One of the arguments for python is the exceptional support of automation differentiation and GPU computing through deep learning libraries. Most python based PPLs focus on static model with differentiable log joints, allowing the application of HMC or variational inference. Unfortunately, the support of efficient automatic differentiation libraries in Julia is still in its infancy. But I hope with some more work by the community and the Turing team, this will change sooner than later.
I thought with libraries like Zygote there is some really nice stuff already in Julia. I'd say it's still early days for good autodiff libraries in general and I think we still haven't really explored what they can do.
