A tool to automatically generate Croissant metadata for datasets.
Project description
Croissant Baker
Automatically generate Croissant JSON-LD metadata for ML datasets — e.g. for PhysioNet, NeurIPS Datasets & Benchmarks submissions, or any platform that benefits from standardized dataset metadata.
Installation
pip install croissant-baker
or with uv:
uv add croissant-baker
Quick start
croissant-baker \
--input /path/to/dataset \
--creator "Your Name,you@example.com" \
--description "My ML dataset" \
--license "CC-BY-4.0" \
--output my-dataset-croissant.jsonld
Or try with the bundled MIMIC-IV Demo test data:
git clone https://github.com/MIT-LCP/croissant-baker.git && cd croissant-baker
uv sync --group dev
croissant-baker \
--input tests/data/input/mimiciv_demo/physionet.org/files/mimic-iv-demo/ \
--creator "Alistair Johnson,aewj@mit.edu,https://physionet.org/" \
--creator "Tom Pollard,tpollard@mit.edu,https://physionet.org/" \
--name "MIMIC-IV Clinical Database Demo" \
--description "Demo subset of MIMIC-IV containing 100 de-identified patients from Beth Israel Deaconess Medical Center" \
--url "https://physionet.org/content/mimic-iv-demo/2.2/" \
--license "https://opendatacommons.org/licenses/odbl/1-0/" \
--rai-data-biases "Single-site cohort from a US academic medical centre" \
--rai-data-limitations "Demo subset limited to 100 patients" \
--output mimic-iv-demo-croissant.jsonld
croissant-baker validate mimic-iv-demo-croissant.jsonld
Supported formats
| Format | Extensions | Notes |
|---|---|---|
| CSV / TSV | .csv, .tsv + .gz, .bz2, .xz |
Streaming with automatic type inference |
| Parquet | .parquet |
Partitioned datasets supported |
| FHIR | .ndjson, .ndjson.gz, .json (Bundle) |
NDJSON bulk export and JSON Bundle |
| JSON / JSONL | .json, .jsonl + .gz |
Arrays, single objects, and JSON Lines |
| WFDB | .hea + .dat / .atr |
PhysioNet waveform data |
| Images | .png, .jpg, .tiff, .bmp, .gif, .webp |
Dimensions and format via Pillow |
Key features
- Automatic type inference for all supported formats
- RAI metadata via
--rai-*CLI flags or--rai-config rai.yaml - Validation against the Croissant spec via
mlcroissant - Dry-run mode, include/exclude glob filters, multiple creators
See the documentation for full CLI reference, examples, and RAI configuration.
Contributing
See CONTRIBUTING.md for guidelines and DEVELOPMENT.md for setup, testing, releases, and how to add new file handlers.
License
MIT License - see LICENSE file.
Project details
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