Benchmark: Filter-Map: Lodash vs Nati

HTML Preparation code:

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

Script Preparation code:

var data = [...Array(1000).keys()]

Tests:

Native filter-map
data.filter((e)=>{ e === 100})
Lodash filter-map
_.filter(data, (e)=>{ e === 100})
ori_find
data.find((e)=>{ e === 100})
lodash find
_.find(data, (e)=>{ e === 100})
my_find
function ori_find(array,target){ const i = array.length if(array[i] === target ){ return array[i] } if(array[i] > target ){ ori_find(animals.slice(0,i),target) } if(array[i] < target ){ ori_find(animals.slice(i+1),target) } } ori_find(data,250)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native filter-map
Lodash filter-map
ori_find
lodash find
my_find

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

I'll break down the benchmark and explain what's being tested, compared, and discussed.

**Benchmark Overview**

The benchmark compares four different implementations of finding an element in an array:

1. Native `filter`-map method (without any libraries)
2. Lodash's `_.filter` function
3. A custom implementation called `ori_find`
4. Another custom implementation called `my_find`

**What is tested?**

The benchmark tests the performance and execution time of each implementation on a given input array (`data`) with a specific target value (100). The test cases are:

1. Native `filter`-map method: uses the built-in `Array.prototype.filter()` and `Array.prototype.map()` methods
2. Lodash's `_.filter`: uses the Lodash library to implement the filtering functionality
3. `ori_find`: a custom implementation that manually iterates over the array to find the target value
4. `my_find`: another custom implementation similar to `ori_find`, but with some differences in the logic

**Comparison of options**

Here's a brief comparison of the four approaches:

* **Native filter-map method**: Fast and efficient, as it leverages the optimized implementation of built-in methods. However, this approach assumes that the target value exists in the array.
* **Lodash filter**: Uses an external library to implement filtering functionality. While Lodash is widely used and maintained, it may introduce additional overhead due to the library's initialization and garbage collection.
* `ori_find`: A custom implementation that manually iterates over the array using a simple iterative approach. This approach is straightforward but can be slower than native methods or libraries like Lodash.
* `my_find`: Similar to `ori_find`, but with some differences in logic, which might make it slightly faster or more efficient.

**Pros and Cons**

Here are some pros and cons of each approach:

* Native filter-map method:
	+ Pros: Fast, efficient, and optimized for built-in methods
	+ Cons: Assumes target value exists in the array
* Lodash filter:
	+ Pros: Wide adoption and maintenance by the Lodash community
	+ Cons: Additional overhead due to library initialization and garbage collection
* `ori_find`:
	+ Pros: Simple and straightforward implementation
	+ Cons: Slower than native methods or libraries like Lodash
* `my_find`:
	+ Pros: Might be slightly faster or more efficient due to differences in logic
	+ Cons: Requires careful analysis of the custom implementation to identify performance benefits

**Library**

Lodash is a popular JavaScript utility library that provides various functions for common tasks, such as array manipulation (`_.filter`, `_.map`), string manipulation (`_.trim`, `_._toUpperCase`), and more. The library's implementation uses techniques like caching, memoization, and optimized algorithms to improve performance.

**Special JS features or syntax**

There are no special JavaScript features or syntax mentioned in the benchmark that would require any specific knowledge of ES6+ features, such as arrow functions, classes, or async/await.

**Alternatives**

Other alternatives for implementing filtering functionality include:

* Using a different library, such as Ramda or Immutable.js
* Implementing custom filtering using bitwise operations (e.g., `Array.prototype.findIndex` with bitwise indexing)
* Utilizing streaming algorithms or parallel processing techniques

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.87 Safari/537.36

Browser/OS: Chrome 80 on Mac OS X 10.15.2

View result in a separate tab

Test name	Executions per second
Native filter-map	1061084.4 Ops/sec
Lodash filter-map	62755.1 Ops/sec
ori_find	1080459.4 Ops/sec
lodash find	66455.2 Ops/sec
my_find	7472008.0 Ops/sec

Related benchmarks:

Filter-Map: Lodash vs Nati (version: 0)

Comparing performance of: Native filter-map vs Lodash filter-map vs ori_find vs lodash find vs my_find

Created: 5 years ago by: Guest

Jump to the latest result

Native filter-map

Lodash filter-map

ori_find

lodash find

my_find

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):