Hi Gophers! I was thinking to start a Go project in the area of Data Science that would allow for convenient and easy concurrent data processing but at the end decided against it mainly because of two reasons:
(1) Almost all data science projects start with a data exploratory analysis of some sort. Unfortunately, Go does not have REPL. Go Playground is not a substitute, for it does not preserve state. On every iteration Playground recompiles and relaunches the entire program, reads all the data anew, performs all the calculations. Not good for an interactive "rapid fire". REPL in a static AOT compiled language is hard, yet Swift somehow managed to implement it. (2) Even if somebody implements incremental Go compiler and provides a proper REPL, people will be longing for data analysis "at your fingertips", missing rich pandas-like API, overloaded operators (python style) and dynamical scoping (like in R). Minimalistic design of Go is unlikely to accommodate all of these "convenience" constructs and for a good reason. I think Go has a place in highly performant concurrent data pipelines and transformations but I am less optimistic it would ever play in the field dominated currently by Python and R and possibly by Julia in the future. I am curious of what am I missing in this line of thinking? Thanks, --Leo -- You received this message because you are subscribed to the Google Groups "golang-nuts" group. To unsubscribe from this group and stop receiving emails from it, send an email to golang-nuts+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/golang-nuts/6009a15f-d944-449e-8bd7-e167b5e7d84d%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
