Benchmark: flatten deep - MeasureThat.net

HTML Preparation code:

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

Script Preparation code:

flattenArray = arr => {
	return arr.reduce( (result, el) => {
		return result.concat(
			Array.isArray(el) ? flattenArray(el) : el
		)
	}, []);
}

Tests:

lodash
_.flattenDeep([1, [2, [3, [4]], 5]]);
mine
flattenArray([1, [2, [3, [4]], 5]]);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash
mine

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

Measuring JavaScript performance is an essential task, and MeasureThat.net is a great resource for it.

The provided JSON represents a benchmark test case where two different implementations of the `flattenDeep` function are compared: one written in plain JavaScript (`mine`) and another using the popular library Lodash (`_`).

Let's break down what's being tested:

**Plain JavaScript Implementation (Mine)**

In this implementation, we define a recursive function `flattenArray` that takes an array as input. It uses the `concat` method to flatten the array by concatenating each element with its own flattened version if it's an array. If not, the element is simply added to the result.

Pros:

* Easy to understand and implement
* Only relies on built-in JavaScript methods

Cons:

* Can be slower due to string concatenation in a loop (a classic performance anti-pattern)
* May have issues with very large arrays or deep recursion

**Lodash Implementation**

The Lodash library provides a function `flattenDeep` that achieves the same result. This implementation is likely written in C++ and optimized for performance.

Pros:

* Optimized for performance using C++ compilation
* Reduces memory allocation and concatenation overhead

Cons:

* Requires an additional dependency (the Lodash library)
* May not be as easy to understand or implement for those without experience with functional programming or libraries

Other considerations when choosing between these approaches:

* **Performance**: For most use cases, the Lodash implementation will be faster due to its optimized C++ code. However, for very large arrays or deep recursion, the plain JavaScript implementation might be sufficient.
* **Memory usage**: The plain JavaScript implementation may consume more memory due to the recursive function calls and string concatenation. The Lodash implementation is likely more memory-efficient.
* **Learning curve**: If you're new to functional programming or libraries, the plain JavaScript implementation might be easier to grasp. However, if you're already familiar with these concepts, the Lodash implementation may feel more natural.

When using a library like Lodash:

* Make sure to understand its purpose and how it's being used in this specific benchmark.
* Consider whether relying on an external library is acceptable for your use case.

As for special JavaScript features or syntax:

* There are no notable features or syntaxes being used in these benchmarks beyond the standard JavaScript features available since ES5.

Alternatives to MeasureThat.net:

* `jsbench` (formerly `benchmark.js`) provides a similar benchmarking framework with more advanced features.
* `micro-benchmark` is another popular benchmarking library for Node.js and browser environments.
* `perf_hooks` is a built-in Node.js module that provides low-level performance measurement capabilities.

Related benchmarks:

flatten deep (version: 0)

Comparing performance of: lodash vs mine

Created: 6 years ago by: Guest

Jump to the latest result

lodash

mine

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):