If the cure for R is that I need to jump fully into the Nix ecosystem, I am not sure that is a solution.

Disappointing about Julia. Only played with it a small bit, but I had assumed it had identified dependency management as a huge problem that needed to be addressed.

Julia’s package management is miles ahead of R, and bests Python’s on a large number of factors. However the last time I used it, it still required you to issue commands into the repl to setup your packages. However, that might have been resolved by now? The language and tooling clips along at a pretty good pace.

You can now set up a Julia environment non-interactively from the command line by running:

    julia --project=. -e 'import Pkg; Pkg.instantiate()'

Not as clean as running

    python -m pip install -r requirements.txt

but it's something.

I find the flexibility of being able to setup and switch environments from within the REPL very enabling, and the Python approach of using the command-line shell feels kinda messy and cobbled together to me. (I felt this way about the Python approach before I even came across Julia, by the way.)

That said, there is a command-line utility jlpkg [1] that makes package management available from the shell. It's not very widely used, but maybe it suits your needs.

Although, the way you phrased

> it still required you to issue commands into the repl to setup your packages

makes me think maybe you didn't know about the Pkg mode in the REPL, and assumed you had to do everything with commands like `Pkg.add("DataFrames"); Pkg.update()` and such? If so, there's a package management mode to the REPL you can access with the ] key, which is kind of its own subshell within the REPL where you can do `add DataFrames`, `update`, and such instead.

[1] https://github.com/fredrikekre/jlpkg

I’m well aware of pkg mode in the repl, wasn’t aware of jlpkg though, that seems good.