No it isn't. This is not how you end up with 7 different frontend JS frameworks in 7 different web applications. Using python/matlab/r for data science is completely fair. These languages are standard in this field, they have the most tools and built-in functionality for this purpose.

I mean if you want to do ML and data science stuff in C# or whatever go right ahead. If you can make that work that's great. But I also think, as someone who aggressively promotes sticking to one language, that it's fair to use Python for data science.

What I don't condone, as I said, is using multiple tools for the same task. So for example, having one team/dev using Python while another uses Matlab and yet another uses R etc.

> Have you ever worked for a software company before? THis is not how it goes.

Yeah, I know. That's the problem. People just introduce new tech like it's nothing. That's why I'm saying it needs to be a big decision. So if it's really worth it okay let's go for it. But for the vast majority of cases it just isn't.

That said I think you're exaggerating those complaints, the docs for C# are quite good imo and I've been working with ASP.NET web apps for half a decade so far and I'm not seeing any problems like you're describing.

Maybe you're miffed about the Framework to Core/.NET switch? That was a bit of a doozy but the ecosystem is so much better for it I'd say it was worth it.

I'm talking about general software development and web dev in particular. There's a trend where you'll see one org has or web app using .net ad react, another using next.js, another using Java and Vue, one djnago and htmx, and so on.

And there is literally no reason for any of these choices, they're all fairly basic web applications that could have all been made in literally any half decent web stack. So whether the devs who made these choices knew or not, they made them based on preference not any kind of reason or need, they're all nails and any hammer would have done the job just fine.

I don't think this is an valid comparison. There's a problem called technology sprawl, which is characterized by needlessly increasing maintenance needs and cognitive load and lower development speeds caused by the need to juggle multiple programming languages or frameworks. There is a fixed cost in maintaining each tech stack and even development environment, and you multiply that cost each time you think it's a good idea to introduce yet another programming language or framework.

Good analogy. If, say, your organisation maintains a fleet of cars - it needs to keep them on the road, get them serviced, replace parts, refresh individual cars regularly etc.

How many different makes and models do you support? A small org might decide that it only makes sense to support one. A larger org might have the resources for 3 or 4, so that there is 1 or 2 "general purpose" models, and then other ones suited to specialised tasks.