This is totally fair. Even the Julia creators regularly mention "stay with existing tools for now, if you are happy." Julia is an increasingly attractive option

This is totally fair. Even the Julia creators regularly mention "stay with existing tools for now, if you are happy." Julia is an increasingly attractive option for greenfield, high-performance development, but for folks who aren't doing a lot of that, a more stable language and mature ecosystem is obviously important. Julia and many libraries can still require some elbow-grease, and the maturity and coverage varies between fields. However, this is rapidly changing as folks do new research in Julia and build up everything else they need along the way. The current situation is very similar to SciPy in the mid-2000s, though with perhaps a somewhat different mix of backgrounds. Here are a few examples: https://github.com/JuliaOpt https://github.com/JuliaOpt https://github.com/jeff-regier/Celeste.jl https://github.com/jeff-regier/Celeste.jl https://github.com/dlfivefifty https://github.com/dlfivefifty https://github.com/JuliaInv https://github.com/JuliaInv http://docs.juliadiffeq.org/latest/ http://docs.juliadiffeq.org/latest/ https://github.com/denizyuret/Knet.jl https://github.com/denizyuret/Knet.jl http://nemocas.org/ http://nemocas.org/ https://juliaplots.github.io/ https://juliaplots.github.io/ So, hopefully you'll have reason to take another look in a few years. The most important thing, to me, is that all of these communities want more open, reproducible, and accessible science. There is plenty of room for growth, because users of closed-source software still probably outnumber py/r/jl by 5:1 or more.