| |
| """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()) |
|
|
|
|