[w323898]

In my opinion, the big rub for using Go in scientific computing is the lack of a REPL. The nature of Go essentially requires it to compile. On the plus side, compilation is very fast so iterating small code changes is practical. But it's still not nearly as nice as typing commands into the prompt and seeing what happens.

Beyond that, Go is easy and performant. It's great for paralellizing workflows via concurrency and compiling tools for distribution. So if you know what you want to do and need to scale up, it could be a great choice.

[Walkman]

Go works with Jupyter Notebook pretty well. It's a little bit complicated to set up, but it is the same REPL than you use for Python: https://walkman.cloud/s/dtoSfw753YSiMAs

[sbinet]

there are actually a couple of real interpreters for Go:

- neugram.io

- https://github.com/cosmos72/gomacro

here is a mybinder that used to use the former, and now uses the latter:

- https://mybinder.org/v2/gh/go-hep/binder/master