---

output: github_document

knitr::opts_chunk$set(
  eval = FALSE,
  collapse = TRUE,
  message = FALSE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

piggyback

piggyback provides an R interface for storing files as GitHub release assets,
which is a convenient way for large/binary data files to piggyback onto public
and private GitHub repositories. This package includes functions for file downloads,
uploads, and managing releases, which then are passed to the GitHub API.

No authentication is required to download data from public repositories.

Installation

Install from CRAN via:

install.packages("piggyback")

You can install the development version from GitHub
with either r-universe or with remotes:

install.packages("piggyback", repos = c('https://ropensci.r-universe.dev', getOption("repos")))
# install.packages("remotes")
remotes::install_github("ropensci/piggyback")

Usage

See getting started vignette
for a more comprehensive introduction.

Download data attached to a GitHub release:

library(piggyback)
pb_download("iris2.tsv.gz", 
            repo = "cboettig/piggyback-tests",
            tag = "v0.0.1",
            dest = tempdir())
#> ℹ Downloading "iris2.tsv.gz"...
#> |======================================================| 100%
fs::dir_tree(tempdir())
#> /tmp/RtmpWxJSZj
#> └── iris2.tsv.gz

Downloading from private repos or uploading to any repo requires authentication,
specifically a GitHub Personal Access Token (PAT). This can be stored as a
gh::gh_token()
or a GITHUB_PAT environment variable - for more information, see the vignette notes on
authentication.

We can also upload data to a release. Start by creating a release:

pb_release_create(repo = "cboettig/piggyback-tests", tag = "v0.0.2")
#> ✔ Created new release "v0.0.2".

then upload to it:

readr::write_tsv(mtcars, "mtcars.tsv.gz")
pb_upload("mtcars.tsv.gz", repo = "cboettig/piggyback-tests")
#> ℹ Uploading to latest release: "v0.0.2".
#> ℹ Uploading mtcars.tsv.gz ...
#> |===================================================| 100%

For improved performance, we can also use piggyback files with
cloud native
workflows to query data without downloading it first.

Motivations

A brief video overview presented as part of Tan Ho’s RStudioConf2022 talk:

https://github.com/ropensci/piggyback/assets/38083823/a1dff640-1bba-4c06-bad2-feda34f47387

piggyback allows you to store data alongside your repository as release assets,
which helps you:

• store files larger than 50MB
• bypass the 2GB GitHub repo size limit

• avoid the downsides of Git LFS
• version data flexibly (by creating/uploading to a new release)
• work with public and private repositories, for free

For more about motivations, see this discussion of
alternatives.

Contributing

Please note that this project is released with a
Contributor Code of Conduct.
By participating in this project you agree to abide by its terms.

codemeta::write_codemeta()