The primary workflow is now to prepare a dataset, then use standard Git practices to propose the change.
For a guided experience, simply run the command with no arguments:
uv run datamanagerThis will launch a menu where you can choose your desired action, including the new "Prepare a dataset for release" option.
You can also use the command-line interface directly for specific tasks or for scripting purposes.
Prepares a dataset for release by uploading it to the staging area and updating the manifest locally. This command intelligently handles both creating new datasets and updating existing ones.
This is the first step of the new workflow.
uv run datamanager prepare <dataset-name.sqlite> <path/to/local/file.sqlite>After running prepare, follow the on-screen instructions:
git add manifest.jsongit commit -m "Your descriptive message"git push- Open a Pull Request in GitHub.
Lists all datasets currently tracked in manifest.json.
uv run datamanager list-datasetsDownloads a dataset from the appropriate R2 bucket (production or internal) and verifies its integrity. The bucket is determined by the dataset's configuration in the manifest.
# Pull the latest version
uv run datamanager pull user-profiles.sqlite
# Pull a specific version
uv run datamanager pull user-profiles.sqlite --version v2Prepares a rollback to a previous stable version by creating a new version entry that points to the old data.
uv run datamanager rollback <dataset-name.sqlite> --to-version v1Prepares the permanent deletion of an entire dataset and all its versions. Requires strong confirmation.
uv run datamanager delete <dataset-name.sqlite>Prepares the permanent deletion of old versions of a dataset, keeping a specified number of recent versions.
uv run datamanager prune-versions <dataset-name.sqlite> --keep 5Checks R2 credentials and reports granular read/write/delete permissions for all three buckets (production, staging, and internal).
uv run datamanager verify



