Download stackgo/examples/read_samples.py from s0duku/the-stack-go: direct link, hf CLI and curl.
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https://huggingface.co/datasets/s0duku/the-stack-go/resolve/main/stackgo/examples/read_samples.py
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3.34 kB
| #!/usr/bin/env python3 | |
| """Stream stackbuild sample Parquet files and inspect their structured fields.""" | |
| from __future__ import annotations | |
| import argparse | |
| import json | |
| from pathlib import Path | |
| import pyarrow.dataset as ds | |
| def _expand_paths(values: list[str]) -> list[str]: | |
| paths: list[str] = [] | |
| for value in values: | |
| path = Path(value) | |
| if path.is_dir(): | |
| paths.extend(str(item) for item in sorted(path.glob("*.parquet"))) | |
| else: | |
| paths.append(value) | |
| if not paths: | |
| raise SystemExit("no Parquet files found") | |
| return paths | |
| def main() -> None: | |
| parser = argparse.ArgumentParser(description=__doc__) | |
| parser.add_argument("paths", nargs="+", help="Parquet files, globs, or a directory") | |
| parser.add_argument("--limit", type=int, default=3, help="maximum matching samples to print") | |
| parser.add_argument("--repo", help="filter by exact repo_id") | |
| parser.add_argument("--kind", choices=("dependency", "target_context"), help="filter by sample kind") | |
| parser.add_argument("--text-chars", type=int, default=400, | |
| help="characters of sample text to include; 0 prints all text") | |
| parser.add_argument("--json", action="store_true", help="emit one JSON object per sample") | |
| args = parser.parse_args() | |
| if args.limit < 1: | |
| parser.error("--limit must be positive") | |
| if args.text_chars < 0: | |
| parser.error("--text-chars must be non-negative") | |
| expression = None | |
| if args.repo: | |
| expression = ds.field("repo_id") == args.repo | |
| if args.kind: | |
| kind_expression = ds.field("kind") == args.kind | |
| expression = kind_expression if expression is None else expression & kind_expression | |
| dataset = ds.dataset(_expand_paths(args.paths), format="parquet") | |
| scanner = dataset.scanner( | |
| columns=["sample_id", "repo_id", "revision_id", "kind", "text", "files", | |
| "token_count", "metadata_json"], | |
| filter=expression, | |
| batch_size=256, | |
| ) | |
| printed = 0 | |
| for batch in scanner.to_batches(): | |
| for row in batch.to_pylist(): | |
| text = row["text"] | |
| record = { | |
| "sample_id": row["sample_id"], | |
| "repo_id": row["repo_id"], | |
| "revision_id": row["revision_id"], | |
| "kind": row["kind"], | |
| "token_count": row["token_count"], | |
| "metadata": json.loads(row["metadata_json"]), | |
| "files": row["files"], | |
| "text": text if args.text_chars == 0 else text[:args.text_chars], | |
| } | |
| if args.json: | |
| print(json.dumps(record, ensure_ascii=False)) | |
| else: | |
| print(f"sample_id: {record['sample_id']}") | |
| print(f"repo_id: {record['repo_id']}") | |
| print(f"kind: {record['kind']}") | |
| print(f"tokens: {record['token_count']}") | |
| print(f"files: {', '.join(item['path'] for item in record['files'][:8])}") | |
| print(f"metadata: {json.dumps(record['metadata'], ensure_ascii=False)}") | |
| print("text:") | |
| print(record["text"]) | |
| print("-" * 72) | |
| printed += 1 | |
| if printed >= args.limit: | |
| return | |
| if __name__ == "__main__": | |
| main() | |