The **futurize** package allows you to easily turn sequential code into parallel code by piping the sequential code to the `futurize()` function. Easy! # TL;DR ```r library(futurize) plan(multisession) library(seriation) o <- seriation::seriate_best(d_supreme) |> futurize() ``` # Introduction The **[seriation]** package provides functions for ordering objects using seriation, ordination techniques for reordering matrices, dissimilarity matrices, and dendrograms. ## Example: Seriate best Example adopted from `help("seriate_best", package = "seriation")`: ```r library(futurize) plan(multisession) library(seriation) data(SupremeCourt) d_supreme <- as.dist(SupremeCourt) o <- seriate_best(d_supreme, criterion = "AR_events") |> futurize() print(o) ``` This will parallelize the computations, given that we have set up parallel workers, e.g. ```r plan(multisession) ``` The built-in `multisession` backend parallelizes on your local computer and works on all operating systems. There are [other parallel backends] to choose from, including alternatives to parallelize locally as well as distributed across remote machines, e.g. ```r plan(future.mirai::mirai_multisession) ``` and ```r plan(future.batchtools::batchtools_slurm) ``` # Supported Functions The following **seriation** functions are supported by `futurize()`: * `seriate_best()` * `seriate_rep()` [seriation]: https://cran.r-project.org/package=seriation [other parallel backends]: https://www.futureverse.org/backends.html