The {bakerrr}
S7 class enables efficient background and
parallel job orchestration in R, making it easy to apply a function to
multiple sets of arguments using configurable daemons. This vignette
demonstrates usage with sample inputs and inspects job status and
results.
Define a simple function and generate a list of argument sets, introducing a mix of numeric and non-numeric (error-producing) cases.
fun <- function(x, y) {
Sys.sleep(2)
x + y
}
# Note how each list item is a set of arguments for the function above.
args_list <- list(
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10)),
list(x = "p", y = ceiling(rnorm(1) * 10)), # Intentional type error
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10)),
# Add more sets as needed
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10)),
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10)),
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10)),
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10)),
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10)),
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10)),
list(x = ceiling(rnorm(1) * 10), y = ceiling(rnorm(1) * 10))
)
Instantiate a bakerrr object and process jobs in parallel with configurable daemon count.
Print job summary and view results. Note that jobs triggering errors report the error messages as designed.
print(new_stirr)
new_stirr@results
#> [[1]]
#> [1] -2
#>
#> [[2]]
#> Error in purrr::in_parallel: non-numeric argument to binary operator
#>
#> [[3]]
#> [1] 16
#>
#> [[4]]
#> [1] 30
#>
#> [[5]]
#> [1] 28
#>
#> [[6]]
#> [1] 3
#>
#> [[7]]
#> [1] -12
#>
#> [[8]]
#> [1] 4
#>
#> [[9]]
#> [1] 17
#>
#> [[10]]
#> [1] 8