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https://github.com/ryapric/loggit

Modern Logging for the R Ecosystem
https://github.com/ryapric/loggit

exception-handler logging r

Last synced: about 2 months ago
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Modern Logging for the R Ecosystem

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README 

        
---

title: "README"

output:

  md_document:

    variant: gfm

vignette: >

  %\VignetteIndexEntry{README}

  %\VignetteEngine{knitr::rmarkdown}

  %\VignetteEncoding{UTF-8}

---



```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>"

)

```



Modern Logging for the R Ecosystem

==================================

Ryan Price 



[![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/loggit)](https://cran.r-project.org/package=loggit)

[![R-CMD-check](https://github.com/ryapric/loggit/workflows/R-CMD-check/badge.svg)](https://github.com/ryapric/loggit/actions)

[![Monthly downloads](https://cranlogs.r-pkg.org/badges/loggit)](https://cran.r-project.org/package=loggit)

[![Support me on Ko-Fi](https://img.shields.io/badge/Ko--fi-F16061?style=for-the-badge&logo=ko-fi&logoColor=white)](https://ko-fi.com/ryapric)



------------------------------------------------------------------------



`loggit` is an [`ndJSON`](https://github.com/ndjson/ndjson-spec) logging library

for R software. It is blazingly fast when writing logs, and has _zero_ external

dependencies. `loggit` can be as simple and unobstrusive as you'd like, or as

involved as your application needs it to be.



Please see below for some quick examples, and [read the

vignettes](https://cran.r-project.org/web/packages/loggit/vignettes/) for the

Getting Started guide, as well as some other use case examples.



Why use `loggit`?

-----------------



There are indeed several logging packages available for R. `loggit`, however,

takes a more modern approach approach to logging in R:



- Opting to use the JSON format, which is parsable by most modern software

- Designed with log streams in mind

- Unobtrusive, yet highly flexible

- Convenient ability to log data, then analyze that log data on the same host.



Additionally, the boilerplate to get going with `loggit` is minimal at worst,

only requiring you to point to the log file. If deploying your R code in a

container ecosystem, you don't even need to do that, since `loggit` will

echo its formatted logs to `stdout`. No need to write custom formatters,

handlers, levels, etc. -- ***just f&ck#n' loggit!***



Quick Examples

--------------



The quickest way to get up & running with `loggit` is to... do nothing special.

`loggit`'s simplest functionality does its best to stay out of your way. You'll

probably want to point it to a log file, though; otherwise, logs will print to

the console, but land in a tempfile.



```{r handlers}

library(loggit)

# set_logfile("./loggit.log")



message("This is a message")

warning("This is a warning")

# stop("This actually throws a critical error, so I'm not actually going to run it here :)"))

#> {"timestamp": "2020-05-31T20:59:33-0500", "log_lvl": "ERROR", "log_msg": "This actually throws a critical error, so I'm not actually going to run it here :)"}



```



You can suppress each part of the console output separately (both the `loggit`

ndJSON and the regular R output) but the default is to post both. Only the

ndJSON is written to the log file.



You can also use the `loggit()` function directly to compose much more custom

logs, including ***entirely custom fields*** (and prevent throwing actual status

codes until you wish to handle them). `loggit` doesn't require that you set

custom logger objects or anything like that: just throw whatever you want at it,

and it'll become a structured log.



```{r loggit}

loggit("ERROR", "This will log an error - but not actually throw one yet", rows = nrow(iris), anything_else = "you want to include")



# Read log file into data frame to implement logic based on entries

logdata <- read_logs()

print(logdata)

if (any(logdata$log_lvl == "ERROR")) {

  print("Errors detected somewhere in your code!") # but you can throw a stop() here, too, for example

}

```



Again, [check out the

vignettes](https://cran.r-project.org/web/packages/loggit/vignettes/) for more

details!



Installation

------------



You can install the latest CRAN release of `loggit` via

`install.packages("loggit")`.



Or, to get the latest development version from GitHub --



Via [devtools](https://github.com/hadley/devtools):



    devtools::install_github("ryapric/loggit")



Or, clone & build from source:



    cd /path/to/your/repos

    git clone https://github.com/ryapric/loggit.git loggit

    make install



To use the most recent development version of `loggit` in your own package, you

can include it in your `Remotes:` field in your DESCRIPTION file:



    Remotes: github::ryapric/loggit



Note that packages being submitted to CRAN *cannot* have a `Remotes` field.

Refer

[here](https://cran.r-project.org/web/packages/devtools/vignettes/dependencies.html)

for more info.



License

-------



MIT