Benchmark: lodash.keys vs Object.keys

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/lodash/4.16.0/lodash.min.js"></script>

Script Preparation code:

var value = {a: 30310, b: 100303, c: 3040494};

Tests:

lodash.size
_.size(value)
native
Object.keys(value).length

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash.size
native

Fastest: N/A

Slowest: N/A

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/138.0.0.0 Safari/537.36

Browser/OS: Chrome 138 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lodash.size	25684284.0 Ops/sec
native	46129824.0 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The benchmark is designed to compare two approaches:

1. **Lodash's `keys()` function**: A popular JavaScript utility library that provides various functions for working with objects, arrays, and other data structures. In this case, we're using a specific version of Lodash (4.16.0).
2. **Native `Object.keys()` function**: The built-in JavaScript function for getting an array of a given object's own enumerable property names.

**What's being tested?**

The benchmark is testing the performance difference between these two approaches when used to get the size (number of elements) of an object, specifically with a predefined object `value` that contains three properties: `a`, `b`, and `c`.

**Options comparison**

Let's consider the pros and cons of each approach:

1. **Lodash's `keys()` function**:
	* Pros:
		+ Often used in production code due to its popularity and versatility.
		+ Can be more convenient for certain use cases, such as when working with complex objects or arrays.
	* Cons:
		+ Adds an extra dependency (the Lodash library) which may not be desirable for all projects.
		+ May incur a small overhead due to the added function call and object lookup.
2. **Native `Object.keys()` function**:
	* Pros:
		+ Built-in, so no additional dependencies are required.
		+ Typically faster since it doesn't involve an extra function call or library overhead.
	* Cons:
		+ May not be as convenient for certain use cases that require more complex object manipulation.

**Library and its purpose**

Lodash is a popular JavaScript utility library that provides a wide range of functions for working with objects, arrays, and other data structures. In this case, the `keys()` function is used to get an array of property names from an object.

**Special JS feature or syntax (not applicable in this example)**

There are no special JS features or syntax mentioned in this benchmark.

**Other alternatives**

If you want to compare the performance of other approaches, here are a few examples:

1. Using `for...in` loop: This would involve iterating over the object's properties using a traditional `for...in` loop, which can be more verbose but still effective.
2. Using `Array.from()` and `Object.keys()`: This approach involves converting the object's property names to an array using `Array.from()` and then passing it to `Object.keys()`, which can provide a middle ground between Lodash's `keys()` function and native `Object.keys()`.
3. Using a custom implementation: Depending on your specific use case, you might be able to write a custom implementation that avoids the overhead of either Lodash's `keys()` function or native `Object.keys()`. However, this would likely require more code and expertise.

I hope this explanation helps!

Related benchmarks:

lodash.keys vs Object.keys (version: 0)

Comparing performance of: lodash.size vs native

Created: 8 years ago by: Guest

Jump to the latest result

lodash.size

native

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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