README

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log4r

log4r is a fast, lightweight, object-oriented approach to logging in R based on the widely-emulated Apache Log4j project.

log4r differs from other R logging packages in its focus on performance and simplicity. As such, it has fewer features – although it is still quite extensible, as seen below – but is much faster. See vignette("performance", package = "log4r") for details.

Unlike other R logging packages, log4r also has first-class support for structured logging. See vignette("structured-logging", package = "log4r") for details.

Installation

install.packages("log4r")

If you want to use the development version, you can install the package from GitHub as follows:

# install.packages("remotes")
remotes::install_github("johnmyleswhite/log4r")

Usage

Logging is configured by passing around logger objects created by logger(). By default, this will log to the console and suppress messages below the "INFO" level:

logger <- logger()

info(logger, "Located nearest gas station.")
#> INFO  [2019-09-04 16:31:04] Located nearest gas station.
warn(logger, "Ez-Gas sensor network is not available.")
#> WARN  [2019-09-04 16:31:04] Ez-Gas sensor network is not available.
debug(logger, "Debug messages are suppressed by default.")

Logging destinations are controlled by Appenders, a few of which are provided by the package. For instance, if we want to debug-level messages to a file:

log_file <- tempfile()
logger <- logger("DEBUG", appenders = file_appender(log_file))

info(logger, "Messages are now written to the file instead.")
debug(logger, "Debug messages are now visible.")

readLines(log_file)
#> [1] "INFO  [2019-09-04 16:31:04] Messages are now written to the file instead."
#> [2] "DEBUG [2019-09-04 16:31:04] Debug messages are now visible."

The appenders parameter takes a list, so you can log to multiple destinations transparently.

For local development or simple batch R scripts run manually, writing log messages to a file for later inspection is convenient. However, for deployed R applications or automated scripts it is more likely you will need to send logs to a central location; see vignette("logging-beyond-local-files", package = "log4r").

To control the format of the messages you can change the Layout used by each appender. Layouts are functions; you can write your own quite easily:

my_layout <- function(level, ...) {
  paste0(format(Sys.time()), " [", level, "] ", ..., collapse = "")
}

logger <- logger(appenders = console_appender(my_layout))
info(logger, "Messages should now look a little different.")
#> 2019-09-04 16:31:04 [INFO] Messages should now look a little different.

With an appropriate layout, you can also use structured logging, enriching log messages with contextual fields:

logger <- logger(appenders = console_appender(logfmt_log_layout()))
info(
  logger, message = "processed entries", file = "catpics_01.csv",
  entries = 4124, elapsed = 2.311
)
#> level=INFO ts=2021-10-22T20:19:21Z message="processed entries" file=catpics_01.csv entries=4124 elapsed=2.311

Older APIs

logger <- create.logger()

logfile(logger) <- log_file
level(logger) <- "INFO"

debug(logger, 'A Debugging Message')
info(logger, 'An Info Message')
warn(logger, 'A Warning Message')
error(logger, 'An Error Message')
fatal(logger, 'A Fatal Error Message')

readLines(log_file)
#> [1] "INFO  [2019-09-04 16:31:05] An Info Message"      
#> [2] "WARN  [2019-09-04 16:31:05] A Warning Message"    
#> [3] "ERROR [2019-09-04 16:31:05] An Error Message"     
#> [4] "FATAL [2019-09-04 16:31:05] A Fatal Error Message"

License

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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