backup_info: Discover existing backups

Description

These function return information on the backups of a file (if any exist)

Usage

backup_info(file, dir = dirname(file))
list_backups(file, dir = dirname(file))
n_backups(file, dir = dirname(file))
newest_backup(file, dir = dirname(file))
oldest_backup(file, dir = dirname(file))

Arguments

file

character scalar: Path to a file.

dir

character scalar. The directory in which the backups of file are stored (defaults to dirname(file))

Value

backup_info() returns a data.frame similar to the output of file.info()

list_backups() returns the paths to all backups of file

n_backups() returns the number of backups of file as an integer scalar

newest_backup() and oldest_backup() return the paths to the newest or oldest backup of file (or an empty character vector if none exist)

Intervals

In rotor, an interval is a character string in the form "<number> <interval>". The following intervals are possible: "day(s)", "week(s)", "month(s)", "quarter(s)", "year(s)". The plural "s" is optional (so "2 weeks" and "2 week" are equivalent). Please be aware that weeks are ISOweeks and start on Monday (not Sunday as in some countries).

Interval strings can be used as arguments when backing up or rotating files, or for pruning backup queues (i.e. limiting the number of backups of a single) file.

When rotating/backing up "1 months" means "make a new backup if the last backup is from the preceding month". E.g if the last backup of myfile is from 2019-02-01 then backup_time(myfile, age = "1 month") will only create a backup if the current date is at least 2019-03-01.

When pruning/limiting backup queues, "1 year" means "keep at least most one year worth of backups". So if you call backup_time(myfile, max_backups = "1 year") on 2019-03-01, it will create a backup and then remove all backups of myfile before 2019-01-01.

Examples

Run this code

# NOT RUN {
# setup example files
tf <- tempfile("test", fileext = ".rds")
saveRDS(cars, tf)
backup(tf)
backup(tf)

backup_info(tf)
list_backups(tf)
n_backups(tf)
newest_backup(tf)
oldest_backup(tf)

# cleanup
prune_backups(tf, 0)
n_backups(tf)
file.remove(tf)
# }