datalad

Retrieve, version, and publish scientific datasets with DataLad and git-annex, and capture computational provenance with datalad run, rerun, and containers-run. Use when cloning or fetching data from OpenNeuro, DANDI, datasets.datalad.org, or any DataLad dataset; when a file in a dataset reads as a broken symlink or a small pointer instead of real data; when an analysis needs a machine-readable record of how each output was produced so it can be re-executed; or when publishing a dataset to siblings such as a GitHub repository plus a storage remote. Also use to decide between DataLad and plain Git for a data-carrying repository.

Version

1.0

License

MIT

Compatibility

Needs datalad 1.6.x on Python 3.10+, plus git and git-annex 10.x. git-annex is not written in Python but installs as a prebuilt wheel from PyPI (`uv pip install git-annex`), from a system package manager, or from conda-forge. Container-based provenance also needs datalad-container (1.2.x) and Singularity/Apptainer or Docker. clone, get, and push need network access; credentialed remotes read secrets from the system keyring or from DATALAD_CREDENTIAL_<NAME>_<COMPONENT> environment variables.