1. Device used to facilitate navigation in foggy conditions by warning of potential hazards ahead.
foghorn makes accessible to the R terminal the CRAN check results for packages maintained by individuals, or for other packages of interest. The results are presented as a colored summary, or as a tibble. The function that generates the summary is designed to be called from your
.Rprofile so you can check on the status of the packages regularly.
As new features are introduced in development versions of R, or new policies are put in place, packages that are not updated frequently may start generating warnings or errors when checked on CRAN’s infrastructure.
foghorn brings this information to your terminal so you don’t have to leave the comfort of your R session to know the results of the CRAN checks for your packages.
You can install the development version of
foghorn from github with:
or the stable version from CRAN:
foghorn provides the results of the package CRAN checks. As a maintainer, you can easily get the results of the checks for your packages by using the email address included in the
DESCRIPTION file of your packages.
summary_cran_results() provides you with a graphical summary of the results of the CRAN checks. The number in parenthesis after the name of the package indicates the number of platforms used by CRAN that produced this result.
summary_cran_results() is actually an alias of
summary(cran_results()), meaning that you can call
cran_results() directly if you want to easily access the underlying data for the results of the CRAN checks. These results are stored in a tibble.
## Results of the checks as a tibble cran_results(email = "firstname.lastname@example.org") #> # A tibble: 5 x 7 #> package error fail warn note ok has_other_issues #> <chr> <int> <int> <int> <int> <int> <lgl> #> 1 foghorn 0 0 0 0 12 FALSE #> 2 phylobase 0 0 0 0 12 FALSE #> 3 riceware 0 0 0 0 12 FALSE #> 4 rncl 0 0 2 3 7 FALSE #> 5 rotl 0 0 3 0 9 FALSE
In addition of your own packages, you can also check the results for any other packages that might be of interest to you:
## either by themselves summary_cran_results(pkg = c("ggplot2", "dplyr")) #> ⚠ Package with warnings on CRAN: #> - ggplot2 (3) #> ★ Packages with notes on CRAN: #> - dplyr (8) #> - ggplot2 (5) cran_results(pkg = c("ggplot2", "dplyr")) #> # A tibble: 2 x 7 #> package error fail warn note ok has_other_issues #> <chr> <int> <int> <int> <int> <int> <lgl> #> 1 dplyr 0 0 0 8 4 FALSE #> 2 ggplot2 0 0 3 5 4 FALSE ## or by combining them with email addresses summary_cran_results(email = "email@example.com", pkg = c("mregions", "ridigbio")) #> ✔ All clear for foghorn, mregions, phylobase, riceware, ridigbio! #> ⚠ Packages with warnings on CRAN: #> - rncl (2) #> - rotl (3) #> ★ Package with notes on CRAN: #> - rncl (3) cran_results(email = "firstname.lastname@example.org", pkg = c("mregions", "ridigbio")) #> # A tibble: 7 x 7 #> package error fail warn note ok has_other_issues #> <chr> <int> <int> <int> <int> <int> <lgl> #> 1 foghorn 0 0 0 0 12 FALSE #> 2 mregions 0 0 0 0 12 FALSE #> 3 phylobase 0 0 0 0 12 FALSE #> 4 riceware 0 0 0 0 12 FALSE #> 5 ridigbio 0 0 0 0 12 FALSE #> 6 rncl 0 0 2 3 7 FALSE #> 7 rotl 0 0 3 0 9 FALSE
(tidyr_checks <- cran_details(pkg = "tidyr")) #> # A tibble: 1 x 7 #> package version result check flavors n_flavors message #> <chr> <chr> <chr> <chr> <chr> <dbl> <chr> #> 1 tidyr 0.8.2 NOTE data for… r-devel-linux-x8… 5 " Note:… summary(tidyr_checks) #> ★ tidyr - note: data for non-ASCII characters #> ❯ r-devel-linux-x86_64-fedora-clang #> ❯ r-devel-linux-x86_64-fedora-gcc #> ❯ r-patched-solaris-x86 #> ❯ r-release-osx-x86_64 #> ❯ r-oldrel-osx-x86_64 #> #> Note: found 23 marked UTF-8 strings
The data from the check results used by this package are either scraped from the CRAN web pages (default), or are from the CRAN database (that CRAN uses to build the webpages). The first option is faster if you want to regularly check a few packages. However, if you are doing statistics on a large number of packages, using the CRAN database is recommended (it’s about 20Mb of data). To use the CRAN database, add
src = "crandb" in your function calls:
Check out the “Details” section in the help files for more information.
Feel free to submit feedback and suggestions by opening an issue on GitHub.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.