So, perhaps it makes sense in your industry to go all-in on Julia. Personally, I'm still burned by the time they announced 1.0 mere days after announcing 0.7,

So, perhaps it makes sense in your industry to go all-in on Julia. Personally, I'm still burned by the time they announced 1.0 mere days after announcing 0.7, and thus meaning that literally nothing in the ecosystem worked at 1.0. If that transition had been managed better, then I would be much more comfortable evangelising Julia now, but it didn't and the decisions behind this make me incredibly uncomfortable in adopting it anywhere where I'm on the hook for failures. Additionally, Python has libraries for everything, and is known (badly at least), by almost everyone in Data Science/programming. When your modelling is a part of a larger project, this matters a lot (and is why I no longer write my production code in R). That being said, I really like Julia, and look forward to checking it out again, hopefully with less breakages in the future.