py_iterator: Create a Python iterator from an R function

View source: R/generator.R

py_iteratorR Documentation

Create a Python iterator from an R function

Description

Create a Python iterator from an R function

Usage

py_iterator(fn, completed = NULL)

Arguments

fn

R function with no arguments.

completed

Special sentinel return value which indicates that iteration is complete (defaults to NULL)

Details

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))

Value

Python iterator which calls the R function for each iteration.

Ending Iteration

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
  }
}

Threading

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.


reticulate documentation built on Jan. 8, 2023, 1:09 a.m.