Benchmark: for...in vs _.values().map

HTML Preparation code:

<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.core.js"></script>

Script Preparation code:

function generateObject(objectSize) {
    let obj = {};
    for (let i = 0; i < objectSize; i++) {
        obj['key' + i] = 'val' + i;
    }
    return obj;
}

Tests:

for...in
const obj = generateObject(100000) const arr = [] let flag = true for (const f in obj) { if (flag) { arr.push(obj[f]) } }
_.values.map
const obj = generateObject(100000) let flag = true _.values(obj).filter(v => flag ? v : null)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for...in
_.values.map

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's dive into the explanation of the provided benchmark.

**What is being tested?**

The benchmark tests the performance difference between two approaches for iterating over an object:

1. `for...in`: This is a traditional loop that uses the `in` operator to iterate over an object's own enumerable properties.
2. `.values()` followed by `.map()`: This approach uses the Lodash library (`_`) to transform an object into an array using the `.values()` method, which returns a map of an object's values, and then filters out the elements based on a condition.

**Options compared**

The two options being tested are:

* `for...in`
* `.values().map()`

These two approaches have different performance characteristics due to the way they handle iteration over objects:

* `for...in`:
	+ Pros: Simple, intuitive syntax; can be used with any type of object.
	+ Cons: Can iterate over inherited properties (if present), which might not be desirable in all cases. Additionally, some older browsers may have issues with this syntax due to security restrictions.
* `.values().map()`: This approach transforms an object into an array and then iterates over it using the `map()` function.

This transformation can introduce additional overhead, such as:

+ Object creation: Converting the object into an array requires creating a new data structure, which can be slower than native iteration.
	+ Memory allocation: The resulting array needs to allocate memory for each element, which can lead to higher memory usage compared to traditional `for...in` iteration.

**Pros and Cons**

The choice between these two approaches depends on the specific use case:

* Use `.values().map()` when:
	+ You need to iterate over an object's values and apply a transformation.
	+ You're working with modern browsers that support Lodash and don't have security restrictions.
* Use `for...in` when:
	+ You only need to iterate over the object's own enumerable properties, without applying any transformations.
	+ You want to minimize memory allocation and object creation.

**Library usage**

The benchmark uses the Lodash library (`_`) for the `.values().map()` approach. Lodash is a popular utility library that provides various functions for working with JavaScript data structures. The `.values()` method returns an iterator over an object's values, which can then be transformed using other methods, such as `filter()`. In this case, the `filter()` method is used to remove elements based on a condition (`flag ? v : null`).

**Special JS feature/syntax**

There are no special JavaScript features or syntaxes mentioned in this benchmark. The focus is on comparing two iteration approaches.

In summary, the benchmark tests the performance difference between traditional `for...in` iteration and using Lodash to transform an object into an array and then iterating over it with `.map()`.

Related benchmarks:

for...in vs _.values().map (version: 0)

Comparing performance of: for...in vs _.values.map

Created: 7 years ago by: Registered User

Jump to the latest result

for...in

_.values.map

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):