README

{bakerrr} provides a clean, modern interface for running background parallel jobs using S7 classes, mirai daemon(s), and callr process management. Perfect for computationally intensive workflows that need robust error handling and progress monitoring.

Features

Installation

install.packages("bakerrr")

Quick Start

# Define your function
compute_sum <- function(x, y) {
  Sys.sleep(1)  # Simulate work
  x + y
}

# Create argument lists for each job
args_list <- list(
  list(x = 1, y = 2),
  list(x = 3, y = 4),
  list(x = 5, y = 6),
  list(x = 7, y = 8)
)

# Create and run bakerrr job
job <- bakerrr::bakerrr(
  fun = compute_sum,
  args_list = args_list,
  n_daemons = 2
) |> 
  bakerrr::run_jobs(wait_for_results = TRUE)

# Check results
job@results
#> [[1]]
#> [1] 3
#> 
#> [[2]]
#> [1] 7
#> 
#> [[3]]
#> [1] 11
#> 
#> [[4]]
#> [1] 15

print(job)
#>    [01] function (x, y) { Sys.sleep(1) x + y }
#>    [02] function (x, y) { Sys.sleep(1) x + y }
#>    [03] function (x, y) { Sys.sleep(1) x + y }
#>    [04] function (x, y) { Sys.sleep(1) x + y }

Advanced Usage

Error Handling

# Function that may fail
risky_function <- function(x) {
  if (x == "error") stop("Intentional error")
  x * 2
}

args_list <- list(
  list(x = 5),
  list(x = "error"),  # This will fail gracefully
  list(x = 10)
)

job <- bakerrr::bakerrr(risky_function, args_list) |>
  bakerrr::run_jobs(wait_for_results = FALSE)
job@results
#> [1] "running"
#> [[1]] [1] 10
#> [[2]] [1] "Error in purrr::in_parallel: Intentional error"
#> [[3]] [1] 20

Background Job Arguments

# Custom logging and process options
compute_sum <- function(x, y) {
  Sys.sleep(1)  # Simulate work
  x + y
}

# Create argument lists for each job
args_list <- list(
  list(x = 1, y = 2),
  list(x = 3, y = 4),
  list(x = 5, y = 6),
  list(x = 7, y = 8)
)
job <- bakerrr::bakerrr(
  fun = compute_sum,
  args_list = args_list,
  bg_args = list(
    stdout = "job_output.log",
    stderr = "job_errors.log",
    supervise = TRUE
  )
) |>
  bakerrr::run_jobs(wait_for_results = FALSE)

Asynchronous Execution

long_running_function <- function() {
  Sys.sleep(5)
}
# Start job without waiting
job <- bakerrr::bakerrr(long_running_function, args_list) |> 
  bakerrr::run_jobs(wait_for_results = FALSE)

# Check status later
summary(job)
#>           Length           Class1           Class2             Mode 
#>                1 bakerrr::bakerrr        S7_object           object
#> ⏳ BackgroundParallelJob [running] - 4 daemon(s), 10 jobs

# Get results when ready
if (!job@bg_job_status$is_alive()) {
  results <- job@results
}

Multiple Functions in Parallel and in Background

You can run multiple different functions, each with their own arguments, in parallel background jobs using {bakerrr}. Just supply a list of functions and a matching list of argument sets:

# List of functions with different logic
fun_list <- list(
  function(x, y) x + y,
  function(x, y) x * y,
  function(x, y) x - y,
  function(x, y) x / y,
  function(x, y) x^y,
  function(x, y) x %% y,
  function(x, y) paste0(x, "-", y),
  function(x, y) mean(c(x, y)),
  function(x, y) max(x, y),
  function(x, y) min(x, y)
)

# Corresponding list of argument sets
set.seed(1)
args_list <- list(
  list(x = 3, y = 6),
  list(x = "p", y = 2),              # type error
  list(x = 5, y = 8),
  list(x = 10, y = 2),
  list(x = 2, y = 5),
  list(x = 13, y = 4),
  list(x = "A", y = 7),              # type error
  list(x = 6, y = 9),
  list(x = 3, y = 4),
  list(x = 1, y = 2)
)

# Run jobs in parallel
job <- bakerrr::bakerrr(
  fun = fun_list,
  args_list = args_list,
  n_daemons = 4
) |> bakerrr::run_jobs(wait_for_results = TRUE)

# Inspect results and status
job@results
#> [[1]]
#> [1] 9
#> 
#> [[2]]
#> Error in purrr::in_parallel: non-numeric argument to binary operator
#> 
#> [[3]]
#> [1] -3
#> 
#> [[4]]
#> [1] 5
#> 
#> [[5]]
#> [1] 32
#> 
#> [[6]]
#> [1] 1
#> 
#> [[7]]
#> [1] "A-7"
#> 
#> [[8]]
#> [1] 7.5
#> 
#> [[9]]
#> [1] 4
#> 
#> [[10]]
#> [1] 1
print(job)
#>    [01] function (x, y) x + y
#>    [02] function (x, y) x * y
#>    [03] function (x, y) x - y
#>    [04] function (x, y) x/y
#>    [05] function (x, y) x^y
#>    [06] function (x, y) x%%y
#>    [07] function (x, y) paste0(x, "-", y)
#>    [08] function (x, y) mean(c(x, y))
#>    [09] function (x, y) max(x, y)
#>    [10] function (x, y) min(x, y)
summary(job)
#>           Length           Class1           Class2             Mode 
#>                1 bakerrr::bakerrr        S7_object           object
bakerrr::status(job)
#> [1] "done"

Performance Tips

Dependencies

Further Help & Documentation

Troubleshooting

Citation

citation("bakerrr")
#> To cite package 'bakerrr' in publications use:
#> 
#>   Shaw A (2025). _bakerrr: Background-Parallel Jobs_. R package version
#>   0.2.0, <https://github.com/anirbanshaw24/bakerrr>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {bakerrr: Background-Parallel Jobs},
#>     author = {Anirban Shaw},
#>     year = {2025},
#>     note = {R package version 0.2.0},
#>     url = {https://github.com/anirbanshaw24/bakerrr},
#>   }

bakerrr ⏲️

Elegant S7-based parallel job orchestration for R