Benchmark: filter vs compact

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/lodash/4.16.0/lodash.min.js"></script>

Script Preparation code:

var ops = [null, 1, 2, 3, 4, 5, null, null, null, 3, 4,5, 6, 34,341,2,2,2,1,212,21212,34,1,3112, null];

Tests:

lodash filter
_.filter(ops, op => !!op)
lodash compact
_.compact(ops)
Native filter
ops.filter(op => !!op)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash filter
lodash compact
Native filter

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 9 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/139.0.0.0 Safari/537.36

Browser/OS: Chrome 139 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lodash filter	5241556.0 Ops/sec
lodash compact	13064680.0 Ops/sec
Native filter	10399775.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark data and explain what's being tested.

**Benchmark Overview**

The benchmark compares the performance of two approaches: using the `_.filter()` method from the Lodash library (a popular utility library for JavaScript) versus a native implementation of the `filter()` function without relying on any external libraries.

**What's being tested?**

1. **_.filter()**: The first test case uses the `_.filter()` method from Lodash to filter out null values from an array (`ops`). This is compared against:
2. **Native filter**: The second test case directly implements a native implementation of the `filter()` function, which iterates through the array and returns only non-null elements.
3. **Compact**: The third test case uses the `_._compact()` method from Lodash to remove consecutive null values from an array.

**Options compared**

The three options being tested are:

* **_.filter() (Lodash)**: This is a convenient way to filter arrays using a simple and efficient implementation.
* **Native filter**: This approach requires manual implementation of the filtering logic, which can be less readable and more error-prone than relying on a well-tested library like Lodash.
* **Compact (Lodash)**: This method removes consecutive null values from an array, which is useful for data processing tasks.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

* **_.filter() (Lodash)**:
	+ Pros: Convenient, efficient, well-tested, and widely supported.
	+ Cons: Adds external dependency on Lodash.
* **Native filter**:
	+ Pros: No external dependencies, allows for manual optimization and control.
	+ Cons: Requires manual implementation of the filtering logic, may be less efficient than using a library.
* **Compact (Lodash)**:
	+ Pros: Efficiently removes consecutive null values, useful for data processing tasks.
	+ Cons: Adds external dependency on Lodash.

**Special JS features or syntax**

None are mentioned in this benchmark. All tests rely on standard JavaScript features and syntax.

**Other alternatives**

If you're interested in exploring other approaches, here are a few alternatives:

* **Array.prototype.filter()**: This is the native method for filtering arrays in JavaScript. While it's not as convenient as using Lodash or writing a custom implementation, it can be a good middle ground.
* **Map or Set filtering**: If you need to filter data structures like Maps or Sets, you may want to consider using their built-in filtering methods (e.g., `filter()` on Maps).

Overall, this benchmark provides a useful comparison of the performance and convenience of using Lodash's filtering methods versus native implementations.

Related benchmarks:

filter vs compact (version: 1)

Comparing performance of: lodash filter vs lodash compact vs Native filter

Created: 9 years ago by: Registered User

Jump to the latest result

lodash filter

lodash compact

Native filter

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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