# 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")