#!/usr/bin/env python3 """ Push a JSONL file into a Hugging Face Datasets repository. Usage: python push_to_hf.py \ --jsonl /path/to/data.jsonl \ --repo-id username/my-dataset \ --split-name train \ --private \ --commit-message "Initial upload" Auth: - Set an environment variable HF_TOKEN with a write-access token, or - Pass --token YOUR_TOKEN Notes: - Requires: datasets>=2.14.0, huggingface_hub>=0.23.0 - If the repo doesn't exist, it will be created. """ import argparse import os import sys from typing import List, Optional from datasets import load_dataset, Dataset, DatasetDict # type: ignore from huggingface_hub import HfApi # type: ignore def parse_args() -> argparse.Namespace: p = argparse.ArgumentParser(description="Push JSONL to a Hugging Face dataset repo") p.add_argument( "--jsonl", nargs=+1, required=True, help="Path(s) to JSONL file(s). You can pass multiple to concatenate.", ) p.add_argument( "--repo-id", required=True, help="Target dataset repo like 'username/dataset_name'", ) p.add_argument( "--split-name", default="train", help="Dataset split name to assign (default: train)", ) p.add_argument( "--private", action="store_true", help="Create the dataset repo as private if it doesn't exist", ) p.add_argument( "--commit-message", default="Add dataset", help="Commit message for the upload", ) p.add_argument( "--token", default=os.environ.get("HF_TOKEN"), help="HF API token (defaults to HF_TOKEN env var)", ) p.add_argument( "--max-shard-size", default="500MB", help="Max shard size used by push_to_hub (e.g., '500MB', '1GB')", ) return p.parse_args() def ensure_repo(repo_id: str, token: Optional[str], private: bool) -> None: api = HfApi() try: api.create_repo( repo_id=repo_id, repo_type="dataset", private=private, exist_ok=True, token=token, ) print(f"✔️ Ensured dataset repo exists: {repo_id} (private={private})") except Exception as e: print(f"❌ Failed to ensure/create repo '{repo_id}': {e}") sys.exit(1) def load_jsonl_as_dataset(files: List[str]) -> Dataset: # datasets will auto-detect JSON Lines when using the 'json' builder print(f"📦 Loading JSONL: {files}") ds = load_dataset("json", data_files=files, split="train") # type: ignore # Basic sanity check print(f"✅ Loaded {len(ds):,} rows with columns: {list(ds.features.keys())}") return ds def push_dataset( ds: Dataset, repo_id: str, split_name: str, token: Optional[str], commit_message: str, max_shard_size: str, ) -> None: print( f"🚀 Pushing split='{split_name}' to https://huggingface.co/datasets/{repo_id} ..." ) # Push a single split; this will create a DatasetDict with that split on the Hub ds.push_to_hub( repo_id=repo_id, split=split_name, token=token, commit_message=commit_message, max_shard_size=max_shard_size, ) print("🎉 Upload complete!") def main() -> None: args = parse_args() if not args.token: print( "❌ No token provided. Set HF_TOKEN env var or pass --token.\n" " Create a token at https://huggingface.co/settings/tokens" ) sys.exit(2) # Expand paths and verify they exist files = [] for f in args.jsonl: f = os.path.expanduser(f) if not os.path.isfile(f): print(f"❌ File not found: {f}") sys.exit(2) files.append(f) ensure_repo(args.repo_id, args.token, args.private) ds = load_jsonl_as_dataset(files) # Optional: cast to string for problematic columns (commented; uncomment if needed) # from datasets import Features, Value # ds = ds.cast(Features({k: Value("string") for k in ds.features})) push_dataset( ds=ds, repo_id=args.repo_id, split_name=args.split_name, token=args.token, commit_message=args.commit_message, max_shard_size=args.max_shard_size, ) if __name__ == "__main__": main()