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.

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.

Lays is called Walkers in the UK and the Sensations brand is still sold.

Here there are in my local supermarket. Personally I prefer the Sensation Thai Sweet Chilli nuts, they are the perfect thing while you wait for food to cook on the BBQ.

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

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.

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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.

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DevSecOps is all about process, I simplified my answer.

At a high level in software there will always be a review phase, where code needs to be built and pass tests (as a minimum). With Git being used by every organisation I have been involved in you will find the organisation/team will claim to follow a variation of ‘Feature branch Workflow’ with review happening at a specific point (Pull Request).

For the last ~10 years every organisation/team I’ve worked in/with has claimed to use a CI to verify the source code as part of that review phase.

In most dysfunctional teams that review phase will be broken, the fastest win is to bring in the CI. Static analysis tools are also impartial in how they review and useful in teaching people how to review.

I don’t say your project must build with no warnings, I say you project must build and I’ll have the CI point out where you have added warnings as part of review. When people complain I’ll point to their teams Ways of Working or an organisations Software Development Plan (or in one case a System Engineering Management Plan).

The sort of team that then chooses to disable this will do so because the leadership are undermining it (normally a team lead turns it off or tells them to just ignore it). There seem to be a few common reasons as to why team leads will do this but it isn’t something you can rationally debate with. The only solution I’ve found is to sideline the problem, change team culture and identify a leader within the team and hand it over to them.

Your talking about teams which are failing due to the environment, those normally understand what is wrong and the best approach is to be a good scrum master (e.g. run retro sessions, identify issues and work to resolve the environment problems with them).

You can’t fix a people problem with process.

For example I’ve worked in DevSecOps for 10+ years, whenever consulting my first step is to implement a CI that picks up Pull Requests, builds them and runs a code analysis tools (e.g. pep8, spotbugs, eslint, etc…) and have the CI comment the Pull Request. The idea is to get an understanding of the projects technical debt and stop things getting worse and ensure the solution ‘just works’.

Teams with huge amounts of technical debt will find a way to disable it when your not looking. They will develop all kinds of reasons and in reality the technical debt was created because of cultural issues in the team.

So I’ve learnt its important if you spot a team doing that, the solution isn’t locking it down the solution so they can’t disable it or more process. But forcing out the technical leader and sitting with the team and working out why each one is fighting the tool and not seeing them as an asset and teaching them to be better.

There will always be someone who is beating you in a metric (buying houses, having kids, promotions, pay, relationships, etc…) fixating on it will drive you mad.

Instead you should compare your current status against where you were and appreciate how you are moving forward

As for age

During university my best mate was 27 who dropped out of his final year, grabbed a random job, then went to college to get a BTEC so they could start the degree.

It was similar in my graduate intake, we had a 26 year old who had been a brickie for 5 years before getting a comp sci degree.

The first person I line managed was a junior 15 years older than me, who had a completely different career stream. They had the house, kids, had managed big teams, etc… honestly I learnt tons from them.

Society is complex, visting a country is different from living there an extended period of time and even then even small geographical distances can result in huge changes in culture.

For example if you started in London and travelled the M4 to Bristol and carried on through Newport and then Cardiff. You would find dramatic differences in housing costs, religiousness, sports played (e.g. football to rugby), views on public transport, job market, jobs people work, education level, favourite drinks, marriage, etc…

You could spend 3 months basing yourself in any one of those locations and derive completely different views on what is wrong with the UK.

Which is why the OP brushed this off as nonsense. It also isn’t uncommon for Americans to go somewhere and suggest it would be miles better if it was exactly like the USA, which is why you get the ad hominem.

It would be like a British Tourist suggesting they don’t drink enough larger or accusing themof being savages for putting salt in tea