R/tar_progress_branches.R

In targets: Dynamic Function-Oriented 'Make'-Like Declarative Pipelines

#' @title Tabulate the progress of dynamic branches.
#' @export
#' @family progress
#' @description Read a project's target progress data for the most recent
#'   run of the pipeline and display the tabulated status
#'   of dynamic branches. Only the most recent record is shown.
#' @return A data frame with one row per target per progress status
#'   and the following columns.
#'   * `name`: name of the pattern.
#'   * `progress`: progress status: `"dispatched"`, `"completed"`,
#'     `"canceled"`, or `"errored"`.
#'   * `branches`: number of branches in the progress category.
#'   * `total`: total number of branches planned for the whole pattern.
#'     Values within the same pattern should all be equal.
#' @inheritParams tar_validate
#' @param names Optional, names of the targets. If supplied, `tar_progress()`
#'   only returns progress information on these targets.
#'   The object supplied to `names` should be `NULL` or a
#'   `tidyselect` expression like [any_of()] or [starts_with()]
#'   from `tidyselect` itself, or [tar_described_as()] to select target names
#'   based on their descriptions.
#' @param fields Optional, names of progress data columns to read.
#'   Set to `NULL` to read all fields.
#' @examples
#' if (identical(Sys.getenv("TAR_EXAMPLES"), "true")) { # for CRAN
#' tar_dir({ # tar_dir() runs code from a temp dir for CRAN.
#' tar_script({
#'   library(targets)
#'   library(tarchetypes)
#'   list(
#'     tar_target(x, seq_len(2)),
#'     tar_target(y, x, pattern = map(x)),
#'     tar_target(z, stopifnot(y < 1.5), pattern = map(y))
#'   )
#' }, ask = FALSE)
#' try(tar_make())
#' tar_progress_branches()
#' })
#' }
tar_progress_branches <- function(
  names = NULL,
  fields = NULL,
  store = targets::tar_config_get("store")
) {
  tar_assert_allow_meta("tar_progress_branches", store)
  tar_assert_scalar(store)
  tar_assert_chr(store)
  tar_assert_nzchar(store)
  progress <- progress_init(path_store = store)
  out <- tibble::as_tibble(progress$database$read_condensed_data())
  out <- tar_progress_branches_summary(out)
  names_quosure <- rlang::enquo(names)
  fields_quosure <- rlang::enquo(fields)
  names <- tar_tidyselect_eval(names_quosure, out$name)
  fields <- tar_tidyselect_eval(fields_quosure, colnames(out)) %|||%
    colnames(out)
  if (!is.null(names)) {
    out <- out[match(names, out$name),, drop = FALSE] # nolint
  }
  out <- out[, base::union("name", fields), drop = FALSE]
  out[order(out$name),, drop = FALSE] # nolint
}

tar_progress_branches_summary <- function(progress) {
  branches <- progress[progress$type == "branch",, drop = FALSE] # nolint
  group <- paste(branches$parent, branches$progress)
  table <- table(group)
  group <- names(table)
  long <- tibble::tibble(
    name = gsub(" .*", "", group),
    progress = gsub(".* ", "", group),
    branches = as.integer(table)
  )
  levels <- c("skipped", "dispatched", "completed", "errored", "canceled")
  bins <- map(levels, ~tar_progress_branches_bin(.x, long))
  out <- progress[progress$type == "pattern",, drop = FALSE] # nolint
  out <- tibble::tibble(name = out$name, branches = out$branches)
  for (bin in bins) {
    out <- base::merge(x = out, y = bin, by = "name", all.x = TRUE)
  }
  for (level in levels) {
    out[[level]] <- replace_na(out[[level]], 0L)
  }
  tibble::as_tibble(out)
}

tar_progress_branches_bin <- function(level, long) {
  out <- long[long$progress %in% level,, drop = FALSE] # nolint
  out[[level]] <- out[["branches"]]
  out[["branches"]] <- NULL
  out[["progress"]] <- NULL
  out
}

# Just for the tar_watch() app. # nolint
tar_progress_branches_gt <- function(path_store) {
  progress <- tar_progress_branches(
    names = NULL,
    fields = NULL,
    store = path_store
  )
  tar_progress_display_gt(progress)
}