Benchmark: lodash .each vs native foreach v4.17.15

HTML Preparation code:

<script src='https://cdn.jsdelivr.net/npm/lodash@4.17.15/lodash.min.js'></script>

Script Preparation code:

var data = [{a: 10000}, {b: 20000}, {c: 30000}, {d: 40000}, {e: 50000}]

Tests:

Lodash
_.each(data,(value, index) => {console.log(value)})
Native
data.forEach((value, index) => {console.log(value)})

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Native

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's dive into the world of JavaScript microbenchmarks and explore what's being tested in this benchmark.

**What is being tested?**

The provided JSON represents a benchmark that compares the performance of two approaches: Lodash's `_.each` method and the native `forEach` loop (introduced in ECMAScript 2015, also known as ES6) with the V8 engine version 4.17.15.

**Options being compared**

There are two options being compared:

1. **Lodash's _.each**: This is a utility function from the Lodash library that iterates over an array and applies a callback function to each element. It uses a traditional loop-based approach, which can be less efficient than the native `forEach` loop.
2. **Native foreach (V8 engine 4.17.15)**: This is a built-in loop construct in JavaScript that allows iterating over arrays using a more concise syntax. The V8 engine version 4.17.15 is used as the baseline for this benchmark.

**Pros and Cons of each approach**

1. **Lodash's _.each**:
	* Pros:
		+ More familiar and intuitive syntax for developers who are not comfortable with native `forEach` loop.
		+ Can be more readable, especially for complex logic or when working with nested loops.
	* Cons:
		+ Generally slower than the native `forEach` loop due to the overhead of the Lodash library.
2. **Native foreach**:
	* Pros:
		+ More efficient than the Lodash approach, as it avoids the overhead of a library function call.
		+ Can be faster and more scalable for large datasets or performance-critical code paths.
	* Cons:
		+ Requires a basic understanding of native JavaScript constructs and loop syntax.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a set of functions for tasks such as array manipulation, functional programming, and more. The `_.each` function is just one of the many utilities available in the library. In this benchmark, Lodash's _.each is used to iterate over an array and print each element.

**Special JS feature or syntax: Native foreach**

The native `forEach` loop introduced in ECMAScript 2015 (ES6) provides a concise and expressive way to iterate over arrays and objects. It uses the `for...of` loop construct, which is easier to read and write than traditional loops. In this benchmark, the native `forEach` loop is used as the baseline for comparison.

**Other alternatives**

If you're interested in exploring alternative approaches or optimizing your code further, consider the following:

1. **Manual iteration**: If you have a specific use case where performance is critical, you can implement manual iteration using a traditional loop (e.g., `for` loop). This approach requires more code and expertise but can be tailored to your specific requirements.
2. **Custom implementation**: Depending on your project's needs, you might want to create a custom implementation of the `forEach` loop or other utility functions. This could involve writing optimized C++ or JavaScript code that takes advantage of specific hardware features or compiler optimizations.

Keep in mind that these alternatives are typically used for more complex scenarios or when performance-critical code paths require manual optimization.

Related benchmarks:

lodash .each vs native foreach v4.17.15 (version: 0)

Comparing performance of: Lodash vs Native

Created: 5 years ago by: Guest

Jump to the latest result

Lodash

Native

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):