Squawkbox is a boiler fleet monitor.

A while ago I was reading about Wayland and this quote stuck with me: A stated goal of Wayland is “every frame is perfect”. And I think this is a goal we should all aspire to. Wayland is talking about the technical side of things (modern GPU stacks are very complex and Wayland is trying to take control back) but it could be applied to UI too. The rule of thumb is: If I take a screenshot of your app at any moment, it must make sense Why care about every frame? It builds trust. Users can’t see the code, so UI is the only way for them to judge the quality of the app. If UI looks good, that means developers had time to polish it, which means that they probably spent a comparable amount of time to iron out the code. It’s a heuristic, but a reasonable one. Now, what does it mean in practice? I can think of a few things: No white flashes between screens. No partially loaded content. No relayout while content loads. Internally consistent. If one part of the UI says “1 update available”, another part should not say “Checking for updates...” Precise animations. Animations often end up being forgotten. A UI might look great in both start and end states but very janky in between. Like this: If you feel like there are weird things going on there, there are! Look at slowed down version: Now let’s apply our rule and take screenshots in the middle of the animation. This doesn’t look right: Neither does this: Both of these frames are not perfect. Let’s look at another example. Safari: Placeholder text here moves from the center but cursor animates from the left position: Not the end of the world by any means, but it does create a feeling that these two components are not in sync with each other. Next thought: maybe they weren’t designed together? If so, then they might not work well together. That’s how trust is lost. This desynchronization can lead to a lot of confusion. For example, in Photos, when switching between Crop and Adjust mode, picture snaps into place immediately but the crop border is animated: This creates a false feeling that something subtly changes when you switch between modes. And you know what? I don’t want my UI to give me false feelings. I want it to be a precise instrument, not an animated toy. Sometimes animations are supposed to help you understand a transition, so it’s doubly sad when they make it harder. Follow the magnifying glass: Same with Youtube. They had the simplest task in the world: move a rectangle from one position to another! Yet they decided to do something very strange: Can you explain this? Does it make sense? Probably a technical limitation of the DOM architecture they decided earlier on. I call these situations “The technology has outsmarted the programmer”. But no matter the reason, the result is an imperfect frame. Sometimes animations are left out as an afterthought. Whatever happens, happens. Then we get this: The details are fascinating to watch: So yeah. Please pay attention not only to the start and end states, but also to everything in between. Every frame matters. I’ll leave you with this unprovoked zoom animation from Preview app. Take care!

In “Why is Claude an Electron App?” Drew Breunig wonders: Claude spent $20k on an agent swarm implementing (kinda) a C-compiler in Rust, but desktop Claude is an Electron app. If code is free, why aren’t all apps native? And then argues that the answer is that LLMs are not good enough yet. They can do 90% of the work, so there’s still a substantial amount of manual polish, and thus, increased costs. But I think that’s not the real reason. The real reason is: native has nothing to offer. API-wise, native apps lost to web apps a long time ago. Native APIs are terrible to use, and OS vendors use everything in their power to make you not want to develop native apps for their platform. That explains the rise of Electron before LLM times, but it’s also a problem that LLMs solve now: if that was a real barrier to developing native apps, it doesn’t exist anymore. Then there’re looks and consistency. Some time ago, maybe in the late 90s and 2000s, native was ahead. It used to look good, it was consistent, and it all actually worked: the more apps used native look and feel, the better user experience was across apps (which we used to call programs). These days, though, native is as bad as the web, if not worse. Consistency is basically out the window. Anything can look like anything, buttons have no borders, contrast doesn’t exist, and neither do conventions. Apple, for example, seems to place traffic lights and corner radius by vibes rather than by any measurable guidelines. Maybe the server should round the corners? Looks could be good, but they also can be bad, and then you are stuck with platform-consistent, but generally bad UI (Liquid Glass ahem). It changes too often, too: the app you made today will look out of place next year, when Apple decides to change look and feel yet again. There’s no native look anymore. Computer UIs also degrade over time Theoretically, native apps can integrate with OS on a deeper level. This sounds nice, but what does that mean in practice? There are almost no good interoperable file formats; everything is locked inside individual apps, most services moved to the web, and OSes dropped the ball for making a good shared baseline. You can integrate with OS-provided calendar, but you can’t do it with web calendar. Well, you can, of course, but it’s easier on the web; native doesn’t help with it at all. Web pages only lead to more web pages Finally, the last hope of people longing for native is performance. They feel that native apps will be faster. Well, they can, but it doesn’t mean they will. Web apps can be faster, too, but in practice, nobody cares. There’s no technical reason why Slack needs to load 80 MiB just to show 10 channel names and 3 messages on a screen. The web is not the problem here! It’s a choice to be bad. What makes you think it’ll be different once the company decides to move to native? Don’t get me wrong: writing this brings me no joy. I don’t think web is a solution either. I just remember good times when native did a better-than-average job, and we were all better for using it, and it saddens me that these times have passed. I just don’t think that kidding ourselves that the only problem with software is Electron and it all will be butterflies and unicorns once we rewrite Slack in SwiftUI is not productive. The real problem is a lack of care. And the slop; you can build it with any stack.

I have a weird relationship with statistics: on one hand, I try not to look at it too often. Maybe once or twice a year. It’s because analytics is not actionable: what difference does it make if a thousand people saw my article or ten thousand? I mean, sure, you might try to guess people’s tastes and only write about what’s popular, but that will destroy your soul pretty quickly. On the other hand, I feel nervous when something is not accounted for, recorded, or saved for future reference. I might not need it now, but what if ten years later I change my mind? Seeing your readers also helps to know you are not writing into the void. So I really don’t need much, something very basic: the number of readers per day/per article, maybe, would be enough. Final piece of the puzzle: I self-host my web projects, and I use an old-fashioned web server instead of delegating that task to Nginx. Static sites are popular and for a good reason: they are fast, lightweight, and fulfil their function. I, on the other hand, might have an unfinished gestalt or two: I want to feel the full power of the computer when serving my web pages, to be able to do fun stuff that is beyond static pages. I need that freedom that comes with a full programming language at your disposal. I want to program my own web server (in Clojure, sorry everybody else). Existing options All this led me on a quest for a statistics solution that would uniquely fit my needs. Google Analytics was out: bloated, not privacy-friendly, terrible UX, Google is evil, etc. What is going on? Some other JS solution might’ve been possible, but still questionable: SaaS? Paid? Will they be around in 10 years? Self-host? Are their cookies GDPR-compliant? How to count RSS feeds? Nginx has access logs, so I tried server-side statistics that feed off those (namely, Goatcounter). Easy to set up, but then I needed to create domains for them, manage accounts, monitor the process, and it wasn’t even performant enough on my server/request volume! My solution So I ended up building my own. You are welcome to join, if your constraints are similar to mine. This is how it looks: It’s pretty basic, but does a few things that were important to me. Setup Extremely easy to set up. And I mean it as a feature. Just add our middleware to your Ring stack and get everything automatically: collecting and reporting. (def app (-> routes ... (ring.middleware.params/wrap-params) (ring.middleware.cookies/wrap-cookies) ... (clj-simple-stats.core/wrap-stats))) ;; <-- just add this It’s zero setup in the best sense: nothing to configure, nothing to monitor, minimal dependency. It starts to work immediately and doesn’t ask anything from you, ever. See, you already have your web server, why not reuse all the setup you did for it anyway? Request types We distinguish between request types. In my case, I am only interested in live people, so I count them separately from RSS feed requests, favicon requests, redirects, wrong URLs, and bots. Bots are particularly active these days. Gotta get that AI training data from somewhere. RSS feeds are live people in a sense, so extra work was done to count them properly. Same reader requesting feed.xml 100 times in a day will only count as one request. Hosted RSS readers often report user count in User-Agent, like this: Feedly/1.0 (+http://www.feedly.com/fetcher.html; 457 subscribers; like FeedFetcher-Google) Mozilla/5.0 (compatible; BazQux/2.4; +https://bazqux.com/fetcher; 6 subscribers) Feedbin feed-id:1373711 - 142 subscribers My personal respect and thank you to everybody on this list. I see you. Graphs Visualization is important, and so is choosing the correct graph type. This is wrong: Continuous line suggests interpolation. It reads like between 1 visit at 5am and 11 visits at 6am there were points with 2, 3, 5, 9 visits in between. Maybe 5.5 visits even! That is not the case. This is how a semantically correct version of that graph should look: Some attention was also paid to having reasonable labels on axes. You won’t see something like 117, 234, 10875. We always choose round numbers appropriate to the scale: 100, 200, 500, 1K etc. Goes without saying that all graphs have the same vertical scale and syncrhonized horizontal scroll. Insights We don’t offer much (as I don’t need much), but you can narrow reports down by page, query, referrer, user agent, and any date slice. Not implemented (yet) It would be nice to have some insights into “What was this spike caused by?” Some basic breakdown by country would be nice. I do have IP addresses (for what they are worth), but I need a way to package GeoIP into some reasonable size (under 1 Mb, preferably; some loss of resolution is okay). Finally, one thing I am really interested in is “Who wrote about me?” I do have referrers, only question is how to separate signal from noise. Performance. DuckDB is a sport: it compresses data and runs column queries, so storing extra columns per row doesn’t affect query performance. Still, each dashboard hit is a query across the entire database, which at this moment (~3 years of data) sits around 600 MiB. I definitely need to look into building some pre-calculated aggregates. One day. How to get Head to github.com/tonsky/clj-simple-stats and follow the instructions: Let me know what you think! Is it usable to you? What could be improved? P.S. You can try the live example at tonsky.me/stats. The data was imported from Nginx access logs, which I turned on and off on a few occasions, so it’s a bit spotty. Still, it should give you a general idea.