Benchmark: alpinejs speed-up transitionIn & transitionOut

HTML Preparation code:

<div
    x-show="open"
    x-transition:enter="transition ease-out duration-300"
    x-transition:enter-start="opacity-0 transform scale-90"
    x-transition:enter-end="opacity-100 transform scale-100"
    x-transition:leave="transition ease-in duration-300"
    x-transition:leave-start="opacity-100 transform scale-100"
    x-transition:leave-end="opacity-0 transform scale-90"
>...</div>

Script Preparation code:

/* Directive `transition` gonna endup kinda like this: */
var attrs = [
  {value: 'enter'}, {value: 'enter-start'}, {value: 'enter-end'},
  {value: 'leave'}, {value: 'leave-start'}, {value: 'leave-end'},
]

Tests:

filter
attrs.filter(attr => ['enter', 'enter-start', 'enter-end'].includes(attr.value)).length > 0
some
attrs.some(attr => ['enter', 'enter-start', 'enter-end'].includes(attr.value))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
filter
some

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36

Browser/OS: Chrome 132 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
filter	20448858.0 Ops/sec
some	100240976.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

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

**Benchmark Overview**

The MeasureThat.net benchmark is designed to measure the performance of JavaScript microbenchmarks, specifically focusing on two optimization techniques: filtering arrays using `filter()` and checking for presence using `some()`.

**Script Preparation Code**

The script preparation code defines an array of attributes (`attrs`) with varying values. The purpose of this code is to provide a sample dataset for the benchmarking process.

```javascript
var attrs = [
  {value: 'enter'}, {value: 'enter-start'}, {value: 'enter-end'},
  {value: 'leave'}, {value: 'leave-start'}, {value: 'leave-end'}
];
```

**Html Preparation Code**

The HTML preparation code defines a `<div>` element with several attributes, including `x-show`, `x-transition`, and others. The purpose of this code is to provide a context for the benchmarking process.

```html
<div x-show="open"
    x-transition:enter="transition ease-out duration-300"
    x-transition:enter-start="opacity-0 transform scale-90"
    x-transition:enter-end="opacity-100 transform scale-100"
    x-transition:leave="transition ease-in duration-300"
    x-transition:leave-start="opacity-100 transform scale-100"
    x-transition:leave-end="opacity-0 transform scale-90">
  ...
</div>
```

**Individual Test Cases**

The benchmark defines two test cases:

1. **filter**
```javascript
attrs.filter(attr => ['enter', 'enter-start', 'enter-end'].includes(attr.value)).length > 0
```
This test case filters the `attrs` array to only include attributes with values that match one of the specified strings (`'enter'`, `'enter-start'`, or `'enter-end'`). The purpose of this test is to measure the performance of filtering arrays using the `filter()` method.

2. **some**
```javascript
attrs.some(attr => ['enter', 'enter-start', 'enter-end'].includes(attr.value))
```
This test case uses the `some()` method to check if any attribute in the `attrs` array has a value that matches one of the specified strings (`'enter'`, `'enter-start'`, or `'enter-end'`). The purpose of this test is to measure the performance of checking for presence using the `some()` method.

**Library and Syntax**

The benchmark uses the following libraries:

* None explicitly, but it appears to rely on some underlying JavaScript libraries (e.g., Vuex, Vue.js) that provide features like `x-transition` in the HTML preparation code.
* It does not use any special JavaScript features or syntax.

**Alternative Approaches**

Some alternative approaches to these tests could be:

1. **Array.prototype.every()` instead of `filter()`: This method would check if all attributes have values that match one of the specified strings, whereas `filter()` checks for at least one match.
2. **Using a different data structure**: Instead of using an array, the benchmark could use an object or another data structure to test performance.
3. **Adding more complexity**: The benchmark could add more attributes or values to the `attrs` array to make it more representative of real-world scenarios.

**Pros and Cons**

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

1. **filter()**
	* Pros: Efficient, widely supported.
	* Cons: May not be suitable for all use cases (e.g., when checking for all values in an array).
2. **some()**
	* Pros: Suitable for checking presence, more concise than `every()` or `includes()`.
	* Cons: May be slower than `filter()` for large datasets.

Keep in mind that these are general pros and cons, and the actual performance differences between these approaches may vary depending on the specific use case and implementation details.

Related benchmarks:

alpinejs speed-up transitionIn & transitionOut (version: 1)

Comparing performance of: filter vs some

Created: 4 years ago by: Registered User

Jump to the latest result

filter

some

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):