You can call Python directly from Julia https://github.com/JuliaPy/PyCall.jl so much of the Python library ecosystem (say, matplotlib) is available to be used in Julia programs.
That helps the adoption story quite a bit. You can do the number-crunching in Julia where performance counts, and then analyse and present the results using Python.
- Using Python directly is a better experience than calling Python from Julia
- I've never run into unsolveable performance issues with Python
So I guess I'm not in the target audience unless I just happen to be curious about a new language? That's kind of my overall point - even if Julia is a good language on its own and I work in data science, I don't have reasons to pick it over Python.
If you haven't hit a brick wall with python, it is just because you haven't run into the right problem. I was doing something that required lots of conditional operations on small matrices. The FFI into numpy's native library really bogged it down. I didn't have permission to install a compiler on that machine so I wrote it in vba in excel. It was 11x faster.
That helps the adoption story quite a bit. You can do the number-crunching in Julia where performance counts, and then analyse and present the results using Python.