I entirely agree with you. Nobody who uses 100% Julia would have a use-case for this, and if that is who you interact with, it can be hard to see outside the bubble. But most of industry, at least in my area of machine learning, use Python and C++. If they are a well-established company, they would never rewrite their software stack from scratch: they will introduce new languages and libraries gradually, relying on interoperability. So, for Julia even to get its foot in the door there, it requires good interop with Python. If it can do that, it will receive the support from any new adopter - hence it is a great return on investment.