I’d actually argue Python stops people learning how to solve problems.

I love teaching juniors and have done so for 10 years but I’ve noticed in the last 4-5 years since Python became the popular choice at universities Graduates aren’t learning anything about Static Types, Memory Management, Object Oriented Programming, Data Encapsulation, Composition, Service Oriented Architecture, etc…

I used to expect most graduates to have a mixed grounding in those concepts and would find excuses for them to work on a small UI projects. I would do this as it gets them used to solving a small problem and UI’s give instant feedback. As Python became dominate university teaching language the graduates aren’t spending their time learning Typescript, Angular, HTML, etc… but instead getting overwhelmed by the concept of types.

Those concepts I want them to learn were created to help make solving problems easier and each has their strengths and weaknesses but most graduates are coming through only knowing how to lay out a small amount of procedural logic using Python and really struggling to move beyond that.

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.

If you have the freedom try Typescript.

The tsx files are almost identical to jsx except for the need to define the field types your ingesting.

While thats a little extra work, it allows Visual Studio Code to perform deeper analysis and provide much more helpful contextual hints.

I grew to love JSX and tried TSX out of interest and you couldn’t convince to go back to pure JS

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.

Nah Linux Mint is a Kia Ceed.

Ubuntu is a Ford Focus, they successfully stole the volvo estate market (Debian). The car was fun, good value and very practical. It was everywhere. Then Ford started increasing the size, weight, price, etc… killing the point of the Focus.

So along comes Kia trying to make a competitor in the Ceed.

In theory the Ceed is a great car, its super cheap, lots of cabin space, nippy, the inside has every modern convenance, but…

• It plays engine noises via speakers that aren’t aligned with what you are doing
• The boot space is rubbish, so 5 people can happily travel in the car you barely fit a suitcase in it
• There is an steering sensitivity button that stays on at 70 MPH with no indication on the display
• A Vauxhall Nova just out accelerated you

Your left wondering why anyone is bothering with hot hatchbacks these days as you climb into your volvo

Debian would be a Volvo Estate, its the boring practical family choice, the owner is soneone boring like an architect or a financial advisor.

Arch is a Vauxhall Nova, second hand battered owned almost exclusively by teenage lads who spend a lot of time/money modifying it (e.g. lowering so it can’t go over speed bumps, adding a massive exhaust to sound good but destroys engine power).

Fedora is something slightly larger/more expensive like a Ford Focus/VW Golf/Vauxhall Astra owned by slightly older lads. The owners spend their time adding lighting kits and the largest sound systems money can buy.

Slackware is clearly a Subaru Impreza, at one point the best World Rally Car but hasn’t been a contender for a while. Almost all are owned by rally fans who spend fantastic amounts of time tinkering with the car to get set it up an ultimate rally car. None of the owners race cars.

OpenSuse is a Nissan Cube, its insanely practical. It should be the modern boring family choice, but it manages to ve too quirky for your architect while not practical enough for van drivers.

I don’t know the other distros well enough.

I run Debian btw

You are far worse than the people you are claiming to act against.

Lots of people can feel something is a problem and struggle to articulate it. So you have to take people on a case by case basis.

OP talks about how they feel diverse characters are shoe horned in or badly written. Ask them to provide an example.

When they can’t, then call them out. They are a bigot and deserve scorn.

If they can provide an example, help them understand the issue and use appropriate language.

Calling someone out who genuinely feels there is a problem doesn’t stop them feeling there is a problem. These people will go looking for some who acknowledges their feelings.

Which is how you make a bigot

I think they are saying most attempts at diversity come from middle aged white guys and just end up being poorly done and so detract from the game/story.

Similar to how 00’s electronic companies just painted it pink to appeal to women or why South Park added Token.

So arguing for more diversity within the companies themselves

I wouldn’t get massively excited.

Python is a scripting language, its shines when you want to write a stand alone file which takes an input and performs a task. Scripting languages are great to learn as a first language and so python is wonderful for non developers.

The issue you hit is the build management solutions for Python are kind of broken and these help support and encourage good development practice so a lot of Python projects end up a collection of scripts rather than a mature project. You can have good projects but…

In raw benchmarks Java has 90% of the performance of C/C++, but in reality Java is more performant because developers get bogged down in memory management on C/C++ and they get more time to optomise in Java as a result. I’m not sure where Rust will come out to be honest.

Python benchmarks at 50% the performance of Java, in reality I’ve found code ends up slightly worse because Python is procedural, library support and streaming is poorly supported.

Take library support, Spring really rose to prominese because of ‘hibernate’ which was a way to abstract talking to different databases through objects, you could switch from PostgreSQL to Oracle through config. Spring data has dumbed this down so I define a plain old Java object and Spring will generate everything I need.

Python expects you to hand craft SQL statements and every database extends SQL slightly differently, so i need to write SQL for every operation and manage/own it. So the win in being able to quickly read/write to a database (since you don’t have to learn anything about Spring) is quickly ruined because of the all the boilerplate and error handling you now have to write.

Every programming languages has communities built around them.

Its becoming clear Rust solves a lot of C/C++ type problems and the embedded communities are definitely shifting over.

Apache is the primary community for Java, a quick look at their project list shows it’s entirely web servers, data engineering and clustered projects for distributed computing.

Personally if you asked me to solve this problem I would use Spring Boot with various Spring libraries for talking to the caddy, user control, etc… Looking at the project, its exactly what they have done

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

Uhh how?

The rate of new features/changes is far higher, uptime went through a bumpy transition but is back to normal. From an engineering perspective it supports my point.

Twitters issues are Elon scaring away advertisers/annoying governments/content creators through his hard line on free speech allowing an explosion in hate speech.

deleted by creator

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.

The team/organisations knowledge is a huge factor but its easy to fall into a trap where no matter what the problem is the solution is X language.

If I have an organisation that knows C# and we need to build a Web Application. I would suggest we need to learn Node.js and Typescript and not invest in a solution that turns C# into web pages.

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.