GSoC

In last blog post, I discussed the basic Web API’s which helps us to create the lazy image loader component. I also discussed the structure which is used in the application, to load the images lazily. The core idea is to wrap the <img> element in a wrapper, <app-lazy-img> element. This enables us the detection of the element in the viewport and corresponding loading only if the image is present in the viewport.

In this blog post, I will be discussing the implementation details about how this is achieved in Loklak search in an optimized manner.

The logic for lazy loading of images in the application is divided into a Component and a corresponding Service. The reason for this splitting of logic will be explained as we discuss the core parts of the code for this feature.

Detecting the Intersection with Viewport

The lazy image service is a service for the lazy image component which is registered at the by the modules which intend to use this app lazy image component. The task of this service is to register the elements with the intersection observer, and, then emit an event when the element comes in the viewport, which the element can react on and then use the other methods of services to actually fetch the image.

@Injectable()
export class LazyImgService {
private intersectionObserver: IntersectionObserver
= new IntersectionObserver(this.observerCallback.bind(this), { rootMargin: '50% 50%' });
private elementSubscriberMap: Map<Element, Subscriber<boolean>>
= new Map<Element, Subscriber<boolean>>();
}

The service has two member attributes, one is IntersectionObserver, and the other is a Map which stores the the reference of the subscribers of this intersection observer. This reference is then later used to emit the event when the element comes in viewport. The rootMargin of the intersection observer is set to 50% this makes sure that when the element is 50% away from the viewport.

The obvserve public method of the service, takes an element and pass it to intersection observer to observe, also put the element in the subscriber map.

public observe(element: Element): Observable<boolean> {
const observable: Observable<boolean> = new Observable<boolean>(subscriber => {
this.elementSubscriberMap.set(element, subscriber);
});
this.intersectionObserver.observe(element);
return observable;
}

Then there is the observer callback, this method, as an argument receives all the objects intersecting the root of the observer, when this callback is fired, we find all the intersecting elements and emit the intersection event. Indicating that the element is nearby the viewport and this is the time to load it.

private observerCallback(entries: IntersectionObserverEntry[], observer: IntersectionObserver) {
entries.forEach(entry => {
if (this.elementSubscriberMap.has(entry.target)) {
if (entry.intersectionRatio > 0) {
const subscriber = this.elementSubscriberMap.get(entry.target);
subscriber.next(true);
this.elementSubscriberMap.delete(entry.target);
}
}
});
}

Now, our LazyImgComponent enables us to uses this service to register its element, with the intersection observer and then reacting to it later, when the event is emitted. This method sets up the IO, to load the image, and subscribes to the event emittes by the service and eventually calls the loadImage method when the element intersects with the viewport.

private setupIntersectionObserver() {
this.lazyImgService
.observe(this.elementRef.nativeElement)
.subscribe(value => {
if (value) {
this.loadImage();
}
});
}

Loading and rendering the image

Our lazy image service has another public API method fetch to fetch the image resource, this method returns an observable, which on successful fetching of image emits a Base64 image string.

public fetch(resource: string): Observable<string> {
return new Observable<string>(subscriber => {
fetch(resource)
.then(this.processStatus)
.then(this.getBufferResponse)
.then(this.arrayBufferToBase64)
.then(strBuffer => {
subscriber.next(strBuffer);
subscriber.complete();
})
.catch((error) => {
subscriber.error(error);
subscriber.complete();
});
});
}

The intermediate promise then chain is for converting the raw response buffer to a Base64 string, this string is then emited as the observable emmision. The component then subscribes to this fetch Observable, when the load image method is called.

private loadImage() {
this.isLoading = true;
this.lazyImgService
.fetch(this.src)
.subscribe(this.handleResponse.bind(this), this.handleError.bind(this));
}

The handler methods for the response and errors then contain the code to handle the effects of loading of results, ie. rendering the image inside the img element. The intresting thing to note here is, if we give the Base64 string as the src attribute of an img tag, instead of resource path then also it renders the image properly.

private handleResponse(imageStr: string) {
const base64Flag = `data:image/${this.imageType};base64,`;
this.elementRef.nativeElement.querySelector('img').src = base64Flag + imageStr;
}

And this completes our workflow of the app-lazy-img and gives us, a robust lazy image loader, and also is compliant with accessibility guidelines, including all the necessary attributes like, title, width, height etc. for the generation of proper accessibility tree. This technique can be extended to any level, and is more or less platform and framework independent, as this relies solely on Web Standards API’s. This is an optimized solution, as at a time only one intersection observer is active on a page and is seeing all the images, rather than per component instance based intersection observers which can be a performane bottleneck in low memory devices.

Resources and Links

• Intersection observer API
• Intersection Observer polyfill for the browsers which don’t support Intersection Observer
• Fetch API documentation
• Fetch API polyfill for the browsers which don’t support fetch.
• Loklak Search Repo