Dynamic imports with Alpine.js

Find out how you can implement dynamic imports with Alpine.js to speed up your website and optimize the user experience.

Jairus Joer

Jairus Joer

The texts in this article were partly composed with the help of artificial intelligence and corrected and revised by us. The following services were used for the generation:

In this article, we will show you how to implement dynamic imports with Alpine.js, load them with a delay using the Intersection Observer API and thus improve the accessibility of your own site and content.

Setup

For this demonstration, we are using our Astro Boilerplate, which we have already discussed in detail in a previous article.

Download Astro Boilerplate

If our boilerplate isn’t right for you, that’s no problem. The steps for implementing dynamic imports work in any project with Alpine.js.

In the following steps, we will install the dependencies required for the subsequent implementation of dynamic imports.

In addition to alpinejs, we also need @alpinejs/intersect, a plugin in the form of a convenient wrapper for the Intersection Obeserver:

npm install alpinejs @alpinejs/intersect

To demonstrate the dynamic import, we use Chart.js, a simple library for the visualization of charts via the <canvas> element:

npm install chart.js

After successfully installing all dependencies, we can start our development environment – in the example of our Astro Boilerplate with npm run dev:

npm run dev

Preparation of the HTML

To visualize Chart.js in the frontend and to be able to understand our implementation later, we place a <canvas> element with the following attributes:

pages/index.astro
<canvas id="chart" x-data="chart" x-intersect.once="once"></canvas>

Implementation of Chart.js

In our demonstration, we follow the example of the Getting Started guide of Chart.js and implement a simple bar chart within our chart() method.

Starting from chart(), we register the asynchronous method once(), which we have already referenced in our <canvas> element.

Within once() we import Chart and registerables asynchronously from the chart.js package and register all required modules of Chart.js via Chart.register(...registerables).

Finally, the bar chart is implemented with a rudimentary data set. Further information on the functionality of Chart.js can be found in the corresponding documentation.

scripts/alpine/chart.ts
export const chart = () => ({
  async once() {
    const { Chart, registerables } = await import("chart.js")
    Chart.register(...registerables)

    const context = document.getElementById('chart')! as HTMLCanvasElement
    
    new Chart(context, {
      type: 'bar',
      data: {
        labels: ['Red', 'Blue', 'Yellow', 'Green', 'Purple', 'Orange'],
        datasets: [{
          label: '# of Votes',
          data: [12, 19, 3, 5, 2, 3],
          borderWidth: 1
        }]
      },
      options: {
        scales: {
          y: {
            beginAtZero: true
          }
        }
      }
    })
  }
})

Configuration of Alpine.js

For reasons of clarity, we have moved the chart() method to a separate file, which we must now reference when initializing Alpine.

However, before we can reference our method in Alpine, we have to initialize the intersect plugin. With Alpine.plugin(intersect) the imported plugin can be initialized and made available via Alpine.

Finally, we add the directive Alpine.data("chart", chart) to the EventListener "alpine:init"

scripts/globals.ts
import Alpine from "alpinejs";
import intersect from "@alpinejs/intersect"
import { chart } from "./alpine/chart";

Alpine.plugin(intersect)

document.addEventListener("alpine:init", () => {
  Alpine.data("chart", chart)
});

Alpine.start();

We first presented our pattern for development with Alpine.js in our article Temporary and persistent state management with Alpine.js.


Verify results

Once we have made all the adjustments, we can verify our desired results with the network analysis of the browser dev tools.

In our scenario, the Chart.js library is only loaded via once() when the <canvas> element enters the viewport for the first time.

Assuming that we need the entire library for our project, we have reduced the initial transfer by ~70 kB (gzip) with this implementation.


Further possibilities

The implementation of Chart.js is just one of many examples in which dynamic imports help to reduce the initial transfer of a website and make content accessible more quickly.

This function is not limited to libraries. It can also be used for more complex components or larger data sets with little additional effort.

In a further step, the loading of this content can be bridged with a loading animation that is controlled via a data object in Alpine.


TL;DR

In this article, we demonstrated how to use Alpine.js and the Intersection Observer API to delay the loading of libraries like Chart.js until they are needed, improving load time and user experience.