Import boilerplate Database(s) — boilerplate

This function imports one or more boilerplate databases from disk. It automatically detects the file format (RDS or JSON) based on file extension. The function can import from a directory (original behaviour) or from a specific file path (new).

Usage

boilerplate_import(
  category = NULL,
  data_path = NULL,
  quiet = FALSE,
  project = "default"
)

Arguments

category

Character or character vector. Category of database to import. Options include "measures", "methods", "results", "discussion", "appendix", "template". If NULL (default), imports all available categories as a unified database. Ignored if data_path points to a specific file.

data_path

Character. Can be either:

A directory path containing database files (original behaviour)
A specific file path to import (e.g., "data/methods_db_20240115_143022.rds") If NULL (default), uses tools::R_user_dir("boilerplate", "data").

quiet

Logical. If TRUE, suppresses all CLI alerts. Default is FALSE.

project

Character. Project name for organizing databases. Default is "default". Projects are stored in separate subdirectories to allow multiple independent boilerplate collections.

Value

List. The imported database(s). If a single category was requested, returns that database. If multiple categories were requested, returns a unified database with each category as a named element.

Examples

# Create a temporary directory and initialise databases
temp_dir <- tempdir()
data_path <- file.path(temp_dir, "boilerplate_import_example", "data")

# Initialise some databases first
boilerplate_init(
  categories = c("methods", "measures"),
  data_path = data_path,
  create_dirs = TRUE,
  create_empty = FALSE,
  confirm = FALSE,
  quiet = TRUE
)

# Import all databases as unified (new default)
unified_db <- boilerplate_import(data_path = data_path, quiet = TRUE)
names(unified_db)
#> [1] "methods"  "measures"

# Access specific category
methods_db <- unified_db$methods
names(methods_db)
#> [1] "sample"             "causal_assumptions" "statistical"       

# Import from a specific file (e.g., timestamped or backup)
# First, save with timestamp to create a timestamped file
boilerplate_save(
  methods_db,
  category = "methods",
  data_path = data_path,
  timestamp = TRUE,
  confirm = FALSE,
  quiet = TRUE
)

# List files to see what's available
list.files(data_path, pattern = "methods.*\\.rds")
#> character(0)

# Import the timestamped file directly
timestamped_file <- list.files(
  data_path, 
  pattern = "methods.*_\\d{8}_\\d{6}\\.rds", 
  full.names = TRUE
)[1]
if (length(timestamped_file) > 0 && file.exists(timestamped_file)) {
  methods_timestamped <- boilerplate_import(
    data_path = timestamped_file, 
    quiet = TRUE
  )
}

# Clean up
unlink(file.path(temp_dir, "boilerplate_import_example"), recursive = TRUE)