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Installation

Source: vignettes/installation.qmd

R

Using {remotes} directly from GitHub:

install.packages("remotes")
remotes::install_github("tidywf/tidydragen") # latest main commit
remotes::install_github("tidywf/tidydragen@v0.0.0.9001") # specific version

Conda

conda-versionconda-latest

The conda package is available from the tidywf channel at https://anaconda.org/tidywf/r-tidydragen.

conda create -n tidydragen_env -c tidywf -c conda-forge r-tidydragen==0.0.0.9001
conda activate tidydragen_env

Docker

ghcr-latestghcr-size

The Docker image is available from the GitHub Container Registry at https://github.com/tidywf/tidydragen/pkgs/container/tidydragen.

docker pull --platform linux/amd64 ghcr.io/tidywf/tidydragen:0.0.0.9001

Docker Compose

The repo ships a docker-compose.yaml that wraps the CLI: it mounts a local input directory (./in, read-only) and output directory (./out), then tidies the input to parquet. Place a pipeline output directory under ./in and run:

mkdir -p in out
docker compose run --rm tidydragen

Override defaults with environment variables (or a .env file): IMAGE_TAG (image tag, defaults to the pinned package version), IN_DIR, OUT_DIR, and FORMAT (parquet | tsv | csv | rds). The image’s ENTRYPOINT is tidydragen.R, so any flags after the service name append to it:

IN_DIR=/path/to/samples docker compose run --rm tidydragen tidy -d /data/in -o /data/out -f tsv

Pixi

If you use Pixi, you can create a new isolated environment with the deployed conda package:

pixi init -c tidywf -c conda-forge ./tidy_env
cd ./tidy_env
pixi add r-tidydragen==0.0.0.9001

Then you can create a task to run the tidydragen.R CLI script:

pixi task add tidydragen "tidydragen.R"
pixi run tidydragen --help

Or activate the environment and use tidydragen directly in an R environment:

pixi shell
R
library(tidydragen)