drake (version 5.0.0)

Show the analysis wildcard used in plan_summaries().

For make(..., parallelism = "Makefile"), see what your Makefile recipes will look like in advance.

Return the default value of the args argument to make().

Give the default command argument to make().

Create the underlying node and edge data frames behind vis_drake_graph().

Return the sessionInfo() of the last call to make().

Default hook argument to make().

Show the default parallelism argument to make() for your system.

Show the default recipe command for make(..., parallelism = "Makefile").

Show the dataset wildcard used in plan_analyses() and plan_summaries().

Do the prework in the prework argument to make().

Drake is a pipeline toolkit (https://github.com/pditommaso/awesome-pipeline) and a scalable, R-focused solution for reproducibility and high-performance computing.

Return the default title of the graph for vis_drake_graph().

Create a workflow plan data frame for the plan argument of make.

For drake caches, list the storr namespaces that are cleaned during a call to clean().

Create the internal runtime parameter list used internally in make().

A hook argument to make() for which no targets get built and no imports get processed.

List the targets that failed in the last call to make().

List the targets that will be built in the first parallelizable stage of the next call to make.

Read the workflow plan from your last attempted call to make().

Store an internal configuration list from drake_config().

Show the R recipe wildcard for make(..., parallelism = "Makefile").

Create the nodes data frame used in the legend of vis_drake_graph().

Show how make() will build your targets in successive parallelizable stages.

List the targets that either (1) are currently being built during a make(), or (2) were being built if the last make() quit unexpectedly.

Read the cached drake_config() list from the last make().

Read the igraph dependency network from your last attempted call to make().

List the possible targets for the targets argument to make(), given a workflow plan data frame.

Do the preparatory work for make() with a distributed computing backend (see the parallelism argument of make()).

Get the build progress of your targets during a make().

Render a visualization using the data frames generated by dataframes_graph().

Run make(), on an existing internal configuration list.

Write dummy timestamp files for make(..., parallelism = "Makefile").