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Cake day: January 3rd, 2024

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  • QT is a cross platform UI development framework, its goal is to look native to the platform it operates on. This video by a linux maintainer from 2014 explains its benefits over GTK, its a fun video and I don’t think the issues have really changed.

    Most GTK advocates will argue QT is developed by Trolltech and isn’t GPL licensed so could go closed source! This argument seems to ignore open source projects use the Open Source releases of QT and if Trolltech did close source then the last open source would be maintained (much like GTK).

    Personally I would avoid Flutter on the grounds its a Google owned library and Google have the attention span of a toddler.

    Not helping that assessment is Google let go of the Fuschia team (which Flutter was being developed for) and seems to have let go a lot of Flutter developers.

    Personally I hate web frontends as local applications. They integrate poorly on the desktop and often the JS engine has weird memory leaks


  • It was a mixture of factors.

    Data was to be dumped into a S3 bucket (minio), this created an event and anouther team had built an orchestrator which would do a couple of things but eventually supply an endpoint a reference to a plain/txt file for analysis.

    For the Java devs they had to [modify the example camel docs.](https://camel.apache.org/manual/rest-dsl.html) and use the built in jackson library to convert the incoming object to a class. This used the default AWS S3 api to create a stream handle which fed into the OpenNLP docs. .

    The Python project first hit a wall in setting up Flask. They followed the instructions and it didn’t work from setup tools. The Java team had just created a new maven project from the Intelij but the same approach didn’t work for the Python team using pycharm. It lost them a couple days, I helped them overcome it.

    Then they hit a wall with Boto3, the team expected to stream data but Boto3 only supports downloading, there was also a complexity issue the AWS SDK in Java waa about 20 lines to setup and a single line to call, it was about 50 lines in Python. On the positive side I got to explain what all the config meant in S3.

    This caused the team anouther few days of delay because the team knew I used a 350MiB Samsung TV guide to test the robustness and had to go learn about Docker volume mounting and they thought they needed a stateful kubernetes service and I had to explain why that was wrong.

    Basically Python threw up a lot of additional complexity and the docs weren’t as helpful as they could have been.



  • You do, but considering the scales they process data I suspect Google would be better building Go tooling (or whatever the dominate internal language is).

    A few years back I was trying to teach some graduates the importance of looking at a programming language ecosystem and selecting it based on that.

    One of my comparison projects was Apache OpenNLP/Camel vs Flask/Spacy.

    Spacy is the go to for NLP, I expected it to be either quicker to develop, easier to use, better results or just less resources.

    I assigned Grads with Java experience Spacy and Python experience OpenNLP.

    The OpenNLP guys were done first, they raved about being able to stream data into the model and how much simplier it made life.

    When compared with the same corpus (Books, Team emails, corporate sharepoint, dev docs, etc…) OpenNLP would complete on 4GiB of RAM in less than a second on 0.5vCPU. Spacy needed 12GiB and was taking ~2 seconds with 2vCPU. They identified the same results…

    Me and a few others ended up spending a day reading the python and trying to optimise it, clearly the juniors had done something daft, they had not.

    It rather undermined my point.


  • My expectation is whatever the solution it needs to dockerise and be really easy to deploy via docker compose or Kubernetes so people can quickly and easily set up their own.

    The front end is effectively static files so I would probably choose Apache or Express (whichever gives me a smaller docker image)…

    For the backend I would choose Java for Spring Boot. An Alpine image with OpenJDK and the app is tiny. Spring has a library for every kind of interface making them trivial to implement but the main reason is hibernate.

    Hibernate (now Spring Data) was the first library for being able to switch out databases without having to change code (its all config). A lot of mastodon instances struggle with the resource requirements of elastic search so letting small instances use something like postgres would seem ideal.

    I have noticed Go/Rust still expect you to write or manage a lot of stuff Spring gives away for free. Python is ok if your backend is really tiny but there is a lot of boilerplate in how Python libraries work so complex projects get hard to manage and I assume interacting with the fediverse will add complexity.




  • If you click the link and follow it through 3 redirects you’ll get to Stamets post.

    Basically risa is listed as having “no rules” but the community admin is/was trying to moderate things to keep it “fun”.

    Stamets and others were upset at the contradiction and through there own posts generated alot of noise to get it resolved the startrek.website admin got sick of the drama.

    To be honest the site admin should require mods to accurately explain their actions “Doesn’t inspire Jahamora” isn’t a great reason and reading stamets examples I think you could build rules fairly easily.

    But I won’t be going to Ten Forward, reading the post was exhausting.


  • Immutable distributions won’t solve the problem.

    You have 3 types of testing unit (descrete part of code), integration (how a software piece works with others) and system testing (e.g. the software running in its environment). Modern software development has build chains to simplify testing all 3 levels.

    Debian’s change freeze effectively puts a known state of software through system testing. The downside its effecitvely ‘free play’ testing of the software so it requires a big pool of users and a lot of time to be effective. This means software in debian can use releases up to 3 years old.

    Something like Fedora relies on the test packs built into the open source software, the issue here is testing in open source world is really variable in quality. So somethinng like Fedora can pull down broken code that passes its tests and compiles.

    The immutable concept is about testing a core set of utilities so you can run the containers of software on top. You haven’t stopped the code in the containers being released with bugs or breaking changes you’ve just given yourself a means to back out of it. It’s a band aid to the actual problem.

    The solution is to look at core parts of the software stack and look to improve the test infrastructure, phoronix manages to run the latest Kernel’s on various types of hardware for benchmarking, why hasn’t the Linux foundation set up a computing hall to compile and run system level testing for staged changes?

    Similarly website’s are largely developed with all 3 levels of testing, using things like Jest/Mocha/etc… for Unit/Integration testing and Robots/Cypress/Selenium/Storybook/etc… for system testing. While GTK and KDE apps all have unit/integration tests where are the system level test frameworks?

    All this is kinda boring while ‘containers!’ is exciting new technology


  • You seem to be intentionally missing the point, but to reiterate…

    You shower before entering a pool to wash the dirt from your body off (your cleaning yourself).

    The more of your body covered the less effective that shower is.

    Ideally everyone would be naked in the shower, but there are probably outfits which increasingly render the shower less and less effective (e.g. speedos are better than shorts, etc .).

    It would not surprise me if a Burkina covered so much that the cleaning shower is rendered pointless


  • The shower before a pool is to ensure people aren’t entering the pool coated in dirt (e.g. sweat, hair, dead skin, etc…).

    The chemicals in a pool are designed to bind to that dirt and kill any bacteria introduced.

    There is a limit to the chemicals you can add to a pool (before it hurts humans) and once the amount has activated you need to drain the pool and refill it.

    Swimming pools hold crazy amounts of water which is also really expensive to heat up, so pools want to do that as little as possible.

    Clothing interfers with cleaning your body, so people entering near fully clothed (e.g. like a Burkina) will likely introduce more dirt into the pool.

    That translates into increased costs for swimming pools or pools which maintain the old schedule and just operate unsafely.

    This is all based on owning a hot tub and learning how to maintain it.

    Hopefully this also explains why it doesn’t matter people enter the sea fully clothed




  • stevecrox@kbin.runtoFediverse@lemmy.worldWhat's going on with kbin.social?
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    5 months ago

    The developer behind KBin seems to have issues delegating/accepting contributors.

    If you look at the pull requests, most have been unreviewed for months and he tends to regularly push his branches once complete and just merge them in.

    That behaviour drove the MBin fork, where 4-5 people were really keen to contribute but were frustrated.

    To some extent that would be ok, its his project and if he doesn’t want to encourage contributions that is his decision but…

    KBin.social has gotten to the size where it really should have multiple admins (or a paid full time person). Which it doesn’t have.

    The developer has also told us he has gone through a divorce, moved into his own place, gotten a full time job and now had surgery.

    Thats a lot for any normal person and he is going through that while trying to wear 2 hats (dev & ops) each of which would consume most of your free time.

    Personally I moved to kbin.run which is run by one of the MBin devs



  • Firstly it was just a bit of fun but from memory…

    Twitter was listed as having 2 data centers and a couple dozen satellite offices.

    I forgot the data center estimate, but most of those satelites were tiny. Google gave me the floor area for a couple and they were for 20-60 people (assuming a desk consumes 6m2 and dividing the office area by that).

    Assuming an IT department of 20 for such an office is rediculous but I was trying to overestimate.


  • The Silicon Valley companies massively over hired.

    Using twitter as an example, they used to publicly disclose every site and their entire tech stack.

    I have to write proposals and estimates and when Elon decided to axe half the company of 8000 I was curious…

    I assigned the biggest functional team I could (e.g. just create units of 10 and plan for 2 teams to compete on everything). I assumed a full 20 person IT department at every site, etc… Then I added 20% to my total and then 20% again for management.

    I came up with an organisation of ~1200, Twitter was at 8000.

    I had excluded content moderators and ad sellers because I had no experience in estimating that but it gives a idea of the problem.

    I think the idea was to deny competition people but in reality that kind of staff bloat will hurt the big companies


  • It does but for the 90’s/00’s a computer typically meant Windows.

    The ops staff would all be ‘Microsoft Certified Engineers’, the project managers had heard of Microsoft FuD about open source and every graduate would have been taught programming via Visual Studio.

    Then you have regulatory hurdles, for example in 2010 I was working on an ‘embedded’ platform on a first generation Intel Atom platform. Due to power constraints I suggested we use Linux. It worked brilliantly.

    Government regulations required anti virus from an approved list and an OS that had been accredited by a specific body.

    The only accredited OS’s were Windows and the approved Anti Viruses only supported Windows. Which is how I got to spend 3 months learning how to cut XP embedded down to nothing.



  • Technical Leads are not rational beings and lots of software is developed from an emotional stand point.

    Engineering is trade offs, every technical decision you make has a pro/con.

    What you should do is write out the core requirements/constraints.Then you weigh the choices to select the option that best meets it.

    What actually happens is someone really likes X framework, Y programming language or Z methodology and so decides the solution and then looks for reasons to justify it.

    Currently the obvious tell is if they pitch Rust. I am not saying Rust is bad, but you’ll notice they will extoll the memory safety or performance and forget about the actual requirements of the project.