Create a Python iterator from an R function
py_iterator(fn, completed = NULL, prefetch = 0L)Python iterator which calls the R function for each iteration.
R function with no arguments.
Special sentinel return value which indicates that
iteration is complete (defaults to NULL).
Number items to prefetch. Set this to a positive integer to avoid a deadlock in situations where the generator values are consumed by python background threads while the main thread is blocked.
In Python, returning from a function without calling yield indicates the
end of the iteration. In R however, return is used to yield values, so
the end of iteration is indicated by a special return value (NULL by
default, however this can be changed using the completed parameter). For
example:
sequence_generator <-function(start) {
value <- start
function() {
value <<- value + 1
if (value < 100)
value
else
NULL
}
}
Some Python APIs use generators to parallellize operations by calling the
generator on a background thread and then consuming its results on
the foreground thread. The py_iterator() function creates threadsafe
iterators by ensuring that the R function is always called on the main
thread (to be compatible with R's single-threaded runtime) even if the
generator is run on a background thread.
Python generators are functions that implement the Python iterator
protocol. In Python, values are returned using the yield keyword. In R,
values are simply returned from the function.
In Python, the yield keyword enables successive iterations to use the state
of previous iterations. In R, this can be done by returning a function that
mutates its enclosing environment via the <<- operator. For example:
sequence_generator <- function(start) {
value <- start
function() {
value <<- value + 1
value
}
}
Then create an iterator using py_iterator():
g <- py_iterator(sequence_generator(10))