Datasets:
File size: 1,405 Bytes
84a242a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | #!/usr/bin/env python3
"""Plan an upload; --upload explicitly publishes to an existing dataset repo."""
import argparse
import json
from pathlib import Path
import re
def main():
p = argparse.ArgumentParser(description=__doc__)
p.add_argument('--repo-id', required=True, help='Actual Hugging Face owner/dataset identifier')
p.add_argument('--upload', action='store_true', help='Perform the upload; default is plan only')
args = p.parse_args()
if not re.fullmatch(r'[A-Za-z0-9][A-Za-z0-9_.-]*/[A-Za-z0-9][A-Za-z0-9_.-]*', args.repo_id):
p.error('Use the actual owner/dataset repository ID.')
root = Path(__file__).resolve().parents[1]
manifest = json.loads((root / 'provenance/repository_files.json').read_text())
print(json.dumps({'repo_id': args.repo_id, 'repo_type': 'dataset', 'folder': str(root),
'payload_files': manifest['total_files'], 'payload_bytes': manifest['total_bytes'],
'upload_requested': args.upload}, indent=2))
if not args.upload:
return
from huggingface_hub import HfApi
api = HfApi()
api.repo_info(repo_id=args.repo_id, repo_type='dataset')
api.upload_folder(repo_id=args.repo_id, repo_type='dataset', folder_path=str(root),
commit_message='Publish MolAS Active Learning AI4DD dataset and research artifacts')
if __name__ == '__main__':
main()
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