Great stuff, and I like the use of a sentinel as a terminator symbol. One aspect of this I would like to explore is that of a lazy sequence as a more fundamental language primitive. Generators in for loops are great, but generators returned by lapply() and friends would enable lazy functional transformations and efficient combination of processing steps. At the lowest level I can see this being facilitated by an ALTREP protocol with a similar API to what you propose.
One big pain point of course is parallel processing. A two level design splitting the iterator index and data generation (like C++ does) could be a better fit if parallelization is desired. Curious to hear your thoughts. Best, Taras > On Aug 11, 2025, at 9:23 PM, Tomasz Kalinowski <kalinows...@gmail.com> wrote: > > Hi all, > > A while back, Hadley and I explored what an iteration protocol for R > might look like. We worked through motivations, design choices, and edge > cases, which we documented here: > https://github.com/t-kalinowski/r-iterator-ideas > > At the end of this process, I put together a patch to R (with tests) and > would like to invite feedback from R Core and the broader community: > https://github.com/r-devel/r-svn/pull/130/files?diff=unified&w=1 > > In summary, the overall design is a minimal patch. It introduces no > breaking changes and essentially no new overhead. There are two parts. > > 1. Add a new `as.iterable()` S3 generic, with a default identity > method. This provides a user-extensible mechanism for selectively > changing the iteration behavior for some object types passed to > `for`. `as.iterable()` methods are expected to return anything that > `for` can handle directly, namely, vectors or pairlists, or (new) a > closure. > > 2. `for` gains the ability to accept a closure for the iterable > argument. A closure is called repeatedly for each loop iteration > until the closure returns an `exhausted` sentinel value, which it > received as an input argument. > > Here is a small example of using the iteration protocol to implement a > sequence of random samples: > > ``` r > SampleSequence <- function(n) { > i <- 0 > function(done = NULL) { > if (i >= n) { > return(done) > } > i <<- i + 1 > runif(1) > } > } > > for(sample in SampleSequence(2)) { > print(sample) > } > > # [1] 0.7677586 > # [1] 0.355592 > ``` > > Best, > Tomasz > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
