---
title: "Bake Parallel Jobs in Background with bakerrr"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Bake Parallel Jobs in Background with bakerrr}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

## Overview

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.

## Job Architecture

 - Daemons: Background R processes that execute jobs in parallel
 - Arguments List: Each element contains named arguments for the target function
 - Results Collection: Automatic aggregation with error capture and reporting

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

## Setup

Define a simple function and generate a list of argument sets, introducing a mix of numeric and non-numeric (error-producing) cases.

```{r, include=TRUE}
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))
)
```

### Creating and Running Jobs

Instantiate a bakerrr object and process jobs in parallel with configurable daemon count.

```{r, include=TRUE}
new_stirr <- bakerrr::bakerrr(
  fun,
  args_list,
  n_daemons = 4
) |>
  bakerrr::run_jobs(wait_for_results = TRUE)

```

### Inspecting Status and Results

Print job summary and view results. Note that jobs triggering errors report the error messages as designed.

```{r, include=TRUE}
print(new_stirr)
new_stirr@results
```

### Notes

 - Use n_daemons to control parallel worker count based on available cores.
 - Error handling is built in; results will include error messages for failed jobs.
 - You can pass additional background job options via bg_args.
 - For more details, see function-level documentation or explore extending with additional job handlers and reporting tools.

.
