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008feb0 | 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 31 32 33 | """Run one loader for the published sample; dependencies run in Docker."""
import argparse
def main():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('library', choices=['datasets', 'pandas', 'duckdb'])
parser.add_argument('--repo', required=True, help='HF dataset ID: mashu-data/repository-name')
args = parser.parse_args()
if args.library == 'datasets':
from datasets import load_dataset
comments = load_dataset(args.repo, 'comments', split='train', streaming=True)
print(next(iter(comments)))
elif args.library == 'pandas':
import pandas as pd
# Read one real shard, not the full dataset, into memory.
url = f'https://huggingface.co/datasets/{args.repo}/resolve/main/data/comments/subreddit=LocalLLaMA/part-0.parquet'
comments = pd.read_parquet(url)
print(comments[['id', 'link_id', 'parent_id', 'depth']].head())
else:
import duckdb
from huggingface_hub import hf_hub_download
# Download one shard to the HF cache, then query the local Parquet file.
path = hf_hub_download(repo_id=args.repo, repo_type='dataset',
filename='data/comments/subreddit=LocalLLaMA/part-0.parquet')
conn = duckdb.connect()
rows = conn.execute('SELECT id, link_id, parent_id, depth FROM read_parquet(?, hive_partitioning=false) LIMIT 20', [path]).fetchall()
print(rows)
if __name__ == '__main__':
main()
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