Using Playwright to screenshot the DOM and return an image from a Netlify Function

Instructor: [0:00] The next thing we're going to do is install Playwright, which is the library that will run headless browsers for us, whether it's Chromium-based, Firefox, or Webkit-based. If we install Playwright, the regular package, it installs all three browsers for us for convenience.

[0:14] This is a lot, and our deploy will actually fail if our package size gets too big. If you look in packages, you can see that there's Playwright Chromium, Playwright Firefox, and Playwright Webkit, which are each different packages corresponding to their respective browsers.

[0:27] We can shrink the package size a little bit by using one of these. Currently, the Playwright team doesn't support a build for Lambda, but they do offer all of their build scripts for somebody else to handle it.

[0:37] We're going to use Playwright AWS Lambda. Playwright AWS Lambda only supports Chromium, but it'll work in our Netlify functions environment, which is what we need. Now that we've added Playwright AWS Lambda to our dependencies, we'll use in our gen OpenGraph image handler.

[0:51] We just added a bunch of code here, so let's go over how it works. First, we import Playwright from the Playwright AWS Lambda package. We launch Chromium. We get the default context.

[1:00] Note that _defaultContext is actually an internal API that we have to use because we're using a third-party Playwright package. We create a new page off that context, which will create a new page in the headless Chromium that we've launched.

[1:12] We can set the content to any HTML we want. In this case, we've set up a head and a body and a div inside the body with an ID of corgi and a content of hello. This div is where we'll render our image into before we take the screenshot. Hello is just test content for us.

[1:28] Then we need to get the dimensions to pass to the screenshot function. To do this, we can use page.evaluate, which allows us to evaluate a function or a string of code inside of the browser context page.

[1:38] In this case, we get the div with an ID of corgi. We use getBoundingClientRect and native browser APIs to get the X and the Y position as well as the width and the height. Then we return that as a serializable object as the variable boundingRect.

[1:52] It's important that we return a serializable object here because we're passing data back and forth between the headless Chromium instance and our Node script. If we just passed the result of getBoundingClientRect, it would become contextified within the browser, which means that it wouldn't be able to get passed through.

[2:06] Finally we await page.screenshot. We clip the screenshot using the boundingRect dimensions that we got in our previous page.evaluate. This gives us a buffer which is all of the data from our screenshot and the div that we rendered.

[2:19] Finally, there's a couple of magic properties that we need to set. We need to set isBase64Encoded to true in our response. We'll set the header's content type to image PNG and the content length to the buffer length.

[2:30] Interestingly, we have to set the buffer length as a string in content length and not as a number. Also note that we don't pass the buffer directly back in the body of the response. We toString it to a base 64 representation.

[2:43] If we open a Node REPL and we try to require our gen-opengraph-image, we can see that we need to install playwright-core. Playwright-core is an additional package that our third party package depends on. If we run the handler in a Node REPL by requiring the file and destructuring the handler, we can see that we've mistyped something.

[3:00] In this case, context is defined twice because defined in the arguments as well as a constant. We'll change the argument to ctx to differentiate them. If we run the handler now, we see something promising. Chromium revision is not downloaded. For us, this doesn't matter. It just means we won't be able to test the function locally.

[3:19] Luckily, because we're using Netlify functions, if we ever need to make changes, we can do a deploy preview to test the function. We'll add and commit our gen-opengraph-image code, the package.json with the new dependencies, as well as the yarn.lock.

[3:30] Note that our build failed because we can't find Playwright AWS Lambda in our file, which is strange because we already installed it. This is where our makefile comes in. Netlify doesn't automatically handle our dependencies for us. We'e going to have to handle that ourselves.

[3:43] In this case, we're going to CD into the function's gen-opengraph-image directory and run yarn. Note that in case yarn was not found. This isn't a problem for us in CI as we can run npm install instead.

[3:54] Note that we get a couple warnings about not having a package-lock.json file because we're not using it locally. We can get yarn to work in CI, but in this case, we don't need to because we aren't using any of the features.

[4:05] Now we've deployed the function. We see another error if we hit the URL.Cannot read property getBoundingClientRect of undefined. That's because we have corgi.children . getBoundingClientRect.

[4:16] This isn't a problem for us as we can include another div inside of the div for the corgi. We've included this additional div because when we render into corgi, we want the user's component to have control over everything.

[4:27] We could also choose to getBoundingClientRect on the corgi div itself, but we're just using this as a place that the user can render a component into as opposed to being the actual size of the actual image that we want to render. This allows the component itself to control how big the screenshot will be.

[4:43] Now if we refresh our function URL, we can see a screenshot of corgis. Note that we haven't specified any sizing. We don't have any serious content here, so the screenshot looks a little weird. It looks a little bit too wide. It looks a little small as well. We'll fix this when we work on porting the component into Playwright.