Getting Started
Run the core dvs workflow on a small dataset, from R or the CLI.
dvs versions large or sensitive data files independently of your source control. File contents go to a content-addressed blob store. Small text meta files sit next to your code and record what is tracked. dvs works alongside Git or on its own.
🔗The core workflow
The CLI and the R package expose the same four verbs: init, add, status,
get. The two walkthroughs below take one small dataset (R's built-in Theoph,
saved as a CSV) through the full loop: initialize a repository, add the file,
check status, delete it, then get it back.
- R walkthrough: the workflow with
library(dvs). - CLI walkthrough: the same workflow from the terminal.
Once the basics are clear, the R Package and CLI sections document every function and command (the R Package section also covers the R-only helper utilities), and Internals goes deeper on storage and configuration.
🔗Installation (advanced users)
CLI (the dvs binary), with cargo:
cargo install --git https://github.com/A2-ai/dvs2 --locked --force --all-features dvs-cliR package (dvs), with rv:
rv add dvs --git https://github.com/A2-ai/dvs2 --branch main --directory dvs-rpkg