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Dependency and Lifecycle Management Workflows

Introduction

Maintaining dependencies, code lifecycles, and release procedures are key responsibilities when developing R packages. devkit provides modules to automate, audit, and safeguard these workflows.

🚀 Bootstrapping the Development Environment

When onboarding a new developer or setting up a clean machine, bootstrap_dev_env() automates the installation of standard R development packages.

# Bootstrap standard development libraries (devtools, testthat, roxygen2, knitr, etc.)
bootstrap_dev_env()

📦 Auditing & Scanning Dependencies

Keeping a clean and accurate DESCRIPTION file is critical for CRAN compliance. devkit provides utilities to identify missing dependencies and detect unused packages.

Auditing DESCRIPTION Dependencies

audit_dependencies() scans your R/ and tests/ directories, compares the found namespaces with those listed in your DESCRIPTION file, and flags discrepancies.

# Audit the current package's dependencies
audit_res <- audit_dependencies()

# Inspect results
print(audit_res$ghost_deps) # Packages used in code but missing from DESCRIPTION
print(audit_res$bloat_deps) # Packages listed in DESCRIPTION but never used in code

Scanning Active Session Dependencies

scan_dependencies() looks at the packages currently attached or loaded in your R session and compares them to the packages actually used by a specific script.

# Scan an active script for unused loaded packages
scan_res <- scan_dependencies("scripts/process_data.R")

print(scan_res$unused_packages) # Attached packages not used by the script

🧹 Safely Uninstalling Packages

CRAN packages should avoid leaving system directories cluttered. devkit includes safe package removal utilities.

Uninstalling a Single Package

remove_package() checks if other installed packages depend on the target package before removing it, preventing broken dependencies.

# Remove a package safely
remove_package("unusedpkg")

Resetting the User Library

remove_user_installed_packages() cleans all user-installed packages from your library paths while strictly preserving base and recommended R packages (such as stats, graphics, survival, Matrix, etc.).

# Clear user-installed packages to restore a clean environment
remove_user_installed_packages()

🛡️ Git Hooks & Safety Pre-flights

To prevent pushing broken code, setup_preflight() installs git pre-commit hooks that validate code styling, documentation, and tests before a commit is finalized.

# Set up a pre-commit hook that runs checks
setup_preflight(run_docs = TRUE, run_tests = TRUE, run_style = TRUE)

Additionally, setup_sentinel() can be used to set up automated session logging for debugging, writing logs to a file in real time.

# Initialize session logging at the debug level
setup_sentinel(log_file = "logs/session.log", log_level = "debug")

🔄 Managing Function Deprecations

When refactoring a package, you often need to deprecate old functions. manage_deprecation() automates: 1. Writing a deprecation warning inside the old function. 2. Creating/updating a wrapper that points to the new function. 3. Scanning existing scripts, tests, and vignettes to automatically replace occurrences of the old function.

# Deprecate an old function in favor of a new one
manage_deprecation(
  old_func = "old_calculate_mean",
  new_func = "calculate_mean",
  wrapper_file = "R/deprecated_wrappers.R",
  refactor = TRUE
)

🚀 Automating Releases

When the package is ready for a new release, architect_release() orchestrates the version bump and drafts NEWS.md.

# Bump package version and write news bullets interactively
architect_release()

And architect_vignette() sets up a new CRAN-compliant vignette skeleton, inserting all standard headers and boilerplate.

# Scaffold a new HTML vignette
architect_vignette(title = "Advanced Workflows")

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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