#!/usr/bin/env python3 """Smoke-test generated STRING Parquet configs with the Hugging Face datasets API.""" import argparse import glob import sys from pathlib import Path from typing import Dict, List CONFIGS = ( "species", "protein_info", "protein_aliases", "protein_sequences", "protein_links", ) SPLITS = ("train", "validation", "test") def parse_args() -> argparse.Namespace: parser = argparse.ArgumentParser(description="Validate local or uploaded STRING HF dataset configs.") parser.add_argument( "--repo-id", default=None, help="Optional HF dataset repo id, for example LiteFold/STRING. If omitted, validates local Parquet.", ) parser.add_argument("--data-dir", type=Path, default=Path("data")) parser.add_argument("--config", choices=CONFIGS, default="protein_links") parser.add_argument("--split", default="train") parser.add_argument("--streaming", action="store_true") parser.add_argument("--preview-rows", type=int, default=3) return parser.parse_args() def local_data_files(data_dir: Path, config: str) -> Dict[str, List[str]]: files: Dict[str, List[str]] = {} for split in SPLITS: pattern = str(data_dir / config / ("%s-*.parquet" % split)) matches = sorted(glob.glob(pattern)) if matches: files[split] = matches if not files: raise SystemExit("No local Parquet files found for config %s under %s" % (config, data_dir)) return files def main() -> int: args = parse_args() try: from datasets import load_dataset except ImportError as exc: raise SystemExit( "datasets is required. Install dependencies with: python -m pip install -r requirements.txt" ) from exc if args.repo_id: dataset = load_dataset(args.repo_id, args.config, split=args.split, streaming=args.streaming) else: files = local_data_files(args.data_dir, args.config) if args.split not in files: raise SystemExit( "Split %s is not present locally for config %s. Available splits: %s" % (args.split, args.config, ", ".join(sorted(files))) ) dataset = load_dataset("parquet", data_files=files, split=args.split, streaming=args.streaming) print("config:", args.config) print("split:", args.split) print("features:", dataset.features) if args.streaming: iterator = iter(dataset) for index in range(args.preview_rows): try: print("row[%d]:" % index, next(iterator)) except StopIteration: break else: print("num_rows:", len(dataset)) for index in range(min(args.preview_rows, len(dataset))): print("row[%d]:" % index, dataset[index]) return 0 if __name__ == "__main__": sys.exit(main())