Deal with check outputs

Sébastien Rochette

2023-06-19

library(checkhelper)

Create a fake package for examples

• The function has no visible global variables and missing documented functions
• The function has @export tag but not @return tag

# Create fake package ----
pkg_path <- tempfile(pattern = "pkg.")
dir.create(pkg_path)

# Create fake package
usethis::create_package(pkg_path, open = FALSE)

#> ✔ Setting active project to '/tmp/RtmpOmxnjd/pkg.e0fa160b8054'
#> ✔ Creating 'R/'
#> ✔ Writing 'DESCRIPTION'
#> ✔ Writing 'NAMESPACE'
#> ✔ Writing 'pkg.e0fa160b8054.Rproj'
#> ✔ Adding '^pkg\\.e0fa160b8054\\.Rproj$' to '.Rbuildignore'
#> ✔ Adding '.Rproj.user' to '.gitignore'
#> ✔ Adding '^\\.Rproj\\.user$' to '.Rbuildignore'
#> ✔ Setting active project to '/mnt/Data/github/ThinkR-open/checkhelper'

# Create function no visible global variables and missing documented functions
cat("
#' Function
#' @importFrom dplyr filter
#' @export
my_fun <- function() {
data %>%
filter(col == 3) %>%
mutate(new_col = 1) %>%
ggplot() +
  aes(x, y, colour = new_col) +
  geom_point()
}
", file = file.path(pkg_path, "R", "function.R"))

attachment::att_amend_desc(path = pkg_path)

#> Saving attachment parameters to yaml config file
#> Updating pkg.e0fa160b8054 documentation
#> ℹ Loading pkg.e0fa160b8054Writing '

# Files of the package
fs::dir_tree(pkg_path, recurse = TRUE)

Avoid missing return value for exported functions

CRAN does not like when exported functions do not have returned value. Using find_missing_tags(), you can detect exported functions with missing or empty @return tag

find_missing_tags(pkg_path)

#> ℹ Loading pkg.e0fa160b8054
#> Missing or empty return value for exported functions: my_fun
#> 
#> 
#> 
#> ℹ Loading pkg.e0fa160b8054

#> $package_doc
#> # A tibble: 0 × 0
#> 
#> $data
#> # A tibble: 0 × 0
#> 
#> $functions
#> # A tibble: 1 × 11
#>      id filename   topic  has_e…¹ has_r…² retur…³ has_n…⁴ rdnam…⁵
#>   <int> <chr>      <chr>  <lgl>   <lgl>   <chr>   <lgl>   <chr>  
#> 1     1 function.R my_fun TRUE    FALSE   ""      FALSE   my_fun 
#> # … with 3 more variables: not_empty_return_value <lgl>,
#> #   test_has_export_and_return <chr>,
#> #   test_has_export_or_has_nord <chr>, and abbreviated variable
#> #   names ¹​has_export, ²​has_return, ³​return_value, ⁴​has_nord,
#> #   ⁵​rdname_value

Deal with check outputs

• get_no_visible() runs the checks and extract no visible global variables and missing documented functions
• print_globals() proposes a template to add missing global variables in a globals.R file. Note that you can also transform all these variables with .data[[variable]]

# Get globals
globals <- get_no_visible(pkg_path, quiet = TRUE)
globals

#> $globalVariables
#> # A tibble: 4 × 7
#>   notes             filep…¹ fun   is_fu…² is_gl…³ varia…⁴ propo…⁵
#>   <chr>             <chr>   <chr> <lgl>   <lgl>   <chr>   <chr>  
#> 1 my_fun: no visib… -       my_f… FALSE   TRUE    data    " impo…
#> 2 my_fun: no visib… -       my_f… FALSE   TRUE    x        <NA>  
#> 3 my_fun: no visib… -       my_f… FALSE   TRUE    y        <NA>  
#> 4 my_fun: no visib… -       my_f… FALSE   TRUE    new_col  <NA>  
#> # … with abbreviated variable names ¹​filepath, ²​is_function,
#> #   ³​is_global_variable, ⁴​variable, ⁵​proposed
#> 
#> $functions
#> # A tibble: 5 × 7
#>   notes             filep…¹ fun   is_fu…² is_gl…³ varia…⁴ propo…⁵
#>   <chr>             <chr>   <chr> <lgl>   <lgl>   <chr>   <chr>  
#> 1 my_fun: no visib… -       my_f… TRUE    FALSE   %>%     <NA>   
#> 2 my_fun: no visib… -       my_f… TRUE    FALSE   mutate  <NA>   
#> 3 my_fun: no visib… -       my_f… TRUE    FALSE   ggplot  <NA>   
#> 4 my_fun: no visib… -       my_f… TRUE    FALSE   aes     <NA>   
#> 5 my_fun: no visib… -       my_f… TRUE    FALSE   geom_p… <NA>   
#> # … with abbreviated variable names ¹​filepath, ²​is_function,
#> #   ³​is_global_variable, ⁴​variable, ⁵​proposed

# Print globals to copy-paste
print_globals(globals)

#> --- Functions to add in NAMESPACE (with @importFrom ?) ---
#> 
#> my_fun: %>%, aes, geom_point, ggplot, mutate
#> 
#> --- Potential GlobalVariables ---
#> -- code to copy to your R/globals.R file --
#> 
#> globalVariables(unique(c(
#> # my_fun: 
#> "data", "new_col", "x", "y"
#> )))

# Store in package using usethis::use_r("globals")