logger

A lightweight, modern and flexibly logging utility for R -- heavily inspired by the futile.logger R package and logging Python module.

Installation

install.packages('logger')

The most recent, development version of logger can also be installed from GitHub:

remotes::install_github('daroczig/logger')

Quick example

Setting the log level threshold to something low and logging various messages in ad-hoc and programmatic ways:

library(logger)
log_threshold(DEBUG)
log_info('Script starting up...')
#> INFO [2018-20-11 22:49:36] Script starting up...

pkgs <- available.packages()
log_info('There are {nrow(pkgs)} R packages hosted on CRAN!')
#> INFO [2018-20-11 22:49:37] There are 13433 R packages hosted on CRAN!

for (letter in letters) {
    lpkgs <- sum(grepl(letter, pkgs[, 'Package'], ignore.case = TRUE))
    log_level(if (lpkgs < 5000) TRACE else DEBUG,
              '{lpkgs} R packages including the {shQuote(letter)} letter')
}
#> DEBUG [2018-20-11 22:49:38] 6300 R packages including the 'a' letter
#> DEBUG [2018-20-11 22:49:38] 6772 R packages including the 'e' letter
#> DEBUG [2018-20-11 22:49:38] 5412 R packages including the 'i' letter
#> DEBUG [2018-20-11 22:49:38] 7014 R packages including the 'r' letter
#> DEBUG [2018-20-11 22:49:38] 6402 R packages including the 's' letter
#> DEBUG [2018-20-11 22:49:38] 5864 R packages including the 't' letter

log_warn('There might be many, like {1:2} or more warnings!!!')
#> WARN [2018-20-11 22:49:39] There might be many, like 1 or more warnings!!!
#> WARN [2018-20-11 22:49:39] There might be many, like 2 or more warnings!!!

Setting a custom log layout to render the log records with colors:

library(logger)
log_layout(layout_glue_colors)
log_threshold(TRACE)
log_info('Starting the script...')
log_debug('This is the second log line')
log_trace('Note that the 2nd line is being placed right after the 1st one.')
log_success('Doing pretty well so far!')
log_warn('But beware, as some errors might come :/')
log_error('This is a problem')
log_debug('Note that getting an error is usually bad')
log_error('This is another problem')
log_fatal('The last problem')

Or simply run the related demo:

demo(colors, package = 'logger', echo = FALSE)

But you could set up any custom colors and layout, eg using custom colors only for the log levels, make it grayscale, include the calling function or R package namespace with specific colors etc. For more details, see the related vignettes.

Why yet another logging R package?

Although there are multiple pretty good options already hosted on CRAN when it comes to logging in R, such as

• futile.logger: probably the most popular log4j variant (and I'm a big fan)
• logging: just like Python's logging package
• loggit: capture message, warning and stop function messages in a JSON file
• log4r: log4j-based, object-oriented logger
• rsyslog: logging to syslog on 'POSIX'-compatible operating systems
• lumberjack: provides a special operator to log changes in data

Also many more work-in-progress R packages hosted on eg GitHub, such as

• https://github.com/smbache/loggr
• https://github.com/nfultz/tron
• https://github.com/metrumresearchgroup/logrrr
• https://github.com/lorenzwalthert/drogger
• https://github.com/s-fleck/yog

But some/most of these packages are

• not actively maintained any more, and/or maintainers are not being open for new features / patches
• not being modular enough for extensions
• prone to scoping issues
• using strange syntax elements, eg dots in function names or object-oriented approaches not being very familiar to most R users
• requires a lot of typing and code repetitions

So based on all the above subjective opinions, I decided to write the n+1th extensible log4j logger that fits my liking -- and hopefully yours as well -- with the focus being on:

• keep it close to log4j
• respect the most recent function / variable naming conventions and general R coding style
• by default, rely on glue when it comes to formatting / rendering log messages, but keep it flexible if others prefer sprintf (eg for performance reasons) or other functions
• support vectorization (eg passing a vector to be logged on multiple lines)
• make it easy to extend with new features (eg custom layouts, message formats and output)
• prepare for writing to various services, streams etc
• provide support for namespaces, preferably automatically finding and creating a custom namespace for all R packages writing log messages, each with optionally configurable log level threshold, message and output formats
• allow stacking loggers to implement logger hierarchy -- even within a namespace, so that the very same log call can write all the TRACE log messages to the console, while only pushing ERRORs to DataDog and eg INFO messages to CloudWatch
• optionally colorize log message based on the log level
• make logging fun

Welcome to the Bazaar, and if you have happened to already use any of the above mentioned R packages for logging, you might find useful the Migration Guide.

Interested in more details?

Check out the main documentation site at https://daroczig.github.io/logger or the vignettes on the below topics:

• Introduction to logger
• The Anatomy of a Log Request
• Customizing the Format and the Destination of a Log Record
• Writing Custom Logger Extensions
• Migration Guide from other logging packages
• Logging from R Packages
• Simple Benchmarks on Performance