R pkg dev
devtools::check() |
build and check the pkg |
Cmd + Shift + E |
devtools::load_all() |
load the pkg |
Cmd + Shift + L |
devtools::document() |
document the pkg |
Cmd + Shift + D |
pak::local_install(upgrade = FALSE) |
install the pkg into the first library of .libPaths()
|
Cmd + Shift + B |
conda
conda install foo -c bar |
install pkg foo from channel bar
|
conda create --file env.yml --prefix ./bar |
install conda pkgs listed in env.yml into the ./bar directory |
conda info -e |
list conda environments installed on this machine |
rattler-build build -r recipe.yaml --output-dir ${HOME}/tmp |
build conda pkg from a recipe file |
rattler-build upload anaconda -o umccr --api-key <xxx> ${HOME}/tmp/r-tidywigits.conda |
upload conda pkg to anaconda |
pkgdown
pkgdown::build_site() |
builds entire site |
pkgdown::build_articles(quiet = FALSE) |
builds vignettes in debug mode |
pkgdown::build_article("developers") |
builds developers vignette only |
Data Version Control
Instead of committing big data files into git, we can store the files remotely (e.g. Google Drive, AWS S3, Cloudflare R2) and just keep track of the data updates in git using DVC.
The R package uses the data files when running the code examples and tests, and when rendering the vignettes. A simple dvc pull will pull the data from the remote storage and allow these processes to take place.
dvc init |
initialise dvc |
dvc remote add -d storage gdrive://<...> |
add GDrive remote |
dvc remote add -d my_r2 s3://<...> |
add Cloudflare R2 remote |
dvc remote modify my_r2 endpointurl https://<...>.r2.cloudflarestorage.com |
add Cloudflare R2 remote endpointurl |
dvc remote list |
list all remotes |
dvc check-ignore * |
check what is dvc-ignored |
dvc list https://github.com/umccr/tidywigits inst/extdata |
list dvc’ed data |
dvc add path/to/folder |
adds folder (and its contents) to dvc |
dvc add path/to/file.txt |
adds file.txt to dvc |
dvc push |
pushes dvc data to remote |
dvc pull |
pulls dvc data from remote |
