Benchmark: Filter Comparison

Script Preparation code:

function isBigEnough(value) {
  return value >= 10
}

Tests:

lodash
_.filter([12, 5, 8, 130, 44], isBigEnough)
plain js
[12, 5, 8, 130, 44].filter(isBigEnough)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash
plain js

Fastest: N/A

Slowest: N/A

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

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Let's break down the provided benchmark definition and options being compared.

**Benchmark Definition**

The benchmark is defined by two test cases:

1. `_.filter([12, 5, 8, 130, 44], isBigEnough)`
2. `[12, 5, 8, 130, 44].filter(isBigEnough)`

Here, we're testing the performance of two approaches: using a library (Lodash) and using plain JavaScript.

**Options being compared**

We have two options:

1. **Lodash's `_.filter()` method**: Lodash is a utility library for JavaScript that provides a set of functions to make common tasks easier. In this case, we're using the `filter()` function from Lodash to apply the `isBigEnough` callback function to an array.
2. **Plain JavaScript's `Array.prototype.filter()` method**: This is the native JavaScript method for filtering arrays.

**Pros and cons of each approach**

**Lodash's `_filter()` method:**

Pros:

* Encapsulation: The logic is encapsulated within the Lodash library, making it easier to reuse and maintain.
* Abstraction: The `_.filter()` function abstracts away the underlying implementation details, allowing developers to focus on the logic rather than the plumbing.

Cons:

* Overhead: Using a library like Lodash introduces additional overhead due to the need to import and initialize the library.
* Dependency: The test case relies on the presence of Lodash in the environment, which may not be the case for all users.

**Plain JavaScript's `Array.prototype.filter()` method:**

Pros:

* No dependency: This approach doesn't rely on an external library, making it more self-contained and easier to run in a variety of environments.
* Native performance: The native implementation is typically optimized for performance.

Cons:

* More verbose: Using the plain `Array.prototype.filter()` method requires more boilerplate code, which can make the test case more cumbersome to write and maintain.
* Less encapsulated logic: The logic is exposed at the surface level, making it less modular and reusable.

**Other considerations**

1. **Context**: Both approaches are sensitive to context and scope. In the Lodash example, `isBigEnough` is passed as a callback function, while in plain JavaScript, we need to create an array instance or modify the existing one.
2. **Nullability**: Both approaches have different handling for null values. Lodash's `_filter()` method will pass through any elements that are null, while plain JavaScript's `Array.prototype.filter()` method will return all elements if any of them are null.

**Library used**

In this benchmark, Lodash is a utility library for functional programming and data manipulation. Its primary purpose is to provide a set of reusable functions for common tasks, such as filtering arrays.

**Special JS feature or syntax**

There's no special JavaScript feature or syntax being tested in this benchmark. The focus is on comparing the performance of two approaches: using a library (Lodash) versus plain JavaScript.

Other alternatives

If you're interested in exploring alternative approaches, some options might include:

* Using another utility library like Moment.js for date manipulation or MathJS for numerical computations.
* Implementing custom logic for filtering arrays without relying on external libraries.
* Testing the performance of other native JavaScript methods, such as `Array.prototype.reduce()` or `Array.prototype.map()`.

Related benchmarks:

Filter Comparison (version: 0)

Comparing performance of: lodash vs plain js

Created: 6 years ago by: Registered User

Jump to the latest result

lodash

plain js

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):