On: Pipelining might be my favorite programming language feature

[SimonDorfman]

The tidyverse folks in R have been using that for a while: https://magrittr.tidyverse.org/reference/pipe.html

[thom → SimonDorfman]

I've always found magrittr mildly hilarious. R has vestigial Lisp DNA, but somehow the R implementation of pipes was incredibly long, complex and produced stack traces, so it moved to a native C implementation, which nevertheless has to manipulate the SEXPs that secretly underlie the language. Compared to something like Clojure's threading macros it's wild how much work is needed.

[madcaptenor → SimonDorfman]

And base R has had a pipe for a couple years now, although there are some differences between base R's |> and tidyverse's %>%: https://www.tidyverse.org/blog/2023/04/base-vs-magrittr-pipe...

[steine65 → SimonDorfman]

R, specifically tidyverse, has a special place in my heart. Tidy principles makes data analysis easy to read and easy to use new functions, since there are standards that must be met to call a function "tidy."

Recently I started using Nushell, which feels very similar.

[flobosg → SimonDorfman]

Base R as well: |> was implemented as a pipe operator in 4.1.0.

[tylermw → flobosg]

Importantly, the base R pipe implements the operation at the language parsing level, so it has basically zero overhead.

[zelphirkalt → tylermw]

I would assume, that most languages do that, or alternatively have a compiler, that is smart enough to ensure there is no actual overhead in the compiled code.

[mvieira38 → SimonDorfman]

R + tidyverse is the gold standard for working with data quickly in a readable and maintainable way, IMO. It's just absolutely seamless. Shoutout to tidyverts (https://tidyverts.org/) for working with time series, too