Dockerize The Resolved Result

This function exports the result from resolve() to a Docker file. For R version >= 3.1.0, the Dockerfile is based on the versioned Rocker image. For R version < 3.1.0, the Dockerfile is based on Debian and it compiles R from source.

Usage

dockerize(
  rang,
  output_dir,
  materials_dir = NULL,
  post_installation_steps = NULL,
  image = c("r-ver", "rstudio", "tidyverse", "verse", "geospatial"),
  rang_as_comment = TRUE,
  cache = FALSE,
  verbose = TRUE,
  lib = NA,
  cran_mirror = "https://cran.r-project.org/",
  check_cran_mirror = TRUE,
  bioc_mirror = "https://bioconductor.org/packages/",
  no_rocker = FALSE,
  debian_version = c("lenny", "squeeze", "wheezy", "jessie", "stretch"),
  skip_r17 = TRUE,
  insert_readme = TRUE,
  copy_all = FALSE,
  method = c("auto", "evercran", "rocker", "debian")
)

dockerize_rang(...)

dockerise(...)

dockerise_rang(...)

Arguments

rang: output from resolve()
output_dir: character, where to put the Docker file and associated content
materials_dir: character, path to the directory containing additional resources (e.g. analysis scripts) to be copied into output_dir and in turn into the Docker container
post_installation_steps: character, additional steps to be added before the CMD part of the Dockerfile, see an example below
image: character, which versioned Rocker image to use. Can only be "r-ver", "rstudio", "tidyverse", "verse", "geospatial" This applies only to R version >= 3.1
rang_as_comment: logical, whether to write resolved result and the steps to reproduce the file to path as comment
cache: logical, whether to cache the packages now. Please note that the system requirements are not cached. For query with non-CRAN packages, this option is strongly recommended. For query with local packages, this must be TRUE regardless of R version. For R version < 3.1, this must be also TRUE if there is any non-CRAN packages.
verbose: logical, pass to install.packages(), the negated value is also passed as quiet to both install.packages() and download.file().
lib: character, pass to install.packages(). By default, it is NA (to install the packages to the default location)
cran_mirror: character, which CRAN mirror to use
check_cran_mirror: logical, whether to check the CRAN mirror
bioc_mirror: character, which Bioconductor mirror to use
no_rocker: logical, whether to skip using Rocker images even when an appropriate version is available. Please keep this as FALSE unless you know what you are doing
debian_version: when Rocker images are not used, which EOL version of Debian to use. Can only be "lenny", "etch", "squeeze", "wheezy", "jessie", "stretch". Please keep this as default "lenny" unless you know what you are doing
skip_r17: logical, whether to skip R 1.7.x. Currently, it is not possible to compile R 1.7.x (R 1.7.0 and R 1.7.1) with the method provided by rang. It affects snapshot_date from 2003-04-16 to 2003-10-07. When skip_r17 is TRUE and snapshot_date is within the aforementioned range, R 1.8.0 is used instead
insert_readme: logical, whether to insert a README file
copy_all: logical, whether to copy everything in the current directory into the container. If inst/rang is detected in output_dir, this is coerced to TRUE.
method: character, can only be "auto", "evercran", "rocker", or "debian". Select which base image is used. "auto" (the default) selects the best option based on the R version. "evercran" is experimental.
...: arguments to be passed to dockerize

Value

output_dir, invisibly

Details

The idea behind this is to determine the installation order of R packages locally. Then, the installation script can be deployed to another fresh R session to install R packages. dockerize() and apptainerize() are more reasonable ways because a fresh R session with all system requirements is provided.

References

The Rocker Project Ripley, B. (2005) Packages and their Management in R 2.1.0. R News, 5(1):8--11.

Examples

# \donttest{
if (interactive()) {
    graph <- resolve(pkgs = c("openNLP", "LDAvis", "topicmodels", "quanteda"),
                    snapshot_date = "2020-01-16")
    dockerize(graph, ".")
    ## An example of using post_installation_steps to install quarto
    install_quarto <- c("RUN apt-get install -y curl git && \\
    curl -LO https://quarto.org/download/latest/quarto-linux-amd64.deb && \\
    dpkg -i quarto-linux-amd64.deb && \\
    quarto install tool tinytex")
    dockerize(graph, ".", post_installation_steps = install_quarto)
}
# }