Benchmark: Native Object.values().some() vs lodash _.some()

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var value = {a: 30310, b: 100303, c: 3040494, d: null, e: undefined, f: 'aaaa', g: [], i: {i1: 'test', i2: 7}, k: 0, l: ''};

Tests:

_.some()
_.some(value, (v) => v)
Native
Object.values(value).some((v) => v)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.some()
Native

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the benchmark and provide insights into the test cases.

**Benchmark Overview**

The benchmark, created on MeasureThat.net, compares the performance of two approaches: using JavaScript's built-in `Object.values()` and `some()` method versus using the popular utility library Lodash's `_some()` function. The goal is to determine which approach yields better performance in terms of speed and efficiency.

**Test Cases**

There are two test cases:

1. **Native**: This test case uses the native JavaScript implementation, where `Object.values()` returns an array of the object's own enumerable property values, and `some()` checks if any of these values pass a provided test function.
2. **_.some() (Lodash)**: This test case uses Lodash's `_some()` function, which is a wrapper around the native JavaScript implementation.

**Options Compared**

The two options being compared are:

* Native JavaScript implementation (`Object.values().some()`)
* Lodash's `_some()` function

**Pros and Cons of Each Approach**

Native JavaScript Implementation (Object.values().some()):

Pros:

* No external dependencies, making it a pure JavaScript solution.
* Simple and concise code.

Cons:

* May have slower performance due to the overhead of creating an array of object values and then checking each value using `some()`.

Lodash's `_some()` Function:

Pros:

* Often optimized for performance, as Lodash is a popular library with a large user base.
* Can provide better performance than the native implementation, especially for larger datasets.

Cons:

* Introduces an external dependency, which may impact performance or code readability in some cases.
* May have additional overhead due to the wrapper function and other utility functions used by Lodash.

**Library (Lodash)**

Lodash is a popular JavaScript utility library that provides a wide range of functions for tasks such as array manipulation, string manipulation, object manipulation, and more. `_some()` is one of these functions, which checks if at least one element in an array passes a test function.

**Special JS Feature/Syntax (Not Applicable)**

In this benchmark, there are no special JavaScript features or syntax being used that would impact the performance comparison.

**Other Alternatives**

If you're interested in exploring other alternatives for checking if any elements in an array pass a test function, here are some options:

* Using `forEach()` and checking for truthiness: `Array.prototype.forEach.call(array, (element) => { return element; });`
* Using `every()` and negating the result: `!Array.prototype.every.call(array, (element) => { return !element; })`

Keep in mind that these alternatives may have different performance characteristics compared to the native implementation or Lodash's `_some()` function.

I hope this explanation helps!

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.82 Safari/537.36

Browser/OS: Chrome 93 on Linux

View result in a separate tab

Test name	Executions per second
_.some()	4017723.2 Ops/sec
Native	4592780.5 Ops/sec

Related benchmarks:

Native Object.values().some() vs lodash _.some() (version: 0)

Comparing performance of: _.some() vs Native

Created: 2 years ago by: Guest

Jump to the latest result

_.some()

Native

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):