The iterors package: Fast, compact iteration and tools

Features

• Main method nextOr(iter, or); allows simpler and faster code.
• iteror objects are cross-compatible with existing code using iterators (such as the foreach package.)
• Optimized performance, with often several times less overhead per item.
• Compatible with Python iterators, via the reticulate package.
• Comes with batteries included: a complete collection of iterator functions, ported, curated and harmonized from packages iterators, itertools, and itertools2,

How is it different from iterators?

iterors uses the method nextOr(it, or) to retrieve the next element. The trick is that the second argument or is lazily evaluated, so it can specify a return value or an action to take at the end of iteration. In particular, or can be a control flow operator like break or next or return.

For example, this is how you can compute a sum over an iteror it:

total <- 0
repeat total <- total + nextOr(it, break)

To contrast with the previous iterators package: In that package nextElem signals end of iteration by throwing an exception, which means all iterator code had to be written inside a tryCatch. Computing a sum over an iterator looked like this:

total <- 0
tryCatch(
  repeat total <- total + nextElem(it),
  error=function(x) {
    if (conditionMessage(x) != "StopIteration") stop(x)
  }
)

Besides requiring less boilerplate, iterator code written using nextOr also performs faster, particularly when using higher-order iterator functions. This is because tryCatch is a relatively expensive operation in R, especially when used once per item. It is also not possible(*) to use break or next to exit an outer loop from inside a tryCatch handler function. while nextOr is designed with that use in mind.

The benchmarking vignette illustrates that computations using iterors can execute several times faster than using iterators.

The iterors package grew out of, and is a complement to, the generators implemented in the async package. async::gen lets you construct iterators with complex logic, using familiar imperative code with ordinary flow control constructs like if for, switch and so on. Meanwhile, functions in this package iterors let you manipulate the output of such a generator in functional style. These two packages form two complementary ways to work with sequential processes.

More reading

For a quick introduction, see vignette("iterors")

For an index of iteror functions organized by task, see vignette("categories", "iterors")

If you are familiar with packages iterators/itertools/itertools2, some functions have been moved. See vignette("cross-reference", "iterors")

To learn how to build custom iterors, see vignette("writing", "iterors")

Installation

For prerelease, run the following after installing devtools:

devtools::install_github('crowding/iterors')

When the package is released, you will be able to install the stable version from CRAN:

install.packages('iterors', dependencies=TRUE)

License

Copyright (c) 2023 Peter Meilstrup. This package as a whole is released under the GNU General Public License (GPL) version 3.0, or (at your option) any later version.

Portions of this package are derived from the iterators package, copyright (c) 2008-2010 Revolution Analytics.

Portions of this package are derived from the itertoolspackage, copyright (c) 2015 Steve Weston.

Portions of this package are derived from the itertools2 package, copyright (c) 2015 John A. Ramey.

Where functions in this package are derived from previous works, this is noted in the Rd documentation, and the original license notice is retained at the top of the relevant source files.