| |
| |
| |
| """Fetch each registered source's text at its pinned revision. |
| |
| Writes one JSON object per document to artifacts/raw/<source>/text.jsonl. Nothing here is |
| committed: the project ships a recipe, not a corpus, because CC-BY-SA-3.0 and |
| CDLA-Sharing-1.0 are not obviously compatible terms on one redistributed work. |
| """ |
| from __future__ import annotations |
|
|
| import argparse |
| import json |
| import sys |
| from pathlib import Path |
| from typing import Dict, Iterable, Iterator, Optional |
|
|
| ROOT = Path(__file__).resolve().parent.parent |
| sys.path.insert(0, str(ROOT)) |
|
|
| from scripts.build_gutenberg_catalogue import GUTENBERG_REPO, matches_source, gutenberg_sources |
| from train.corpus import SOURCES, CorpusSource, get_source |
| from train.paths import shared_dir |
|
|
| |
| TEXT_COLUMN = { |
| "sedthh/gutenberg_english": "TEXT", |
| "roneneldan/TinyStories": "text", |
| "wikimedia/wikipedia": "text", |
| "biglam/gutenberg-poetry-corpus": "line", |
| } |
|
|
|
|
| def write_documents(rows: Iterable[Dict[str, object]], dest: Path) -> int: |
| """Write ``{"text": ...}`` per line, skipping empties. Returns documents written.""" |
| dest.parent.mkdir(parents=True, exist_ok=True) |
| written = 0 |
| with dest.open("w", encoding="utf-8") as fh: |
| for row in rows: |
| text = row.get("text") |
| if not isinstance(text, str) or not text.strip(): |
| continue |
| fh.write(json.dumps({"text": text}, ensure_ascii=False) + "\n") |
| written += 1 |
| return written |
|
|
|
|
| def fetch_gutenberg_batch(sources: list[CorpusSource], limit_rows: int = 0) -> Dict[str, int]: |
| """Fetch multiple Gutenberg sources in one streaming pass. Returns {source_name: count}. |
| |
| Stop after reading N rows from the source (0 = no limit). This is a COST bound, not a |
| document count: rows that are filtered out — non-matching books, blank text, malformed |
| metadata — still consume the budget, so fewer than N documents may be written. The budget |
| is shared across all sources in the single pass. |
| """ |
| from datasets import load_dataset |
|
|
| |
| if not sources or not all(s.hf_repo == GUTENBERG_REPO for s in sources): |
| raise ValueError("fetch_gutenberg_batch requires all sources to be from gutenberg_english") |
|
|
| revision = sources[0].hf_revision |
| if not all(s.hf_revision == revision for s in sources): |
| raise ValueError("All Gutenberg sources must use the same revision") |
|
|
| |
| file_handles = {} |
| for src in sources: |
| dest = shared_dir("raw") / src.name / "text.jsonl" |
| dest.parent.mkdir(parents=True, exist_ok=True) |
| file_handles[src.name] = dest.open("w", encoding="utf-8") |
|
|
| try: |
| |
| kwargs = {"split": sources[0].hf_split, "revision": revision, "streaming": True} |
| ds = load_dataset(GUTENBERG_REPO, **kwargs) |
|
|
| counts = {src.name: 0 for src in sources} |
| seen = 0 |
|
|
| for row in ds: |
| seen += 1 |
| if limit_rows and seen > limit_rows: |
| break |
|
|
| md = row.get("METADATA") |
| if isinstance(md, str): |
| try: |
| md = json.loads(md) |
| except json.JSONDecodeError: |
| continue |
| if not isinstance(md, dict): |
| continue |
|
|
| text = row.get("TEXT") |
| if not isinstance(text, str) or not text.strip(): |
| continue |
|
|
| |
| for src in sources: |
| if matches_source(md, src): |
| file_handles[src.name].write(json.dumps({"text": text}, ensure_ascii=False) + "\n") |
| counts[src.name] += 1 |
|
|
| return counts |
|
|
| finally: |
| |
| for fh in file_handles.values(): |
| if not fh.closed: |
| fh.close() |
|
|
|
|
| def iter_source_rows(source: CorpusSource, limit_rows: int = 0) -> Iterator[Dict[str, object]]: |
| """Stream a source's rows, normalised to ``{"text": str}`` and filtered if Gutenberg. |
| |
| Stop after reading N rows from the source (0 = no limit). This is a cost bound, not a |
| document count: rows that are filtered out — non-matching books, blank text, malformed |
| metadata — still consume the budget, so fewer than N documents may be yielded. |
| """ |
| from datasets import load_dataset |
|
|
| column = TEXT_COLUMN.get(source.hf_repo) |
| if column is None: |
| raise ValueError( |
| f"no text column registered for {source.hf_repo}; add it to TEXT_COLUMN" |
| ) |
|
|
| kwargs = {"split": source.hf_split, "revision": source.hf_revision, "streaming": True} |
| if source.hf_config: |
| kwargs["name"] = source.hf_config |
| ds = load_dataset(source.hf_repo, **kwargs) |
|
|
| seen = 0 |
| for row in ds: |
| seen += 1 |
| if limit_rows and seen > limit_rows: |
| return |
|
|
| if source.hf_repo == GUTENBERG_REPO: |
| md = row.get("METADATA") |
| if isinstance(md, str): |
| try: |
| md = json.loads(md) |
| except json.JSONDecodeError: |
| continue |
| if not isinstance(md, dict) or not matches_source(md, source): |
| continue |
| text = row.get(column) |
| if not isinstance(text, str) or not text.strip(): |
| continue |
| yield {"text": text} |
|
|
|
|
| def fetch_source(source: CorpusSource, dest: Optional[Path] = None, |
| limit_rows: int = 0) -> int: |
| """Fetch one source to ``artifacts/raw/<name>/text.jsonl``. Returns documents written.""" |
| target = dest or (shared_dir("raw") / source.name / "text.jsonl") |
| return write_documents(iter_source_rows(source, limit_rows), target) |
|
|
|
|
| def main() -> int: |
| p = argparse.ArgumentParser(description=__doc__, |
| formatter_class=argparse.RawDescriptionHelpFormatter) |
| p.add_argument("--source", action="append", default=None, |
| help="Source name (repeatable). Default: all registered sources.") |
| p.add_argument("--limit-rows", type=int, default=0, |
| help="Stop after reading N rows from the source (0 = no limit). " |
| "This is a cost bound, not a document count: rows that are filtered out " |
| "— non-matching books, blank text, malformed metadata — still consume the " |
| "budget, so fewer than N documents may be written. For smoke tests.") |
| args = p.parse_args() |
|
|
| names = args.source or sorted(SOURCES) |
|
|
| |
| gutenberg_sources_all = gutenberg_sources() |
| requested_gutenberg = [n for n in names if n in gutenberg_sources_all] |
| requested_other = [n for n in names if n not in gutenberg_sources_all] |
|
|
| |
| |
| |
| |
| if len(requested_gutenberg) > 1: |
| sources_objs = [get_source(name) for name in requested_gutenberg] |
| print(f"fetching {len(sources_objs)} Gutenberg sources in one pass ...", flush=True) |
| counts = fetch_gutenberg_batch(sources_objs, limit_rows=args.limit_rows) |
| for name, count in counts.items(): |
| print(f" {name}: {count:,} documents") |
| if count == 0: |
| print(f" WARNING: {name} produced no documents", file=sys.stderr) |
| else: |
| |
| for name in requested_gutenberg: |
| src = get_source(name) |
| print(f"fetching {name} from {src.hf_repo}@{src.hf_revision} ...", flush=True) |
| n = fetch_source(src, limit_rows=args.limit_rows) |
| print(f" {n:,} documents") |
| if n == 0: |
| print(f" WARNING: {name} produced no documents", file=sys.stderr) |
|
|
| |
| for name in requested_other: |
| try: |
| src = get_source(name) |
| except KeyError as exc: |
| print(f"ERROR: {exc}", file=sys.stderr) |
| return 1 |
| print(f"fetching {name} from {src.hf_repo}@{src.hf_revision} ...", flush=True) |
| n = fetch_source(src, limit_rows=args.limit_rows) |
| print(f" {n:,} documents") |
| if n == 0: |
| print(f" WARNING: {name} produced no documents", file=sys.stderr) |
|
|
| return 0 |
|
|
|
|
| if __name__ == "__main__": |
| raise SystemExit(main()) |
|
|