Tootfinder

Subtooting since people in the original thread wanted it to be over, but selfishly tagging @… and @… whose opinions I value...
I think that saying "we are not a supply chain" is exactly what open-source maintainers should be doing right now in response to "open source supply chain security" threads.
I can't claim to be an expert and don't maintain any important FOSS stuff, but I do release almost all of my code under open licenses, and I do use many open source libraries, and I have felt the pain of needing to replace an unmaintained library.
There's a certain small-to-mid-scale class of program, including many open-source libraries, which can be built/maintained by a single person, and which to my mind best operate on a "snake growth" model: incremental changes/fixes, punctuated by periodic "skin-shedding" phases where make rewrites or version updates happen. These projects aren't immortal either: as the whole tech landscape around them changes, they become unnecessary and/or people lose interest, so they go unmaintained and eventually break. Each time one of their dependencies breaks (or has a skin-shedding moment) there's a higher probability that they break or shed too, as maintenance needs shoot up at these junctures. Unless you're a company trying to make money from a single long-lived app, it's actually okay that software churns like this, and if you're a company trying to make money, your priorities absolutely should not factor into any decisions people making FOSS software make: we're trying (and to a huge extent succeeding) to make a better world (and/or just have fun with our own hobbies share that fun with others) that leaves behind the corrosive & planet-destroying plague which is capitalism, and you're trying to personally enrich yourself by embracing that plague. The fact that capitalism is *evil* is not an incidental thing in this discussion.
To make an imperfect analogy, imagine that the peasants of some domain have set up a really-free-market, where they provide each other with free stuff to help each other survive, sometimes doing some barter perhaps but mostly just everyone bringing their surplus. Now imagine the lord of the domain, who is the source of these peasants' immiseration, goes to this market secretly & takes some berries, which he uses as one ingredient in delicious tarts that he then sells for profit. But then the berry-bringer stops showing up to the free market, or starts bringing a different kind of fruit, or even ends up bringing rotten berries by accident. And the lord complains "I have a supply chain problem!" Like, fuck off dude! Your problem is that you *didn't* want to build a supply chain and instead thought you would build your profit-focused business in other people's free stuff. If you were paying the berry-picker, you'd have a supply chain problem, but you weren't, so you really have an "I want more free stuff" problem when you can't be arsed to give away your own stuff for free.
There can be all sorts of problems in the really-free-market, like maybe not enough people bring socks, so the peasants who can't afford socks are going barefoot, and having foot problems, and the peasants put their heads together and see if they can convince someone to start bringing socks, and maybe they can't and things are a bit sad, but the really-free-market was never supposed to solve everyone's problems 100% when they're all still being squeezed dry by their taxes: until they are able to get free of the lord & start building a lovely anarchist society, the really-free-market is a best-effort kind of deal that aims to make things better, and sometimes will fall short. When it becomes the main way goods in society are distributed, and when the people who contribute aren't constantly drained by the feudal yoke, at that point the availability of particular goods is a real problem that needs to be solved, but at that point, it's also much easier to solve. And at *no* point does someone coming into the market to take stuff only to turn around and sell it deserve anything from the market or those contributing to it. They are not a supply chain. They're trying to help each other out, but even then they're doing so freely and without obligation. They might discuss amongst themselves how to better coordinate their mutual aid, but they're not going to end up forcing anyone to bring anything or even expecting that a certain person contribute a certain amount, since the whole point is that the thing is voluntary & free, and they've all got changing life circumstances that affect their contributions. Celebrate whatever shows up at the market, express your desire for things that would be useful, but don't impose a burden on anyone else to bring a specific thing, because otherwise it's fair for them to oppose such a burden on you, and now you two are doing your own barter thing that's outside the parameters of the really-free-market.

it's 2025 :-) all i want, as a SUMO (support.mozilla.org) knowledge base writer, is something that will take automated screenshots of Thunderbird for Android, Windows, macOS and Linux. Is that too much to ask :-) ? evidently so!!!!

Finished reading "The Steerswoman" by Rosemary Kirstein. It's a great little fantasy novel. I'd call it "hard sci-fi" if it was set in space. Is there a term for medieval stories that don't get too magical?
The hero of this story is a member of a special guild that is all about preserving and acquiring knowledge. Sworn to speak the truth. Much of the story is her drawing conclusions about the world she inhabits. There are swords and scheming wizards. On t…

Epstein shit and adjacent, Rural America, Poverty, Abuse
Everyone who's not a pedophile thinks pedophiles are bad, but there's this special obsessed hatred you'll find among poor rural Americans. The whole QAnon/Epstein obsession may not really make sense to folks raised in cities. Like, why do these people think *so much* about pedophiles? Why do they think that everyone in power is a pedophile? Why would the Pizzagate thing make sense to anyone? What is this unhinged shit? A lot of folks (who aren't anarchists) might be inclined to ask "why can't these people just let the cops take care of it?"
I was watching Legal Eagle's run down on the Trump Epstein thing earlier today and I woke up thinking about something I don't know if I've ever talked about. Now that I'm not in the US, I'm not at any risk of talking about it. I don't know how much I would have been before, but that's not something I'm gonna dig into right now. So let me tell you a story that might explain a few things.
I'm like 16, maybe 17. I have my license, so this girl I was dating/not dating/just friends with/whatever would regularly convince me to drive her and her friends around. I think she's like 15 at the time. Her friends are younger than her.
She tells me that there's a party we can go to where they have beer. She was told to invite her friends, so I can come too. We're going to pick her friends up (we regularly fill the VW Golf well beyond the legal limit and drive places) and head to the party.
So I take these girls, at least is 13 years old, down to this party. I'm already a bit sketched out bringing a 13 year old to a party. We drive out for a while. It's in the country. We drive down a long dark road. Three are some barrel fires and a shack. This is all a bit strange, but not too abnormal for this area. We're a little ways outside of a place called Mill City (in Oregon).
We park and walk towards the shack. This dude who looks like a rat comes up and offers us beer. He laughs and talks to the girl who invited me, "What's he doing here? You're supposed to bring your girl friends." She's like, "He's our ride." I don't remember if he offered me a beer or not.
We go over to this shed and everyone starts smoking, except me because I didn't smoke until I turned 18. The other girls start talking about the rat face dude, who's wandered over by the fire with some other guys. They're mainly teasing one of the 13 year old girls about having sex with him a bunch of times. They say he's like, 32 or something. The other girls joke about him only having sex with 13 year olds because he's too ugly to have sex with anyone closer to his own age.
Somewhere along the line it comes out that he's a cop. I never forgot that, it's absolutely seared in to my memory. I can picture his face perfectly still, decades later, and them talking about how he's a deputy, he was in his 30's, and he was having sex with a 13 year old girl. I was the only boy there, but there were a few older men. This was a chunk of the good ol' boys club of the town. I think there were a couple of cops besides the one deputy, and a judge or the mayor or some kind of big local VIP.
I kept trying to get my friend to leave, but she wanted to stay. Turns out under age drinking with cops seems like a great deal if you're a kid because you know you won't get busted. I left alone, creeped the fuck out.
I was told later that I wasn't invited and that I couldn't talk about it, I've always been good at compartmentalization, so I never did.
Decades later it occurred to me what was actually happening. I'm pretty sure that cop was giving meth he'd seized as evidence to these kids. This wasn't some one-off thing. It was regular. Who knows how many decades it went on after I left, or how many decades it had been going on before I found out. I knew this type of thing had happened at least a few times before because that's how that 13 year old girl and that 32 year old cop had hooked up in the first place.
Hearing about Epstein's MO, targeting these teenage girls from fucked up backgrounds, it's right there for me. I wouldn't be surprised if they were involved in sex trafficking of minors or some shit like that... but who would you call if you found out? Half the sheriff's department was there and the other half would cover for them.
You live in the city and shit like that doesn't happen, or at least you don't think it happens. But rural poor folks have this intuition about power and abuse. It's right there and you know it.
Trump is such a familiar character for me, because he's exactly that small town mayor or sheriff. He'll will talk about being tough on crime and hunting down pedophiles, while hanging out at a party that exists so people can fuck 8th graders.
The problem with the whole thing is that rural folks will never break the cognitive dissonance between "kill the peods" and "back the blue." They'll never go kill those cops. No, the pedos must be somewhere else. It must be the elites. It must be outsiders. It can't be the cops and good ol' boys everyone respects. It can't be the mayor who rigs the election to win every time. It can't be the "good upstanding" sheriff. Nah, it's the Clintons.
To be fair, it's probably also the Clitnons, a bunch of other politicians, billionaires, etc. Epstein was exactly who everyone thought he was, and he didn't get away with it for so long without a whole lot of really powerful help.
There are still powerful people who got away with involvement with #Epstein. #Trump is one of them, but I don't really believe that he's the only one.
#USPol #ACAB

About morbid thriftiness (Autism Spectrum Condition)
As you may have noticed, I am morbidly thrifty. Usually I don't buy stuff that I don't need — and if I decide that I actually need something, I am going to ponder about it for a while, look for value products, and for the best price. And with some luck, I'm going to decide I don't need it that bad after all.
One reason for that is probably how I was raised. My parents taught me to be thrifty, so I have to be. It doesn't matter that, from retrospective, I see that their thriftiness was applied rather arbitrarily to some spendings and not others, or that perhaps they were greedy — spending less on individual things so that they could buy more. Well, I can't delude myself like that, so I have to be thrifty for real. And when I fail, when I pay too much, when I get cheated — I feel quite bad about it.
The other reason is that I keep worrying about my future. It doesn't matter how rich I may end up — I'll keep worrying that I'll run out of money in the future. Perhaps I'll lose a job and won't be able to find anything for a long time, Perhaps something terrible will happen and I'm going to need to pay a lot suddenly.
Another thing is that I easily get attached to objects. Well, it's easier to be thrifty when you really don't want to replace stuff. Over time you also learn to avoid getting new stuff at all, since the more stuff you have, the more stuff may break and need to be thrown away.
Finally, there's my environmental responsibility. I admit that I don't do enough — but at least the things I can do, I do.
[EDIT: and yes, I feel bad about how expensive my new phone was, even though it's of much higher quality than the last one. Also, I got a worse deal because I waited too long.]
#ActuallyAutistic

Isn't it weird how when a Federal Crown Corporation - Marine Atlantic - buys a new ship... there is nary a mention that it was built in China (#BCPoli #BCFerries

I just finished "An Ember in the Ashes" by Sabaa Tahir. I picked it up because I found her non-fantasy novel "All My Rage" extremely compelling, and I enjoyed fantasy a lot as a genre in my youth but as my politics have changed I'm too disappointed to enjoy a lot of fantasy any more but I thought Tahir might not fall into that.
Although I don't think Ember in the Ashes is bad, it's definitely not what I was looking for, and I don't think I'll pursue the sequels, at least not right now.
Overall the writing was weaker in a lot of ways than All My Rage, and in terms of basic fantasy quality, the worldbuilding was noticeably lacking, the romantic subplot felt stilted, and the politics were a bit murky. Compared to what I felt was Tahir's deft, delicate, and very meaningful handling of trauma in All My Rage, trauma in Ember felt overused and thin.
I also recently finished "Black Panther Red Wolf" by Marlon James, which had excellent world building and (to me) a much more nuance in both romance and in handling trauma. The politics felt a bit off for this one too I guess, but for me it was an overall more enjoyable (if much more difficult) read.
#AmReading

Happy Fourth of July. A fine new recording that's worth a listen today.
Ben Folds with the National Symphony Orchestra, "But Wait, There's More" (live, 2024)
Wait, there's more.
Don't think we can take too much more.
Pray that there's a bottom somewhere in sight.
Brothers and sisters hold tight.
https://

Should we teach vibe coding? Here's why not.
Should AI coding be taught in undergrad CS education?
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I teach undergraduate computer science labs, including for intro and more-advanced core courses. I don't publish (non-negligible) scholarly work in the area, but I've got years of craft expertise in course design, and I do follow the academic literature to some degree. In other words, In not the world's leading expert, but I have spent a lot of time thinking about course design, and consider myself competent at it, with plenty of direct experience in what knowledge & skills I can expect from students as they move through the curriculum.
I'm also strongly against most uses of what's called "AI" these days (specifically, generative deep neutral networks as supplied by our current cadre of techbro). There are a surprising number of completely orthogonal reasons to oppose the use of these systems, and a very limited number of reasonable exceptions (overcoming accessibility barriers is an example). On the grounds of environmental and digital-commons-pollution costs alone, using specifically the largest/newest models is unethical in most cases.
But as any good teacher should, I constantly question these evaluations, because I worry about the impact on my students should I eschew teaching relevant tech for bad reasons (and even for his reasons). I also want to make my reasoning clear to students, who should absolutely question me on this. That inspired me to ask a simple question: ignoring for one moment the ethical objections (which we shouldn't, of course; they're very stark), at what level in the CS major could I expect to teach a course about programming with AI assistance, and expect students to succeed at a more technically demanding final project than a course at the same level where students were banned from using AI? In other words, at what level would I expect students to actually benefit from AI coding "assistance?"
To be clear, I'm assuming that students aren't using AI in other aspects of coursework: the topic of using AI to "help you study" is a separate one (TL;DR it's gross value is not negative, but it's mostly not worth the harm to your metacognitive abilities, which AI-induced changes to the digital commons are making more important than ever).
So what's my answer to this question?
If I'm being incredibly optimistic, senior year. Slightly less optimistic, second year of a masters program. Realistic? Maybe never.
The interesting bit for you-the-reader is: why is this my answer? (Especially given that students would probably self-report significant gains at lower levels.) To start with, [this paper where experienced developers thought that AI assistance sped up their work on real tasks when in fact it slowed it down] (https://arxiv.org/abs/2507.09089) is informative. There are a lot of differences in task between experienced devs solving real bugs and students working on a class project, but it's important to understand that we shouldn't have a baseline expectation that AI coding "assistants" will speed things up in the best of circumstances, and we shouldn't trust self-reports of productivity (or the AI hype machine in general).
Now we might imagine that coding assistants will be better at helping with a student project than at helping with fixing bugs in open-source software, since it's a much easier task. For many programming assignments that have a fixed answer, we know that many AI assistants can just spit out a solution based on prompting them with the problem description (there's another elephant in the room here to do with learning outcomes regardless of project success, but we'll ignore this over too, my focus here is on project complexity reach, not learning outcomes). My question is about more open-ended projects, not assignments with an expected answer. Here's a second study (by one of my colleagues) about novices using AI assistance for programming tasks. It showcases how difficult it is to use AI tools well, and some of these stumbling blocks that novices in particular face.
But what about intermediate students? Might there be some level where the AI is helpful because the task is still relatively simple and the students are good enough to handle it? The problem with this is that as task complexity increases, so does the likelihood of the AI generating (or copying) code that uses more complex constructs which a student doesn't understand. Let's say I have second year students writing interactive websites with JavaScript. Without a lot of care that those students don't know how to deploy, the AI is likely to suggest code that depends on several different frameworks, from React to JQuery, without actually setting up or including those frameworks, and of course three students would be way out of their depth trying to do that. This is a general problem: each programming class carefully limits the specific code frameworks and constructs it expects students to know based on the material it covers. There is no feasible way to limit an AI assistant to a fixed set of constructs or frameworks, using current designs. There are alternate designs where this would be possible (like AI search through adaptation from a controlled library of snippets) but those would be entirely different tools.
So what happens on a sizeable class project where the AI has dropped in buggy code, especially if it uses code constructs the students don't understand? Best case, they understand that they don't understand and re-prompt, or ask for help from an instructor or TA quickly who helps them get rid of the stuff they don't understand and re-prompt or manually add stuff they do. Average case: they waste several hours and/or sweep the bugs partly under the rug, resulting in a project with significant defects. Students in their second and even third years of a CS major still have a lot to learn about debugging, and usually have significant gaps in their knowledge of even their most comfortable programming language. I do think regardless of AI we as teachers need to get better at teaching debugging skills, but the knowledge gaps are inevitable because there's just too much to know. In Python, for example, the LLM is going to spit out yields, async functions, try/finally, maybe even something like a while/else, or with recent training data, the walrus operator. I can't expect even a fraction of 3rd year students who have worked with Python since their first year to know about all these things, and based on how students approach projects where they have studied all the relevant constructs but have forgotten some, I'm not optimistic seeing these things will magically become learning opportunities. Student projects are better off working with a limited subset of full programming languages that the students have actually learned, and using AI coding assistants as currently designed makes this impossible. Beyond that, even when the "assistant" just introduces bugs using syntax the students understand, even through their 4th year many students struggle to understand the operation of moderately complex code they've written themselves, let alone written by someone else. Having access to an AI that will confidently offer incorrect explanations for bugs will make this worse.
To be sure a small minority of students will be able to overcome these problems, but that minority is the group that has a good grasp of the fundamentals and has broadened their knowledge through self-study, which earlier AI-reliant classes would make less likely to happen. In any case, I care about the average student, since we already have plenty of stuff about our institutions that makes life easier for a favored few while being worse for the average student (note that our construction of that favored few as the "good" students is a large part of this problem).
To summarize: because AI assistants introduce excess code complexity and difficult-to-debug bugs, they'll slow down rather than speed up project progress for the average student on moderately complex projects. On a fixed deadline, they'll result in worse projects, or necessitate less ambitious project scoping to ensure adequate completion, and I expect this remains broadly true through 4-6 years of study in most programs (don't take this as an endorsement of AI "assistants" for masters students; we've ignored a lot of other problems along the way).
There's a related problem: solving open-ended project assignments well ultimately depends on deeply understanding the problem, and AI "assistants" allow students to put a lot of code in their file without spending much time thinking about the problem or building an understanding of it. This is awful for learning outcomes, but also bad for project success. Getting students to see the value of thinking deeply about a problem is a thorny pedagogical puzzle at the best of times, and allowing the use of AI "assistants" makes the problem much much worse. This is another area I hope to see (or even drive) pedagogical improvement in, for what it's worth.
1/2

PLpol, pseudoliberalism
Tell me, is a "liberal" the kind of person to claim that a woman must not become a president, as she'll get mad with power? Does a "liberal" declare their tolerance for specific people by using insulting names for them? Does a "liberal" call certain minorities "loafers"? Does a "liberal" support dismantling public services for "cost reduction"? Yet these are the views held by the voters of PO/KO, the Polish party often called "liberal".
It is not a liberal party, and it won't be one, because they have too much to lose. For years now, they exist only as an alternative to the "conservative" PiS party — not as something truly opposite, but as a comfortable alternative that's not all that different. So the Polish can gladly focus their contrarian, hateful nature into voting against one or the other party, without having to worry too much that some immoral rainbow force will try to shatter the bubble of their worldview.
#PLpol

Someone mentioned the "awesome" web site for Milwaukee Critical Mass, but I think they may have been taking the piss...
But honestly, I'd rather see this than an overdone 'full of shit' web site with too much.
As it is, it gives the basic info. Sometimes that's all you need.
Although (sigh) it looks like it hasn't been updated since April.
➡️

Nottingham, short visit rent or housesit, anyone know a place?
Nottingham-related #AskFedi: anyone know of a Nottingham-area house or flat that's going to be empty over part or all of the summer? and that's potentially rentable for not too much for a few days, or wants house-sitting for a while?
It would be so that me and a friend/colleague could go and use the space to do some writing work together. We are reliable conscientious old(ish) people who'd leave it clean and not be any bother :-)
Boosts very welcome.
#Nottingham #AskFedi

The key is not allow boys to be raised by older boys, even ones who are legally adults. By the time they’re thinking about dating, they are likely to be ruined.
The problem is too much gendering in childhood. So many people are raised to think in binary gender terms compelled to conform to gender norms and believe in binary-gender ideology.
I will never run out of gratitude for being the only boy in my family for much of my childhood.

It's really telling how much of the conversation around AI boils down to,
"Is there any value in humans being able to think?"
Which all too quickly reduces to
"Is there any value in humans” ?
https://bsky.app/profile/kevinriggle.b

Just to clarify, are you envisioning something like PayPal, where creators can receive direct payments from their supporters?
Or is it more like a system where users can pay to boost posts so they appear more prominently in others’ feeds?
@…

How to tell a vibe coder of lying when they say they check their code.
People who will admit to using LLMs to write code will usually claim that they "carefully check" the output since we all know that LLM code has a lot of errors in it. This is insufficient to address several problems that LLMs cause, including labor issues, digital commons stress/pollution, license violation, and environmental issues, but at least it's they are checking their code carefully we shouldn't assume that it's any worse quality-wise than human-authored code, right?
Well, from principles alone we can expect it to be worse, since checking code the AI wrote is a much more boring task than writing code yourself, so anyone who has ever studied human-computer interaction even a little bit can predict people will quickly slack off, stating to trust the AI way too much, because it's less work. I'm a different domain, the journalist who published an entire "summer reading list" full of nonexistent titles is a great example of this. I'm sure he also intended to carefully check the AI output, but then got lazy. Clearly he did not have a good grasp of the likely failure modes of the tool he was using.
But for vibe coders, there's one easy tell we can look for, at least in some cases: coding in Python without type hints. To be clear, this doesn't apply to novice coders, who might not be aware that type hints are an option. But any serious Python software engineer, whether they used type hints before or not, would know that they're an option. And if you know they're an option, you also know they're an excellent tool for catching code defects, with a very low effort:reward ratio, especially if we assume an LLM generates them. Of the cases where adding types requires any thought at all, 95% of them offer chances to improve your code design and make it more robust. Knowing about but not using type hints in Python is a great sign that you don't care very much about code quality. That's totally fine in many cases: I've got a few demos or jam games in Python with no type hints, and it's okay that they're buggy. I was never going to debug them to a polished level anyways. But if we're talking about a vibe coder who claims that they're taking extra care to check for the (frequent) LLM-induced errors, that's not the situation.
Note that this shouldn't be read as an endorsement of vibe coding for demos or other rough-is-acceptable code: the other ethical issues I skipped past at the start still make it unethical to use in all but a few cases (for example, I have my students use it for a single assignment so they can see for themselves how it's not all it's cracked up to be, and even then they have an option to observe a pre-recorded prompt session instead).

How popular media gets love wrong
Now a bit of background about why I have this "engineered" model of love:
First, I'm a white straight cis man. I've got a few traits that might work against my relationship chances (e.g., neurodivergence; I generally fit pretty well into the "weird geek" stereotype), but as I was recently reminded, it's possible my experience derives more from luck than other factors, and since things are tilted more in my favor than most people on the planet, my advice could be worse than useless if it leads people towards strategies that would only have worked for someone like me. I don't *think* that's the case, but it's worth mentioning explicitly.
When I first started dating my now-wife, we were both in graduate school. I was 26, and had exactly zero dating/romantic experience though that point in my life. In other words, a pretty stereotypical "incel" although I definitely didn't subscribe to incel ideology at all. I felt lonely, and vaguely wanted a romantic relationship (I'm neither aromantic nor asexual), but had never felt socially comfortable enough to pursue one before. I don't drink and dislike most social gatherings like parties or bars; I mostly hung around the fringes of the few college parties I attended, and although I had a reasonable college social life in terms of friends, I didn't really do anything to pursue romance, feeling too awkward to know where to start. I had the beginnings of crushes in both high school and college, but never developed a really strong crush, probably correlated with not putting myself in many social situations outside of close all-male friend gatherings. I never felt remotely comfortable enough to act on any of the proto-crushes I did have. I did watch porn and masturbate, so one motivation for pursuing a relationship was physical intimacy, but loneliness was as much of a motivating factor, and of course the social pressure to date was a factor too, even though I'm quite contrarian.
When I first started dating my now-wife, we were both in graduate school. I was 26, and had exactly zero dating/romantic experience though that point in my life. In other words, a pretty stereotypical "incel" although I definitely didn't subscribe to incel ideology at all. I felt lonely, and vaguely wanted a romantic relationship (I'm neither aromantic nor asexual), but had never felt socially comfortable enough to pursue one before. I don't drink and dislike most social gatherings like parties or bars; I mostly hung around the fringes of the few college parties I attended, and although I had a reasonable college social life in terms of friends, I didn't really do anything to pursue romance, feeling too awkward to know where to start. I had the beginnings of crushes in both high school and college, but never developed a really strong crush, probably correlated with not putting myself in many social situations outside of close all-male friend gatherings. I never felt remotely comfortable enough to act on any of the proto-crushes I did have. I did watch porn and masturbate, so one motivation for pursuing a relationship was physical intimacy, but loneliness was as much of a motivating factor, and of course the social pressure to date was a factor too, even though I'm quite contrarian.
I'm lucky in that I had some mixed-gender social circles already like intramural soccer and a graduate-student housing potluck. Graduate school makes a *lot* more of these social spaces accessible, so I recognize that those not in school of some sort have a harder time of things, especially if like me they don't feel like they fit in in typical adult social spaces like bars.
However, at one point I just decided that my desire for a relationship would need action on my part and so I'd try to build a relationship and see what happened. I worked up my courage and asked one of the people in my potluck if she'd like to go for a hike (pretty much clearly a date but not explicitly one; in retrospect not the best first-date modality in a lot of ways, but it made a little more sense in our setting where we could go for a hike from our front door). To emphasize this point: I was not in love with (or even infatuated with) my now-wife at that point. I made a decision to be open to building a relationship, but didn't follow the typical romance story formula beyond that. Now of course, in real life as opposed to popular media, this isn't anything special. People ask each other out all the time just because they're lonely, and some of those relationships turn out fine (although many do not).
I was lucky in that some aspects of who I am and what I do happened to be naturally comforting to my wife (natural advantage in the "appeal" model of love) but of course there are some aspects of me that annoy my wife, and we negotiate that. In the other direction, there's some things I instantly liked about my wife, and other things that still annoy me. We've figured out how to accept a little, change a little, and overall be happy with each other (though we do still have arguments; it's not like the operation/construction/maintenance of the "love mechanism" is always perfectly smooth). In particular though, I approached the relationship with the attitude of "I want to try to build a relationship with this person," at first just because of my own desires for *any* relationship, and then gradually more and more through my desire to build *this specific* relationship as I enjoyed the rewards of companionship.
So for example, while I think my wife is objectively beautiful, she's also *subjectively* very beautiful *to me* because having decided to build a relationship with her, I actively tried to see her as beautiful, rather than trying to judge whether I wanted a relationship with her based on her beauty. In other words, our relationship is more causative of her beauty-to-me than her beauty-to-me is causative of our relationship. This is the biggest way I think the "engineered" model of love differs from the "fire" and "appeal" models: you can just decide to build love independent of factors we typically think of as engendering love (NOT independent of your partner's willingness to participate, of course), and then all of those things like "thinking your partner is beautiful" can be a result of the relationship you're building. For sure those factors might affect who is willing to try building a relationship with you in the first place, but if more people were willing to jump into relationship building (not necessarily with full commitment from the start) without worrying about those other factors, they might find that those factors can come out of the relationship instead of being prerequisites for it. I think this is the biggest failure of the "appeal" model in particular: yes you *do* need to do things that appeal to your partner, but it's not just "make myself lovable" it's also: is your partner putting in the effort to see the ways that you are beautiful/lovable/etc., or are they just expecting you to become exactly some perfect person they've imagined (and/or been told to desire by society)? The former is perfectly possible, and no less satisfying than the latter.
To cut off my rambling a bit here, I'll just add that in our progress from dating through marriage through staying-married, my wife and I have both talked at times explicitly about commitment, and especially when deciding to get married, I told her that I knew I couldn't live up to the perfect model of a husband that I'd want to be, but that if she wanted to deepen our commitment, I was happy to do that, and so we did. I also rearranged my priorities at that point, deciding that I knew I wanted to prioritize this relationship above things like my career or my research interests, and while I've not always been perfect at that in my little decisions, I've been good at holding to that in my big decisions at least. In the end, *once we had built a somewhat-committed relationship*, we had something that we both recognized was worth more than most other things in life, and that let us commit even more, thus getting even more out of it in the long term. Obviously you can't start the first date with an expectation of life-long commitment, and you need to synchronize your increasing commitment to a relationship so that it doesn't become lopsided, which is hard. But if you take the commitment as an active decision and as the *precursor* to things like infatuation, attraction, etc., you can build up to something that's incredibly strong and rewarding.
I'll follow this up with one more post trying to distill some advice from my ramblings.
#relationships #love

So #Gentoo #Python eclasses are pretty modern, in the sense that they tend to follow the best practices and standards, and eventually deal with deprecations. Nevertheless, they have a long history and carry quite some historical burden, particularly regarding to naming.
The key point is that the eclasses were conceived as a replacement for the old eclasses: "distutils" and "python". Hence, much like we revision ebuilds, I've named the matching eclasses "distutils-r1" and "python-r1". For consistency, I've also used the "-r1" suffix for the remaining eclasses introduced at the time: "python-any-r1", "python-single-r1" and "python-utils-r1" — even though there were never "r0"s.
It didn't take long to realize my first mistake. I've made the multi-impl eclass effectively the "main" eclass, probably largely inspired by the previous Gentoo recommendations. However, in the end I've found out that for the most use cases (i.e. where "distutils-r1" is not involved), there is no real need for multi-impl, and it makes things much harder. So if I were naming them today, I would have named it "python-multi", to indicate the specific use case — and either avoid designating a default at all, or made "python-single" the default.
What aged even worse is the "distutils-r1" eclass. Admittedly, back when it was conceived, distutils was still largely a thing — and there were people (like me) who avoided unnecessary dependency on setuptools. Of course, nowadays it has been entirely devoured by setuptools, and with #PEP517 even "setuptools" wouldn't be a good name anymore. Nowadays, people are getting confused why they are supposed to use "distutils-r1" for, say, Hatchling.
Admittedly, this is something I could have done differently — PEP517 support was a major migration, and involved an explicit switch. Instead of adding DISTUTILS_USE_PEP517 (what a self-contradictory name) variable, I could have forked the eclass. Why didn't I do that? Because there used to be a lot of code shared between the two paths. Of course, over time they diverged more, and eventually I've dropped the legacy support — but the opportunity to rename was lost.
In fact, as a semi-related fact, I've recognized another design problem with the eclass earlier — I should have gone for two eclasses rather than one: a "python-phase" eclass with generic sub-phase support, and a "distutils" (or later "python-pep517") implementing default sub-phases for the common backends. And again, this is precisely how I could have solved the code reuse problem when I introduced PEP517 support.
But then, I didn't anticipate how the eclasses would end up looking like in the end — and I can't really predict what new challenges the Python ecosystem is going to bring us. And I think it's too late to rename or split stuff — too much busywork on everyone.

How popular media gets love wrong
Had some thoughts in response to a post about loneliness on here. As the author emphasized, reassurances from people who got lucky are not terribly comforting to those who didn't, especially when the person who was lucky had structural factors in their favor that made their chances of success much higher than those is their audience. So: these are just my thoughts, and may not have any bearing on your life. I share them because my experience challenged a lot of the things I was taught to believe about love, and I think my current beliefs are both truer and would benefit others seeing companionship.
We're taught in many modern societies from an absurdly young age that love is not something under our control, and that dating should be a process of trying to kindle love with different people until we meet "the one" with whom it takes off. In the slightly-less-fairytale corners of modern popular media, we might fund an admission that it's possible to influence love, feeding & tending the fire in better or worse ways. But it's still modeled as an uncontrollable force of nature, to be occasionally influenced but never tamed. I'll call this the "fire" model of love.
We're also taught (and non-boys are taught more stringently) a second contradictory model of love: that in a relationship, we need to both do things and be things in order to make our partner love us, and that if we don't, our partner's love for us will wither, and (especially if you're not a boy) it will be our fault. I'll call this the "appeal" model of love.
Now obviously both of these cannot be totally true at once, and plenty of popular media centers this contradiction, but there are really very few competing models on offer.
In my experience, however, it's possible to have "pre-meditated" love. In other words, to decide you want to love someone (or at least, try loving them), commit to that idea, and then actually wind up in love with them (and them with you, although obviously this second part is not directly under your control). I'll call this the "engineered" model of love.
Now, I don't think that the "fire" and "appeal" models of love are totally wrong, but I do feel their shortcomings often suggest poor & self-destructive relationship strategies. I do think the "fire" model is a decent model for *infatuation*, which is something a lot of popular media blur into love, and which drives many (but not all) of the feelings we normally associate with love (even as those feelings have other possible drivers too). I definitely experienced strong infatuation early on in my engineered relationship (ugh that sounds terrible but I'll stick with it; I promise no deception was involved). I continue to experience mild infatuation years later that waxes and wanes. It's not a stable foundation for a relationship but it can be a useful component of one (this at least popular media depicts often).
I'll continue these thoughts in a reply, by it might take a bit to get to it.
#relationships

The liberal obsession with optics serves the right and persuades no one. There is literally an active ethnic cleansing happening in the US right now, and the only thing that matters is making that as hard as possible to carry out.
Anarchists destroying intelligence assets saves lives. Every escooter thrown at a cop car is one less escort for a goon too afraid to kidnap random brown people without being flanked by a branch full of bad apples. Spray paint is not violence. Vandalism is not violence. Community self defense in all forms is legitimate.
Make no mistake, these raids are about changing demographics. Demographic trends have been shifting blue for a long time, and the right has, for a long time, been blaming "white replacement." Conspiracy theory aside, Democrats have also been relying on the growth of black and brown voters as a block. The nuances of whiteness as an identity are lost on the current administration and their supporters. They see that "white people will be a minority by 2050" and equate that with the "end of Western Civilization."
The only way to "save Western Civilization" is to change those demographics. Forced birth and forced removal are two sides of the same white nationalist objective. Of course they can't have due process, because they need to be able to kidnap anyone who they see as a threat to their demographic future.
They don't care about optics. The plan is to murder away any threat and flood everyone else with propaganda. There is no mythical middle. There's no one unconvinced. They know this, but they win when democrats buy that myth and save the police the work of policing the protests.
If your protest is 90% "peaceful," they'll take pictures of the 10% that isn't. If it's 99% peaceful, they'll shoot rubber bullets and teargas until someone throws a brick and take 100 pictures from a dozen angles. If its 100% "peaceful" and no one can be provoked, they'll generate pictures with AI or photoshop like they did during the George Floyd uprising and the pictures from the CHOP/CHAZ. Do you have literally no memory?
#USPol #FiftyFiftyOne #50501movenent #resistance #NoKingsDay #NoKingsDayOfAction

LLM coding is the opposite of DRY
An important principle in software engineering is DRY: Don't Repeat Yourself. We recognize that having the same code copied in more than one place is bad for several reasons:
1. It makes the entire codebase harder to read.
2. It increases maintenance burden, since any problems in the duplicated code need to be solved in more than one place.
3. Because it becomes possible for the copies to drift apart if changes to one aren't transferred to the other (maybe the person making the change has forgotten there was a copy) it makes the code more error-prone and harder to debug.
All modern programming languages make it almost entirely unnecessary to repeat code: we can move the repeated code into a "function" or "module" and then reference it from all the different places it's needed. At a larger scale, someone might write an open-source "library" of such functions or modules and instead of re-implementing that functionality ourselves, we can use their code, with an acknowledgement. Using another person's library this way is complicated, because now you're dependent on them: if they stop maintaining it or introduce bugs, you've inherited a problem, but still, you could always copy their project and maintain your own version, and it would be not much more work than if you had implemented stuff yourself from the start. It's a little more complicated than this, but the basic principle holds, and it's a foundational one for software development in general and the open-source movement in particular. The network of "citations" as open-source software builds on other open-source software and people contribute patches to each others' projects is a lot of what makes the movement into a community, and it can lead to collaborations that drive further development. So the DRY principle is important at both small and large scales.
Unfortunately, the current crop of hyped-up LLM coding systems from the big players are antithetical to DRY at all scales:
- At the library scale, they train on open source software but then (with some unknown frequency) replicate parts of it line-for-line *without* any citation [1]. The person who was using the LLM has no way of knowing that this happened, or even any way to check for it. In theory the LLM company could build a system for this, but it's not likely to be profitable unless the courts actually start punishing these license violations, which doesn't seem likely based on results so far and the difficulty of finding out that the violations are happening. By creating these copies (and also mash-ups, along with lots of less-problematic stuff), the LLM users (enabled and encouraged by the LLM-peddlers) are directly undermining the DRY principle. If we see what the big AI companies claim to want, which is a massive shift towards machine-authored code, DRY at the library scale will effectively be dead, with each new project simply re-implementing the functionality it needs instead of every using a library. This might seem to have some upside, since dependency hell is a thing, but the downside in terms of comprehensibility and therefore maintainability, correctness, and security will be massive. The eventual lack of new high-quality DRY-respecting code to train the models on will only make this problem worse.
- At the module & function level, AI is probably prone to re-writing rather than re-using the functions or needs, especially with a workflow where a human prompts it for many independent completions. This part I don't have direct evidence for, since I don't use LLM coding models myself except in very specific circumstances because it's not generally ethical to do so. I do know that when it tries to call existing functions, it often guesses incorrectly about the parameters they need, which I'm sure is a headache and source of bugs for the vibe coders out there. An AI could be designed to take more context into account and use existing lookup tools to get accurate function signatures and use them when generating function calls, but even though that would probably significantly improve output quality, I suspect it's the kind of thing that would be seen as too-baroque and thus not a priority. Would love to hear I'm wrong about any of this, but I suspect the consequences are that any medium-or-larger sized codebase written with LLM tools will have significant bloat from duplicate functionality, and will have places where better use of existing libraries would have made the code simpler. At a fundamental level, a principle like DRY is not something that current LLM training techniques are able to learn, and while they can imitate it from their training sets to some degree when asked for large amounts of code, when prompted for many smaller chunks, they're asymptotically likely to violate it.
I think this is an important critique in part because it cuts against the argument that "LLMs are the modern compliers, if you reject them you're just like the people who wanted to keep hand-writing assembly code, and you'll be just as obsolete." Compilers actually represented a great win for abstraction, encapsulation, and DRY in general, and they supported and are integral to open source development, whereas LLMs are set to do the opposite.
[1] to see what this looks like in action in prose, see the example on page 30 of the NYTimes copyright complaint against OpenAI (#AI #GenAI #LLMs #VibeCoding