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(BiocParallel) slow_fcn <- function(x) { Sys.sleep(0.1) # emulate work x^2 } xs <- 1:1000 ys <- bplapply(xs, slow_fcn) |> futurize() ``` # Introduction This vignette demonstrates how to use this approach to parallelize functions such as `bplapply()`, `bpmapply()`, and `bpvec()` in the **[BiocParallel]** package. For example, consider the `bplapply()` function. It works like base-R `lapply()`, but uses the **BiocParallel** framework to process the tasks concurrently. It is commonly used something like: ```r library(BiocParallel) xs <- 1:1000 ys <- bplapply(xs, slow_fcn) ``` The parallel backend is controlled by the `BiocParallel::register()`, similar to how we use `future::plan()` in futureverse. We can use the **futurize** package to tell **BiocParallel** to hand over the orchestration of parallel tasks to futureverse. All we need to do is to pass the expression to `futurize()` as in: ```r library(futurize) library(BiocParallel) xs <- 1:1000 ys <- bplapply(xs, slow_fcn) |> futurize() ``` This will distribute the calculations across the available parallel workers, given that we have set parallel workers, e.g. ```r plan(multisession) ``` The built-in `multisession` backend parallelizes on your local computer and it 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 `futurize()` function supports parallelization of all **BiocParallel** functions that take argument `BPPARAM`. Specifically, * `bplapply()` and `.bplapply_impl()` * `bpmapply()` and `.bpmapply_impl()` * `bpvec()` * `bpaggregate()` The following functions are currently not supported: * `bpiterate()` - technically supported, but because this function does not support using `DoparParam()` with it, it effectively does not work with `futurize()` * `bpvectorize()` * `register()` [BiocParallel]: https://bioconductor.org/packages/BiocParallel/ [other parallel backends]: https://www.futureverse.org/backends.html