rotor provides a cross platform R reimagination of logrotate. It is a companion package to the logging package lgr. In contrast to logrotate, rotor relies solely on information encoded in a suffixes of file names for conditionally creating backups (i.e. a timestamp or index). It therefore also works with backups created by other tools, as long as the filename has a format that rotor can understand.

rotate(), rotate_date(), and rotate_time() move a file and insert a suffix (either an integer or a timestamp) into the filename. In addition, they create an empty file in place of the original one. This is useful for log rotation. backup(), backup_date() and backup_time() do the same but keep the original file.

rotor also includes utility functions for finding and examining the backups of a file: list_backups(), backup_info(), n_backups, newest_backup(), oldest_backup(). See the function reference for details.


You can install the released version of rotor from CRAN with:

And the development version from GitHub with:


First we create a temporary directory for the files created by the code examples


# create a directory
td <- file.path(tempdir(), "rotor")
dir.create(td, recursive = TRUE)

# create an example logfile
tf <- file.path(td, "mylogfile.log")
writeLines("An important message", tf)

Indexed backups

backup() makes a copy of a file and inserts an index between the filename and the file extension. The file with the index 1 is always the most recently made backup.

rotate() also backs up a file, but replaces the original file with an empty one.

The max_backups parameter limits the maximum number of backups rotor will keep of a file. Notice how the zipped backup we created above moves to index 4 as we create two new backups.

We can also use prune_backups() to delete old backups. Other than ensuring that no new backups is created, it works identically to using backup() with the max_backups parameter. By setting it to 0, we delete all backups.

prune_backups(tf, max_backups = 0)

Timestamped backups

rotor can also create timestamped backups. backup_date() creates uses a Date (yyyy-mm-dd) timestamp, backup_time() uses a full datetime-stamp by default (yyyy-mm-dd--hh-mm-ss). The format of the timestamp can be modified with a subset of the formatting tokens understood by strftime() (within certain restrictions). Backups created with both functions are compatible with each other (but not with those created with backup_index()).

# be default backup_date() only makes a backup if the last backups is younger
# than 1 day, so we set `age` to -1 for this example
backup_date(tf, age = -1)  
backup_date(tf, format = "%Y-%m", age = -1)
backup_time(tf, format = "%Y-%m-%d_%H-%M-%S")  # Python logging
backup_time(tf, format = "%Y%m%dT%H%M%S")  # ISO 8601 compatible

#>                                                       path      name
#> 1  /tmp/RtmpTB9vY3/rotor/mylogfile.2020-01-02_10-05-52.log mylogfile
#> 2 /tmp/RtmpTB9vY3/rotor/mylogfile.2020-01-02--10-05-52.log mylogfile
#> 5      /tmp/RtmpTB9vY3/rotor/mylogfile.20200102T100552.log mylogfile
#> 3           /tmp/RtmpTB9vY3/rotor/mylogfile.2020-01-02.log mylogfile
#> 4              /tmp/RtmpTB9vY3/rotor/mylogfile.2020-01.log mylogfile
#>                    sfx ext size isdir mode               mtime
#> 1  2020-01-02_10-05-52 log   26 FALSE  664 2020-01-02 10:05:52
#> 2 2020-01-02--10-05-52 log   26 FALSE  664 2020-01-02 10:05:52
#> 5      20200102T100552 log   26 FALSE  664 2020-01-02 10:05:52
#> 3           2020-01-02 log   26 FALSE  664 2020-01-02 10:05:52
#> 4              2020-01 log   26 FALSE  664 2020-01-02 10:05:52
#>                 ctime               atime  uid  gid uname grname
#> 1 2020-01-02 10:05:52 2020-01-02 10:05:52 1032 1032 fleck  fleck
#> 2 2020-01-02 10:05:52 2020-01-02 10:05:52 1032 1032 fleck  fleck
#> 5 2020-01-02 10:05:52 2020-01-02 10:05:52 1032 1032 fleck  fleck
#> 3 2020-01-02 10:05:52 2020-01-02 10:05:52 1032 1032 fleck  fleck
#> 4 2020-01-02 10:05:52 2020-01-02 10:05:52 1032 1032 fleck  fleck
#>             timestamp
#> 1 2020-01-02 10:05:52
#> 2 2020-01-02 10:05:52
#> 5 2020-01-02 10:05:52
#> 3 2020-01-02 00:00:00
#> 4 2020-01-01 00:00:00

If we examine the “timestamp” column in the example above, we see that missing date information is always interpreted as the start of the period; i.e. so "2019-01" is equivalent to "2019-01-01--00--00--00" for all intents and purposes.

prune_backups(tf, max_backups = 0)  # cleanup
#> character(0)

Besides passing a total number of backups to keep, max_backups can also be a period or a date / datetime for timestamped backups.


rotor’s dependencies are intentionally kept slim. It only comes with two non-base dependencies:

  • R6: A light weight system for encapsulated object-oriented programming.
  • dint: A toolkit for working year-quarter and year-month dates that I am also the author of. It is used by rotate_date() and rotate_time() to deal with calendar periods (such as weeks or months).

Both packages have no transitive dependencies (i.e they do not depend on anything outside of base R)