In this example we are going to execute the following script and create a log of it’s execution:
example.R:
#' Setup
library(dplyr)
library(ggplot2)
#' Prepare data
x <- mtcars |>
as_tibble(rownames = "car")
print(x)
#' Create and save plot
ggplot(data = x) +
geom_point(mapping = aes(x = mpg, y = hp, size = wt, colour = as.factor(am)))
ggsave("plot1.png")
We are going to use the run()
function to execute the
script, and since this vignette is created on Linux we can use the
whirl.track_files
option to automatically track the used
files:
The verbosity_level
is set to minimal
for
nicer printing in this vignette. Now we are ready to execute the
script:
result <- run("example.R")
#> ══ Executing scripts and generating logs ═══════════════════════════════════════
#> → Executing scripts in parallel using 1 cores
#> The following steps will be executed
#> • Step 1: Unnamed chunk
#>
#>
#> ── Step 1: Unnamed chunk ───────────────────────────────────────────────────────
#>
#> ✔ example.R: Completed succesfully
#>
#>
#> ══ End of process ══════════════════════════════════════════════════════════════
print(result)
#> # A tibble: 1 × 6
#> id tag script status result log_dir
#> <dbl> <chr> <chr> <chr> <list> <chr>
#> 1 1 NA /tmp/RtmpeaqwRR/file22ffef05393/examp… succe… <named list> /tmp/R…
The script is now executed and you can access the logs below: