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To save time for repeated plotting, this function is divided into drake_graph_info() and render_sankey_drake_graph(). A legend is unfortunately unavailable for the graph itself, but you can see what all the colors mean with visNetwork::visNetwork(drake::legend_nodes()).


  file = character(0),
  selfcontained = FALSE,
  build_times = "build",
  digits = 3,
  targets_only = FALSE,
  from = NULL,
  mode = c("out", "in", "all"),
  order = NULL,
  subset = NULL,
  make_imports = TRUE,
  from_scratch = FALSE,
  group = NULL,
  clusters = NULL,
  show_output_files = TRUE,
  config = NULL



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


Name of a file to save the graph. If NULL or character(0), no file is saved and the graph is rendered and displayed within R. If the file ends in a .png, .jpg, .jpeg, or .pdf extension, then a static image will be saved. In this case, the webshot package and PhantomJS are required: install.packages("webshot"); webshot::install_phantomjs(). If the file does not end in a .png, .jpg, .jpeg, or .pdf extension, an HTML file will be saved, and you can open the interactive graph using a web browser.


Logical, whether to save the file as a self-contained HTML file (with external resources base64 encoded) or a file with external resources placed in an adjacent directory. If TRUE, pandoc is required.


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.


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.


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


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.


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.




A visNetwork graph.


if (FALSE) {
isolate_example("Quarantine side effects.", {
if (suppressWarnings(require("knitr"))) {
load_mtcars_example() # Get the code with drake_example("mtcars").
if (requireNamespace("networkD3", quietly = TRUE)) {
if (requireNamespace("visNetwork", quietly = TRUE)) {
# Plot the network graph representation of the workflow.
# Show the legend separately.
visNetwork::visNetwork(nodes = drake::legend_nodes())
make(my_plan) # Run the project, build the targets.
sankey_drake_graph(my_plan) # The black nodes from before are now green.
# Plot a subgraph of the workflow.
sankey_drake_graph(my_plan, from = c("small", "reg2"))