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With the returned data frames, you can plot your own custom visNetwork graph.


  from = NULL,
  mode = c("out", "in", "all"),
  order = NULL,
  subset = NULL,
  build_times = "build",
  digits = 3,
  targets_only = FALSE,
  font_size = 20,
  from_scratch = FALSE,
  make_imports = TRUE,
  full_legend = FALSE,
  group = NULL,
  clusters = NULL,
  show_output_files = TRUE,
  hover = FALSE,
  on_select_col = NULL,
  config = NULL



Arguments to make(), such as plan and targets.


Optional collection of target/import names. If from is nonempty, the graph will restrict itself to a neighborhood of from. Control the neighborhood with mode and order.


Which direction to branch out in the graph to create a neighborhood around from. Use "in" to go upstream, "out" to go downstream, and "all" to go both ways and disregard edge direction altogether.


How far to branch out to create a neighborhood around from. Defaults to as far as possible. If a target is in the neighborhood, then so are all of its custom file_out() files if show_output_files is TRUE. That means the actual graph order may be slightly greater than you might expect, but this ensures consistency between show_output_files = TRUE and show_output_files = FALSE.


Optional character vector. Subset of targets/imports to display in the graph. Applied after from, mode, and order. Be advised: edges are only kept for adjacent nodes in subset. If you do not select all the intermediate nodes, edges will drop from the graph.


Character string or logical. If character, the choices are 1. "build": runtime of the command plus the time it take to store the target or import. 2. "command": just the runtime of the command. 3. "none": no build times. If logical, build_times selects whether to show the times from `build_times(..., type = "build")`` or use no build times at all. See build_times() for details.


Number of digits for rounding the build times


Logical, whether to skip the imports and only include the targets in the workflow plan.


Numeric, font size of the node labels in the graph


Logical, whether to assume all the targets will be made from scratch on the next make(). Makes all targets outdated, but keeps information about build progress in previous make()s.


Logical, whether to make the imports first. Set to FALSE to increase speed and risk using obsolete information.


Logical. If TRUE, all the node types are printed in the legend. If FALSE, only the node types used are printed in the legend.


Optional character scalar, name of the column used to group nodes into columns. All the columns names of your original drake plan are choices. The other choices (such as "status") are column names in the nodes . To group nodes into clusters in the graph, you must also supply the clusters argument.


Optional character vector of values to cluster on. These values must be elements of the column of the nodes data frame that you specify in the group argument to drake_graph_info().


Logical, whether to include file_out() files in the graph.


Logical, whether to show text (file contents, commands, etc.) when you hover your cursor over a node.


Optional string corresponding to the column name in the plan that should provide data for the on_select event.




A list of three data frames: one for nodes, one for edges, and one for the legend nodes. The list also contains the default title of the graph.


if (FALSE) {
isolate_example("Quarantine side effects.", {
if (requireNamespace("visNetwork", quietly = TRUE)) {
if (suppressWarnings(require("knitr"))) {
load_mtcars_example() # Get the code with drake_example("mtcars").
# Get a list of data frames representing the nodes, edges,
# and legend nodes of the visNetwork graph from vis_drake_graph().
raw_graph <- drake_graph_info(my_plan)
# Choose a subset of the graph.
smaller_raw_graph <- drake_graph_info(
  from = c("small", "reg2"),
  mode = "in"
# Inspect the raw graph.
# Use the data frames to plot your own custom visNetwork graph.
# For example, you can omit the legend nodes
# and change the direction of the graph.
graph <- visNetwork(nodes = raw_graph$nodes, edges = raw_graph$edges)
visHierarchicalLayout(graph, direction = 'UD')