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>> we use .NET for backend and React for frontend. You don't need anything else

...

>> sure maybe you have some data science people who need python,

This is how it happens though; it's not "let's form a company with 10 developers; don't worry what tools they use!". It's starting with a single problem using common tools, then adding specialized problems where you could still use the same tools but they are not optimized, then adding an acquisition product that uses different tech, then growing to 100 or 1000 developers and may all use React or C# (doubtful) but don't use it the same way...

>> If you're going to make a change then migrate everything

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





> This is how it happens though

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.




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