Littler Examples

We show and discuss a few of the files included in the inst/examples/ source directory of littler (which becomes the examples/ directory once installed). In a few cases we remove comment lines to keep things more concise on this page. We use $ to denote a shell (i.e. terminal) prompt.

Note that some systems (such as macOS) cannot install littler as r (as lower-case and upper-case are by default the same; not a great idea). And for example the zsh has r as a builtin so you would have to use /usr/bin/r. See the littler FAQ for more.

Simple Direct Command-line Use

littler can be used directly on the command-line just like, say, bc, easily consuming standard input from a pipe:

$ echo 'cat(pi^2,"\n")' | r
9.869604

Equivalently, commands that are to be evaluated can be given on the command-line

$ r -e 'cat(pi^2, "\n")'
9.869604

But unlike bc(1), GNU R has a vast number of statistical functions. For example, we can quickly compute a summary() and show a stem-and-leaf plot for file sizes in a given directory via

$ ls -l /boot | awk 'BEGIN {print "size"} !/^total/ {print $5}' | \
     r -de "print(summary(X[,1])); stem(X[,1])"

(Note that some systems may not have /boot in which case you can try /sbin or another directory.)

As we saw in the preceding example, the program can also be shortened like using the new -d option which reads from stdin and assigns to a data.frame named X.

And, last but not least, this (somewhat unwieldy) expression can be stored in a helper script (where we now switch to using an explicit readLines() on stdin):

#!/usr/bin/env r

fsizes <- as.integer(readLines(file("stdin")))
print(summary(fsizes))
stem(fsizes)

(where calling #!/usr/bin/env is a trick from Python which allows one to forget whether r is installed in /usr/bin/r, /usr/local/bin/r, ~/bin/r, …).

install.r: Direct CRAN Installation

This is one of my favourite littler scripts which I use frequently to install packages off CRAN.

#!/usr/bin/env r

if (is.null(argv) | length(argv)<1) {
  cat("Usage: installr.r pkg1 [pkg2 pkg3 ...]\n")
  q()
}

## adjust as necessary, see help('download.packages')
repos <- "https://cran.rstudio.com" 

## this makes sense on Debian where no packages touch /usr/local
lib.loc <- "/usr/local/lib/R/site-library"

install.packages(argv, lib.loc, repos)

I invoke it all the time with one, two or more packages to install (or reinstall).

$ install.r digest RcppCNPy

It conveniently installs all dependencies, and uses the chosen target directory, all while keeping my R prompt (or prompts with multiple sessions) free to do other things. Also, if used with options("Ncpu") set, then (remote CRAN) packages will be installed in parallel.

install2.r: With Cmdline Parsing

Thanks to the fabulous docopt package, we also have a variant install2.r with optional settings of repo and location. It was first installed with littler 0.2.1. The current (i.e., 0.3.3 as of this writing) version is more featureful and longer and included to keep this brief. Some usage examples are

$ install2.r -l /tmp/lib Rcpp BH                         # install into given library
$ install2.r -- --with-keep.source drat                  # keep the source
$ install2.r -- --data-compress=bzip2 stringdist         # prefer bz2 compression

Another very useful option is -n N or --ncpus N which will parallelize the installation across N processes. This can be set automagically by setting options("Ncpus").

Installing From Sources

Starting with version 0.2.2, install.r and install2.r now recognise installable source files. So one can also do this:

$ install.r digest_0.6.8.tar.gz

check.r: Simple Checker

A related use case is to check packages via check.r. This script runs R CMD check, but also installs package dependencies first as tests may have dependencies not yet satisfied on the test machine. It offers a number of options:

$ check.r  -h
Usage: check.r [-h] [-x] [--as-cran] [--repo REPO] [--install-deps] [--install-kitchen] [--deb-pkgs PKGS...] [--use-sudo] [--library LIB] [--setwd DIR] [TARGZ ...]

-a --as-cran          customization similar to CRAN's incoming [default: FALSE]
-r --repo REPO        repository to use, or NULL for file [default: https://cran.rstudio.com]
-i --install-deps     also install packages along with their dependencies [default: FALSE]
-k --install-kitchen  even install packages 'kitchen sink'-style up to suggests [default: FALSE]
-l --library LIB      when installing use this library [default: /usr/local/lib/R/site-library]
-s --setwd DIR        change to this directoru before undertaking the test [default: ]
-d --deb-pkgs PKGS    also install binary .deb packages with their dependencies [default: FALSE]
-u --use-sudo         use sudo when installing .deb packages [default: TRUE]
-h --help             show this help text
-x --usage            show help and short example usage
$

rcc.r: R CMD check wrapper

The script rcc.r will also check a source tarball, and offers another set of options:

$ rcc.r -h
Usage: rcc.r [-h] [-x] [-c] [-f] [-q] [--args ARGS] [--libpath LIBP] [--repos REPO] [PATH...]

-c --as-cran          should '--as-cran' be added to ARGS [default: FALSE]
-a --args ARGS        additional arguments to be passed to 'R CMD CHECK' [default: ]
-l --libpath LIBP     additional library path to be used by 'R CMD CHECK' [default: ]
-r --repos REPO       additional repositories to be used by 'R CMD CHECK' [default: ]
-f --fast             should vignettes and manuals be skipped [default: FALSE]
-q --quiet            should 'rcmdcheck' be called qietly [default: FALSE]
-h --help             show this help text
-x --usage            show help and short example usage
$

build.r: Building Packages

A related script is build.r which I often use inside a source repository to quickly build a source tarball. Like rcc.r, it has a switch -f or --fast to omit building of vignettes.

$ build.r            # without argument works on current directory
$ build.r digest/    # with directory argument builds tar.gz from repo in directory

installGithub.r: GitHub install

$ installGithub.r RcppCore/RcppEigen

#!/usr/bin/env r
#
# A simple example to install one or more packages from GitHub
#
# Copyright (C) 2014 - 2015  Carl Boettiger and Dirk Eddelbuettel
#
# Released under GPL (>= 2)

## load docopt and remotes (or devtools) from CRAN
suppressMessages(library(docopt))       # we need docopt (>= 0.3) as on CRAN
suppressMessages(library(remotes))      # can use devtools as a fallback

## configuration for docopt
doc <- "Usage: installGithub.r [-h] [-d DEPS] REPOS...

-d --deps DEPS      Install suggested dependencies as well? [default: NA]
-h --help           show this help text

where REPOS... is one or more GitHub repositories.

Examples:
  installGithub.r RcppCore/RcppEigen                     

installGithub.r is part of littler which brings 'r' to the command-line.
See http://dirk.eddelbuettel.com/code/littler.html for more information.
"

## docopt parsing
opt <- docopt(doc)
if (opt$deps == "TRUE" || opt$deps == "FALSE") {
    opt$deps <- as.logical(opt$deps)
} else if (opt$deps == "NA") {
    opt$deps <- NA
}

invisible(sapply(opt$REPOS, function(r) install_github(r, dependencies = opt$deps)))

update.r: CRAN package update

One of the scripts I use the most (interactively) is update.r which updates installed packages. An earlier version looked like the following example, the current version is a little longer and has more features:

#!/usr/bin/env r 
#
# a simple example to update packages in /usr/local/lib/R/site-library
# parameters are easily adjustable

## adjust as necessary, see help('download.packages')
repos <- "https://cloud.r-project.org" 

## this makes sense on Debian where no package touch /usr/local
lib.loc <- "/usr/local/lib/R/site-library"

## r use requires non-interactive use
update.packages(repos=repos, ask=FALSE, lib.loc=lib.loc)

Another very useful option is -n N or --ncpus N which will parallelize the upgrade across N processes. This can be set automagically by setting options(Ncpus).

knit.r: Calling knitr

Here is another convenience script, knit.r, which knits a given file after testing the file actually exists.

#!/usr/bin/r
#
# Simple helper script for knitr
#
# Dirk Eddelbuettel, May 2013
#
# GPL-2 or later

if (is.null(argv)) {
    cat("Need an argument FILE.Rnw\n")
    q(status=-1)
}


file <- argv[1]
if (!file.exists(file)) {
    cat("File not found: ", file, "\n")
    q(status=-1)
}

require(knitr)
knit2pdf(file)

roxy.r: Running roxygen

Similar to the previous example, the script roxy.r one uses roxygen to extract documentation from R files – either in the current directory, or in the given directory or directories.

#!/usr/bin/r
#
# Simple helper script for roxygen2::roxygenize() 
#
# Dirk Eddelbuettel, August 2013
#
# GPL-2 or later

## load roxygen
library(roxygen2)

## check all command-line arguments (if any are given) for directory status
argv <- Filter(function(x) file.info(x)$is.dir, argv)

## loop over all argument, with fallback of the current directory, and
## call compileAttributes() on the given directory
sapply(ifelse(length(argv) > 0, argv, "."), FUN=roxygenize, roclets="rd")

compAttr.r: Compiling Attributes

The next script, compAttr., can be used with Rcpp, and particularly is powerful Attributes feature, in order to auto-generate helper code. It is similar to the preceding script, but invokes compileAttributes() instead.

#!/usr/bin/r
#
# Simple helper script for compileAttributes() 
#
# Dirk Eddelbuettel, July 2014
#
# GPL-2 or later

## load Rcpp
suppressMessages(library(Rcpp))

## check all command-line arguments (if any are given) for directory status
argv <- Filter(function(x) file.info(x)$is.dir, argv)

## loop over all argument, with fallback of the current directory, and
## call compileAttributes() on the given directory
sapply(ifelse(length(argv) > 0, argv, "."), compileAttributes)

render.r: Render Markdown

The render.r script generalizes the earlier knit.r to convert Markdown into its designated output.

#!/usr/bin/env r
#
# Another example to run a shiny app
#
# Copyright (C) 2016  Dirk Eddelbuettel
#
# Released under GPL (>= 2)

suppressMessages(library(docopt))       # we need docopt (>= 0.3) as on CRAN

## configuration for docopt
doc <- "Usage: render.r [-h] [-x] [FILES...]

-h --help            show this help text
-x --usage           show help and short example usage"

opt <- docopt(doc)          # docopt parsing

if (opt$usage) {
    cat(doc, "\n\n")
    cat("Examples:
  render.r foo.Rmd bar.Rmd        # convert two given files

render.r is part of littler which brings 'r' to the command-line.
See http://dirk.eddelbuettel.com/code/littler.html for more information.\n")
    q("no")
}

library(rmarkdown)

## helper function 
renderArg <- function(p) {
    if (!file.exists(p)) stop("No file '", p, "' found. Aborting.", call.=FALSE)
    render(p)
}

## render files using helper function 
sapply(opt$FILES, renderArg)

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