#!/usr/bin/env python3 """Validate every Dataset Card configuration with Hugging Face Datasets. This script performs a real local load_dataset call. It deliberately does not contact the Hub and therefore does not validate publication, visibility, the Dataset Viewer, or the platform-generated Croissant endpoint. """ from __future__ import annotations import argparse import csv import json import sys from pathlib import Path import yaml def read_card(root: Path) -> dict: text = (root / "README.md").read_text(encoding="utf-8") if not text.startswith("---\n"): raise ValueError("README.md must begin with YAML frontmatter") return yaml.safe_load(text.split("---", 2)[1]) or {} def csv_fallback(root: Path, configs: list[dict]) -> list[dict]: """Dependency-light structural load; not a substitute for datasets.""" results = [] for config in configs: name = config["config_name"] specs = config.get("data_files") or [] if len(specs) != 1: raise ValueError(f"{name}: expected exactly one data_files entry") spec = specs[0] path = root / spec["path"] with path.open(newline="", encoding="utf-8-sig") as handle: reader = csv.DictReader(handle) rows = sum(1 for _ in reader) columns = list(reader.fieldnames or []) results.append( { "configuration": name, "split": spec["split"], "path": spec["path"], "rows": rows, "columns": columns, "loader": "python.csv", "status": "PASS", } ) return results def main() -> int: parser = argparse.ArgumentParser() parser.add_argument("root", nargs="?", default=".") parser.add_argument( "--require-hf-datasets", action="store_true", help="fail instead of using the CSV structural fallback", ) parser.add_argument("--json-out") args = parser.parse_args() root = Path(args.root).resolve() configs = read_card(root).get("configs") or [] try: from datasets import get_dataset_config_names, load_dataset except ImportError as exc: if args.require_hf_datasets: print( "Hugging Face Datasets is not installed. Install " "requirements-validation.txt before using " "--require-hf-datasets.", file=sys.stderr, ) return 2 results = csv_fallback(root, configs) report = { "status": "PASS_STRUCTURAL_CSV_ONLY", "hf_datasets_clean_load": "NOT_RUN_DEPENDENCY_UNAVAILABLE", "detail": str(exc), "configurations": results, } else: expected = [item["config_name"] for item in configs] discovered = get_dataset_config_names(str(root)) if discovered != expected: raise RuntimeError( f"configuration mismatch: expected {expected}, got {discovered}" ) results = [] for config in configs: name = config["config_name"] spec = config["data_files"][0] dataset = load_dataset( str(root), name=name, split=spec["split"], ) results.append( { "configuration": name, "split": spec["split"], "rows": dataset.num_rows, "columns": dataset.column_names, "loader": "datasets.load_dataset", "status": "PASS", } ) report = { "status": "PASS_LOCAL_HF_DATASETS_CLEAN_LOAD", "hf_datasets_clean_load": "PASS", "configurations": results, } rendered = json.dumps(report, indent=2, sort_keys=True) + "\n" if args.json_out: Path(args.json_out).write_text(rendered, encoding="utf-8") print(rendered, end="") return 0 if __name__ == "__main__": raise SystemExit(main())