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Google published Zanzibar: Google’s Consistent, Global Authorization System in 2019. It describes a system for authorization – enforcing who can do what – which maxes out both flexibility and scalability. Google has lots of different apps that rely on Zanzibar, and bigger scale than practically any other company, so it needed Zanzibar. The Zanzibar paper made quite a stir. There are at least four companies that advertise products as being inspired by or based on Zanzibar. It says a lot for everyone to loudly reference this paper on homepages and marketing materials: companies aren’t advertising their own innovation as much as simply saying they’re following the gospel. A short list of companies & OSS products I found: Companies WorkOS FGA Authzed auth0 FGA Ory Permify Open source Ory Keto (Go) Warrant (Go) probably the basis for WorkOS FGA, since WorkOS acquired Warrant. SpiceDB (Go) the basis for Authzed. Permify (Go) OpenFGA (Go) the basis of auth0 FGA. I read the paper, and have a few notes, but the Google Zanzibar Paper, annotated by AuthZed is the same thing from a real domain expert (albeit one who works for one of these companies), so read that too, or instead. Features My brief summary is that the Zanzibar paper describes the features of the system succinctly, and those features are really appealing. They’ve figured out a few primitives from which developers can build really flexible authorization rules for almost any kind of application. They avoid making assumptions about ID formats, or any particular relations, or how groups are set up. It’s abstract and beautiful. The gist of the system is: Objects: things in your data model, like documents Users: needs no explanation Namespaces: for isolating applications Usersets: groups of users Userset rewrite rules: allow usersets to inherit from each other or have other kinds of set relationships Tuples, which are like (object)#(relation)@(user), and are sort of the core ‘rule’ construct for saying who can access what There’s then a neat configuration language which looks like this in an example: name: "doc" relation { name: "owner"} relation { name: "editor" userset_rewrite { union { child { _this f } } child { computed_userset { relation: "owner" } } relation { name: "viewer" userset_rewrite { union { child {_this f} } child { computed_userset & relation: "editor" 3 } child { tuple_to_userset { tupleset { relation: "parent" } computed_userset { object: $TUPLE_USERSET_OBJECT # parent folder relation: "viewer" } } } } } } It’s pretty neat. At this point in the paper I was sold on Zanzibar: I could see this as being a much nicer way to represent authorization than burying it in a bunch of queries. Specifications & Implementation details And then the paper discusses specifications: how much scale it can handle, and how it manages consistency. This is where it becomes much more noticeably Googley. So, with Google’s scale and international footprint, all of their services need to be globally distributed. So Zanzibar is a distributed system, and it is also a system that needs good consistency guarantees so that it avoid the “new enemy” problem, nobody is able to access resources that they shouldn’t, and applications that are relying on Zanzibar can get a consistent view of its data. Pages 5-11 are about this challenge, and it is a big one with a complex, high-end solution, and a lot of details that are very specific to Google. Most noticeably, Zanzibar is built with Spanner Google’s distributed database, and Spanner has the ability to order timestamps using TrueTime, which relies on atomic clocks and GPS antennae: this is not standard equipment for a server. Even CockroachDB, which is explicitly modeled off of Spanner, can’t rely on having GPS & atomic clocks around so it has to take a very different approach. But this time accuracy idea is pretty central to Zanzibar’s idea of zookies, which are sort of like tokens that get sent around in its API and indicate what time reference the client expects so that a follow-up response doesn’t accidentally include stale data. To achieve scalability, Zanzibar is also a multi-server architecture: there are aclservers, watchservers, a Leopard indexing system that creates compressed skip list-based representations of usersets. There’s also a clever solution to the caching & hot-spot problem, in which certain objects or tuples will get lots of requests all at once so their database shard gets overwhelmed. Conclusions Zanzibar is two things: A flexible, relationship-based access control model A system to provide that model to applications at enormous scale and with consistency guarantees My impressions of these things match with AuthZed’s writeup so I’ll just quote & link them: There seems to be a lot of confusion about Zanzibar. Some people think all relationship-based access control is “Zanzibar”. This section really brings to light that the ReBAC concepts have already been explored in depth, and that Zanzibar is really the scaling achievement of bringing those concepts to Google’s scale needs. link And Zookies are very clearly important to Google. They get a significant amount of attention in the paper and are called out as a critical component in the conclusion. Why then do so many of the Zanzibar-like solutions that are cropping up give them essentially no thought? link I finished the paper having absorbed a lot of tricky ideas about how to solve the distributed-consistency problems, and if I were to describe Zanzibar, those would be a big part of the story. But maybe that’s not what people mean when they say Zanzibar, and it’s more a description of features? I did find that Permify has a zookie-like Snap Token, AuthZed/SpiceDB has ZedTokens, and Warrant has Warrant-Tokens. Whereas OpenFGA doesn’t have anything like zookies and neither does Ory Keto. So it’s kind of mixed on whether these Zanzibar-inspired products have Zanzibar-inspired implementations, or focus more on exposing the same API surface. For my own needs, zookies and distributed consistency to the degree described in the Zanzibar paper are overkill. There’s no way that we’d deploy a sharded five-server system for authorization when the main application is doing just fine with single-instance Postgres. I want the API surface that Zanzibar describes, but would trade some scalability for simplicity. Or use a third-party service for authorization. Ideally, I wish there was something like these products but smaller, or delivered as a library rather than a server.
I watched a large part of All Watched Over By Machines of Loving Grace this month. This also counts as a “listening” item, because the theme song, “Baby Love Child” by Pizzicato Five, is also spectacular. Guitar Moves is a good series of interviews by Matt Sweeney, who I mostly know via his involvement in Bonnie Prince Billy. It’s a really cool format. I like how he interviews guitarists with recognizable sounds, and you get to see how little they need to play to sound just like themselves. The episode with St. Vincent is excellent too: she’s one of my guitar heroes: check out the guitar solo in Just The Same But Brand New, or her version of Dig a Pony. I also watched No Other Land. Everyone should watch No Other Land. AI thoughts roundup I don’t have a conclusion. Really, that’s my current state: ambivalence. I acknowledge that these tools are incredibly powerful, I’ve even started incorporating them into my work in certain limited ways (low-stakes code like POCs and unit tests seem like an ideal use case), but I absolutely hate them. I hate the way they’ve taken over the software industry, I hate how they make me feel while I’m using them, and I hate the human-intelligence-insulting postulation that a glorified Excel spreadsheet can do what I can but better. Nolan Lawson: AI ambivalence As I always say, the purpose of the system is what it does. Or, in this case, how I think about AI stuff is mostly affected by how people use AI stuff, and how people use AI stuff is a real mixed bag. There’s the tidal wave of spam, the aesthetic of fascism, the low-effort marketing materials with nonsense images, the non-consensual AI porn. I see all of the bad stuff every day both online and in the odd subway ad. The good stuff seems pretty theoretical, though: the press releases about AI-driven medical advances never seem to break into the real world. The stories about engineers 10x’ing their ability seem pretty mixed: we’re already at the hangover-and-regret phase with programmers bemoaning how they’ve generated so much slop and lost so much knowledge. Anyway, I’m mildly optimistic about the potential! But it’s a lot like crypto in that you could theoretically use the technology for something good but most people loudly used it for bad stuff, and people including me judged it based on what it did. AI has to start doing some good stuff soon. Potential isn’t enough. I think one thing chatGPT’s invention has revealed is how many people - including some very important people in society - find just basic reading and writing to be laborious and cumbersome to perform, and how oddly closely that type of strained literacy correlates with having other shitty opinions. From mtsw on Bluesky, about this story about Andrew Cuomo using ChatGPT to half-assedly write a policy platform. Right off the bat I should say that judging people for their level of literacy reeks of classism and so on. My own ability to read & write has a lot to do with my place in society: I went to good schools, had a stable home life, and smart parents. However, “the way that society was set up” kind of evened this out. Extremely social people with cultural capital and chiseled jawlines and biceps would get their rewards, and people like… myself, we would get rewarded for literacy and critical thinking. When one group needed the other, it was usually some kind of payment or partnership: Cuomo pays his scriptwriter, the TV show creator pays the actors. And some people can do both sides of the equation. But LLMs definitely indicate that people do not like this deal. Whew, they don’t like writing, but they also don’t like paying the writers or reading what they write. Maybe they could rejigger the system so that they could do it all. They have ideas for music and art but no interest in learning about music, practicing instruments, going to art school, or concentrating on a task for a long time, so why not generate it all? Why not, well - there are reasons, those reasons being that the generated output usually passes their own vibe check but once someone who looks closely at things or reads all the words encounters it, everyone points at the slop and it’s embarrassing. (Cuomo will never be embarrassed) Plus, you’re always going to get average results by asking a device that is incapable of creativity or thought. Also, you’ll miss out on the human experience of creating. And you’ll be indirectly feeding output data into training data for future LLMs, consequentially making their output worse. (Cuomo does not care about consequences) Colophon update I’ve moved the images for this website to Bunny (that’s an affiliate link, here’s a non-affiliate link if that’s what you prefer). When I initially moved my photos to this website, I set them up with Amazon S3 for storage and CloudFront to serve them with a CDN. Using AWS is painful for me, so I moved them to Cloudflare R2, which is Cloudflare’s equivalent to S3, and Cloudflare as a CDN. Thanks to owning my own domains, swapping out image hosts is pretty quick: switching to Bunny took all of five minutes. So what’s the deal with Bunny? Partly I’ve become a little more negative on Cloudflare and R2: I think Cloudflare’s technology is neat, but R2 has iffy reliability and Cloudflare has iffy politics. I’m also intrigued by diversifying my dependencies geographically. Bunny is a Slovenian company, and my email is from an Australian company. This probably won’t have any practical effect, but it feels kind of good for obvious reasons to even minutely hedge my bets here. So far Bunny has been great. They don’t support the S3 protocol but they do support SFTP, which works just as well for my purposes and works great with the beautiful Transmit app. Before, with R2, I was using the significantly less beautiful Cyberduck application because Cloudflare R2 doesn’t support all of the S3 protocol. It seems to be just as fast as Cloudflare was, too. And I’m somewhat reassured by the prospect of paying Bunny. I don’t like the feeling of getting “free” services like I can from Cloudflare. I want that customer relationship. Reading Then again, pop culture is powerful, and even the dumbest marketing both affects and reflects it. Busch Light’s can holder shaped like a cup that holds beer is dumb, which is fine, because most beer promos are. But the fact that the brand frames it as a functional, masculine alternative to Stanley’s H2.0 Flowstate affirms a similarly retrograde outlook on gender roles to the one that young American men are seeking out on the political right. From my friend Dave’s article about Busch Light’s weird attempt to riff on the Stanley Tumbler trend. I was once a loyal listener of the Chapo Trap House podcast, but fell off of it in 2020 when their support of Bernie Sanders led them to be jerks about Elizabeth Warren. But reading this Vanity Fair article about the cohosts of the podcast endeared them to me a bit. “Like to thank” is linguistic phlegm. “I’d like to thank the Academy.” They’d “like to thank” me. Well I’d like to be 6’3” and drive a G Wagon, thanks. I’d like you to accept my novella. I’d like to quit paying three dollars to Submittable every time I want to send a story out. The world is full of actions I would like to do. The most direct way to say thank you is just to say it: “thank you, name, for doing X.” “I’d like to thank” is a performative thanks, a thanks with a smirk and a blink, eyeing for extra credit. Just because people say it in their award show acceptance speeches doesn’t mean you should say it, too. In fact, that’s the reason you shouldn’t say it. Loved this article “Close reading my rejections” from friend of the blog Barrett Hathcock.
(async () => { const colors = ['fb6b1d','e83b3b','831c5d','c32454','f04f78','f68181','fca790','e3c896','ab947a','966c6c','625565','3e3546','0b5e65','0b8a8f','1ebc73','91db69','fbff86','fbb954','cd683d','9e4539','7a3045','6b3e75','905ea9','a884f3','eaaded', '8fd3ff', '4d9be6', '4d65b4', '484a77', '30e1b9', '8ff8e2'].map(c => `#${c}`); const mask = document.querySelector('#mask'); const replacement = await fetch('/images/2025-04-12-tidbyt-second-life-tidbyt-mask.svg').then(r => r.text()); mask.style = ''; mask.innerHTML = replacement; let i = 0; let delay = 10; const svg = mask.querySelector('svg'); svg.removeAttribute('width'); svg.removeAttribute('height'); svg.setAttribute('style', 'width:auto;height:auto;position:absolute;top:0;right:0;bottom:0;left:0;opacity:0.4;'); for (const path of svg.querySelectorAll('path')) { delay += 20; delay *= 1.02; setTimeout(() => { path.setAttribute('fill', colors[i++ % colors.length]); }, delay) path.addEventListener('mouseover', () => { path.setAttribute('fill', colors[i++ % colors.length]); }); } })() Remember the Tidbyt? It’s a super low-resolution, internet-connected, wood-paneled display that I wrote a review of it back in 2022. It’s been on my shelf for years now, showing the time, weather, warning me when the UV is going to be high. In 2023 I used it as an excuse to learn some Rust, to render custom graphics. It’s a toy, a distraction, a worry stone for me to work on when I need something open-ended and low-stakes. Anyway, the company that made the Tidbyt is no more. They got acquihired by Modal, a company that makes serverless AI compute hosting. So, they aren’t making devices right now, and the blog post promises that their cloud services will keep working. I don’t hold anything against the Tidbyt team: in fact, our Val Town office was coincidentally right next to theirs in a WeWork, and we met in real life! They’re very nice folks, and were doing so much with a small team. Lots of respect to them. Modal made a smart choice acquiring Tidbyt. But realistically, it’s time to make sure my device doesn’t become e-waste. The Tidbyt is ready for this One of the biggest critiques of the Tidbyt was that it was just an LED matrix and an ESP chip. You could buy an LED matrix on Sparkfun, the ESP, a power supply, some wood for the enclosure, and you’d have your own DIY Tidbyt. Maybe you could do it for half the price! But that’s also a strength. The Tidbyt is not some custom SoC with an exotic custom software stack and boutique hardware. It is what it looks like: a neat combination of commonplace parts. That makes it kind of future-proof and flexible. The first step is to replace the firmware. Tidbyt’s stock firmware routes all of its requests through the Tidbyt company’s servers. I want to eliminate that hop. Replacing the firmware Thankfully, Tidbyt published their ‘HDK’, which is an open source version of their stock firmware. It’s remarkably simple: It connects to Wifi It downloads a WebP image from a URL It displays that WebP image The HDK contains the code to do this stuff. There’s very little code required, but it does drag in a WebP decoder, Wifi library, and a library for running the LED matrix. But, setting up the HDK I ran into issues both small and large: it had issues with HTTPS URLs and Wifi passwords that contain spaces. Plus nobody has been added as a contributor to the HDK repository, so Pull Requests aren’t being accepted and it hasn’t had a change in 7 months. But the community came to the rescue with tronbyt’s firmware-http, a fork of the HDK that fixes every issue I experienced. Open source works! So back in 2022 I included this chart of the Tidbyt network: With an updated HDK, this workflow is a lot simpler. Instead of sending images to the Tidbyt servers and those Tidbyt servers delivering them to my device, the device makes requests directly of the server that generates the images. Replacing pixlet The Tidbyt team wrote pixlet, a little framework for generating pixel graphics that the Tidbyt displays. It lets you define a React-like tree of components - some text in a stack, a rectangle, images, and so on - and does all of the layout and rendering. The tronbyt community also forked pixlet and are actively developing it, which is fantastic. But this part of the stack I really never liked. That’s why I spent so much time reimplementing it in Rust and JavaScript. Partly it’s the language - pixlet apps are written in starlark, which is kind of an outgrowth of the Bazel build system from Google. Starlark is sort of like Python, but isn’t actually compatible with anything in the Python ecosystem. It’s very niche, limited, and overall just weird. I think I understand why Tidbyt would choose Starlark - it’s fast and has hermetic execution - making it safe to run untrusted Starlark programs because they can’t access the filesystem, network, or even the system clock without being given explicit controlled APIs to do those things. If you’re building a cloud service that runs a lot of untrusted user code, dictating that code is all Starlark is a really good cheat code - I know firsthand how hard it is to run untrusted JavaScript. But I’m not building a cloud service full of untrusted code. People who are self-hosting their Tidbyt devices (dozens of us!) don’t benefit from the tradeoffs of the Starlark language. They’d be better off with something normal. I rewrote pixlet again It’s called indiepixel and it’s a Python reimplementation of pixlet. It supports almost the entire pixlet API, and comes with the added benefit of being Python. You can use Python modules! You can read from the filesystem, parse CSVs, do all of your usual Python stuff. You can embed it in a Python application to render some graphics. What does indiepixel do currently? Renders text in the glorious retro BDF pixel font format. Renders pixelated pie charts, rectangles, and boxes. Supports animation for its WebP outputs. Provides a nice UI for browsing your selection of screens. It’ll probably never be finished, but it works well enough to power my Tidbyt. I’m running indiepixel on a free Render server instance, but it should run pretty much the same on any Python-compatible hosting: the only tricky dependency is Pillow, which it uses for image parsing and rendering. My free time for computer-oriented side projects has been limited, due to other commitments and an intention to get offline on the weekends. I’ve been sewing, biking, and running more. So I really want a side project I can enjoy, and indiepixel has fit the bill. It’s really satisfying to implement a new widget and see it rendered in blocky 64x32 pixels. The Pillow image rendering library for Python is mostly wonderful and very powerful. Why Python? Why is indiepixel written in Python? Well - I learned from tidbyt-rs that Rust would be an awkward fit as a scripting language for rendering graphics. The well-known Rust complexities around memory management made simple things difficult for me, which would make them totally unacceptable for others. Besides the attraction of being able to compile a small binary that might be able to run on the Tidbyt itself, Rust didn’t have many other advantages. The Pillow module really is such an advantage for Python. JavaScript doesn’t have a real alternative: there’s sharp, a great module for image conversion, but nothing that has such a great canvas interface. node-canvas is fine, but it doesn’t support WebP or animation, which are critical features for this project. I also wanted a test out the amazing new Python tooling that Astral is cooking up, like uv. I now have a better grasp of the Python ecosystem than I did a few months ago, and it’s optimistic but mixed. uv is amazing, but Python has a lot of legacy cruft around packaging. People are critical of NPM, but I think it did benefit from being established after PyPI and learning from its lessons. Thank you Steven Loria for a PR that fixed everything and made it all work and saved me months of tweaking settings. The graphic I watercolored that Tidbyt a while while ago and have been seriously dragging my feet on finishing this blog post. Sometimes the watercolor-illustration wags the technical-blog-post dog’s tail? Anyway, it’s a callback to that little world, with some small tweaks: this time I thought it’d be nice to have it be both watercolored and interactive. That ‘cybernetic’ feel. The secret recipe: a nice palette from lospec, creating a black & white mask of areas in Affinity Photo and vectorizing it with potrace, and then just some JavaScript that recolors based on hover handling. If you’re using the Tidbyt or some similar pixel-displaying device, try out indiepixel! It’s niche and has required a silly amount of effort to generate a glorified weather clock in my apartment, but it was a fun time chasing another interest.
I used to make little applications just for myself. Sixteen years ago (oof) I wrote a habit tracking application, and a keylogger that let me keep track of when I was using a computer, and generate some pretty charts. I’ve taken a long break from those kinds of things. I love my hobbies, but they’ve drifted toward the non-technical, and the idea of keeping a server online for a fun project is unappealing (which is something that I hope Val Town, where I work, fixes). Some folks maintain whole ‘homelab’ setups and run Kubernetes in their basement. Not me, at least for now. But I have been tiptoeing back into some little custom tools that only I use, with a focus on just my own computing experience. Here’s a quick tour. Hammerspoon Hammerspoon is an extremely powerful scripting tool for macOS that lets you write custom keyboard shortcuts, UIs, and more with the very friendly little language Lua. Right now my Hammerspoon configuration is very simple, but I think I’ll use it for a lot more as time progresses. Here it is: hs.hotkey.bind({"cmd", "shift"}, "return", function() local frontmost = hs.application.frontmostApplication() if frontmost:name() == "Ghostty" then frontmost:hide() else hs.application.launchOrFocus("Ghostty") end end) Not much! But I recently switched to Ghostty as my terminal, and I heavily relied on iTerm2’s global show/hide shortcut. Ghostty doesn’t have an equivalent, and Mikael Henriksson suggested a script like this in GitHub discussions, so I ran with it. Hammerspoon can do practically anything, so it’ll probably be useful for other stuff too. SwiftBar I review a lot of PRs these days. I wanted an easy way to see how many were in my review queue and go to them quickly. So, this script runs with SwiftBar, which is a flexible way to put any script’s output into your menu bar. It uses the GitHub CLI to list the issues, and jq to massage that output into a friendly list of issues, which I can click on to go directly to the issue on GitHub. #!/bin/bash # <xbar.title>GitHub PR Reviews</xbar.title> # <xbar.version>v0.0</xbar.version> # <xbar.author>Tom MacWright</xbar.author> # <xbar.author.github>tmcw</xbar.author.github> # <xbar.desc>Displays PRs that you need to review</xbar.desc> # <xbar.image></xbar.image> # <xbar.dependencies>Bash GNU AWK</xbar.dependencies> # <xbar.abouturl></xbar.abouturl> DATA=$(gh search prs --state=open -R val-town/val.town --review-requested=@me --json url,title,number,author) echo "$(echo "$DATA" | jq 'length') PR" echo '---' echo "$DATA" | jq -c '.[]' | while IFS= read -r pr; do TITLE=$(echo "$pr" | jq -r '.title') AUTHOR=$(echo "$pr" | jq -r '.author.login') URL=$(echo "$pr" | jq -r '.url') echo "$TITLE ($AUTHOR) | href=$URL" done Tampermonkey Tampermonkey is essentially a twist on Greasemonkey: both let you run your own JavaScript on anybody’s webpage. Sidenote: Greasemonkey was created by Aaron Boodman, who went on to write Replicache, which I used in Placemark, and is now working on Zero, the successor to Replicache. Anyway, I have a few fancy credit cards which have ‘offers’ which only work if you ‘activate’ them. This is an annoying dark pattern! And there’s a solution to it - CardPointers - but I neither spend enough nor care enough about points hacking to justify the cost. Plus, I’d like to know what code is running on my bank website. So, Tampermonkey to the rescue! I wrote userscripts for Chase, American Express, and Citi. You can check them out on this Gist but I strongly recommend to read through all the code because of the afore-mentioned risks around running untrusted code on your bank account’s website! Obsidian Freeform This is a plugin for Obsidian, the notetaking tool that I use every day. Freeform is pretty cool, if I can say so myself (I wrote it), but could be much better. The development experience is lackluster because you can’t preview output at the same time as writing code: you have to toggle between the two states. I’ll fix that eventually, or perhaps Obsidian will add new API that makes it all work. I use Freeform for a lot of private health & financial data, almost always with an Observable Plot visualization as an eventual output. For example, when I was switching banks and one of the considerations was mortgage discounts in case I ever buy a house (ha 😢), it was fun to chart out the % discounts versus the required AUM. It’s been really nice to have this kind of visualization as ‘just another document’ in my notetaking app. Doesn’t need another server, and Obsidian is pretty secure and private.
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The appeal of "vibe coding" — where programmers lean back and prompt their way through an entire project with AI — appears partly to be based on the fact that so many development environments are deeply unpleasant to work with. So it's no wonder that all these programmers stuck working with cumbersome languages and frameworks can't wait to give up on the coding part of software development. If I found writing code a chore, I'd be looking for retirement too. But I don't. I mean, I used to! When I started programming, it was purely because I wanted programs. Learning to code was a necessary but inconvenient step toward bringing systems to life. That all changed when I learned Ruby and built Rails. Ruby's entire premise is "programmer happiness": that writing code should be a joy. And historically, the language was willing to trade run-time performance, memory usage, and other machine sympathies against the pursuit of said programmer happiness. These days, it seems like you can eat your cake and have it too, though. Ruby, after thirty years of constant improvement, is now incredibly fast and efficient, yet remains a delight to work with. That ethos couldn't shine brighter now. Disgruntled programmers have finally realized that an escape from nasty syntax, boilerplate galore, and ecosystem hyper-churn is possible. That's the appeal of AI: having it hide away all that unpleasantness. Only it's like cleaning your room by stuffing the mess under the bed — it doesn't make it go away! But the instinct is correct: Programming should be a vibe! It should be fun! It should resemble English closely enough that line noise doesn't obscure the underlying ideas and decisions. It should allow a richness of expression that serves the human reader instead of favoring the strictness preferred by the computer. Ruby does. And given that, I have no interest in giving up writing code. That's not the unpleasant part that I want AI to take off my hands. Just so I can — what? — become a project manager for a murder of AI crows? I've had the option to retreat up the manager ladder for most of my career, but I've steadily refused, because I really like writing Ruby! It's the most enjoyable part of the job! That doesn't mean AI doesn't have a role to play when writing Ruby. I'm conversing and collaborating with LLMs all day long — looking up APIs, clarifying concepts, and asking stupid questions. AI is a superb pair programmer, but I'd retire before permanently handing it the keyboard to drive the code. Maybe one day, wanting to write code will be a quaint concept. Like tending to horses for transportation in the modern world — done as a hobby but devoid of any economic value. I don't think anyone knows just how far we can push the intelligence and creativity of these insatiable token munchers. And I wouldn't bet against their advance, but it's clear to me that a big part of their appeal to programmers is the wisdom that Ruby was founded on: Programming should favor and flatter the human.
About half a year ago I encountered a paper bombastically titled “the ultimate conditional syntax”. It has the attractive goal of unifying pattern match with boolean if tests, and its solution is in some ways very nice. But it seems over-complicated to me, especially for something that’s a basic work-horse of programming. I couldn’t immediately see how to cut it down to manageable proportions, but recently I had an idea. I’ll outline it under the “penultimate conditionals” heading below, after reviewing the UCS and explaining my motivation. what the UCS? whence UCS out of scope penultimate conditionals dangling syntax examples antepenultimate breath what the UCS? The ultimate conditional syntax does several things which are somewhat intertwined and support each other. An “expression is pattern” operator allows you to do pattern matching inside boolean expressions. Like “match” but unlike most other expressions, “is” binds variables whose scope is the rest of the boolean expression that might be evaluated when the “is” is true, and the consequent “then” clause. You can “split” tests to avoid repeating parts that are the same in successive branches. For example, if num < 0 then -1 else if num > 0 then +1 else 0 can be written if num < 0 then -1 > 0 then +1 else 0 The example shows a split before an operator, where the left hand operand is the same and the rest of the expression varies. You can split after the operator when the operator is the same, which is common for “is” pattern match clauses. Indentation-based syntax (an offside rule) reduces the amount of punctuation that splits would otherwise need. An explicit version of the example above is if { x { { < { 0 then −1 } }; { > { 0 then +1 } }; else 0 } } (This example is written in the paper on one line. I’ve split it for narrow screens, which exposes what I think is a mistake in the nesting.) You can also intersperse let bindings between splits. I doubt the value of this feature, since “is” can also bind values, but interspersed let does have its uses. The paper has an example using let to avoid rightward drift: if let tp1_n = normalize(tp1) tp1_n is Bot then Bot let tp2_n = normalize(tp2) tp2_n is Bot then Bot let m = merge(tp1_n, tp2_n) m is Some(tp) then tp m is None then glb(tp1_n, tp2_n) It’s probably better to use early return to avoid rightward drift. The desugaring uses let bindings when lowering the UCS to simpler constructions. whence UCS Pattern matching in the tradition of functional programming languages supports nested patterns that are compiled in a way that eliminates redundant tests. For example, this example checks that e1 is Some(_) once, not twice as written. if e1 is Some(Left(lv)) then e2 Some(Right(rv)) then e3 None then e4 Being cheeky, I’d say UCS introduces more causes of redundant checks, then goes to great effort to to eliminate redundant checks again. Splits reduce redundant code at the source level; the bulk of the paper is about eliminating redundant checks in the lowering from source to core language. I think the primary cause of this extra complexity is treating the is operator as a two-way test rather than a multi-way match. Splits are introduced as a more general (more complicated) way to build multi-way conditions out of two-way tests. There’s a secondary cause: the tradition of expression-oriented functional languages doesn’t like early returns. A nice pattern in imperative code is to write a function as a series of preliminary calculations and guards with early returns that set things up for the main work of the function. Rust’s ? operator and let-else statement support this pattern directly. UCS addresses the same pattern by wedging calculate-check sequences into if statements, as in the normalize example above. out of scope I suspect UCS’s indentation-based syntax will make programmers more likely to make mistakes, and make compilers have more trouble producing nice error messages. (YAML has put me off syntax that doesn’t have enough redundancy to support good error recovery.) So I wondered if there’s a way to have something like an “is pattern” operator in a Rust-like language, without an offside rule, and without the excess of punctuation in the UCS desugaring. But I couldn’t work out how to make the scope of variable bindings in patterns cover all the code that might need to use them. The scope needs to extend into the consequent then clause, but also into any follow-up tests – and those tests can branch so the scope might need to reach into multiple then clauses. The problem was the way I was still thinking of the then and else clauses as part of the outer if. That implied the expression has to be closed off before the then, which troublesomely closes off the scope of any is-bound variables. The solution – part of it, at least – is actually in the paper, where then and else are nested inside the conditional expression. penultimate conditionals There are two ingredients: The then and else clauses become operators that cause early return from a conditional expression. They can be lowered to a vaguely Rust syntax with the following desugaring rules. The 'if label denotes the closest-enclosing if; you can’t use then or else inside the expr of a then or else unless there’s another intervening if. then expr ⟼ && break 'if expr else expr ⟼ || break 'if expr else expr ⟼ || _ && break 'if expr There are two desugarings for else depending on whether it appears in an expression or a pattern. If you prefer a less wordy syntax, you might spell then as => (like match in Rust) and else as || =>. (For symmetry we might allow && => for then as well.) An is operator for multi-way pattern-matching that binds variables whose scope covers the consequent part of the expression. The basic form is like the UCS, scrutinee is pattern which matches the scrutinee against the pattern returning a boolean result. For example, foo is None Guarded patterns are like, scrutinee is pattern && consequent where the scope of the variables bound by the pattern covers the consequent. The consequent might be a simple boolean guard, for example, foo is Some(n) && n < 0 or inside an if expression it might end with a then clause, if foo is Some(n) && n < 0 => -1 // ... Simple multi-way patterns are like, scrutinee is { pattern || pattern || … } If there is a consequent then the patterns must all bind the same set of variables (if any) with the same types. More typically, a multi-way match will have consequent clauses, like scrutinee is { pattern && consequent || pattern && consequent || => otherwise } When a consequent is false, we go on to try other alternatives of the match, like we would when the first operand of boolean || is false. To help with layout, you can include a redundant || before the first alternative. For example, if foo is { || Some(n) && n < 0 => -1 || Some(n) && n > 0 => +1 || Some(n) => 0 || None => 0 } Alternatively, if foo is { Some(n) && ( n < 0 => -1 || n > 0 => +1 || => 0 ) || None => 0 } (They should compile the same way.) The evaluation model is like familiar shortcutting && and || and the syntax is supposed to reinforce that intuition. The UCS paper spends a lot of time discussing backtracking and how to eliminate it, but penultimate conditionals evaluate straightforwardly from left to right. The paper briefly mentions as patterns, like Some(Pair(x, y) as p) which in Rust would be written Some(p @ Pair(x, y)) The is operator doesn’t need a separate syntax for this feature: Some(p is Pair(x, y)) For large examples, the penultimate conditional syntax is about as noisy as Rust’s match, but it scales down nicely to smaller matches. However, there are differences in how consequences and alternatives are punctuated which need a bit more discussion. dangling syntax The precedence and associativity of the is operator is tricky: it has two kinds of dangling-else problem. The first kind occurs with a surrounding boolean expression. For example, when b = false, what is the value of this? b is true || false It could bracket to the left, yielding false: (b is true) || false Or to the right, yielding true: b is { true || false } This could be disambiguated by using different spellings for boolean or and pattern alternatives. But that doesn’t help for the second kind which occurs with an inner match. foo is Some(_) && bar is Some(_) || None Does that check foo is Some(_) with an always-true look at bar ( foo is Some(_) ) && bar is { Some(_) || None } Or does it check bar is Some(_) and waste time with foo? foo is { Some(_) && ( bar is Some(_) ) || None } I have chosen to resolve the ambiguity by requiring curly braces {} around groups of alternative patterns. This allows me to use the same spelling || for all kinds of alternation. (Compare Rust, which uses || for boolean expressions, | in a pattern, and , between the arms of a match.) Curlies around multi-way matches can be nested, so the example in the previous section can also be written, if foo is { || Some(n) && n < 0 => -1 || Some(n) && n > 0 => +1 || { Some(0) || None } => 0 } The is operator binds tigher than && on its left, but looser than && on its right (so that a chain of && is gathered into a consequent) and tigher than || on its right so that outer || alternatives don’t need extra brackets. examples I’m going to finish these notes by going through the ultimate conditional syntax paper to translate most of its examples into the penultimate syntax, to give it some exercise. Here we use is to name a value n, as a replacement for the |> abs pipe operator, and we use range patterns instead of split relational operators: if foo(args) is { || 0 => "null" || n && abs(n) is { || 101.. => "large" || ..10 => "small" || => "medium" ) } In both the previous example and the next one, we have some extra brackets where UCS relies purely on an offside rule. if x is { || Right(None) => defaultValue || Right(Some(cached)) => f(cached) || Left(input) && compute(input) is { || None => defaultValue || Some(result) => f(result) } } This one is almost identical to UCS apart from the spellings of and, then, else. if name.startsWith("_") && name.tailOption is Some(namePostfix) && namePostfix.toIntOption is Some(index) && 0 <= index && index < arity && => Right([index, name]) || => Left("invalid identifier: " + name) Here are some nested multi-way matches with overlapping patterns and bound values: if e is { // ... || Lit(value) && Map.find_opt(value) is Some(result) => Some(result) // ... || { Lit(value) || Add(Lit(0), value) || Add(value, Lit(0)) } => { print_int(value); Some(value) } // ... } The next few examples show UCS splits without the is operator. In my syntax I need to press a few more buttons but I think that’s OK. if x == 0 => "zero" || x == 1 => "unit" || => "?" if x == 0 => "null" || x > 0 => "positive" || => "negative" if predicate(0, 1) => "A" || predicate(2, 3) => "B" || => "C" The first two can be written with is instead, but it’s not briefer: if x is { || 0 => "zero" || 1 => "unit" || => "?" } if x is { || 0 => "null" || 1.. => "positive" || => "negative" } There’s little need for a split-anything feature when we have multi-way matches. if foo(u, v, w) is { || Some(x) && x is { || Left(_) => "left-defined" || Right(_) => "right-defined" } || None => "undefined" } A more complete function: fn zip_with(f, xs, ys) { if [xs, ys] is { || [x :: xs, y :: ys] && zip_with(f, xs, ys) is Some(tail) => Some(f(x, y) :: tail) || [Nil, Nil] => Some(Nil) || => None } } Another fragment of the expression evaluator: if e is { // ... || Var(name) && Map.find_opt(env, name) is { || Some(Right(value)) => Some(value) || Some(Left(thunk)) => Some(thunk()) } || App(lhs, rhs) => // ... // ... } This expression is used in the paper to show how a UCS split is desugared: if Pair(x, y) is { || Pair(Some(xv), Some(yv)) => xv + yv || Pair(Some(xv), None) => xv || Pair(None, Some(yv)) => yv || Pair(None, None) => 0 } The desugaring in the paper introduces a lot of redundant tests. I would desugar straightforwardly, then rely on later optimizations to eliminate other redundancies such as the construction and immediate destruction of the pair: if Pair(x, y) is Pair(xx, yy) && xx is { || Some(xv) && yy is { || Some(yv) => xv + yv || None => xv } || None && yy is { || Some(yv) => yv || None => 0 } } Skipping ahead to the “non-trivial example” in the paper’s fig. 11: if e is { || Var(x) && context.get(x) is { || Some(IntVal(v)) => Left(v) || Some(BoolVal(v)) => Right(v) } || Lit(IntVal(v)) => Left(v) || Lit(BoolVal(v)) => Right(v) // ... } The next example in the paper compares C# relational patterns. Rust’s range patterns do a similar job, with the caveat that Rust’s ranges don’t have a syntax for exclusive lower bounds. fn classify(value) { if value is { || .. -4.0 => "too low" || 10.0 .. => "too high" || NaN => "unknown" || => "acceptable" } } I tend to think relational patterns are the better syntax than ranges. With relational patterns I can rewrite an earlier example like, if foo is { || Some(< 0) => -1 || Some(> 0) => +1 || { Some(0) || None } => 0 } I think with the UCS I would have to name the Some(_) value to be able to compare it, which suggests that relational patterns can be better than UCS split relational operators. Prefix-unary relational operators are also a nice way to write single-ended ranges in expressions. We could simply write both ends to get a complete range, like >= lo < hi or like if value is > -4.0 < 10.0 => "acceptable" || => "far out" Near the start I quoted a normalize example that illustrates left-aligned UCS expression. The penultimate version drifts right like the Scala version: if normalize(tp1) is { || Bot => Bot || tp1_n && normalize(tp2) is { || Bot => Bot || tp2_n && merge(tp1_n, tp2_n) is { || Some(tp) => tp || None => glb(tp1_n, tp2_n) } } } But a more Rusty style shows the benefits of early returns (especially the terse ? operator) and monadic combinators. let tp1 = normalize(tp1)?; let tp2 = normalize(tp2)?; merge(tp1, tp2) .unwrap_or_else(|| glb(tp1, tp2)) antepenultimate breath When I started writing these notes, my penultimate conditional syntax was little more than a sketch of an idea. Having gone through the previous section’s exercise, I think it has turned out better than I thought it might. The extra nesting from multi-way match braces doesn’t seem to be unbearably heavyweight. However, none of the examples have bulky then or else blocks which are where the extra nesting is more likely to be annoying. But then, as I said before it’s comparable to a Rust match: match scrutinee { pattern => { consequent } } if scrutinee is { || pattern => { consequent } } The || lines down the left margin are noisy, but hard to get rid of in the context of a curly-brace language. I can’t reduce them to | like OCaml because what would I use for bitwise OR? I don’t want presence or absence of flow control to depend on types or context. I kind of like Prolog / Erlang , for && and ; for ||, but that’s well outside what’s legible to mainstream programmers. So, dunno. Anyway, I think I’ve successfully found a syntax that does most of what UCS does, but much in a much simpler fashion.
I really like RTS games. I pretty much grew up on them, starting with Command&Conquer 3: Kane’s Wrath, moving on to StarCraft 2 trilogy and witnessing the downfall of Command&Conquer 4. I never had the disks for any other RTS games during my teenage years. Yes, the disks, the ones you go to the store to buy! I didn’t know Steam existed back then, so this was my only source of games. There is something magical in owning a physical copy of the game. I always liked the art on the front (a mandatory huge face for all RTS!), game description and screenshots on the back, even the smell of the plastic disk case.
Following up on a previous article I wrote about backwards compatibility, I came across this document from Rick Byers of the Chrome team titled “Blink principles of web compatibility” which outlines how they navigate introducing breaking changes. “Hold up,” you might say. “Breaking changes? But there’s no breaking changes on the web!?” Well, as outlined in their Google Doc, “don’t break anyone ever” is a bit unrealistic. Here’s their rationale: The Chromium project aims to reduce the pain of breaking changes on web developers. But Chromium’s mission is to advance the web, and in some cases it’s realistically unavoidable to make a breaking change in order to do that. Since the web is expected to continue to evolve incrementally indefinitely, it’s essential to its survival that we have some mechanism for shedding some of the mistakes of the past. Fair enough. We all need ways of shedding mistakes from the past. But let’s not get too personal. That’s a different post. So when it comes to the web, how do you know when to break something and when to not? The Chrome team looks at the data collected via Chrome's anonymous usage statistics (you can take a peak at that data yourself) to understand how often “mistake” APIs are still being used. This helps them categorize breaking changes as low-risk or high-risk. What’s wild is that, given Chrome’s ubiquity as a browser, a number like 0.1% is classified as “high-risk”! As a general rule of thumb, 0.1% of PageVisits (1 in 1000) is large, while 0.001% is considered small but non-trivial. Anything below about 0.00001% (1 in 10 million) is generally considered trivial. There are around 771 billion web pages viewed in Chrome every month (not counting other Chromium-based browsers). So seriously breaking even 0.0001% still results in someone being frustrated every 3 seconds, and so not to be taken lightly! But the usage stats are merely a guide — a partially blind one at that. The Chrome team openly acknowledges their dataset doesn’t tell the whole story (e.g. Enterprise clients have metrics recording is disabled, China has Google’s metric servers are disabled, and Chromium derivatives don’t record metrics at all). And Chrome itself is only part of the story. They acknowledge that a change that would break Chrome but align it with other browsers is a good thing because it’s advancing the whole web while perhaps costing Chrome specifically in the short term — community > corporation?? Breaking changes which align Chromium’s behavior with other engines are much less risky than those which cause it to deviate…In general if a change will break only sites coding specifically for Chromium (eg. via UA sniffing), then it’s likely to be net-positive towards Chromium’s mission of advancing the whole web. Yay for advancing the web! And the web is open, which is why they also state they’ll opt for open formats where possible over closed, proprietary, “patent-encumbered” ones. The chromium project is committed to a free and open web, enabling innovation and competition by anyone in any size organization or of any financial means or legal risk tolerance. In general the chromium project will accept an increased level of compatibility risk in order to reduce dependence in the web ecosystem on technologies which cannot be implemented on a royalty-free basis. One example we saw of breaking change that excluded proprietary in favor of open was Flash. One way of dealing with a breaking change like that is to provide opt-out. In the case of Flash, users were given the ability to “opt-out” of Flash being deprecated via site settings (in other words, opt-in to using flash on a page-by-page basis). That was an important step in phasing out that behavior completely over time. But not all changes get that kind of heads-up. there is a substantial portion of the web which is unmaintained and will effectively never be updated…It may be useful to look at how long chromium has had the behavior in question to get some idea of the risk that a lot of unmaintained code will depend on it…In general we believe in the principle that the vast majority of websites should continue to function forever. There’s a lot going on with Chrome right now, but you gotta love seeing the people who work on it making public statements like that — “we believe…that the vast majority of websites should continue to function forever.” There’s some good stuff in this document that gives you hope that people really do care and work incredibly hard to not break the web! (It’s an ecosystem after all.) It’s important for [us] browser engineers to resist the temptation to treat breaking changes in a paternalistic fashion. It’s common to think we know better than web developers, only to find out that we were wrong and didn’t know as much about the real world as we thought we did. Providing at least a temporary developer opt-out is an act of humility and respect for developers which acknowledges that we’ll only succeed in really improving the web for users long-term via healthy collaborations between browser engineers and web developers. More 👏 acts 👏 of 👏 humility 👏 in tech 👏 please! Email · Mastodon · Bluesky
react-router-devtools enhances debugging by adding automatic logging for loaders & actions, plus direct links to code origins in console logs.