This package is considered a duplicate. The official version of this package is found at:https://gesistsa.r-universe.dev/rang

Package: rang 0.3.0

Chung-hong Chan

rang: Reconstructing Reproducible R Computational Environments

Resolve the dependency graph of R packages at a specific time point based on the information from various 'R-hub' web services <https://blog.r-hub.io/>. The dependency graph can then be used to reconstruct the R computational environment with 'Rocker' <https://rocker-project.org>.

Authors:Chung-hong Chan [aut, cre], David Schoch [aut], Egor Kotov [ctb]

rang_0.3.0.tar.gz
rang_0.3.0.zip(r-4.7)rang_0.3.0.zip(r-4.6)rang_0.3.0.zip(r-4.5)
rang_0.3.0.tgz(r-4.6-any)rang_0.3.0.tgz(r-4.5-any)
rang_0.3.0.tar.gz(r-4.7-any)rang_0.3.0.tar.gz(r-4.6-any)
rang_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rang/json (API)

# Install 'rang' in R:

install.packages('rang', repos = c('https://e-kotov.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gesistsa/rang/issues

Pkgdown/docs site:https://gesistsa.github.io

Datasets:

recipes - Recipes for Building Container Images

On CRAN:

reproducibility reproducible-research

7.28 score 80 stars 16 scripts 212 downloads 21 exports 22 dependencies

Last updated from:0a4e273caf. Checks:9 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	OK	137
source / vignettes	OK	218
linux-release-x86_64	OK	183
macos-release-arm64	OK	109
macos-oldrel-arm64	OK	220
windows-devel	OK	90
windows-release	OK	96
windows-oldrel	OK	289
wasm-release	OK	109

Exports:apptainerise apptainerise_rang apptainerize apptainerize_rang as_pkgrefs convert_edgelist create_turing dockerise dockerise_rang dockerize dockerize_rang export_rang export_renv generate_installation_order query_sysreqs resolve singularise singularise_rang singularize singularize_rang use_rang

Dependencies:askpass cachem cli curl fastmap glue here httr jsonlite lifecycle memoise mime openssl parsedate pkgsearch R6 remotes renv rlang rprojroot sys vctrs

Create research compendia

Case 1: Create a Turing-style research compendium | Other ideas | Case 2: Enhance an existing research compendium | What to share?

Rendered fromcompendium.Rmdusingknitr::rmarkdown

Last update: 2023-10-08
Started: 2023-10-08

FAQ

General questions | Docker questions | Apptainer/Singularity questions

Rendered fromfaq.Rmdusingknitr::rmarkdown

Last update: 2023-04-18
Started: 2023-02-15

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Create an Apptainer/Singularity Definition File of The Resolved Result	apptainerise apptainerise_rang apptainerize apptainerize_rang singularise singularise_rang singularize singularize_rang
Convert Data Structures into Package References	as_pkgrefs as_pkgrefs.character as_pkgrefs.default as_pkgrefs.sessionInfo
Convert Data Structures to rang edgelist	convert_edgelist convert_edgelist.default convert_edgelist.rang convert_edgelist.ranglet
Create executable research compendium according to the Turing Way	create_turing
Dockerize The Resolved Result	dockerise dockerise_rang dockerize dockerize_rang
Export The Resolved Result As Installation Script	export_rang
Export The Resolved Result As a renv Lockfile	export_renv
Create a Data Frame of The Resolved Result This function exports the results from 'resolve()' to a data frame, which each row represents one installation step. The order of rows is the installation order. By installing packages in the specified order, one can install all the resolved packages without conflicts.	generate_installation_order
Query for System Requirements	query_sysreqs
Recipes for Building Container Images	recipes
Resolve Dependencies Of R Packages	resolve
Setup rang for a directory	use_rang