Automatic Codebook and Tracking for 'Spark' and 'dplyr' Pipelines

Documentation for package ‘autocodebook’ version 0.1.0

auto_filter	Filter with automatic tracking
auto_mutate	Mutate with automatic codebook registration
auto_summarise	Summarise with automatic codebook registration
cb_checkpoint	Checkpoint a Spark DataFrame
cb_export	Export codebook to file
cb_get	Get the current codebook as a tibble
cb_init	Initialize autocodebook session
cb_register	Manually register a variable in the codebook
cb_render	Render the codebook as a gt table
cb_reset	Reset the codebook (clear all entries)
cb_set_default_cache	Toggle default caching for big-data verbs
cb_set_verbose	Toggle verbose diagnostic messages
flow_diagram	Draw the eligibility flow as a CONSORT-style flowchart
flow_diagram_export	Save the eligibility flowchart to a file
flow_get	Get the current flow tree (raw structure)
flow_reset	Reset the flow tree
flow_table	Flow tree as a tidy table
generate_report	Generate a standardized report from the current session
track_export	Export tracking table to file
track_get	Get the current tracking log as a tibble
track_outcomes	Attach outcome counts to the current leaves (CONSORT flowchart)
track_render	Render the tracking log as a gt table
track_reset	Reset the tracking log
track_split	Split the cohort into branches by a column (CONSORT flowchart)
track_step	Record a tracking step