CRAN Submission Guide

This skill covers the complete CRAN submission process, from pre-submission preparation through to acceptance and post-release tasks. CRAN (Comprehensive R Archive Network) is the primary repository for R packages and has strict quality requirements.

Rules

•All exported functions must have @returns and @examples documentation
•Version number must be greater than the current CRAN version
•Test on multiple platforms before submission (Windows, macOS, Linux, R-devel)
•Fix all ERRORs and WARNINGs - CRAN will reject packages with any
•NOTEs should be explained in cran-comments.md
•Title case for Title field with no period at the end, under 65 characters
•Use cph role for copyright holders in Authors@R
•Check all URLs with urlchecker::url_check()
•Examples must run without errors (use \donttest{} sparingly)
•Respond to CRAN within 2 weeks or submission will be archived

Pre-Submission Checklist

Essential Documentation Requirements

Every exported function must have:

#' Function Title
#'
#' @description
#' Detailed description of what the function does.
#'
#' @param x Description of parameter x
#' @param y Description of parameter y
#'
#' @returns A data.frame with columns:
#'   \item{col1}{Description of column 1}
#'   \item{col2}{Description of column 2}
#'
#' @examples
#' # Basic usage
#' result <- my_function(x = 1, y = 2)
#' print(result)
#'
#' # Advanced usage
#' result2 <- my_function(x = 1:10, y = 20)
#'
#' @export
my_function <- function(x, y) {
  # implementation
}

Critical: Use @returns (not @return) for consistency with roxygen2 7.0+.

DESCRIPTION File Requirements

code

Package: packagename
Title: A Package That Does Amazing Things  # Title case, < 65 chars, no period
Version: 0.1.0  # Must be > current CRAN version
Authors@R: c(
    person("First", "Last", email = "email@example.com",
           role = c("aut", "cre"),
           comment = c(ORCID = "0000-0000-0000-0000")),
    person("Another", "Author", role = "aut"),
    person("Company Name", role = "cph")  # Copyright holder
    )
Description: Provides tools for amazing analysis. This package implements
    novel algorithms and provides intuitive interfaces. Functions include
    data processing, visualization, and reporting capabilities.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.0
URL: https://username.github.io/packagename/, https://github.com/username/packagename
BugReports: https://github.com/username/packagename/issues
Suggests:
    testthat (>= 3.0.0),
    knitr,
    rmarkdown
VignetteBuilder: knitr
Config/testthat/edition: 3

Title field rules:

•Title case (capitalize major words)
•No period at end
•Under 65 characters
•Don't start with "A Package for..." (redundant)
•Be specific about what it does

Description field rules:

•One paragraph
•Indent continuation lines with 4 spaces
•Don't start with "This package..."
•Explain what the package does, not just list features
•Mention key algorithms or papers if relevant

Version Numbering

For new submissions:

code

Version: 0.1.0

For updates (must be > CRAN version):

code

# If CRAN has 0.1.0, use:
Version: 0.1.1  # Bug fixes
Version: 0.2.0  # New features
Version: 1.0.0  # Major release

Development versions (not for CRAN):

code

Version: 0.1.0.9000  # Development version after 0.1.0

Multi-Platform Testing

Local Testing

# Standard check
devtools::check()

# Check with remote checking (stricter)
devtools::check(remote = TRUE, manual = TRUE)

# Check with --as-cran flag
devtools::check(args = c('--as-cran'))

Windows Testing

# Check on Windows builder (CRAN's Windows server)
devtools::check_win_devel()   # R-devel
devtools::check_win_release() # R-release
devtools::check_win_oldrelease() # R-oldrelease

You'll receive an email with results in ~30 minutes.

R-hub Testing

# Install rhub
install.packages("rhub")

# Validate email first time
rhub::validate_email()

# Check on multiple platforms
rhub::check_for_cran()

# Specific platforms
rhub::check(platform = "windows-x86_64-devel")
rhub::check(platform = "ubuntu-gcc-release")
rhub::check(platform = "macos-highsierra-release-cran")
rhub::check(platform = "solaris-x86-patched")

# List available platforms
rhub::platforms()

Note: R-hub can be unreliable. GitHub Actions with r-lib/actions is often more reliable.

GitHub Actions

Most reliable multi-platform testing:

# Set up GitHub Actions
usethis::use_github_action("check-standard")

Tests on:

•macOS (release)
•Windows (release)
•Ubuntu (devel, release, oldrel-1)

URL Checking

# Check all URLs in documentation and vignettes
urlchecker::url_check()

# Fix or explain any broken URLs

Common issues:

•DOIs should use https://doi.org/ not http://dx.doi.org/
•Use permanent URLs, not redirects
•Some URLs may be temporarily down (explain in cran-comments.md)

Creating cran-comments.md

Create cran-comments.md in package root:

markdown

## Test environments
* local R installation, R 4.4.0
* ubuntu 22.04 (on GitHub Actions), R-devel, R-release, R-oldrel-1
* windows-latest (on GitHub Actions), R-release
* macos-latest (on GitHub Actions), R-release
* win-builder (devel and release)

## R CMD check results

0 errors | 0 warnings | 1 note

* This is a new release.

## Downstream dependencies

There are currently no downstream dependencies for this package.

For Updates

markdown

## Test environments
* local R installation, R 4.4.0
* ubuntu 22.04 (on GitHub Actions), R-devel, R-release, R-oldrel-1
* windows-latest (on GitHub Actions), R-release
* macos-latest (on GitHub Actions), R-release

## R CMD check results

0 errors | 0 warnings | 0 notes

## What's changed

This is a minor release that fixes bugs and adds new features:

* Fixed issue with X (#123)
* Added new function Y
* Improved documentation for Z

## Downstream dependencies

I have run R CMD check on downstream dependencies of my package.
All packages passed.

Explaining NOTEs

markdown

## R CMD check results

0 errors | 0 warnings | 1 note

* Checking CRAN incoming feasibility ... NOTE

  Maintainer: 'First Last <email@example.com>'

  New submission

  Possibly misspelled words in DESCRIPTION:
    MCMC (3:49)
    PyMC (9:31)

  These are not misspelled:
  * MCMC is a standard acronym for Markov Chain Monte Carlo
  * PyMC is the name of a Python library

Submission Process

First Submission

# 1. Final checks
devtools::check()
devtools::check_win_devel()
rhub::check_for_cran()
urlchecker::url_check()

# 2. Build the package
devtools::build()

# 3. Submit to CRAN
devtools::submit_cran()

# This will:
# - Build the package
# - Run R CMD check
# - Ask for confirmation
# - Submit to CRAN via web form

Manual Submission

If submit_cran() doesn't work:

•Build package: devtools::build()
•Go to https://cran.r-project.org/submit.html
•Upload .tar.gz file
•Fill in maintainer email and comments
•Submit

Confirmation Email

You'll receive an email asking to confirm submission:

•Click the confirmation link within 24 hours
•CRAN will then review your package

CRAN Review Process

Timeline

•Submission: Upload package
•Confirmation (immediate): Confirm via email
•Automated checks (minutes to hours): CRAN runs checks
•Human review (days to weeks): CRAN volunteer reviews
•Acceptance or rejection: Email notification

Typical timeline: 1-2 weeks, but can be longer during busy periods.

Common Rejection Reasons

•ERRORs or WARNINGs in R CMD check
•Missing documentation (no @returns or @examples)
•Examples fail or take too long (>5 seconds per example)
•License issues (incompatible or missing LICENSE file)
•DESCRIPTION problems (title, description formatting)
•Failed tests on CRAN's systems
•Large package size (>5 MB without justification)
•Writing to user's home directory without permission
•Internet resources without checks (must fail gracefully if offline)
•Non-standard file permissions

Common R CMD Check Issues and Fixes

1. Undefined Global Variables

Problem:

code

checking R code for possible problems ... NOTE
my_function: no visible binding for global variable 'x'
my_function: no visible binding for global variable 'y'

Cause: Using NSE (non-standard evaluation) with dplyr, data.table, etc.

Solution:

# In R/globals.R
utils::globalVariables(c("x", "y", "z"))

# Or use .data pronoun
library(dplyr)
my_function <- function(df) {
  df %>%
    mutate(z = .data$x + .data$y)
}

2. Unused Imports

Problem:

code

checking dependencies in R code ... NOTE
Namespace in Imports field not imported from: 'package'

Solution: Remove from DESCRIPTION or use somewhere:

#' @importFrom package function

3. Non-ASCII Characters

Problem:

code

checking R files for non-ASCII characters ... NOTE

Solution: Use Unicode escapes:

# Bad
"Müller"

# Good
"M\u00fcller"

4. Examples Fail

Problem:

code

checking examples ... ERROR

Solution: Wrap problematic examples:

#' @examples
#' # Basic example (always runs)
#' result <- my_function(x = 1)
#'
#' \donttest{
#' # Slow example (skipped on CRAN)
#' slow_result <- slow_function(x = 1:1000000)
#' }
#'
#' \dontrun{
#' # Requires authentication (never runs)
#' api_result <- call_api(key = "your-key")
#' }

Rules:

•\donttest{}: Runs locally and on CI, skipped on CRAN (for slow examples)
•\dontrun{}: Never runs automatically (for examples needing setup)
•Don't overuse - most examples should run

5. Missing Imports

Problem:

code

checking dependencies in R code ... WARNING
'::' or ':::' imports not declared from:
  'package'

Solution: Add to DESCRIPTION Imports and use:

#' @importFrom package function

Or declare in NAMESPACE:

code

importFrom(package, function)

6. LaTeX/PDF Errors

Problem:

code

checking PDF version of manual ... WARNING

Solution: Fix .Rd formatting issues or use:

yaml

# In GitHub Actions
build_args: 'c("--no-manual")'

7. Vignette Build Fails

Problem:

code

checking re-building of vignette outputs ... WARNING

Solution: Ensure vignettes build:

devtools::build_vignettes()

# Check for missing packages in Suggests

8. File Permissions

Problem:

code

checking file modes ... NOTE

Solution: Fix permissions:

bash

chmod 644 R/*.R
chmod 644 man/*.Rd
chmod 755 configure

9. Package Size

Problem:

code

checking installed package size ... NOTE
  installed size is X Mb
  sub-directories of 1Mb or more:
    data   Y Mb

Solution:

•Compress data: tools::resaveRdaFiles("data")
•Use LazyData: true in DESCRIPTION
•Consider external data package
•Explain large size in cran-comments.md

10. Writing to User Directories

Problem: Package writes to home directory or modifies environment

Solution: Use temporary directories:

# Bad
write.csv(data, "~/mypackage/output.csv")

# Good
tmpdir <- tempdir()
write.csv(data, file.path(tmpdir, "output.csv"))

# For configuration
config_dir <- tools::R_user_dir("mypackage", which = "config")
if (!dir.exists(config_dir)) {
  dir.create(config_dir, recursive = TRUE)
}

11-20. Additional Common Issues

11. Suggested packages not declared:

# Conditional usage
if (requireNamespace("ggplot2", quietly = TRUE)) {
  # Use ggplot2
} else {
  message("Install ggplot2 for better plots")
}

12. Internet resources without checks:

# Check connectivity
check_connection <- function(url) {
  tryCatch({
    httr::GET(url, httr::timeout(5))
    TRUE
  }, error = function(e) {
    message("Cannot connect to ", url)
    FALSE
  })
}

13. Testing failures:

# Skip tests on CRAN if they require internet/auth
testthat::skip_on_cran()
testthat::skip_if_offline()

14. Long-running tests:

# In tests/testthat.R
Sys.setenv("NOT_CRAN" = "true")

# In test files
testthat::skip_on_cran()  # Skip slow tests

15. Missing LICENSE file:

# For MIT license
usethis::use_mit_license()

# Creates LICENSE and LICENSE.md

16. Undeclared S3 methods:

#' @export
print.myclass <- function(x, ...) {
  # implementation
}

# In NAMESPACE (auto-generated by roxygen2)
S3method(print, myclass)

17. Examples too long:

•Keep examples under 5 seconds each
•Use smaller datasets
•Wrap slow parts in \donttest{}

18. Rd cross-references broken:

#' @seealso \code{\link{other_function}}
#' @seealso \code{\link[otherpackage]{their_function}}

19. Non-standard installation:

•Don't require user interaction during installation
•Use configure script for system dependencies
•Document requirements clearly

20. Archived dependencies:

•Check that all dependencies are on CRAN
•Update or remove archived dependencies

21-30. More Issues

21. Data documentation missing:

#' Dataset Title
#'
#' @description Description of dataset
#'
#' @format A data frame with 100 rows and 5 variables:
#' \describe{
#'   \item{var1}{Description of var1}
#'   \item{var2}{Description of var2}
#' }
#' @source \url{https://example.com/data}
"dataset_name"

22. NAMESPACE conflicts:

# Don't export everything
#' @keywords internal
internal_function <- function() {}

23. Windows path issues:

# Use file.path() not paste
file.path("dir", "file.txt")  # Good
# Not: paste("dir", "file.txt", sep = "/")  # Bad

24. Encoding issues: Add to DESCRIPTION:

code

Encoding: UTF-8

25. Undeclared attachments:

# Don't use library() in package code
# Use :: or importFrom instead
dplyr::filter()  # Good
# Not: library(dplyr); filter()  # Bad

26. Examples with \dontrun only:

•Every function needs runnable examples
•Use \donttest{} instead of \dontrun{} when possible

27. Biased package names:

•Don't use "R" prefix (e.g., "Rpackage")
•Don't use misleading names
•Check name isn't trademarked

28. Missing return values:

#' @returns A numeric vector of length n
#' @returns NULL (invisibly) if no output

29. Improper TRUE/FALSE:

# Use TRUE/FALSE, not T/F
if (condition == TRUE)  # Good
# Not: if (condition == T)  # Bad

30. Unconventional directory structure:

•Follow standard R package structure
•No spaces in file names
•Use lowercase for .R files

31-50. Advanced Issues

31-40: Platform-specific code, parallel processing issues, memory leaks, C/C++ code problems, Fortran code issues, Java dependencies, system command calls, graphic device problems, locale-specific code, timezone issues

41-50: Partial argument matching, 1:length() issues, sapply() problems, dependency version constraints, circular dependencies, namespace pollution, documentation warnings, alias issues, keyword problems, cross-reference errors

Resubmission After Rejection

Responding to CRAN Comments

If rejected, you'll get an email with issues. Fix them and resubmit:

markdown

## Resubmission

This is a resubmission. In this version I have:

* Fixed the DESCRIPTION title to be in title case
* Added \value sections to all exported functions
* Ensured all examples run without errors
* Fixed the NOTE about global variables by using utils::globalVariables()

## Test environments
...

Important:

•Address ALL comments from CRAN
•Be polite and professional
•Explain what you changed
•Resubmit within 2 weeks

Version Bumping

After rejection, bump patch version:

code

# First submission
Version: 0.1.0

# After rejection
Version: 0.1.0  # Keep same version if resubmitting same release

# Or bump if making significant changes
Version: 0.1.1

Reverse Dependency Checking

If your package has downstream dependencies (packages that depend on yours):

# Install revdepcheck
install.packages("revdepcheck")

# Check reverse dependencies
revdepcheck::revdep_check(num_workers = 4)

# View results
revdepcheck::revdep_report()

# If issues found, contact maintainers

Post-Acceptance Tasks

After CRAN Acceptance

# 1. Create GitHub release
usethis::use_github_release()

# 2. Bump to development version
usethis::use_dev_version()

# This changes:
# Version: 0.1.0  ->  Version: 0.1.0.9000

Announce Release

•Tweet about it
•Post on R-bloggers
•Update website
•Email interested users

Monitor CRAN

Check CRAN check results daily:

code

https://cran.r-project.org/web/checks/check_results_PACKAGENAME.html

Fix any issues that arise on CRAN's servers.

Common Pitfalls

1. Submitting with WARNINGs

Problem: Package has warnings but submitter thinks they're acceptable

Fix: CRAN will auto-reject. Fix ALL warnings before submission.

2. Not Testing on Windows

Problem: Package works on Mac/Linux but fails on Windows

Fix: Use check_win_devel() and GitHub Actions before submission.

3. Examples That Require Setup

Problem: Examples assume files/data/authentication exist

Fix: Examples must be self-contained or use \dontrun{}.

4. Not Responding Quickly

Problem: Wait too long to respond to CRAN

Fix: Respond within 2 weeks or submission is archived.

5. Arguing with CRAN

Problem: Trying to argue that a NOTE is acceptable

Fix: Either fix it or provide a clear, technical explanation in cran-comments.md.

6. Incomplete Documentation

Problem: Missing @returns or @examples

Fix: Every exported function needs both.

7. Version Confusion

Problem: Trying to submit 0.1.0 when CRAN has 0.1.0

Fix: Bump version to 0.1.1 or higher.

8. Large Package Size

Problem: Package is 10+ MB

Fix: Compress data, use external data, or justify in cran-comments.md.

9. Too Many Imports

Problem: Importing 20+ packages

Fix: Consider if all are necessary. Each import is a dependency burden.

10. Not Reading CRAN Policies

Problem: Violating policies unknowingly

Fix: Read https://cran.r-project.org/web/packages/policies.html

Final Pre-Submission Checklist

Good luck with your CRAN submission!