I use Python extensively at work for one main reason: Tensorflow. We're an ML shop, and Python has the most well-developed tools for ML. Ruby doesn't have anything that even compares to numpy in quality, let alone all the things built on top of it like scipy and pandas. It will take a huge amount of effort for Python to catch up.
Personally as an infrastructure engineer, I'd be incredibly happy to drop Python, and almost everyone on my team agrees. When you're building complex data processing pipelines that have to support the hundreds of features that scientists ask for, having static types (especially ones that differentiate between different dimensions of tensors) is a huge win over having to write a unit test for all the possible combinations of things that can happen.
Unfortunately from a solid infrastructure perspective, Ruby is even messier than Python due to the rampant metaprogramming culture. This doesn't matter so much in web dev where the layers of complexity are not that thick, but in other types of development it becomes a real burden very quickly. That might be one reason why Python is preferred over Ruby.
Personally as an infrastructure engineer, I'd be incredibly happy to drop Python, and almost everyone on my team agrees. When you're building complex data processing pipelines that have to support the hundreds of features that scientists ask for, having static types (especially ones that differentiate between different dimensions of tensors) is a huge win over having to write a unit test for all the possible combinations of things that can happen.
Unfortunately from a solid infrastructure perspective, Ruby is even messier than Python due to the rampant metaprogramming culture. This doesn't matter so much in web dev where the layers of complexity are not that thick, but in other types of development it becomes a real burden very quickly. That might be one reason why Python is preferred over Ruby.