I am primarily a Python programmer, and I think it's a good idea to be able to program in Python, because it's core competency is that it is pretty good at lots of things (web scripting, data science, ML, etc. etc.). However, sometimes you need the best language for [x], and that language is often something written for [x].
Part of the reason why, is that the "simplicity and coherence" that people think they will get from a homogenous environment, rarely pans out. Ten years ago people were trying to use JS for everything, and it seemed like it would drive backend languages like Python away, because using JS for both front-end and back-end would be "simpler". It didn't turn out that way.
The fact is that the problem spaces differ more than the languages. Even if you know, let's say, Python web development, it doesn't mean you can do Python data science, or Python ML, or etc. Whereas, if you know Python web development, and you have to figure out Ruby webdev code, there will be a little bit of a learning curve but it won't require as much of a mindset change. If you need to convert Python data science code to R, if you're already familiar with the concepts involved, the language learning is not nearly as big an issue as if you only know Python, but not the domain space involved.
I'm sure there are still places trying to pursue the "one language" homogenous environment. The payoff is not what they were hoping for.