R While Loops
Advance the state that controls repetition and keep a second safety bound.
How it works
while repeats while its scalar condition is true. Something in the body must make progress towards stopping, or the loop needs an explicit limit. This example processes a fixed pending count with a separate maximum-steps guard. It performs no network request or real queue mutation.
Run this R example
These examples run locally with R, not PHP, Python or JavaScript. The reviewed baseline is R 4.5.2 on Windows x64/UCRT, using only packages shipped with R. This is a tested version, not a newest-release claim. Install your own R from the official R project; an IDE is optional. Save the complete source as while-loops.R in a separate learning folder and run Rscript --vanilla while-loops.R. Keep code and fictional fixtures separate from a real project.
Bhylu has no R browser runner. There is no Try in playground link because the existing Python and JavaScript editors do not execute R. No package installation, account, network dataset, Apache, MySQL or PHP setting is needed to run these base-R sources.
The complete download uses a local scope, restores its temporary options and treats unexpected warnings as errors. Examples that handle an expected warning do so narrowly. Random examples change only their R process’s RNG state. File examples own their temporary output; figure examples leave their named PNG in the current learning folder and refuse to overwrite it. Use a new empty folder to rerun a figure.
Download the complete while-loops.R · Download all source files with hash checks
For the optional collection downloader, save download-examples.mjs in an empty folder and run node download-examples.mjs. Local preview before publishing uses node download-examples.mjs http://127.0.0.1:8000/examples/r/. It refuses an existing bhylu-r-examples folder and does not install or execute R.
Example
local({
previous_options <- options(warn = 2, digits = 8, stringsAsFactors = FALSE)
on.exit(options(previous_options), add = TRUE)
pending <- 3L
handled <- 0L
while (pending > 0L && handled < 10L) {
pending <- pending - 1L
handled <- handled + 1L
}
cat("handled:", handled, "pending:", pending, "\n")
invisible(NULL)
})
Focus on the lesson operations
This excerpt omits the complete script’s option/resource setup. Use the full download to execute it.
pending <- 3L
handled <- 0L
while (pending > 0L && handled < 10L) {
pending <- pending - 1L
handled <- handled + 1L
}
cat("handled:", handled, "pending:", pending, "\n")
Expected result
handled: 3 pending: 0
The pending value decreases every iteration, and handled limits the work even if a later edit damages the progress rule. Both conditions are scalar. In a real external polling loop you would also need a timeout and an explicit failure result.
For API behaviour, consult the official Introduction to R and your installed help pages. These small examples do not establish real-world statistical conclusions or production performance.