1 }, { id: '900111', Count: 1 }, { id: '989222', Count: 1 }, { id: '999999', Count: 1 } ]; const target = [{"id":"111","subject":"SAMPLE","comments":10012},{},{"id":"333","subject":"SAMPLE","comments":0},{},{},{},{},{},{},{}]; const xx =[]; for (let i = 0; i < List.length; i+=1){ if('id' in target[i]){ xx.push(Object.assign(target[i],List[i])) } }
object.keys
const List = [ { id: '111', Count: 2 }, { id: '222', Count: 2 }, { id: '333', Count: 2 }, { id: '323333', Count: 1 }, { id: '555111', Count: 1 }, { id: '700000', Count: 1 }, { id: '700001', Count: 1 }, { id: '900111', Count: 1 }, { id: '989222', Count: 1 }, { id: '999999', Count: 1 } ]; const target = [{"id":"111","subject":"SAMPLE","comments":10012},{},{"id":"333","subject":"SAMPLE","comments":0},{},{},{},{},{},{},{}]; const xx =[]; for (let i = 0; i < List.length; i+=1){ if(Object.keys(target[i]).length){ xx.push(Object.assign(target[i],List[i])) } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for-in
object.keys

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

The provided JSON represents two test cases for measuring the performance of JavaScript microbenchmarks on Measurthat.net.

**Overview**

Both test cases use an array `List` and an object `target`. The goal is to iterate through the `List` array and create a new object by merging elements from `List` with existing objects in `target`. However, there are differences in how the iteration is performed.

**Test Case 1: "for-in"**

This test case uses the traditional `for` loop syntax with an index variable `i`, where `i` ranges from 0 to `List.length - 1`. The iteration condition checks if the key `'id'` exists in the current object of `target[i]`. If it does, the object is merged using `Object.assign`.

**Test Case 2: "object.keys"**

This test case uses the `Object.keys()` method to iterate through the properties of each object in `target`. The condition checks if the length of the resulting array from `Object.keys(target[i])` is greater than 0. If it is, the object is merged using `Object.assign`.

**Comparison and Analysis**

Both approaches have their pros and cons:

* **for-in**: This approach uses a traditional loop and can be more predictable in terms of performance, as the iteration is not dependent on the properties of the objects.
	+ Pros: Easy to understand and implement, potential for better performance due to less overhead from dynamic property checks.
	+ Cons: May have slower performance due to the need to check if the key exists in each object, which can lead to additional iterations.
* **object.keys**: This approach uses a more modern and concise syntax to iterate through properties. It's also more flexible, as it doesn't require checking for existing keys explicitly.
	+ Pros: More concise and readable, less overhead from property checks, and potentially faster performance due to fewer iterations.
	+ Cons: May have slower performance if the objects are not sparse (i.e., all properties exist), or if the length of `Object.keys(target[i])` is very large.

**Library Usage**

Neither test case uses an external library explicitly. However, it's worth noting that the use of `Object.assign()` and the fact that the objects being iterated through have keys with specific names (e.g., `'id'`) might be considered edge cases or conventions rather than using a specific library.

**Special JS Features**

There are no special JavaScript features or syntax used in these test cases beyond what's described above.

**Other Alternatives**

If you wanted to improve the performance of these tests, you could consider:

* Using `for...of` loop instead of traditional `for` loops for iteration.
* Utilizing a `Map` data structure for fast property lookups.
* Implementing a more efficient merge function using techniques like object spreading or merging strategies.
* Optimizing the array and object sizes to reduce overhead.

Keep in mind that the performance differences between these approaches will likely be negligible unless you're working with extremely large datasets.

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/88.0.4324.190 Safari/537.36

Browser/OS: Chrome 88 on Windows

View result in a separate tab

Test name	Executions per second
for-in	374168.5 Ops/sec
object.keys	112589.5 Ops/sec

Related benchmarks:

asasasasasa (version: 0)

a

Comparing performance of: for-in vs object.keys

Created: 3 years ago by: Guest

Jump to the latest result

for-in

object.keys

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):