Dynamic Function-Oriented 'Make'-Like Declarative Workflows


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Documentation for package ‘targets’ version 0.4.2

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targets-package targets: Dynamic Function-Oriented Make-Like Declarative Pipelines for R
cross Emulate dynamic branching.
head Emulate dynamic branching.
map Emulate dynamic branching.
sample Emulate dynamic branching.
tail Emulate dynamic branching.
tar_branches Reconstruct the branch names and the names of their dependencies.
tar_cancel Cancel a target mid-build under a custom condition.
tar_config_get Get configuration settings from _targets.yaml.
tar_config_set Write configuration settings to _targets.yaml.
tar_cue Declare the rules that cue a target.
tar_delete Delete locally stored target return values.
tar_deps Code dependencies
tar_deps_raw Code dependencies (raw version)
tar_destroy Destroy all or part of the data store.
tar_dir Execute code in a temporary directory.
tar_edit Open _targets.R for editing.
tar_envir For developers only: get the environment of the current target.
tar_envvars Show environment variables to customize 'targets'
tar_exist_meta Check if target metadata exists.
tar_exist_objects Check if local output data exists for one or more targets.
tar_exist_process Check if process metadata exists.
tar_exist_progress Check if progress metadata exists.
tar_exist_script Check if the target script exists.
tar_github_actions Set up GitHub Actions to run a targets pipeline
tar_glimpse Visualize an abridged fast dependency graph.
tar_group Group a data frame to iterate over subsets of rows.
tar_helper Write a helper R script.
tar_helper_raw Write a helper R script (raw version).
tar_invalidate Invalidate targets and global objects in the metadata.
tar_load Load the values of targets.
tar_load_raw Load the values of targets (raw version).
tar_make Run a pipeline of targets.
tar_make_clustermq Run a pipeline of targets in parallel with persistent 'clustermq' workers.
tar_make_future Run a pipeline of targets in parallel with transient 'future' workers.
tar_manifest Produce a data frame of information about your targets.
tar_meta Read a project's metadata.
tar_name Get the name of the target currently running.
tar_network Return the vertices and edges of a pipeline dependency graph.
tar_objects List saved targets
tar_option_get Get a target option.
tar_option_reset Reset all target options.
tar_option_set Set target options.
tar_outdated Check which targets are outdated.
tar_path Identify the file path where a target will be stored.
tar_pattern Emulate dynamic branching.
tar_pid Get main process ID.
tar_poll Repeatedly poll progress in the R console.
tar_process Get main process info.
tar_progress Read progress.
tar_progress_branches Tabulate the progress of dynamic branches.
tar_progress_summary Summarize target progress.
tar_prune Remove targets that are no longer part of the pipeline.
tar_read Read a target's value from storage.
tar_read_raw Read a target's value from storage (raw version)
tar_renv Set up package dependencies for compatibility with 'renv'
tar_script Write a _targets.R script to the current working directory.
tar_seed Get the random number generator seed of the target currently running.
tar_sitrep Show the cue-by-cue status of each target.
tar_target Declare a target.
tar_target_raw Define a target using unrefined names and language objects.
tar_test Test code in a temporary directory.
tar_timestamp Get the timestamp(s) of a target.
tar_timestamp_raw Get the timestamp(s) of a target (raw version).
tar_traceback Get a target's traceback
tar_validate Validate a pipeline of targets.
tar_visnetwork Visualize an abridged fast dependency graph.
tar_watch Shiny app to watch the dependency graph.
tar_watch_server Shiny module server for tar_watch()
tar_watch_ui Shiny module UI for tar_watch()
tar_workspace Load a saved workspace and seed for debugging.
tar_workspaces List saved target workspaces.