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
