Benchmark: Lodash `sum()` vs `.reduce()`

HTML Preparation code:

<script src='https://cdn.jsdelivr.net/npm/lodash@4.17.10/lodash.min.js'></script>

Script Preparation code:

toSum = (arr) => arr.reduce((prev, curr) => prev + curr, 0);

Tests:

Custom
toSum([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]);
Lodash
_.sum([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Custom
Lodash

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/134.0.0.0 Safari/537.36 OPR/119.0.0.0

Browser/OS: Opera 119 on Windows

View result in a separate tab

Custom

46.2M/s

Lodash

9.0M/s

View exact numbers

Test name	Executions per second
✓ Custom	46,222,504 Ops/sec
Lodash	9,027,102 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 benchmark and explain what's being tested, compared options, pros and cons of each approach, and other considerations.

**Benchmark Overview**

The benchmark is designed to compare the performance of two approaches to calculate the sum of an array: using the `reduce()` method and using a custom implementation. The test also includes another variant that uses the Lodash library's `sum()` function.

**Comparison Options**

1. **Custom Implementation**: This option uses a simple loop to iterate over the array elements and add them up.
2. **Lodash `sum()`**: This option uses the Lodash library's built-in `sum()` function, which is optimized for performance.
3. **Lodash `.reduce()`**: This option uses the Lodash library's `reduce()` function, which is also optimized for performance.

**Pros and Cons of Each Approach**

1. **Custom Implementation**:
	* Pros: No external dependency, easy to understand and implement.
	* Cons: May not be optimized for performance, can be slower than other options.
2. **Lodash `sum()`**:
	* Pros: Optimized for performance, provides a simple and efficient way to calculate the sum.
	* Cons: Requires including an additional library (Lodash), may not be as easy to understand for those without knowledge of Lodash.
3. **Lodash `.reduce()`**:
	* Pros: Provides a flexible and powerful way to calculate the sum, optimized for performance.
	* Cons: Requires including an additional library (Lodash), may require more understanding of Lodash's API.

**Library Used**

The test uses the Lodash library version 4.17.10. Lodash is a popular JavaScript utility library that provides various functions for tasks such as array manipulation, string manipulation, and more.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntax used in this benchmark. The tests only use standard JavaScript functionality.

**Other Alternatives**

If you want to explore alternative approaches, here are a few options:

* Using `Array.prototype.reduce()` without Lodash: This approach is similar to the custom implementation but uses the built-in `reduce()` method.
* Using `Array.prototype.forEach()` and a variable to accumulate the sum: This approach is another way to iterate over an array and calculate the sum.

In conclusion, this benchmark provides a simple and informative comparison of three approaches to calculate the sum of an array: custom implementation, Lodash `sum()`, and Lodash `.reduce()`. The results can help developers choose the most efficient and suitable approach for their specific use cases.

Lodash `sum()` vs `.reduce()` (version: 0)

Comparing performance of: `Custom vs Lodash`

Created: 2 years ago by: Guest

Go to the latest result

Custom

Lodash

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Lodash `sum()` vs `.reduce()` (version: 0)

Comparing performance of: Custom vs Lodash

Created: 2 years ago by: Guest

Go to the latest result

Custom

Lodash

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `Custom vs Lodash`