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

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

## Documentation for package ‘autocodebook’ version 0.1.0

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

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