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Let’s go for my web review for the week 2024-34.

Unbundling Profile: MIT Libraries - SPARC

Tags: research, copyright, open-access

It’s good to see major institutions like this get out of contracts with scientific publishing companies. Those unfortunately became mostly parasitic. Open access should be the norm for research.

https://sparcopen.org/our-work/big-deal-knowledge-base/unbundling-profiles/mit-libraries/

Make Firefox Private Again

Tags: tech, mozilla, privacy

Since they unfortunately turned on private attribution by default (why? Mozilla, why?). Here is an easy automated way to turn it off.

https://make-firefox-private-again.com/

Being on The Semantic Web is easy, and, frankly, well worth the bother

Tags: tech, web, semantic

With all those bots and scripts crawling the Web, some of the semantic web vision got silently implemented.

https://csvbase.com/blog/13

Markov chains are funnier than LLMs

Tags: tech, ai, machine-learning, gpt, markov-chains, funny

Interesting musing. The predictability in tone doesn’t make for very funny content indeed. Also as a side-effect this might help people remember that Markov chain are a thing and much less expensive.

https://emnudge.dev/blog/markov-chains-are-funny/

ugh. I picked up a shitty NUC from ewaste…

Tags: tech, security

Scary thread… developers should know better than do this and ship it on devices around the world. Their data is now anyone for the taking and users’ privacy can’t be ensured.

https://digipres.club/@foone/112990331505043510

NetAlert X

Tags: tech, networking, security, tools

Looks like a nice tool to monitor your network.

https://netalertx.com/

Free, OpenSource IPv6 Textbook

Tags: tech, book, ip, networking

Looks like an interesting resource to learn about IPv6.

https://ipv6textbook.com/

Andries Brouwer on the OOM killer

Tags: tech, linux, kernel, memory

Funny musing about the OOM killer. With nice pointers if you want to dive further into the topic.

https://quuxplusone.github.io/blog/2024/08/22/overcommit/

The Closed-Loop Benchmark Trap

Tags: tech, benchmarking

Be sure to pick the right behavior model when you make a benchmark. Otherwise you might just measure the wrong thing.

https://buttondown.com/jaffray/archive/the-closed-loop-benchmark-trap/

What is std::ref?

Tags: tech, c++

A little refresher about std::ref and std::cref. They come in handy sometimes, but also if you don’t realize you need them you’ll generate more copies than necessary.

https://www.sandordargo.com/blog/2024/08/21/std-ref

SIMD Matters :: Box2D

Tags: tech, cpu, simd, performance, physics, simulation

SIMD is hard to use, not all problems can apply to it. But when they can, the performance gain can be great.

https://box2d.org/posts/2024/08/simd-matters/

uv: Unified Python packaging

Tags: tech, python, tools

Looks like there’s another contender for package management for Python. This is sooo fragmented now… this one is compelling though.

https://astral.sh/blog/uv-unified-python-packaging

Common Causes of Memory Leaks in JavaScript

Tags: tech, javascript, memory, leak

There are many ways to create a memory leak in Javascript. Here is a good list of the things to pay attention to.

https://www.trevorlasn.com/blog/common-causes-of-memory-leaks-in-javascript

Toasts are Bad UX – Max Schmitt

Tags: tech, web, frontend, ux

It’s better than no feedback. It’s a bit lazy and far from perfect though.

https://maxschmitt.me/posts/toasts-bad-ux

Reckoning

Tags: tech, web, frontend, ux, criticism

Interesting series about the rise of the javascript frontend framework, the bad practices which came with them and the very real impacts on the users. There are indeed better ways.

https://infrequently.org/series/reckoning/

Don’t Repeat Yourself and the Strong Law of Small Numbers - iRi

Tags: tech, design, programming

This is a good point. The DRY principle has value but the trick is finding the right time to apply it.

https://jerf.org/iri/post/2024/dry_strong/

Code review antipatterns

Tags: tech, codereview

Starts like a satire, but there’s a serious conclusion in the end. Indeed, mind the power dynamics in code reviews. Be nice, steer away from those antipatterns, especially since you might be on the receiving end the next time.

https://www.chiark.greenend.org.uk/~sgtatham/quasiblog/code-review-antipatterns/

Interview with Ron Jeffries

Tags: tech, agile, history, criticism

Very nice interview. This is an interesting reflection on the past 20+ years of Agile Software Development.

https://ronjeffries.com/articles/-x024/-v04/8/

Decision Logs

Tags: tech, product-management

Nice way to keep in check how and why behavior changes as the requests from various stakeholders come in.

https://buttondown.com/j2kun/archive/decision-logs/

Bug squash: An underrated interview question

Tags: tech, hr, interviews, debugging

This is indeed a nice way to approach technical interviews. Unfortunately it requires quite some effort to setup and maintain. You also have to find the right bugs to put in the interview and this is a rarity.

https://blog.jez.io/bugsquash/

Bye for now!

In the final instalment of The DropTimes' "Meet the Candidate" campaign for the Drupal Association's 2024 Board Election, we sit down with Alejandro Moreno Lopez, Partner Manager and Developer Relations at Pantheon. Alejandro discusses his journey within the Drupal community, his vision for reducing the Association's dependency on DrupalCon, and his commitment to fostering collaboration and innovation. With voting open until September 5th, this interview offers key insights into how Alejandro plans to contribute to the future of Drupal.

The "Drupal Decoupled" project introduces a new Composer Project Template and Recipes integration, streamlining the setup for decoupled architecture. This update promises to reduce developers' development time and effort.

Are you interested in learning robotics with Python? Can physical electronics-based projects grow a child's interest in coding? This week on the show, we speak with author Marwan Alsabbagh about his book "Build Your Own Robot - Using Python, CRICKIT, and Raspberry Pi."

[ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

I've been spending some time recently trying to get the Umami demo message from toolbar into the navigation module.

Since Plasma 5.18, nearly five years ago, Plasma has shipped with a "telemetry" system. It’s opt-in, allowing users to send a small amount of data back to us.

Was it useful or worth it? It's a question that comes up occasionally, and the answer is mixed. I believe it showed real potential, though the reality of our implementation was somewhat underwhelming and didn't really deliver. There are many lessons learned that are worth sharing with other projects that might face similar endeavours.

The good bits

Where we had data available for topics being discussed it worked. To give two concrete examples from memory:

• A developer claimed, "No one is using a screen smaller than 1024x768," while bumping the minimum size of a window. This was proved wrong; the number of users at 800x600 or even 640x480 is surprisingly high. Still low as an overall percentage, but higher than you would ever intuitively think. Presumably, it's the default for a lot of virtual machines.

• Four years ago, a developer claimed, "No one still uses only OpenGL2; we can change the code to do XYZ." A check of our user base showed it would have affected nearly 5% of our users, so the change was abandoned.

Interestingly, this last topic came up again very recently, as it held back colour management improvements, but in a narrower Wayland-only path and with a fallback. After checking metrics again, the usage was below 1%, so we went ahead with that merge request.

So, are metrics worth it just to stop developers and designers from making nonsense claims out of thin air? Absolutely! 90% of stats are just made up on the spot. Metrics are just as much about preventing changes as it is about sparking changes.

Indirect impact

The other important part is having a more general sense of the landscape. Currently, we have a lot of hard conversations about how quickly we push the move to Wayland. We have voices wanting to maintain support, and we have voices wanting to push quicker. These decisions shouldn't be made just by who can be the loudest. For every individual topic that came up in those discussions, I would always have in mind our current adoption value at the time.

Should we care about Nvidia? Knowing they make up about 25% of our user base makes the decision for us. I ran with an Nvidia card in one machine because of this, implementing Nvidia context loss handling and doing what we could during the Wayland transition
We don't test BSD while developing Plasma, but we also let it hold us back. Should we care about it more or less? My opinion matches exactly what the metrics say.

Some stats and graphs:

Another role of metrics is being a conversation starter—people will fawn over a graph. More topics on Reddit will be about our Wayland usage rather than the topic I'm trying to discuss. I'll focus on Wayland examples beacuse that's a topic close to me.

Wayland adoption over time

I keep tabs on what our metrics show here. We can see the slow increase from under 20% to around 45% over time, showing the progress as both we and the Wayland ecosystem evolved. At Plasma 6, we switched the defaults a small bump in the graph can be seen. but 45% still seemed rather disappointing.

Filtering on just Plasma 6 reveals the true story:

There's still 20% of users switching away, or using a distro with a different default, or having carried over presets, but it's more promising. Interestingly, we can see that the GPU vendor distribution differs between X11 and Wayland.

Problems and lessons learned

Ultimately, despite the positive parts it would be hard to call our telemetry a staggering success. For the handful of examples above, there are a hundreds of cases where we had no data to back anything up. The range of data points was pitiful and it wasn't often used

The viewing tool is really, really important!

Data collection without viewing it is meaningless. As shown above, we often need to drill down and cross-reference filters to extract conclusions.

The original plan was to use the existing UI provided by kuserfeedback, which did not scale at all and quickly fell over. It was designed for high-fidelity data for a small number of users, not what we had.

In a rush, we pivoted to using Grafana because there was already a setup hosted.

It worked—ish, but it’s not designed for this, especially combined with our data structure, which was a manual NoSQL in normal SQL. Every graph needed to be written by hand, and it felt very much like fighting the system rather than working with it. Combined with the limited access permissions granted, it wasn't used by many people.

It being used is the number one indicator of its usefulness!

We need to find a tool specifically designed for visualization and querying datasets (maybe Apache Superset?).

Time-based data just makes noise

Our system sent updates every N days with basically the same data every time. This made writing queries way messier than it should have been. It never added any value; I would always be interested in what the current stats are. As described in the Wayland usage graphs above, if I'm making a Wayland decision, it doesn't matter what most people are using; it matters what people on the latest release are using. We always ended up having to add filters to focus on just the latest version.

The upgrade story needs planning in advance

The amount of data we collected was tiny—some GPU information, screen information, language, and a few other fragments. The plan was to slowly add more and more stats over time, but we hit a wall. Our UX involved the user selecting to enable metrics and it being a fire-and-forget operation.

What do we do when we want to add more data? For example, whether you use an analog or digital clock. We would need to prompt the user and reset their settings in the meantime, which is at odds with it being a setting. The whole thing became such an ordeal that made it not worthwhile.

Wrap up

The project didn't fail, when we had data and it was used it worked, but overall our implementation falls short. I would like to open a discussion at Akademy on how we move forward with our current system potentially starting from scratch treating it more like a survey that we prompt to auto populate and submit each year.

Using React in Drupal Themes Editor Fri, 08/23/2024 - 11:39

React can rightfully be called a game-changer JavaScript library for Drupal developers, as it can completely change the way interfaces are built. By integrating it into Drupal themes, we can enter a completely new world full of creativity and convenient functions, thus improving user experiences significantly. 
With the help of React, interfaces of websites built on Drupal will no longer be static and boring: they become real, interactive, and fast. Less words, let's learn more details about how you can benefit from using React in Drupal themes.

In this episode, we continued the break from JourneyInbox to look through more of the Go standard library. In this session, we talked about middleware, request context, and using databases.

The End Product

Throughout this summer, I’ve developed a C++ library called MankalaEngine, implementing three opponents for the games of Bohnenspiel and Oware.

The current library is highly extensible. After implementing all the base classes and Bohnenspiel, adding Oware to the library was fairly fast and straightforward. This focus on extensibility has been a priority since the beginning of the project. Given that the Mancala family of games comprises numerous variants, designing the API with this in mind has proven valuable.

The three provided opponents use a random selection algorithm, Minimax, and MTD-f. The Minimax and MTD-f opponents were implemented with optimizations like alpha-beta pruning and transposition tables, making them both very capable, consistently outperforming the random opponent.

For a more detailed overview of what was accomplished, I wrote a work report on KDE’s wiki.

What I’ve learned

The last few months have been a very enriching experience from a technical standpoint.

Contributing to a “real-world” project allowed me to learn about technologies I hadn’t used before. For example, I learned how to use CMake and how to set up a CI pipeline.

I also faced concerns that don’t typically arise when developing a school or personal project, such as adhering to an organization’s software standards. To this end, I learned about open-source licenses and new programming idioms.

Interacting With The Community

Since MankalaEngine is a completely new library, my interaction with the community was limited, as there isn’t an existing group of contributors for this particular project.

I mainly interacted with my mentors, who were very helpful. Although less frequently, I also had the opportunity to communicate with other KDE contributors through mailing lists, from whom I also learned a great deal.

During Debconf, Edward Betts and myself started packaging Home Assistant for Debian. It consists of hundreds of Python packages. So far, we counted at least 675 packages. That’s a lot, though most packages are just libraries to talk with some IoT devices and some APIs. It’s fairly easy to create a new package: it takes me about 15 to 20 minutes, probably half that time to Edward. And it’s a lot of fun. So far in one month of time, we managed to package about 1 third of the list (probably 200+ Python packages already). Once we’ve done all the dependencies, we may start to have fun with the core of the application! At the current speed, hopefully we’ll be done before the end of the year. Edward and myself have swear to make at least one package a day, which I’ve been doing so far, and Edward did a way more… We also received contributions from Silton0506, Tianyu, piotr, EiPi Fun, sourabhtk37, and Count-Dracula, as per the very bottom of the TODO list in the wiki (see link below).

If you have a bit of free time, we’d love to have more contributors. Here’s were to get the needed information:

We created a team in Salsa: https://salsa.debian.org/homeassistant-team/

Our TODO list: https://wiki.debian.org/Python/HomeAssistant

Our DDPO Q/A page: https://qa.debian.org/developer.php?login=team%2Bhomeassistant%40tracker.debian.org

Feel free to join us on IRC: #debian-homeassistant

Discussing with a lot of people about it, I realized that A LOT of DDs are actually using Home Assistant. Wouldn’t you like it better if it was just a “apt install” away ? Any DD can simply take a package in the wiki, open an ITP, upload it’s debianized source on Salsa, and upload to the Debian archive. Most are very easy simple packages to make.

Interview With Keynote Speaker, Preston So Published Date Thursday, August 22nd, 2024 - 06:10 pm bcross Thu, 08/22/2024 - 18:10

Talking to Preston So is easy. 

I was nervous before our conversation simply because on paper there are things about the man that are frankly intimidating. Author of Content Strategy for Mobile Karen McGrane named Preston “the smartest guy in the field” in 2024. He was called “probably the smartest person working in this industry right now” by Deane Barker, author of Web Content Management. 

But Preston So one-on-one is so personable, so engaging, that he instantly put me at ease. We talked about some aspects of his life and career, his experiences working in Drupal and other content management systems, what his keynote will be about, as well as his love of travel and learning languages.

Preston, you work at dotCMS. Can you talk a bit about what your job is and what it is you're doing?

Many of the folks who know me from the Drupal world are probably a little surprised to see that I've gone over to a Java-based CMS. But I used to work at Oracle also, which was a Java-based CMS. I don't really have a lot of opinions about Java versus PHP, but I know there's some strong opinions on both sides.

But dotCMS is really interesting as a company. We're an open source CMS. You can see all of our code, all of what we do. You can contribute if you want to. So in that case, it's very similar to Drupal. 

I joined dotCMS about five or six months ago as our new VP of product. And in that role, I basically oversee all of our sort of product or product-related functions. And that means our product team, our design team, our data function, our developer relations function. And also, I work on our analyst relations functions as well. So I wear a lot of hats at dotCMS.

And it's very similar to what I was doing before. I mean, my background has always been in software, in the actual engineering … in coding.

I read in your bio about your interest in voice interface and voice content. Can you talk a bit about your interest in non-traditional interfaces like voice?

This ties into the writing I've done in the past around what I call the “channel explosion”…. These days, content needs to go to a lot of different places. One of the things that we often forget, especially those of us who have primarily worked with web content, is that content isn't just read, right? It's also spoken. It's also aural. It's visual. It's spatial. There are so many things about content that aren't really … tied to that rectangular box that we call the website or the screen or the web browser.

And a really good example of that is voice interfaces and voice bots or voice assistants. About seven or eight years ago, I was part of a really amazing team at Acquia, [that] worked on the first ever Alexa skill for the state of Georgia, building an Amazon Alexa skill that would allow people to ask questions: like, how do I register to vote or how do I enroll my child in pre-K?

Content needs to come from a single source of truth. You're seeing a lot of these new use cases emerge where people want to serve content to a mobile app, people want to serve content to a Roku device, people want to serve content to an AR overlay, for example, in your Vision Pro.

One of the reasons why I've been so interested in voice is because it really throws out a lot of the prescriptions and a lot of the ideas that we have about content, a lot of those biases that we have towards written, visual online content…. Web content is actually more abstracted away from natural human language and natural human biology than is speech-based interfaces or how we actually converse.

So I wrote a book about five years ago called Voice Content and Usability. In that book, I talk about voice content strategy, voice content design, how do you actually get content ready for a voice interface? And how do you actually implement an end-to- end voice interface that needs to consume content from a CMS?

When that book came out, there weren't a whole lot of Alexa content-driven implementations. It was basically just Capital One balance checking and Domino's Pizza ordering. And that was about it. No one had ever done a content-driven voice interface that was more informational rather than transactional.

Unfortunately, a lot of the things that have happened over the last few years with generative AI have really thrown those approaches out the window, because oftentimes with AI, you don't really feed it content. You're looking at content that is being reconstituted … by the AI as opposed to something that you're actually serving. But for governments, it's a much, much bigger concern for that content to stay up to date.

[You want] to help somebody learn how to get health insurance, or how to file a death certificate, [and that] cannot be mucked up by AI hallucinations or incorrectness. This is one of the reasons why voice content strategy and voice content still remains so relevant.

Your bio says that you're interested in “endangered and underserved languages”. Where else does your interest in learning languages come from?

My biggest passion outside of work, outside of professional pursuits, is travel and languages. A lot of it comes from my background. I spent a good amount of time in Brazil when I was younger, so I'm fluent in Portuguese because I did an exchange program there. I taught English there in college as well. I also spent time in Wales.

Some of the richest interactions and some of the richest experiences I have when I travel are when I'm able to converse in a language that is a very seldom learned language, a very atypical language. It's a language that people don't really often take the time to learn or have much of an interest in learning. But [these languages are the way] in which you can get to know the culture, get to know the food, get to know just the way that people interact in these other environments and in these other languages. 

Languages are entire universes unto themselves. Especially those languages that have that rich, rich tradition of oral language traditions or rich literature that stretches back for centuries. I love to focus on languages that I can speak right now with people today.

Right now, I'm focusing on three languages – two of them are incredibly difficult. The third is a little bit easier, and it's all towards a vacation I've got planned with a friend coming up in November. We're headed to South Africa, and so I'm learning Afrikaans, which is obviously at the center of Middle Dutch, the sort of colonial language in South Africa, but I'm also learning Xhosa and Zulu, which are two of the Nguni languages spoken in South Africa.

Can you say a little more about the keynote presentation that you're going to be giving at Twin Cities Drupal Camp?

Over the past four to five years, I've been tracking sort of dissatisfaction on both sides of CMS. 

I think one of the things that's really unique about the content management system is that it occupies a very unique ecological niche in the software world. Whereas a lot of other software products have a focus on individual personas, like Salesforce for salespeople. CRM tools tend to be for those kinds of folks. 

The CMS has always been very unique in software because it brings together people with very different skills and very different priorities. Two of those personas that are probably the chief personas that the CMS deals with are, number one, the CMS developer. And then number two, the sort of content practitioner or content team or content architect or compliance reviewer or accessibility reviewer, everyone who has a stake in making sure that content is successful.

But we know based on just hearing from folks around the CMS industry that we're starting to see a bit of a schism right now, which is that there is, number one, a trend for developers to go towards headless CMSs, like Contentful, Sanity, some of those, and really go in that direction. But the problem with that is that it kind of leaves content teams with their hands tied behind their back. They can't really do drag and drop layout management anymore. They can't do preview of all of their different sites anymore. There's a lot of issues that come up with headless CMS.

But by the same token, developers today really don't want to work with the sort of monolithic or traditional CMS anymore. I love Twig. I love PHP template. There's a lot of folks who don't. There's a lot of folks, especially who are coming into front-end development nowadays, that really, really don't like to work with those paradigms. 

One of the things that I think is really important is that as we contend with this huge influx of new JavaScript frameworks like Astro, SELT, so on and so forth, and also new delivery channels like we were talking about earlier, Blaine, around AR, VR, voice, AI, so on and so forth, it becomes a really big concern.

How do we actually collaborate effectively in a CMS that works for everybody and not just one half of the back office? One of the struggles that we see very often is that oftentimes headless CMSs will say, well, hey, content is just the data. Let us handle the presentation. Let us handle the front-end. Let us handle how things look.

But what that does is it severs all those linkages with how content authors want to preview, with how content editors want to be able to look at and review or schedule content or review things for compliance or review things for accessibility, so on and so forth. But developers also don't want to be held back.

The topic of my talk is really what I call the universal CMS, which is a new pair and I am really quickly getting a lot of traction. It really is about restoring the balance that characterized the early static web CMS era. Basically saying, hey, we could do all these really cool things with the website, but we had a handshake where we agreed that, hey, developers, if you hand over control over layout and control over all of these visual components, I will give you obviously control over how to code the whole thing.

But this unique grand compromise that we forged is something that is starting to come back. We are starting to see headless CMSs build in visual editing features which violate the peer headless architectural prescription. We are also seeing a lot of the old traditional CMSs or monolithic CMSs begin to build a lot more APIs and SDKs for JavaScript developers or mobile app developers to build on top of. And so I think what we are going to start to see here is a convergence between both the headless CMSs and the traditional CMSs towards a new equilibrium which I call universal CMS.

And here in just a few years, I think we are going to get rid of this full distinction between headless and monolithic and all of those tired terms that have a lot of baggage with them.

[Short bio]

Preston So (he/they) is a product executive with over 25 years in software, 17 years in content technologies, and 9 years leading product, design, engineering, and developer relations functions at organizations such as Oracle, Acquia, dotCMS, Time Inc., and Gatsby. He is Vice President, Product at dotCMS and the author of Immersive Content and Usability (A Book Apart, 2023), Gatsby: The Definitive Guide (O'Reilly, 2021), Voice Content and Usability (A Book Apart, 2021), and Decoupled Drupal in Practice (Apress, 2018).

Named “the smartest guy in the field” by Content Strategy for Mobile author Karen McGrane in 2024 and “probably the smartest person working in this industry right now” by Web Content Management author Deane Barker in 2020, Preston is a globally recognized authority on the intersections of content, design, and code. He is an editor at A List Apart and former top-read columnist at CMSWire. Preston is a frequent presenter with 17 years of speaking engagements spanning over 50 conferences, including SXSW Interactive (2017, 2017 encore, 2018) and An Event Apart (2020–22) and keynotes in three languages. He is based in New York City, where he can often be found immersing himself in languages that are endangered or underserved.

Posted In Drupal Planet

Diego wrote about his dislike for Advent of Code and that reminded me I hadn’t written up my experience from 2023. Mostly because, spoiler, I never actually completed it and always intended to do so and then write it up. I think it’s time to accept I’m not going to do that, and write down some thoughts before I forget all of them. These are somewhat vague, given the time that’s elapsed, but I think still relevant. You might also find Roger’s problem write up interesting.

I’ve tried AoC a couple of times before; I think I had a very brief attempt back in 2021, and I got 4 days in for 2022. For Advent of Code 2023 I tried much harder to actually complete the challenges, and got most of the way there. I didn’t allow myself to move on to the next day until fully completing the previous day, and didn’t end up doing the second half of December 24th, or any of December 25th.

Rust

First I want to talk about Rust, which is the language I chose to use for the problems. I’ve dabbled a little in it, but I’d like more familiarity with the basic language, and some programming problems seemed like a good way to get that. It’s a language I want to like; I’ve spent a lot of my career writing C, do more in Go these days, and generally think Rust promises a low level, run-time light environment like C but with the rough edges taken off.

I set myself the challenge of using just bare Rust; no external crates, no use of cargo. I was accused of playing on hard mode by doing this, but it really wasn’t the intention - I figured that I should be able to do what I needed without recourse to anything outside the core language, and didn’t want what seemed like the extra complexity of dealing with cargo.

That caused problems, however. I’m used to by-default generic error handling in Go through the error type, but Rust seems to have much more tightly typed errors. I was pointed at anyhow as the right way to do this in Rust. I still find this surprising; I ended up using unwrap() a lot when I think with more generic error handling I could have used ?.

The other thing I discovered is that by default rustc is heavy on the debug output. I got significantly better results on some of the solutions with rustc -O -C target-cpu=native source.rs. I probably shouldn’t be surprised by this, but worth noting.

Rust, to me, has a syntax only a C++ programmer could love. I am not a C++ programmer. Coming from C I found Go to be a nice, simple syntax to learn. Rust has not been the same. There’s a lot more punctuation, and it’s not always clear to me what it’s doing. This applies more when reading other people’s code than when writing it myself, obviously, but I see a lot of Rust code that could give Perl a run for its money in terms of looking like line noise.

The borrow checker didn’t bug me too much, but did add overhead to my thinking. The Rust compiler is generally very good at outputting helpful error messages when the programmer is an idiot. I ended up having to use a RefCell for one solution, and using .iter() for loops rather than explicit iterators (why, why is this different?). I also kept forgetting to explicitly mark variables as mutable when declaring them.

Things I liked? There’s a rich set of first class data types. Look, I’m a C programmer, I’m easily pleased. You give me some sort of hash array and I’ll be happy. Rust manages that, tuples, strings, all the standard bits any modern language can provide. The whole impl thing for adding methods to structures I like as a way of providing some abstraction, though I think Go has a nicer syntax for it. The compiler, as mentioned, is great at spitting out useful errors for the most part. Also although I wasn’t using external crates for AoC I do appreciate there’s a decent ecosystem there now (though that brings up another gripe: rust seems to still be a fairly fast moving target, to the extent I can no longer rely on the compiler in Debian stable to be able to compile random projects I find).

Advent of Code

Let’s talk about the advent of code bit now. Hopefully it’s long enough since it came out that this won’t be spoilers for anyone, but if you haven’t attempted the 2023 AoC and might, you might want to stop reading here.

First, a refresher on the format for those who might not be aware of it. Problems are posted daily from December 1st until the 25th. Each is in 2 parts; the second part is not viewable until you have provided the correct answer for the first part. There’s a whole leaderboard thing going on, but the puzzle opens at midnight UTC-5 so generally by the time I wake up and have time to look the problem has been solved many times over; no chance of getting listed.

Credit to AoC creator, Eric Wastl, for writing up the set of problems in an entertaining fashion. I quite enjoyed seeing how the puzzle would be phrased each day, and the whole thing obviously brings a lot of joy to folk I know.

I always start AoC thinking it’ll be a fun set of puzzles to solve. Then something happens and I miss a day or two, and all of a sudden I’ve a bunch of catching up to do and it’s all a bit more of a chore. I hit that at some points this time, but made a concerted effort to try and power through it.

That perseverance was required up front, because I found the second part of Day 1 to be ill specified, and had to iterate a few times to actually calculate the desired solution (IIRC, issues about whether sevenone at the end of a line ended up as 7 or 1 really tripped me up). I don’t recall any other problems that bit me as hard on the specification as this one, but it happening up front was unfortunate.

The short example input doesn’t always help with this either; either it’s not enough to be able to extrapolate patterns, or it doesn’t show all the variations you need to account for (that aren’t fully specified in the text), or in a few cases it turned out I needed to understand the shape of the actual data to produce a solution that could actually complete in a reasonable time.

Which brings me to another matter, sometimes brute force doesn’t actually work. This is fine, but the second part of the day’s problem can change the approach you’d take. So sometimes I got lucky in the way I handled the first half, and doing the second half was a simple 5 minute tweak, and sometimes I had to entirely change the way I was storing data.

You might claim that if I was a better programmer I’d have always produced a first half solution that was amenable to extension for the second half. First, I dispute that; I think there are always situations where the problem domain can change in enough directions that you can’t handle all of them without a lot of effort. Secondly, I didn’t find AoC an environment that encouraged me to optimise for generic solutions. Maybe some of the puzzles in isolation would allow for that, but a month of daily problems to solve while still engaging in regular life meant I hacked things up, took short cuts based on the knowledge I had of the input data, etc, etc.

Overall I can see the appeal, but the sheer quantity and the fact I write code as part of my day job just made it feel too much like a chore, rather than a fun mental exercise. I did wonder how they’d look as a set of interview puzzles (obviously a subset, rather than all of them), but I’m not sure how you’d actually use them for that - I wouldn’t want anyone to have to solve them in a live interview.

So, in case it’s not obvious, I’m not planning to engage in AoC again this yet. But I’m continuing to persevere with Rust (though most of my work stuff is thankfully still Go).

Machine learning and artificial intelligence are transforming the world as we know it. With the power of data, you will have countless opportunities to create something new, unique, and exciting. Whether you are a seasoned data scientist or a curious beginner, you need a platform that can help you build, train, deploy, and manage your machine learning models with ease and efficiency. Azure Machine Learning has always been the backbone for machine learning tasks, and we want to further help you in your machine learning journey by improving the way you write code.

The VS Code extension for Azure Machine Learning has been in preview for a while and we are excited to announce the general availability of the VS Code extension for Azure Machine Learning. You can use your favorite VS Code setup, either desktop or web, to build, train, deploy, debug, and manage machine learning models with Azure Machine Learning from within VS Code. This means that the extension is stable, reliable, ready for production use, and comes with additional features, such as VNET support.

 

“We have been using the VS Code extension for Azure Machine Learning since its preview release, and it has significantly streamlined our workflow. The ability to manage everything from building to deploying models directly within our preferred VS Code environment has been a game-changer. The seamless integration and robust features like interactive debugging and VNET support have enhanced our productivity and collaboration. We are thrilled about its general availability and look forward to leveraging its full potential in our AI projects.” – Ornaldo Ribas Fernandes: Co-founder and CEO, Fashable

Azure Machine Learning

Azure Machine Learning (Azure ML) is a cloud-based service that enables you to build, train, deploy, and manage machine learning models.

With Azure Machine Learning service, you can:

• Build and train machine learning models faster, and easily deploy to the cloud or the edge.
• Use the latest open-source technologies such as TensorFlow, PyTorch, or Jupyter.
• Experiment locally and then quickly scale up or out with large GPU-enabled clusters in the cloud.
• Interactively debug experiments, pipelines, and deployments using the built-in VS Code debugger.
• Speed up data science with automated machine learning and hyper-parameter tuning.
• Track your experiments, manage models, and easily deploy with integrated CI/CD tooling.

With this extension installed, you can accomplish much of this workflow directly from Visual Studio Code. The VS Code extension provides a user interface to create and manage Azure ML resources, such as experiments, compute targets, environments, and deployments. It also supports the Azure ML 2.0 CLI, which is the new command-line tool that simplifies the specification and execution of machine learning tasks.

Get Started with Azure Machine Learning Extension One click Connect to VS Code from Azure ML Studio

To get started with VS Code, navigate to the compute section of your Azure Machine Learning Studio. Find the desired compute instance and click on the VS Code (Web) or VS Code (Desktop) links under the “Applications” section.

Don’t have an Azure ML workspace or compute instance? Check out the guide here: Tutorial: Create workspace resources – Azure Machine Learning | Microsoft Learn

VS Code Desktop

After clicking on the link for VS Code desktop, the browser will ask you for your permission to launch the VS Code Desktop application. VS Code desktop will ask you to sign in using your Microsoft/Azure account.

Follow the sign-in prompts, then you should be all set up to develop your own machine learning models using your favorite VS Code set up!

VS Code Web

After clicking on the link, VS Code (Web) will open to a new tab on your browser. It may ask you to sign in using your Microsoft/Azure account, so VS Code will have permission to access your Azure subscription and workspace. Note the connection process may take a few minutes.

After signing in, you should now be connected to your Azure Machine Learning workspace inside of VS Code. Time to build your own machine learning model using the full power of VS Code!

Feedback

Give the Azure Machine Learning extension a try and let us know what you think. If you have any questions or feedback, please let us know your thoughts in this survey! You can also file an issue on our public GitHub repo with any questions or concerns you may have.

Need a guide to help you get started or documentation? Check out the tutorials here: Azure Machine Learning documentation | Microsoft Learn

The post Announcing the General Availability of the VS Code extension for Azure Machine Learning appeared first on Python.

This week I built a LocalGov Drupal dashboard, so we can better keep track of all our projects.

Hello everyone! Time flies and now we’re already in the final week of GSoC. In this blog post I’ll be sharing the progress I’ve made since my last update, focusing primarily on subtitle styling.

Subtitle Editor

The first thing I did was to enhance the existing subtitle editor. The updated editor now serves as an interface for editing ASS events, which include various components. With the new subtitle editor, we can easily modify elements such as the event’s layer, style, margins, and more. I’ve also simplified the effects section, allowing us to control subtitle scrolling by simply adjusting checkboxes and combo boxes for speed, direction, and range.

However, the most significant change is the text field and the buttons above it. To better understand these changes, it’s important to first introduce the relationship between ASS styles and events. In ASS files, each event must be assigned a valid style that applies to the entire event text. Additionally, ASS override tags are special text blocks within events that allow precise control over the styles of different parts of the text, rather than the entire text. (There are some exceptions, like “Set Position.”)

The text field has been enhanced to assist users in inputting ASS override tags using the provided buttons. For instance, when a user clicks the “Toggle Bold” button, tags are automatically inserted or adjusted to toggle the bold style for either the selected text or the text following the cursor if nothing is selected. Additionally, the text field features a highlighter that renders different parts of the tags in distinct styles, making them more distinguishable, and an auto-completer that lists all valid presets as we start typing a tag name.

For those who prefer the previous subtitle editor, which only displays the rendered text, a “Simple Editor” is also available. This editor syncs with the normal editor but displays only the text without tags while rendering some basic tag effects. However, due to the complexities of ASS tag rules, style editing in the Simple Editor can sometimes behave unpredictably. So it’s best suited for simpler use cases before or after editing styles.

Subtitle Manager

Continuing from the previous improvements, the Subtitle Manager is now integrated with style management and has been divided into four sections: File, Event, Style, and Info, which correspond to the four main components of ASS subtitles. Each section, except for the File section, includes a sidebar for switching between different subtitle files. Additionally, when in the Style section, we can drag and drop a style item onto a subtitle file name in the sidebar to efficiently move or copy styles between files. The same functionality is available in the Event section, where we can move or copy an entire layer to another file.

Misc Style Editor

A new widget, the Style Editor, was created to edit styles and provide a preview.

Convert Old Global Style

Old styles will now be automatically converted to the “Default” style in the new project. Font size, outline, and shadow will be scaled to maintain the original effects.

Different Default Styles for Layers

Now, we can assign different default styles to each layer, which will automatically be applied to a subtitle event when it’s created on the corresponding layer. This feature is especially useful for quickly building a subtitle file with multiple speakers, allowing each speaker to have a distinct style.

Summary

It has been a wonderful summer getting involved in the KDE community and contributing to Kdenlive! I may not be the best at coding, but I’ve learned a lot throughout this journey. Thanks for everyone who has gave me guidence — Eugen Mohr, Farid Abdelnour, and especially my mentor, Jean-Baptiste Mardelle. While GSoC is coming to an end, my journey with KDE is just beginning. After these updates, I plan to continue improving subtitle functions, including making it easier for users to input more ASS override tags and refining the UI and user experience. See you in my next blog :)

As part of The DropTimes' "Meet the Candidate" campaign for the Drupal Association's 2024 Board Election, Albert Hughes, Product Owner at Stanford University, discusses his candidacy and vision for expanding Drupal’s reach. With the election running until 5 September, Albert shares how his diverse experiences and commitment to innovation can shape the future of the Drupal community.

PORTLAND, Ore., 22 August 2024—The Drupal Association is pleased to announce Tag1 Consulting as a partner for the Drupal 7 Extended Security Support Provider Program. This initiative aims to support Drupal 7 users by carefully selecting providers to deliver extended security support services beyond the 5 January 2025 end-of-life (EOL) date.

The Drupal 7 Extended Security Support Provider Program allows organizations that cannot migrate from Drupal 7 to newer versions by the EOL date to continue using a version of Drupal 7 that is secure and compliant. This program complements the Association’s Drupal 7 Certified Migration Providers Program, which Tag1 is also a participant in, that helps organizations find the right partner to transition their sites from Drupal 7 to Drupal 11.

Tag1’s Drupal 7 extended support offers proactive security and compatibility updates for D7, backed by their team of top Drupal contributors and security experts who led its creation and evolution. With their support, users can continue running D7 as long as they need.

“We’re very pleased to add Tag1 to our Drupal 7 Extended Security Support Program,” commented Tim Doyle, CEO of the Drupal Association.  “Tag1 brings a wealth of experience with Drupal and the Drupal Community, and we’re happy they’re applying their expertise to Drupal 7 support.” 

As organizations prepare for the transition from Drupal 7, Tag1 Consulting will provide the necessary support to keep their sites secure and operational.

“As one of the oldest and most well-known consulting companies in the Drupal ecosystem, we're proud to offer trusted support for Drupal 7 after its end of life,” said Jeremy Andrews, Tag1’s CEO. “Our team is dedicated to helping organizations keep their sites secure and running smoothly, with the same expertise and care that we've brought to the community for over 20 years.”

More information on Drupal 7 Extended Support from Tag1.

About the Drupal Association

The Drupal Association is a nonprofit organization that fosters and supports the Drupal software project, the community, and its growth. Our mission is to drive innovation and adoption of Drupal as a high-impact digital public good, hand-in-hand with our open source community. Through various initiatives, events, and programs, the Drupal Association helps ensure the ongoing development and success of the Drupal project.

About Tag1 Consulting, Inc.

Tag1 is a global technology consulting firm and recognized leader in the Drupal community. Known for our innovative work with top-tier organizations and our pivotal contributions to the Drupal platform itself, we provide unmatched expertise in key areas such as Drupal architecture, performance, scalability, and security. With over 100 team members across 20+ countries, we are the only organization with experience providing Extended Support for Drupal after End-of-Life, proudly having provided commercial support for Drupal 6 for over six years beyond its EOL. The largest and most well known users of Drupal, with the most demanding security needs have relied on Tag1’s Extended Support including Acquia, Pantheon, Fortive, Symantec, Capegmini, the Drupal Association and Drupal.org.

Worried about the future of your Drupal 7 website? With Drupal 7 reaching end-of-life in January 2025, many site owners and developers are facing a tough decision: migrate to a new version of Drupal or to a new platform altogether, or risk running an unsupported site.

Read more michaelemeyers Thu, 08/22/2024 - 07:00

por Allythy

O Debian Day é um evento anual que celebra o aniversário do Debian, uma das distribuições GNU/Linux mais importante do Software Livre, criada em 16 de Agosto de 1993, por Ian Murdock.

No último sábado (17/08/2024) no Sebrae-RN comemoramos os 31 anos Debian em Natal, no Rio Grande do Norte. A celebração, foi organizada pela PotiLivre(Comunidade Potiguar de Software Livre), destacou os 31 anos de história do Debian. O evento contou com algumas palestras e muitas discussões sobre Software Livre. Tivemos 70 inscrições, 40 estiverem presentes.

O Debian Day em Natal foi uma ocasião para celebrar a trajetória do Debian e reforçar a importância do Software Livre.

Palestrantes

Agradecemos imensamente a Isaque Barbosa Martins, Eduardo de Souza Paixão, Fernando Guisso,que palestraram nessa edição! Obrigado por compartilhar tanto conhecimento com a comunidade. Esperamos ver vocês novamente em futuros encontros!

09:00 - 09:40 - Conhecendo projeto Debian - Allytthy e Clara Nobre 09:40 - 10:20 - Proxmox e Homelab: Como Transformei um Mini PC em um Servidor de Respeito) - Fernando Guisso 10:20 - 10:40 Intervalo 10:40 - 11:20 - Analisando a aplicação de algoritmos criptográficos em pacotes de redes - Isaque Barbosa Martins 11:20 - 12:00 - Introdução a escalação de privilégio em sistemas GNU/Linux - Eduardo de Souza Paixão

Link dos slides do Debian Day

Participantes

Um grande obrigado também a todos os participantes, nós fazemos isso por vocês! Esperamos que tenham aprendido, se divertido e feito novas conexões entre a comunidade

Essa edição do Debina Day Natal foi organizada por: Allythy, Clara Nobre, Gabriel Damazio e Marcel Ribeiro.

A new version of the Open Source AI Definition has been released with one new feature and a cleaner text, based on comments received from public discussions and recommendations. We’re continuing our march towards having a stable release by the end of October 2024, at All Things Open. Get involved by joining the discussion on the forum, finding OSI staff around the world and online at the weekly town halls. 

New feature: clarified Open Source model and Open Source weights

• Under “What is Open Source AI,” there is a new paragraph that (1) identifies both models and weights/parameters as encompassed by the word “system” and (2) makes it clear that all components of a larger system have to meet the standard. There is a new sentence in the paragraph after the “share” bullet making this point.
• Under the heading “Open Source models and Open Source weights,” there is a description of the components for both of those for machine learning systems. We also edited the paragraph below those additions to eliminate some redundancy.

Training data in the preferred form to make modifications

The role of training data is one of the most hotly debated parts of the definition. After long deliberation and co-design sessions we have concluded that defining training data as a benefit, not a requirement, is the best way to go.

Training data is valuable to study AI systems: to understand the biases that have been learned, which can impact system behavior. But training data is not part of the preferred form for making modifications to an existing AI system. The insights and correlations in that data have already been learned.

Data can be hard to share. Laws that permit training on data often limit the resharing of that same data to protect copyright or other interests. Privacy rules also give a person the rightful ability to control their most sensitive information, such as decisions about their health. Similarly, much of the world’s Indigenous knowledge is protected through mechanisms that are not compatible with later-developed frameworks for rights exclusivity and sharing.

• Open training data  (data that can be reshared) provides the best way to enable users to study the system, along with the preferred form of making modifications.
• Public training data  (data that others can inspect as long as it remains available) also enables users to study the work, along with the preferred form.
• Unshareable non-public training data  (data that cannot be shared for explainable reasons) gives the ability to study some of the systems biases and demands a detailed description of the data – what it is, how it was collected, its characteristics, and so on – so that users can understand the biases and categorization underlying the system.

OSI believes these extra requirements for data beyond the preferred form of making modifications to the AI system both advance openness in all the components of the preferred form of modifying the AI system and drive more Open Source AI in private-first areas such as healthcare.

Other changes

• The Checklist is separated into its own document. This is to separate the discussion about how to identify Open Source AI from the establishment of general principles in the Definition. The content of the Checklist has also been fully aligned with the Model Openness Framework (MOF), allowing for an easy overlay.
• Under “Preferred form to make modifications,” the word “Model” changed to “Weights.” The word “Model”  was referring only to parameters, and was inconsistent with how the word “model” is used in the rest of the document.
• There is an explicit reference to the intended recipients of the four freedoms: developers, deployers and end users of AI systems.
• Incorporated credit to the Free Software Definition.
• Added references to conditions of availability of components, referencing the Open Source Definition.

Next steps

• Continue iterating through drafts after meeting diverse stakeholders at the worldwide roadshow, collect feedback and carefully look for new arguments in dissenting opinions. 
• Decide how to best address the reviews of new licenses for datasets, documentation and the agreements governing model parameters.
• Keep improving the FAQ.
• Prepare for post-stable-release: Establish a process to review future versions of the Open Source AI Definition.

Collecting input and endorsements

We will be taking draft v.0.0.9 on the road collecting input and endorsements, thanks to a grant by the Sloan Foundation. The lively conversation about the role of data in building and modifying AI systems will continue at multiple conferences from around the world, the weekly town halls and online throughout the Open Source community. 

The first two stops are in Asia: Hong Kong for AI_dev August 21-23, then Beijing for Open Source Congress August 25-27. Other events are planned to take place in Africa, South America, Europe and North America. These are all steps toward the conclusion of the co-design process that will result in the release of the stable version of the Definition in October at All Things Open. 

Creating an Open Source AI Definition is an arduous task over the past two years, but we know the importance of creating this standard so the freedoms to use, study, share and modify AI systems can be guaranteed. Those are the core tenets of Open Source, and it warrants the dedicated work it has required. You can read about the people who have played key roles in bringing the Definition to life in our Voices of Open Source AI Definition on the blog. 

How to get involved

The OSAID co-design process is open to everyone interested in collaborating. There are many ways to get involved:

• Join the forum: share your comment on the drafts.
• Leave comment on the latest draft: provide precise feedback on the text of the latest draft.
• Follow the weekly recaps: subscribe to our monthly newsletter and blog to be kept up-to-date.
• Join the town hall meetings: we’re increasing the frequency to weekly meetings where you can learn more, ask questions and share your thoughts.
• Join the workshops and scheduled conferences: meet the OSI and other participants at in-person events around the world.

One of the many OSAID workshops organized by the OSI around the world