> Julia is a growing alternative to Fortran/C/etc for long-running computations, it remains awkward and unpleasant for interactive analysis Did you mean to wri

> Julia is a growing alternative to Fortran/C/etc for long-running computations, it remains awkward and unpleasant for interactive analysis Did you mean to write short-running scripts? If anything, the Julia dev workflow is biased towards interactive analysis in a REPL a la R or IPython/Jupyter. I don't mean to imply that there's no startup overhead, but how often are you restarting the REPL when doing EDA? Unless it's more than once every few minutes (which is a very odd workflow), then startup overhead is effectively amortized. > A real strength of R (in comparison not just to Julia but also to python) is that such a repository exists CRAN is certainly a cut above many other package repos here, but I'm not sure "trust their tools" can apply to all packages on there. Anecdotally, I've had a lot of issues with compiled dependencies and missing/out of date external assets on less well-trodden packages. There's a reason MRAN, Conda and JuliaBinaryWrappers exist after all. For whatever reason, Julia package maintainers also seem more receptive to making their work compatible with other libraries as well. This goes beyond just multiple dispatch as well--imagine if tidyverse/non-tidyverse wasn't such a hard split.