Benchmark: Lodash's Sum vs Reduce vs For-Loop

HTML Preparation code:

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

Script Preparation code:

window.tabs = Array.from({
    length: 1e7
}, () => Math.floor(Math.random() * 40));

Tests:

lodash sum
const total = _.sum(window.tabs);
javascript reduce
const total = window.tabs.reduce((a,b) => a+b);
javascript for loop
let total = 0; for (const tab of window.tabs) { total += tab; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash sum
javascript reduce
javascript for loop

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, compared, and the pros/cons of each approach.

**Benchmark Overview**

The benchmark compares three approaches to sum up an array of numbers:

1. **Lodash's Sum**: Uses the `_.sum()` method from the Lodash library.
2. **Reduce**: Uses the `reduce()` method native to JavaScript.
3. **For-Loop**: A traditional loop using a `for` statement.

**Library: Lodash**

Lodash is a popular utility library for JavaScript that provides various functions, including mathematical operations like summing arrays. In this benchmark, Lodash's `_.sum()` method is used to calculate the total of an array of random numbers generated by the script preparation code.

The pros of using Lodash in this context are:

* **Convenience**: Lodash provides a simple and readable way to perform common tasks, making the code more concise.
* **Performance**: Lodash's implementation is optimized for performance, which may result in faster execution times.

However, there are also some cons:

* **Dependency**: The benchmark relies on Lodash being included as a script in the HTML file, which can add extra overhead and dependencies.
* **Additional size**: Including Lodash adds to the overall size of the benchmark code, which might be a concern for very small arrays or performance-critical applications.

**Native JavaScript Methods**

The `reduce()` method is a native JavaScript function that applies a reduction operation to an array. In this case, it's used to sum up the array elements by providing an initial value and a callback function that adds each element to the accumulator.

Pros of using `reduce()` in this context:

* **Performance**: As a native method, `reduce()` has less overhead compared to using a library like Lodash.
* **No dependencies**: No additional libraries need to be included or loaded.

However, there are some cons:

* **Code readability**: While the `reduce()` syntax can be concise, it might require more mental effort to understand and maintain, especially for those new to JavaScript.
* **Debugging challenges**: Debugging issues with `reduce()` might be more difficult due to its functional programming nature.

**For-Loop**

The traditional `for` loop is a fundamental construct in many programming languages. In this benchmark, it's used to iterate over the array elements and sum them up manually.

Pros of using a `for` loop:

* **Low-level control**: A `for` loop provides direct access to the array elements and allows for fine-grained control over the iteration process.
* **No dependencies**: No additional libraries need to be included or loaded.

However, there are some cons:

* **Code readability**: While not as concise as Lodash's `_.sum()` method, a `for` loop can be more readable if you're familiar with its syntax and mechanics.
* **Performance overhead**: The manual iteration process using a `for` loop might introduce performance overhead compared to the optimized native methods or library functions.

**Other Considerations**

The benchmark also includes information about the browser, device platform, operating system, and execution frequency per second. This data can help users understand how different factors affect the results of the benchmark.

In terms of alternatives, other options for summing arrays in JavaScript could include:

* Using `Array.prototype.forEach()` with a callback function
* Utilizing `Array.prototype.map()` followed by `Array.prototype.reduce()`
* Leveraging specialized libraries like Math.js or FastJS

However, these alternatives might not be as efficient or readable as the approaches used in this benchmark.

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/120.0.0.0 Safari/537.36

Browser/OS: Chrome 120 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lodash sum	28.9 Ops/sec
javascript reduce	16.7 Ops/sec
javascript for loop	17.4 Ops/sec

Related benchmarks:

Lodash's Sum vs Reduce vs For-Loop (version: 2)

Comparing performance of: lodash sum vs javascript reduce vs javascript for loop

Created: 10 months ago by: Registered User

Jump to the latest result

lodash sum

javascript reduce

javascript for loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):