Archive for the ‘Web Technologies’ Category

Pushing computation to the front: client-side compression

Client → Server Compression

Content from a web server being automatically gzipped (via apache, nginx, etc.) and transferred to the browser isn’t anything new, but there’s really nothing in the way of compression when going in the other direction (i.e. transferring content from the client to the server). This is not too surprising, as most client payloads are small bits of textual content and/or binary content that is already well compressed (e.g. JPEG images), where there’s little gain from compression and you’re likely to just waste CPU cycles doing it. That said, when your frontend client is a space for content creation, you’re potentially going to run into cases where you’re sending a lot of uncompressed data to the server.

Use-case: ScratchGraph Export

ScratchGraph has an export feature that essentially renders the page (minus UI components) as a string of HTML. This string packaged along with some metadata and sent to the server, which sends it to a service running puppeteer, that renders the HTML string to either an image or a PDF. The overall process looks something like this:

ScratchGraph Export Flow

The HTML string being sent to the server is relatively large, a couple of MBs, due to:

  • The CSS styles (particularly due to external resources being pulled in and inlined as base64 URLs)
  • The user simply having lots of content

To be fair, it’s usually the former rather than the latter, and optimizing to avoid the inlining of resources (the intent of which was to try and do exports entirely in the browser) would have a greater impact in reducing the amount of data being transferred to the server. However, for the purposes of this blog post (and also because it leads to a more complex discussion on how the application architecture can/should evolve and what this feature looks like in the future), we’re going to sidestep that discussion and focus on what benefits data compression may offer.

Compression with pako

I was more than ready to implement a compression algorithm, but was happy to discover pako, which does zlib compression. Compressing (i.e. deflating) with pako is very simple, below I encode the HTML string to UTF8 via TextEncoder.encode() (this is because I want UTF8, this isn’t a requirement of pako), which returns a Uint8Array, then use that as the input for pako.deflate(), which also returns a Uint8Array.

const staticHtmlUtf8Arr = (new TextEncoder()).encode(html); const compressedStaticHtmlUtf8Arr = pako.deflate(staticHtmlUtf8Arr);

Here’s what that looks like in practice, exporting the diagram shown above:

ScratchGraph Export, with pako compression, results

That’s fairly significant, as the data size has been reduced by 1,237,266 bytes (42.77%)!

The final bit for the frontend is sending this to the server. I use a FormData object for the XHR call and, for the compressed data, I put append it as a Blob:

formData.append( "compressedStaticHtml", new Blob([compressedStaticHtmlUtf8Arr], {type: 'application/zlib'}), "compressedStaticHtml" );

Handling the compressed data server-side with PHP

PHP support zlib compression/decompression via the zlib module. The only additional logic needed server-side is calling gzuncompress() to decompressed the compressed data.

$staticHtml = gzuncompress(file_get_contents($compressedStaticHtmlFile->getFilePath()));

Note that $compressedStaticHtmlFile is an object representing a file pulled from the request (note that FormData will append a Blob in the same manner as a file, so server-side, you’re dealing with the data as a file). The File.getFilePath() method here is simply returning the path for the uploaded file.

Limitations

Compressing and decompressing data will cost CPU cycles and, for zlib and most algorithms, this will scale with the size of the data. So considerations around what the client-side system looks like and the size of the data need to be taken into account. In addition, compression within a browser’s main thread can lead to UI events, reflow, and repaint being blocked (i.e. the page becomes unresponsive). If the compression time is significant, performing it within a web worker instead would be a better path.

Copy & pasting non-textual objects in the browser

Interacting with the clipboard

A proper way to deal with clipboard access has been a dream for web developers for years. There’s out-of-the-box browser support, via keyboard shortcuts and content menu commands, for <input>, <textarea>, or elements with the contenteditable attribute. However, for more complex interactions or dealing with application-defined, non-textual objects (e.g. something composed of multiple DOM elements that is manipulable by the user, such as the ScratchGraph notes and connectors shown below) we need to start looking at the available Javascript APIs.

ScratchGraph entities and connectors

Clipboard API vs document.execCommand() + paste event

The bad news is that document.execCommand() (using the “cut”, “copy” commands) is still the de-facto way of writing to the clipboard, despite this method being deemed obsolete. The good news is that there does seems to be good progress, in terms of stability and browser implementation, of the Clipboard API.

For reading from the clipboard, the paste event seems to be the best way to go, however there is the inherent limitation that this event will only be triggered by “paste actions” from the browser’s interface (e.g. the use hitting Ctrl + V). Again, there is good news in that the Clipboard API would allow more flexibility here and there is good progress towards browser support.

Despite the good news around the Clipboard API, given the state of where things are now, in September 2020, using document.execCommand() and the paste event seems to be the way to go; the Clipboard API, as well as the corresponding permissions via the Permissions API, are still in the process of being implemented in browsers. However, most of what’s in this post will (hopefully) still be valid with the Clipboard API, with the clipboard interaction code being more robust and the more hacky bits being thrown away.

Copying to the clipboard with document.execCommand(“copy”)

Selecting plain text and copying it to the clipboard is straightforward with an <input> or <textarea>:

  • Call the select() method on the element
  • Call document.execCommand("copy");

We can make a generic method to copy arbitrary text to the clipboard by programmatically creating a <textarea>, setting its value to the text we want, performing the above operations to copy its contents to the clipboard, and finally removing the created <textarea>.

const Clipboard = { copyText: function(_text) { const textAreaElem = document.createElement('textarea'); textAreaElem.textContent = _text; document.body.appendChild(textAreaElem); textAreaElem.select(); document.execCommand("copy"); document.body.removeChild(textAreaElem); } };

Now, using this method, if we can serialize an object to some sort of textual format, we can put it on the clipboard. JSON is a good option, as it’s easy to work with in Javascript.

Object → JSON → Plain text → Clipboard

In ScratchGraph, entities like notes, connectors, etc. have a toJSON() method, which returns a JSON serialized representation of the entity, e.g.:

this.toJSON = function() { const serializedObj = { "id": self.getId(), "owner_id": self.ownerId, "sheet_id": self.sheetId, "position_x": self.getX(), "position_y": self.getY(), ... }; return serializedObj; }

When a user initiates a request to copy something, say by hitting Ctrl + C, we iterate over all the selected entities, get the serialized JSON for each, and build an array of JSON objects. Next we construct a JSON object containing that array, along with some metadata around context (application name, version, etc.). Finally, we JSON.stringify this object to get a plain text representation and use the Clipboard.copyText() method to write to the clipboard.

document.addEventListener('keydown', function(e) { // Copy selected entities on Ctrl + C if(e.ctrlKey && e.key === 'c') { const entitiesSelected = currentGroupTransformationContainer.getEntities(); const entitiesJsonArr = []; entitiesSelected.forEach(function(e) { entitiesJsonArr.push(e.toJSON()); }); ... const strForClipboard = JSON.stringify({ "application": "scratchgraph", "version": "1.0", "entities": entitiesJsonArr, ... }); Clipboard.copyText(strForClipboard); } });

Pasting from the clipboard

To read what’s on the clipboard, we can listen for and implement a handler on the paste event.

While you can listen for the paste event on any DOM element, I’ve found it tricky to isolate to specific elements because the element that has focus isn’t always obvious and I’ve run into situations where an offscreen <input> gets focus and the clipboard content simply gets pasted into that input. It’s more reliable to listen on the document and determine if and where to paste something based on the metadata embedded when we copied data to the clipboard.

Sketching out what we need to deal with, we get the following:

  • Listen for paste events on the document
  • Check if there’s plain-text content being pasted
  • Try to parse the plain-text content as JSON
  • Check whatever metadata is in the object to see if it’s something copied from our application and it’s something we can read/interpret.
  • If it’s something we can handle, suppress any default behavior and do what is needed to clone and create new objects.

This is simplified for clarity, but the code in ScratchGraph looks something like this:

document.addEventListener('paste', function(e) { if(typeof e.clipboardData === 'undefined' || typeof e.clipboardData.items === 'undefined') { return; } const items = e.clipboardData.items; for (let i=0; i<items.length; ++i) { if (items[i].kind === 'string' && items[i].type === "text/plain") { try { const clipboardJson = JSON.parse(e.clipboardData.getData('text/plain')); if(clipboardJson.application === "scratchgraph") { e.preventDefault(); createFromClipboardJson(clipboardJson); } } catch(err) { } } } });

The createFromClipboardJson() method handles the application-specific logic of reading the data and creating copies. In ScratchGraph, I’m dealing with entities, so I don’t actually deserialize, I just read the bits of data needed to be make a clone and create something with a new ID (i.e. new entity). However, YMMV, based on the type of objects you’re dealing with, how your application handles data, and/or how you deal with state.

Limitations and future work

As I mentioned, there are limitations here when it comes to reading or writing from/to the clipboard. The paste event will only be triggered by interactions supported by the browser, so creating something like a button to paste content isn’t possible. document.execCommand("copy") is now considered obsolete and the method presented to allow copying arbitrary bits of text is pretty hacky, though it is versatile in that you can bind the method to application-specific interactions (e.g. a button to copy content). A further limitation here is that data can only be copied as plain-text and we’re not actually encoding any type information; this manifests in some non-ideal behavior, where what’s put on the clipboard can be pasted into any application that accepts plain-text.

The Clipboard API looks to be a promising solution to these limitations. I’m hoping to revisit this in the near future to update the clipboard interaction logic to use the API and have an all-round cleaner and more robust solution.

Pushing computation to the front: video snapshots

Video and the Canvas API

The Canvas API is surprising versatile. The image parameter of the CanvasRenderingContext2D.drawImage() method will accept images from a number of different sources including an HTMLVideoElement. I touched on this a bit in a previous post about processing the data from video streams, however HTMLVideoElement can also handle loading and rendering video files, with all modern browsers capable of tackling the non-trivial tasks of decoding and rendering H.264 MP4 or VP8/VP9 WebM content (and, of course, you get all the benefits of the client’s GPU hardware that the browser takes advantage of). This opens up the possibility of capturing frames from video files which can be used for preview images, poster images, or substituting in an image when video playback isn’t possible (e.g. for a print layout, which is the issue I’ve run into with ScratchGraph).

Setting up the HTMLVideoElement

This is fairly standard, here we’ll load an H.264 MP4 with the filename “test.mp4”:

const video = document.createElement('video'); const videoSource = document.createElement('source'); videoSource.setAttribute('type', 'video/mp4'); videoSource.setAttribute('src', 'test.mp4'); video.appendChild(videoSource);

For reference, here’s the test video:

Next, we want to seek to a point in the video where we want to capture the frame and also bind to an event that’ll tell us when we’re able to read the frame data from the HTMLVideoElement. The seeked event works well. The other potentially viable option is the loadeddata event, but I ran into some issues here, which I’ll describe later.

video.addEventListener('seeked', function(e) { // capture the video frame at the point seeked to... }); // seek to 2s video.currentTime = 2;

Render the frame onto a canvas

The Canvas API makes this really easy and the process mirrors what’s described in the post on thumbnail generation:

/** * * @param {HTMLVideoElement} video * @param {Number} newWidth * @param {Number} newHeight * @param {Boolean} proportionalScale * @returns {Canvas} */ videoFrameToCanvas: function(video, newWidth, newHeight, proportionalScale) { if(proportionalScale) { if(video.videoWidth > video.videoHeight) { newHeight = newHeight * (video.videoHeight / video.videoWidth); } else if(video.height > video.videoWidth) { newWidth = newWidth * (video.videoWidth / video.videoHeight); } else {} } const canvas = document.createElement('canvas'); canvas.width = newWidth; canvas.height = newHeight; const canvasCtx = canvas.getContext('2d'); canvasCtx.drawImage(video, 0, 0, newWidth, newHeight); return canvas; }

I added this method to the canvas-image-transformer library; referencing the method we can now flesh out the seeked event handler. For this test, we’ll also render out what’s on the canvas to an <img> element in the document to see what’s been captured.

video.addEventListener('seeked', function(e) { // capture the video frame at the point seeked to const frameOnCanvas = CanvasImageTransformer.videoFrameToCanvas(video, 500, 500, true); document.getElementById('testImage').src = frameOnCanvas.toDataURL(); });

frameOnCanvas is a canvas with the captured frame, and here’s what it looks like transformed & rendered into an <img> element:

canvas-image-transformer-test-video-frame-capture

Issues

  • Something not immediately obvious is that the seeked event is not fired if video.currentTime = 0 (i.e. you want to seek to the first frame of a video). However, you can use a very small time value (e.g. video.currentTime = 0.000000001), which will typically seek to the first frame in most cases. That said, it is a hacky/non-elegant solution.
  • There are cross-browser issues with the loadeddata event. In Firefox, you will only get a frame capture if you don’t seek. If you do attempt to seek, you’ll get a empty frame and the canvas will have a transparent image. Conversely, in Chrome (and other Webkit-based browsers), you will only get a frame if you do seek. The standard states that the event should be fired when “the user agent can render the media data at the current playback position for the first time” which seem to indicate an implementation flaw in both browsers.
  • The test video was taken on my phone and the frames themselves are upsided-down, this is typical with smartphone videos as it’s expected that playback will take into account metadata indicating orientation. In Firefox, this isn’t taken into account when using CanvasRenderingContext2D.drawImage() with HTMLVideoElement, so you get an upsided-down image on the canvas.

Alternatives & limitations

I couldn’t think of a ton of options for decoding H.264 or VP8/VP9. If you’re looking to create something yourself, a server-side service invoking FFmpeg seems like the best option. I played around with Puppeteer, but Puppeteer comes with Chromium, which lacks the audio and video support you get out-of-the box with Chrome. Although, installing and using Chrome server-side with Puppeteer has potential.

There are also third-party services which can handle video decoding and transcoding, and those are solid server-side options.

As with thumbnail generation, here again we’re looking at workloads that have potential to be moved to the frontend, where you have hardware better suited for graphics work and the possibility of reducing backend complexity. On the other hand, the same limitations comes into play, as you have less control over the execution environment and no clear path for backfill or migration needs.

Pushing computation to the front: thumbnail generation

Frontend possibilities

As the APIs brought forward by HTML5 about a decade ago have matured and the devices running web browsers have continued to improve in computational power, looking at what’s possible on the frontend and the ability to bring backend computations to the frontend has been increasingly interesting to me. Such architectures would see each user’s browsers as a worker for certain tasks and could simply backend systems, as those tasks are pushed forward to the client. Using Canvas for image processing tasks is one area that interesting and that I’ve had success with.

For Mural, I did the following Medium-esque image preload effect, the basis of which is generating a tiny (16×16) thumbnail which is loaded with the page. That thumbnail is blurred via CSS filter, and transitions to the full-resolution image once it’s loaded. The thumbnail itself is generated entirely on the frontend when a card is created and saved alongside the card data.

In this post, I’ll run though generating and handling that 16×16 thumbnail. This is fairly straightforward use of the Canvas API, but it does highlight how frontend clients can be utilized for operations typically relegated to server-side systems.

The image processing code presented is encapsulated in the canvas-image-transformer library.

<img> → <canvas>

A precursor for any sort of image processing is getting the image data into a <canvas>. The <img> element and corresponding HTMLImageElement interface don’t provide any sort of pixel-level read/write functionality, whereas the <canvas> element and corresponding HTMLCanvasElement interface does. This transformation is pretty straightforward:

The code is as follows (an interesting thing to note here is that this can all be done without injecting anything into the DOM or rendering anything onto the screen):

const img = new Image(); img.onload = function() { const canvas = document.createElement('canvas'); canvas.width = img.width; canvas.height = img.height; const canvasCtx = canvas.getContext('2d'); canvasCtx.drawImage(img, 0, 0, img.width, img.width); // the image has now been rendered onto canvas } img.src = "https://some-image-url";

Resizing an image

Resizing is trivial, as it can be handled directly via arguments to CanvasRenderingContext2D.drawImage(). Adding in a bit of math to do proportional scaling (i.e. preserve aspect ratio), we can wrap the transformation logic into the following method:

/** * * @param {HTMLImageElement} img * @param {Number} newWidth * @param {Number} newHeight * @param {Boolean} proportionalScale * @returns {Canvas} */ imageToCanvas: function(img, newWidth, newHeight, proportionalScale) { if(proportionalScale) { if(img.width > img.height) { newHeight = newHeight * (img.height / img.width); } else if(img.height > img.width) { newWidth = newWidth * (img.width / img.height); } else {} } var canvas = document.createElement('canvas'); canvas.width = newWidth; canvas.height = newHeight; var canvasCtx = canvas.getContext('2d'); canvasCtx.drawImage(img, 0, 0, newWidth, newHeight); return canvas; }

Getting the transformed image from the canvas

My goto method for getting the data off a canvas and into a more interoperable form is to use the HTMLCanvasElement.toDataURL() method, which allows easily getting the image as a PNG or JPEG. I do have mixed feeling about data-URIs; they’re great for the web, because so much of the web is textually based, but they’re also horribly bloated and inefficient. In any case, I think interoperability and ease-of-use usually wins out (esp. here where we’re dealing with a 16×16 thumbnail and the data-uri is relatively lightweight) and getting a data-uri is generally the best solution.

Using CanvasRenderingContext2D.getImageData() to get the raw pixel from a canvas is also an option but, for a lot of use-cases, you’d likely need to compress and/or package the data in some way to make use of it.

Save the transformed image

With a data-uri, saving the image is pretty straightforward. Send it to the server via some HTTP method (POST, PUT, etc.) and save it. For a 16×16 PNG the data-uri textual representation is small enough that we can put it directly in a relational database and not worry about a conversion to binary.

Alternatives & limitations

The status quo alternative is having this sort of image manipulation logic encapsulated within some backend component (method, microservice, etc.) and, to be fair, such systems work well. There’s also some very concrete benefits:

  • You are aware of and have control over the environment in which the image processing is done, so you’re isolated from browser quirks or issues stemming from a user’s computing environment.
  • You have an easier path for any sort of backfill (e.g. how do you generate thumbnails for images previously uploaded?) or migration needs (e.g. how can you move to a different sized thumbnail?); you can’t just run though rows in a database and make a call to get what you need.

However, something worth looking at is that backend systems and server-side environments are typically not optimized for any sort of graphics workload, as processing is centered around CPU cores. In contrast, the majority of frontend environments have access to a GPU, even fairly cheap phone have some sort of GPU that is better suited for “embarassing parallel”-esque graphics operations, the performance benefits of which you get for free with the Canvas API in all modern browsers.

In Chrome, see the output of chrome://gpu:

chrome settings, canvas hardware acceleration

Scale, complexity and cost also come into play. Thinking of frontend clients as computational nodes can change the architecture of systems. The need for server-side resources (hardware, VMs, containers, etc.) is eliminated. Scaling concerns are also, to a large extent, eliminated or radically changed as operations are pushed forward to the client.

Future work

What’s presented here is just scratching the surface of what’s possible with Canvas. WebGL also presents as a ton of possibilities and abstraction layers like gpu.js are really interesting. Overall, it’s exciting to see the web frontend evolve beyond a mechanism for user input and into a layer in which substantive computation can be done.

Embedding content with oEmbed

History

Embedding external content has been a feature of the web since the introduction of the iframes ages ago. However, embedding as a business strategy didn’t seem to be a thing until sometime around the late 2000s or the early 2010s, as social networking became big business, blogging became really popular, and there was concern over walled gardens. In this environment, embedding became a component for growth, and it was no doubt successful for now behemoths like Youtube and Twitter (another component was adding social networking to sites, à la Google+ or Dunder Mifflin Infinity). Almost any site dealing in content had an embed feature or an embedded “widget.” Even Grovo, where I worked, was on this train as well with the Grovo Widget, though I was not involved in its development. It some cases this made sense and provided utility, in many others it was just copying what seemed to be working for others in ecosystem without regard for product or overall business strategy.

It seems like around this time oEmbed was drafted and Embedly was founded.

oEmbed

My view on how embeds were done was based on what you see in most UIs: you get a embed code (which is a snippet of HTML, likely encapsulated within an iframe), you paste that into a page, and the browser does the rest.

I learned about oEmbed working on Mural. oEmbed is an interesting protocol which allows consumers to request data representing what a resource should look like in an embedded context, given the URL of that resource. The overall flow looks something like this:

Figuring out what the oEmbed endpoint is involves looking at a <link> element from the resource’s HTML page. Unfortunately this does mean you have the overhead and complexity of downloading and parsing an HTML document to get the endpoint. An alternative is pulling from the list of providers in the oEmbed repo and looking at the oEmbed endpoints and allowed URL schemes for resources.

In either case, the result for the end-user is that by simply providing the URL for a resource, the appropriate content for an embed can be provided. Here’s what this looks like in Squarespace:

Embedly

Unfortunately, the video above is a lie. While everything described around oEmbed would allow for a flow like that, Squarespace (and a surprising number of other popular sites, like Medium) outsource handling of oEmbed to Embedly.

Embedly seems to do a few other things, but primarily it seems to proxy oEmbed content. What’s the value-add? According to Embedly:

We take care of every step of the process: retrieving information about a URL, checking it against malware registries, extracting content, making additional API calls to providers that support them, parsing RSS feeds, and performing validation. We save you time so that you can focus on making your app great.

The only aspect there I find compelling for the price tag is “checking it against malware registries,” but there’s little info on what level of protection they’re actually providing there.

I dealt with Embedly directly when working on Mural and it was a frustrating experience. First, note that if you’re not registered as an Embedly provider, sites that proxy through Embedly will return incorrect oEmbed data. On Squarespace, I noticed the Embedly response would have a type of “link” and not provide any of the data to do an HTML embed (so what’s shown in the video above will not happen, and it will appear as if the resource is not embeddable). Registering as a provider involves filling out a form with some endpoint information and example URLs, easy enough, but I had to wait weeks with no responses or status updates. For a request put in on Jan. 31, 2018, the Embedly integration was not done until Apr. 9th, 2018. A terrible experience overall and surprising for a company that is (a) owned by Medium and (b) seems to be a critical dependency for so many sites.

The short of it is, if as a provider, users can’t embed your content on a site, see if you need to register as an Embedly provider. If you do, good luck.

The Future

The excitement and prominence around blogging seems to have died down and this seems to have corresponded with the excitement around embedding content diminishing as well. That said, I think being able to embed content is still, and will continue to be, a powerful mechanism on the web. Even with its flaws oEmbed works nicely in this landscape. I can’t say the same for Embedly.

Serving mjs files with nginx

In my previous post on ES modules, I mentioned adopting the mjs file extension for modules files. Unfortunately, there’s no entry for the mjs extension in nginx’s default mime.types file, meaning it’ll be served as application/octet-stream instead of application/javascript. The MIME type for mjs files can be set by explicitly including mime.types in a server, http, or location block & adding a types block with the MIME type and file extension:

server { include mime.types; types { application/javascript mjs; } ... }

Writing and testing ES modules

The toolchain

ES modules are one of the more exciting additions to the Javascript language. Effectively being able to break-off and modularize has continually led to better code and development practices in my experience. For server-side Javascript, Node and its associated module system took hold, but there was nothing comparable for browsers. However, Node-based toolchains to produce frontend code also became a thing, doing rollup, transpilation, minification, etc. This wasn’t necessarily a bad thing, and came with some noted benefits such as better support for unit testing scaffolds and integration into CI pipelines, but it also set a stage for increasingly complex toolchains and an ecosystem whereby frontend components were Node-based server-side components first, and transformed into frontend components after. The latter, in turn, led to a state where you were always working with a toolchain (it wasn’t just for CI or producing optimized distributables) as there was no path to directly load these components in a browser, and I’d argue also led to a state where components were being composed with an increasing and ridiculous number of dependencies, as the burden of resolving and flattening dependencies fell to to the toolchain.

ES modules aren’t any sort of silver bullet here, but it does show a future where some of this complexity can be rolled back, the toolchain only needs to handle and be invoked for specific cases, and there is less impedance in working with frontend code. We’re not there yet, but I’m hopeful and as such I’ve adopted ES modules in projects where I’ve been able to.

A look at GraphPaper

GraphPaper was the first project where I committed to ES modules for the codebase. At the time, support for ES modules was limited in both Node and browsers (typically incomplete support and put behind a feature flag), so for both development work and producing distributables, I used rollup.js + Babel to produce an IIFE module. This worked well, though it’s a pain to do a build every for every code change I want to see in the browser. I also remember this being pretty easy to setup initially, but the package.json became more convoluted with Babel 6, when everything was split into smaller packages (I understand the rationale, but the developer experience is horrible and pushes the burden of understanding various babel components to consumers).

Structuring the module

Structuring was fairly simple. Everything that was meant to be accessible by consumers was declared in a single file (GraphPaper.js), declared via export statements (i.e. it was just a file with a bunch of export * from … statements). This file also served as the input for rollup.js:

{ input: 'src/GraphPaper.js', output: { format: 'iife', file: 'dist/graphpaper.min.js', name: 'GraphPaper', sourcemap: true }, plugins: [ babel(babelConfig), ], }

In a modern browser, it would be possible to import the GraphPaper ES module directly, like so:

<script type="module"> import * as GraphPaper from '../src/GraphPaper.js'; ... </script>

However, the way dependent web workers are built and encapsulated makes this impossible (explained here).

Another problem, but one that’s fixable, is that I wrote import and export statements without file extensions. For browsers, this leads to an issue as the browser will just request what’s declared in the statement and not append any file extension (so a statement like import { LineSet } from './LineSet'; results in a request to the server for ./LineSet, not ./LineSet.js, as the file is named. Moving forward, the recommendation to use the .mjs extension and explicitly specifying the extension in import statements seems to be a good idea; in addition to addressing the issue with browser requests, when working in Node .mjs files will automatically be treated as ES modules.

Pushing aside the web worker issue, we can see a future where rollup.js isn’t necessary, or at least not necessary for producing browser-compatible (e.g. IIFE) modules. It’s role can be limited to concatenation and orchestrating optimizations (e.g. minification) for distributables. Similarly, for Babel, it’s role can be reduced or eliminated. As support for newer ES features (particularly those in ES6 and ES7) continues to improve across systems (browsers, Node, etc.), and users adopt these systems, transpilation won’t be as necessary. The exception is the case where developers want to use the very latest ES features, but I think we’re quickly approaching a point of diminishing returns here, especially relative to the cost of toolchain complexity.

Testing with jasmine-es6, moving to Ava

For testing, I found jasmine-es6 to be one of the simpler ways to test ES modules at the time. Ava existed, but I remember running into issues getting it working. I remember also toying with Jest at some point and also running into issues. In the end, jasmine-es6 worked well, I never had issues importing and writing tests for a module. Here’s a sample test from the codebase:

import { Point } from '../src/Point' import { Line } from '../src/Line' import { LineSet } from '../src/LineSet' describe("LineSet constructor", function() { it("creates LineSet from Float64Array coordinates", function() { const typedArray = Float64Array.from([1,2,3,4,5,6,7,8]); const ls = new LineSet(typedArray); const lineSetArray = ls.toArray(); expect(ls.count()).toBe(2); expect(lineSetArray[0].isEqual(new Line(new Point(1, 2), new Point(3, 4)))).toBe(true); expect(lineSetArray[1].isEqual(new Line(new Point(5, 6), new Point(7, 8)))).toBe(true); }); });

jasmine-es6 has and continues to work really well despite being deprecated. I’ll likely adopt and reformat the tests to Ava at some point the future. I’ve played around with it again recently and it was a much smoother experience, it’s also better supported and I like the simpler syntax around tests more-so than the Jasmine syntax. I’m looking to do this when Node has stable support for ES modules, as this would mean not worrying about pulling in and configuring Babel for running tests (though it’ll likely still be around for rollup.js).

Takeaways

Overall, it’s been fairly smooth working with ES modules and it looks like things will only improve in the future. Equally exciting is the potential reduction in toolchain complexity that comes with better support for ES modules.

  • Support for ES modules continues to improve across libraries, browsers, and Node
  • It’s probably a good idea to use the .mjs file extension
  • Rollup.js is still needed for now to make browser-compatible (e.g. IIFE) modules, but will likely take on a more limited role in the future (concatenation & minification)
  • Better support for ES6 and ES7 features across the board will mean that Babel, and transpilation in general, won’t be as necessary

Finding, fetching, and rendering favicons with puppeteer

I’ve been working a bit with fetching favicons and noted some of the complexity I encountered:

  • The original way to adding favicons to a site, placing /favicon.ico file in the root directory, is alive and well; browsers will make an HTTP GET request to try and fetch this file.
  • Within the HTML document, <link rel="icon" is the correct way to specify the icon. However, a link tag with <link rel="shortcut icon" is also valid and acceptable, but “shortcut” is redundant and has no meaning (of course, if you’re trying to parse or query the DOM, it’s a case you need to consider).
  • Like other web content, the path in a <link> tag can an absolute URL, with may or may not declare a protocol, or a relative URL.
  • While there is really good support for PNG favicons, ICO files are still common, even on popular sites (as of writing this Github, Twitter, and Gmail, all use ICO favicons).
  • When not using ICO files, they is usually multiple <link> tags, with different values for the sizes attribute, in order to declare different resolutions of the same icon (ICO is a container format, so all the different resolution icons are packaged together).
  • The correct MIME type for ICO files is image/vnd.microsoft.icon, but the non-standard image/x-icon is much more common.
  • Despite the popularity of ICOs and PNGs, there’s a bunch of other formats with varying degrees of support across browsers: GIF (animated/non-animated), JPEG, APNG, SVG. Of particular note is SVG, as it’s the only non-bitmap format on this list, and is increasing being supported.

The goal was to generate simple site previews for ScratchGraph, like this:

ScratchGraph Site Preview

Finding the favicon URL was one concern. My other concern was rendering the icon to a common format, while this isn’t technically necessary, it does lower the complexity in the event that I wanted to do something with the icon, other than just rendering within the browser.

Finding the favicon URL

I wrote the following code to try and find the URL of the “best” favicon using Puppeteer (Page is the puppeteer Page class):

/** * * @param {Page} page * @param {String} pageUrl * @returns {Promise<String>} */ const findBestFaviconURL = async function(page, pageUrl) { const rootUrl = (new URL(src)).protocol + "//" + (new URL(src)).host; const selectorsToTry = [ `link[rel="icon"]`, `link[rel="shortcut icon"]` ]; let faviconUrlFromDocument = null; for(let i=0; i<selectorsToTry.length; i++) { const href = await getDOMElementHRef(page, selectorsToTry[i]); if(typeof href === 'undefined' || href === null || href.length === 0) { continue; } faviconUrlFromDocument = href; break; } if(faviconUrlFromDocument === null) { // No favicon link found in document, best URL is likley favicon.ico at root return rootUrl + "/favicon.ico"; } if(faviconUrlFromDocument.substr(0, 4) === "http" || faviconUrlFromDocument.substr(0, 2) === "//") { // absolute url return faviconUrlFromDocument; } else if(faviconUrlFromDocument.substr(0, 1) === '/') { // favicon relative to root return (rootUrl + faviconUrlFromDocument); } else { // favicon relative to current (src) URL return (pageUrl + "/" + faviconUrlFromDocument); } };

This will try to get a favicon URL via:

  • Try to get the icon URL referenced in the first link[rel="icon"] tag
  • Try to get the icon URL referenced in the first link[rel="icon shortcut"] tag
  • Assume that if we don’t find an icon URL in the document, there’s a favicon.ico relative to the site’s root URL

Getting different sizes of the icon or trying to get a specific size is not supported. Also, for URLs pulled from the document via link[rel=… tags, there’s some additional code to see if URL is absolute, relative to the site/document root, or relative to the current URL and, if necessary, construct and return an absolute URL.

The getDOMElementHRef function to query the href attribute is as follows:

/** * * @param {Page} page * @param {String} query * @returns {String} */ const getDOMElementHRef = async function(page, query) { return await page.evaluate((q) => { const elem = document.querySelector(q); if(elem) { return (elem.getAttribute('href') || ''); } else { return ""; } }, query); };

Fetching & rendering to PNG

Puppeteer really shines at being able to load and render the favicon, and providing the mechanisms to save it out as a screenshot. You could attempt to read the favicon image data directly, but there is significant complexity here given the number of different image formats you may encounter.

Rendering the favicon is relatively straightfoward:

  • Render the favicon onto the page by having the Page goto the favicon URL
  • Query the img element on the page
  • Make the Page’s document.body background transparent (to capture any transparency in the icon when we take the screenshot)
  • Take a screenshot of that img element, such that a binary PNG is rendered

Here is the code to render the favicon onto the page:

/** * * @param {Page} page * @returns {ElementHandle|null} */ const renderFavicon = async function(page) { let faviconUrl = await findBestFaviconURL(page, src); try { console.info(`R${reqId}: Loading favicon from ${faviconUrl}`); await page.goto(faviconUrl, {"waitUntil" : "networkidle0"}); } catch(err) { console.error(`R${reqId}: failed to get favicon`); } const renderedFaviconElement = await page.$('img') || await page.$('svg'); return renderedFaviconElement; };

Finally, here’s the snippet to render the favicon to a PNG:

if(renderedFaviconElement) { const renderedFaviconElementTagName = await (await renderedFaviconElement.getProperty('tagName')).jsonValue(); if(renderedFaviconElementTagName === 'IMG') { await page.evaluate(() => document.body.style.background = 'transparent'); } const faviconPngBinary = await renderedFaviconElement.screenshot( { "type":"png", "encoding": "binary", "omitBackground": true } ); }

EDIT 4/7/2020: Updated code snippets to correctly handle SVG favicons. With SVGs, an <svg> element will be rendered on the page (instead of an <img> element). Also, there is no <body> element, as the SVG is rendered directly and not embedded within an HTML document, and hence no need to set the document’s body background to transparent.

SVG filters and invisible paths

The setup

Let’s just right into it and look at a few paths:

  • We have the arrow thingy (M100 100 L330 453 L349 349 L527 349 L100 100)
  • The horizontal line (M50 50 L200 50)
  • The vertical line (M125 10 L125 50)

There’s some CSS to style the paths:

path { fill: none; stroke-width: 3px; stroke: url('#gradient'); }

There’s also some code for the linear gradient, but that’s not relevant here.

A blur filter

A simple SVG gaussian blur filter can be done as follows:

<defs> <filter id="blur"> <feGaussianBlur in="SourceGraphic" stdDeviation="2" /> </filter> </defs>

Applying that filter to the paths (via filter:url(#blur) CSS rule), we get the following:

So, that kinda works, but the horizontal and vertical paths are now invisible!

A problem with filterUnits

The issue surfaces due to the value of the filterUnits attribute on the filter element is set to objectBoundingBox (which is also the default when a value is not specified). From the SVG spec:

Keyword objectBoundingBox should not be used when the geometry of the applicable element has no width or no height, such as the case of a horizontal or vertical line, even when the line has actual thickness when viewed due to having a non-zero stroke width since stroke width is ignored for bounding box calculations. When the geometry of the applicable element has no width or height and objectBoundingBox is specified, then the given effect (e.g., a gradient or a filter) will be ignored.

objectBoundingBox simply means that the x, y, width, height attributes on the filter are relative to the bounding box of the element referencing the filter, so it’s confusing why this should be an issue at all. In any case, it’s of course problematic for paths which have no width and height.

The solution

The solution is simply to change the filterUnits attribute to userSpaceOnUse. If you make use of the x, y, width, height attributes on the element, they will also need to be updated, as these attributes will now represent the coordinate system in which the element referencing the filter is (as opposed to the bounding box of that element).

<defs> <filter id="blur" filterUnits="userSpaceOnUse"> <feGaussianBlur in="SourceGraphic" stdDeviation="2" /> </filter> </defs>

A simple fix but this is an annoying issue and I see no clear reason as to why filterUnits="objectBoundingBox" should be problematic for elements without a defined width and height.

setInterval with 0ms delays within Web Workers

The 4ms minimum

Due to browser restrictions, you typically can’t have a setInterval call where the delay is set to 0, from MDN:

In modern browsers, setTimeout()/setInterval() calls are throttled to a minimum of once every 4 ms when successive calls are triggered due to callback nesting (where the nesting level is at least a certain depth), or after certain number of successive intervals.

I confirmed this by testing with the following code in Chrome and Firefox windows:

setInterval(() => { console.log(`now is ${Date.now()}`); }, 0);

In Firefox 72:

Firefox window setInterval with 0ms delay

In Chrome 79:

Chrome window setInterval with 0ms delay

The delay isn’t exact, but you can see that it typically comes out to around 4ms, as expected. However, things are a little different with web workers.

The delay with web workers

To see the timing behavior within a web worker, I used the following code for the worker:

const printNow = function() { console.log(`now is ${Date.now()}`); }; setInterval(printNow, 0); onmessage = function(_req) { };

… and created it via const worker = new Worker('worker.js');.

In Chrome, there’s no surprises, the behavior in the worker was similar to what it was in the window:

Chrome window setInterval with 0ms delay

Things get interesting in Firefox:

Firefox window setInterval with 0ms delay

Firefox starts grouping the log messages (the blue bubbles), as we get multiple calls to the function within the same millisecond. Firefox’s UI becomes unresponsive (which is weird and I didn’t expect as this is on an i7-4790K with 8 logical processors and there’s little interaction between the worker and the parent window), and there’s a very noticeable spike in CPU usage.

Takeaway

setInterval() needs a delay and you shouldn’t depend on the browser to set something reasonable. It would be nice if setInterval(.., 0) would tell the browser to execute as fast as reasonably possible, adjusting for UI responsiveness, power consumption, etc. but that’s clearly not happening here and as such it’s dangerous to have a call like this which may render the user’s browser unresponsive.