rlog is an opinionated, lightweight logging package for R.
It relies on long standing Unix traditions, to write simple log messages in a flexible way.
Log message output looks like this:
2021-02-21 17:19:06 [INFO] This is my log message
Install rlog from GitHub with the following:
::install_github("sellorm/rlog") devtools
We think so, yes!
There are already loads of logging packages for R. Many are no longer maintained and of the remaining selection some are overly complex, making them less approachable for beginners.
Since logging should be an essential part of any production application or pipeline I think it’s important that as many people as possible are introduced to good logging practice.
If rlog doesn’t have enough features for you, I’d recommend the excellent “logger” instead.
The rlog philosophy is the Unix philosophy and as such, we expect applications using rlog to be able to integrate with other enterprise software quickly and efficiently.
rlog is simple by design and it relies on existing Unix/Linux norms to get the job done.
The best way to use rlag is to call the functions directly from within your applications.
There is one function per log message level:
::log_fatal("my fatal message")
rlog::log_error("my error message")
rlog::log_warn("my warn message")
rlog::log_info("my info message")
rlog::log_debug("my debug message")
rlog::log_trace("my trace message") rlog
If you run this code as-is without setting a custom
LOG_LEVEL
with the environment variable, you’ll get output
like this:
2021-02-21 17:19:06 [FATAL] fatal
2021-02-21 17:19:06 [ERROR] error
2021-02-21 17:19:06 [WARN] warn
2021-02-21 17:19:06 [INFO] info
The “DEBUG” and “TRACE” message won’t be printed, since the default
LOG_LEVEL
is “INFO” and those message have lower
priority.
Play around with setting the LOG_LEVEL
directly in R and
seeing what messages are emitted:
Sys.setenv("LOG_LEVEL" = "ERROR")
::log_fatal("my fatal message")
rlog::log_error("my error message")
rlog::log_warn("my warn message")
rlog::log_info("my info message")
rlog::log_debug("my debug message")
rlog::log_trace("my trace message") rlog
Gives us this output:
2021-02-21 17:19:06 [FATAL] fatal
2021-02-21 17:19:06 [ERROR] error
Remember though, the best way to set the environment variable is outside of the app. That way it’s easier to change at run-time.
So in your terminal you can do something like this before you run your script:
$ export LOG_LEVEL=TRACE
$ ./my_script.R
Or you can even call your script with the appropriate value at run-time:
$ LOG_LEVEL=ERROR ./my_script.R
If you’re using RStudio Connect users can set an environment variable
called LOG_LEVEL
in the “Vars” tab of their apps control
panel.
rlog relies on an environment variable called LOG_LEVEL
to control which log messages are emitted.
If it’s not set, it will default to “INFO”.
The available levels – in decreasing order of severity – are as follows:
When the LOG_LEVEL
environment variable is set to
“INFO”, only messages at that level and above will be emitted.
Another example:
This is a really powerful way of only including the messages you want
to see in the log files at any given time. For example, you may choose
to set the LOG_LEVEL
to “TRACE” while developing your
application or if it runs into a problem in production, but you might
choose to run the application with a LOG_LEVEL
of “ERROR”
under normal circumstances.
rlog outputs it log messages into the console in the same way that most Unix/Linux tools do. Ordinary messages go to “standard output” (stdout) and errors go to “standard error” (stderr).
This means they can be captured in the standard Unix/Linux way:
./my_script.R > /path/to/file.log 2>&1
This command redirects stderr to stdout and drops it all into the
/path/to/file.log
file.
You can also keep the “normal” and error outputs separate:
./my_script.R > /path/to/file.log 2> /path/to/errors.log
Many enterprise software products, such as RStudio Connect will capture this output automatically and save it for you.