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The goal of repo.data is to make repository data accessible. Mainly it consumes existing data but the idea is to also generate it.

Installation

You can install the development version of repo.data like so:

remotes::install_github("llrs/repo.data")

Example

We can get a data.frame of all packages on CRAN archive:

library(repo.data)
ca <- cran_archive()
head(ca)
#>         package      published_date version cran_team   size   status
#> 1            A3 2013-02-07 09:00:29   0.9.1    hornik  45252 archived
#> 2            A3 2013-03-26 18:58:40   0.9.2    ligges  45907 archived
#> 3            A3 2015-08-16 21:05:54   1.0.0    hornik  42810  current
#> 4 AalenJohansen 2023-03-01 10:42:11     1.0    ligges 165057  current
#> 5          aaMI 2005-06-24 15:55:17   1.0-0      root   2968 archived
#> 6          aaMI 2005-10-17 19:24:18   1.0-1      root   3487 archived

We can also check CRAN comments about the packages on its archive:

cc <- cran_comments()
head(cc)
#>       package
#> 1       aaSEA
#> 2         aba
#> 3      abbyyR
#> 4      abcADM
#> 5    abcdeFBA
#> 6 ABCExtremes
#>                                                                                        comment
#> 1               Archived on 2022-06-21 as check problems were not corrected despite reminders.
#> 2                         Archived on 2022-03-27 as check problems were not corrected in time.
#> 3                                          Archived on 2023-11-03 at the maintainer's request.
#> 4                                 Archived on 2023-03-02 as issues were not corrected in time.
#> 5                         Archived on 2022-03-07 as check problems were not corrected in time.
#> 6 Archived on 2015-06-19 as incomplete maintainer address was not corrected despite reminders.
#>         date   action
#> 1 2022-06-21 archived
#> 2 2022-03-27 archived
#> 3 2023-11-03 archived
#> 4 2023-03-02 archived
#> 5 2022-03-07 archived
#> 6 2015-06-19 archived

Or estimate the last date of update of our packages, by the information on the session info or a data.frame:

cran_session(session = sessionInfo())
#> [1] "2024-11-08"
ip <- installed.packages()
cran_date(ip)
#> [1] "2024-12-08"

Other packages and related analysis :

History

This package comes from the analysis on CRAN data on https://llrs.dev