Benchmark: Lodash.js vs Native (filter)

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

var max1 = 100000; // 100,000 (100 Thousand)
var max2 = 10000000; // 10,000,000 (10 Million)
var max3 = 100000000; // 100,000,000 (100 Million)

var arr1 = [];
//for (var i = 0; i <= max1; i++) { arr1.push(i); }

var arr2 = [];
for (var i = 0; i <= max2; i++) { arr2.push(i); }

var arr3 = [];
//for (var i = 0; i <= max3; i++) { arr3.push(i); }

Tests:

Native
arr2.filter(function (element) { return element === 900; });
Lodash.js filter
_.filter(arr2, function (element) { return element === 900; });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native
Lodash.js filter

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

I'll break down the provided JSON benchmark definition and test cases to explain what's being tested, compared, and its pros/cons.

**Benchmark Definition**

The benchmark defines two tests: one native (JavaScript) and another using Lodash.js library. Both tests use the `filter()` method on an array of numbers generated by pushing values from 0 to a large number (100k, 10M, or 100M).

**Native Filter Test**

* The test creates three arrays (`arr1`, `arr2`, `arr3`) and pushes numbers from 0 to `max1`, `max2`, and `max3` respectively.
* It then uses the native JavaScript `filter()` method on each array to find a specific element (900) using an anonymous function as the callback.

**Lodash.js Filter Test**

* The test imports Lodash.js library via HTML script tag.
* It creates two arrays (`arr2`) and pushes numbers from 0 to `max2` and `max3`.
* It then uses the `_filter()` function from Lodash.js on each array, passing in `arr2` or `arr3`, and an anonymous function as the callback to find a specific element (900).

**Comparison**

The two tests are compared to determine which one is faster. The results show that the native JavaScript `filter()` method outperforms Lodash.js `_filter()` function.

**Pros/Cons of Different Approaches**

Native JavaScript `filter()`:

* Pros:
	+ No external library dependency.
	+ Can be optimized by browsers or JavaScript engines for native execution.
* Cons:
	+ May require more CPU cycles and memory due to the overhead of the `filter()` method implementation.
	+ Requires manual handling of edge cases, like null or undefined values.

Lodash.js `_filter()`:

* Pros:
	+ Provides a standardized and maintainable API for filtering arrays.
	+ Can be optimized by Lodash.js developers for performance.
* Cons:
	+ Requires an external library dependency, which may add overhead.
	+ May not provide the best native JavaScript execution performance due to the abstraction layer.

**Other Considerations**

* Data size: The benchmark uses large arrays with millions of elements, which can affect performance. Other benchmarks might use smaller datasets or different types of data structures (e.g., linked lists).
* Browser/JS engine variations: Different browsers and JavaScript engines may optimize `filter()` method differently, affecting the results.
* Lodash.js version: The benchmark uses an older version of Lodash.js (4.17.4). newer versions might optimize `_filter()` for better performance.

**Alternatives**

Other alternatives to native JavaScript `filter()` or Lodash.js `_filter()` include:

* Vanilla Node.js `filter()` method
* Other external library functions like `Array.prototype.filter()` from other libraries (e.g., jQuery, Moment.js)
* Custom implementation using a different data structure or algorithm.

Related benchmarks:

Lodash.js vs Native (filter) (version: 0)

Comparing performance of: Native vs Lodash.js filter

Created: 5 years ago by: Guest

Jump to the latest result

Native

Lodash.js filter

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):