By Liam Bigelow
We’re delighted to launch Pagefind, an open-source tool that adds search to your static websites without hosting any infrastructure, while respecting your users’ bandwidth.
At CloudCannon, we firmly believe there are very few challenges that should block the path to static site adoption, and we’re constantly working to make that journey as joyful as possible for everyone with a presence on the web.
Our SSGs through the ages series delves into the history of this space, and one of the trends that we’re seeing is larger and larger projects migrating to static websites, helped in part by the efficiency of static site generators like Hugo. We build many such sites for ourselves — the CloudCannon documentation is nothing to sneeze at — as well as for our Enterprise partners, and our customers build yet more on our platform every day. As this scale continues to increase, we find ourselves encountering new and interesting challenges. In the past we have released open-source tools for component-driven development, internationalization, pagination and portability. Now, we have our sights set on search.
The Problem
You’ve just built a large documentation website and you’re ready to launch, but first, you want people to be able to search your site. What do you pick?
The way we see it, this is a fork in the road. In one direction, you’d be grabbing a frontend search library and running the queries inside your users’ browser. In the other, you’d be spinning up your own infrastructure, or signing up for a third-party platform.
Personally, I love the idea of frontend search. It means I don’t have to maintain extra servers or integrate with a third party, and I can continue to deliver an entirely static site contained within its repository. It fits with CloudCannon’s Git-based content ethos as well. Much like how you continue to own your content via Git, you will continue to own your search.
Unfortunately, most static search libraries only work on sufficiently small sites; frontend search necessitates sending a search index to the user, and with existing tools a single index can be many megabytes for a large site . That’s a big problem for our users on low-bandwidth devices, and even if your search works well now, what will happen when your site grows? Plus, building out a local index can be a chore, often feeling like an exercise in re-templating your content into a different format.
It’s these limitations that often drives developers to connect a third-party platform, or host your own search index. This would fix your scaling problem, but then you’d have external dependencies on extra infrastructure or a third-party vendor, and you’d start to erode the original benefits of a fully static site.
After delivering many projects via both avenues, we set out on the journey of building a tool that meets our design goals — namely, efficiently searching our large sites well into the future, without shifting the burden to our users.
Our Solution: Pagefind
This is where Pagefind comes in, neatly solving the issues we encounter day to day, and even adding some handy features along the way. Pagefind works great on the smallest sites you have on hand, and comfortably scales with you up to some of the largest static sites you can think of — we can run a full-text search on the entirety of MDN in under 300KB total, including the Pagefind library itself. For most sites, this will be closer to 100KB. All without hosting any dedicated infrastructure.
Pagefind exists as two halves. First, Pagefind is a CLI application that runs after your site builds and indexes the rendered HTML, automatically injecting everything needed to search it into the static contents. This workflow fits into a methodology we call “Static Site Chaining”, static site generators that themselves take a static site as input. This allows you to get off the ground with zero config, and control what is and isn’t indexed from your existing templates directly.
The other half of Pagefind is the frontend search library that accesses the index and runs queries against it. The magic happens in the handoff between these two halves, and primarily in the way Pagefind outputs index chunks. Rather than build one large search index, Pagefind splits the search space into ordered chunks. This means that searching for the word “CloudCannon” doesn’t need to load the region of the index containing the word “Jamstack”. Additionally, full text and metadata for results are stored in yet another location, giving you fine grained control over how much is loaded over the network at a given time. Even better, since Pagefind handles injecting the library into your site and loading it in the browser, this internal structure isn’t something you ever interface with.
To give you a taste of how easy search can be, here’s how to index a Hugo site after it builds:
hugo
npx pagefind --source public
Or Jekyll:
jekyll build
npx pagefind --source _site
Indeed, any static folder of HTML files can be indexed by Pagefind. And with a CloudCannon postbuild script, you can automatically index your site every time it builds.
Now, to search our site in the browser:
let pagefind = await import("/_pagefind/pagefind.js");
let search = await pagefind.search("nice");
let result = await search.results[0].data();
Or, for the easiest search experience on the planet, just drop the Pagefind UI snippet into your template, customize the CSS variables, and let it do its thing.
You can test out how quickly Pagefind searches the CloudCannon blog.
To say we’re all pretty excited about this one is an understatement. Plus, beyond simple search queries Pagefind supports “exact quote searches”, tagging and filtering content, term frequency ranking, and more. All in the same low-bandwidth package that keeps our firm footing in the #leanweb.
To get started with Pagefind, all documentation can be found at pagefind.app.
We’re excited to see more people use Pagefind, and even more excited to get feedback! So if you hit any problems, or have any ideas to improve Pagefind, open an issue or a discussion in the GitHub repository and we’ll be there to help.
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