| """Publish the generated dataset to the Hugging Face Hub (the one manual step). | |
| hf auth login # once, paste a write token | |
| python scripts/push_to_huggingface.py --repo <user>/<dataset> # add --private if you like | |
| The whole project folder becomes the dataset repository: the Parquet shards in data/ (with | |
| config.json and manifest.json), the README.md dataset card whose `configs:` block makes every | |
| table browsable in the Dataset Viewer, and the generator source, so the dataset is reproducible | |
| from the repository alone. The upload is resumable: re-run the same command after any | |
| interruption and it continues where it stopped (its bookkeeping lives in .cache/, ignored by git). | |
| """ | |
| import argparse | |
| import os | |
| from pathlib import Path | |
| from huggingface_hub import HfApi | |
| ROOT = Path(__file__).resolve().parents[1] | |
| IGNORE = ["__pycache__/**", "*.pyc", "*.tmp", ".git/**", ".gitignore", ".cache/**", ".DS_Store", | |
| "data_*/**", "*.log"] | |
| def main() -> None: | |
| parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) | |
| parser.add_argument("--repo", required=True, help="dataset repository id, e.g. alexander/semantic-potential-routing") | |
| parser.add_argument("--private", action="store_true", help="create the repository as private") | |
| parser.add_argument("--token", default=os.environ.get("HF_TOKEN"), help="write token (default: HF_TOKEN or cached login)") | |
| parser.add_argument("--workers", type=int, default=None, help="parallel upload workers (default: library choice)") | |
| args = parser.parse_args() | |
| shards = sorted((ROOT / "data").glob("*/part-*.parquet")) | |
| if not shards or not (ROOT / "data" / "manifest.json").exists(): | |
| raise SystemExit("No finished dataset in data/ - run scripts/run_local_sweep.py first.") | |
| print(f"Uploading {len(shards)} Parquet shards " | |
| f"({sum(f.stat().st_size for f in shards) / 1e9:.2f} GB) plus README and source to {args.repo} ...") | |
| api = HfApi(token=args.token) | |
| api.create_repo(args.repo, repo_type="dataset", private=args.private, exist_ok=True) | |
| api.upload_large_folder(repo_id=args.repo, folder_path=ROOT, repo_type="dataset", | |
| ignore_patterns=IGNORE, num_workers=args.workers) | |
| print(f"Done: https://huggingface.co/datasets/{args.repo}") | |
| if __name__ == "__main__": | |
| main() | |