"""Stage 4: aggregate report + provenance. Reads every uploaded per-shard stats file, sums the counts, ranks which banned terms actually fired (the key audit surface), and writes cleaning_report_1930s.json plus a README to the destination repo. Safe to run mid-pipeline. Run: python scripts/report.py """ import json import re import time from collections import Counter from huggingface_hub import CommitOperationAdd, hf_hub_download import config from build_list import load_or_build from common import api, HF_TOKEN, ensure_dst_repo, list_repo_files_safe def download_json(path_in_repo): local = hf_hub_download(config.DST_REPO, path_in_repo, repo_type="dataset", token=HF_TOKEN) with open(local, "r", encoding="utf-8") as f: return json.load(f) def main(): ensure_dst_repo() banned_terms, meta, tiers = load_or_build() files = list_repo_files_safe(config.DST_REPO) stat_files = sorted(p for p in files if re.match(r"stats/shard_\d+\.json$", p)) strip_stat_files = sorted(p for p in files if re.match(r"strip_stats/shard_\d+\.json$", p)) print(f"Found {len(stat_files):,} filter stat files and {len(strip_stat_files):,} strip stat files.") # --- Stage 0.5 footer-strip totals (if that stage has run) --- strip_totals = { "n_shards_stripped": len(strip_stat_files), "n_docs": 0, "n_docs_changed": 0, "n_docs_flagged_unstripped": 0, "n_lines_removed": 0, "chars_in": 0, "chars_out": 0, "removed_by_pattern": Counter(), } for sf in strip_stat_files: st = download_json(sf) for k in ["n_docs", "n_docs_changed", "n_docs_flagged_unstripped", "n_lines_removed", "chars_in", "chars_out"]: strip_totals[k] += int(st.get(k, 0)) strip_totals["removed_by_pattern"].update(st.get("removed_by_pattern", {})) top_footers = strip_totals["removed_by_pattern"].most_common(20) strip_totals["top_footer_patterns"] = top_footers strip_totals["removed_by_pattern"] = dict(strip_totals["removed_by_pattern"]) strip_totals["chars_removed_pct"] = ( 100.0 * (strip_totals["chars_in"] - strip_totals["chars_out"]) / max(strip_totals["chars_in"], 1) ) totals = { "source_repo": config.SRC_REPO, "destination_repo": config.DST_REPO, "cutoff_year": config.CUTOFF_YEAR, "min_banned_hits": config.MIN_BANNED_HITS, "banned_list_meta": meta, "n_banned_terms": len(banned_terms), "n_shards_done": len(stat_files), "tier_counts": (meta or {}).get("tier_counts", {}), "n_input": 0, "n_kept": 0, "n_removed": 0, "chars_in": 0, "chars_kept": 0, "removed_by_term": Counter(), "removed_by_reason": Counter(), "boilerplate_hits": Counter(), } for sf in stat_files: st = download_json(sf) for k in ["n_input", "n_kept", "n_removed", "chars_in", "chars_kept"]: totals[k] += int(st.get(k, 0)) totals["removed_by_term"].update(st.get("removed_by_term", {})) totals["removed_by_reason"].update(st.get("removed_by_reason", {})) totals["boilerplate_hits"].update(st.get("boilerplate_hits", {})) top_terms = totals["removed_by_term"].most_common(30) top_boilerplate = totals["boilerplate_hits"].most_common(20) totals["top_firing_terms"] = top_terms totals["top_boilerplate_hits"] = top_boilerplate totals["removed_by_term"] = dict(totals["removed_by_term"]) totals["removed_by_reason"] = dict(totals["removed_by_reason"]) totals["boilerplate_hits"] = dict(totals["boilerplate_hits"]) totals["docs_removed_pct"] = 100.0 * totals["n_removed"] / max(totals["n_input"], 1) totals["docs_kept_pct"] = 100.0 * totals["n_kept"] / max(totals["n_input"], 1) totals["chars_kept_pct"] = 100.0 * totals["chars_kept"] / max(totals["chars_in"], 1) totals["footer_strip"] = strip_totals totals["updated_at"] = time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()) print(json.dumps({k: v for k, v in totals.items() if k != "removed_by_term"}, indent=2, sort_keys=True)) config.ensure_dirs() report_path = config.OUT_DIR / "cleaning_report_1930s.json" with open(report_path, "w", encoding="utf-8") as f: json.dump(totals, f, indent=2, sort_keys=True) top_lines = "\n".join(f"- `{t}`: {c:,}" for t, c in top_terms) or "- (none yet)" footer_lines = "\n".join(f"- `{p}`: {c:,}" for p, c in top_footers) or "- (strip stage not run yet)" st = strip_totals readme = f"""--- dataset_info: features: - name: text dtype: string --- # think-dataset-clean-1930s `{config.SRC_REPO}` with a **tiered** anachronism keyword filter applied. A document is dropped only on strong evidence of post-**{config.CUTOFF_YEAR}** content, which avoids polysemy false positives (e.g. "compiler of this volume", bee "drone", birdsong "twitter", the Black Hole of Calcutta): - **Tier 1** ({totals["tier_counts"].get("tier1", 0)}) — coined well after {config.CUTOFF_YEAR}; **one hit drops** the document. - **Tier 2** ({totals["tier_counts"].get("tier2", 0)}) — real anachronisms; need **≥2 distinct tier-2/3 hits (≥1 tier-2)** to drop. - **Tier 3** ({totals["tier_counts"].get("tier3", 0)}) — polysemous / has a pre-{config.CUTOFF_YEAR + 1} sense; **never drops alone**, only corroborates. - **Strip-only** ({totals["tier_counts"].get("strip", 0)}) + format tells — reproduction/boilerplate (URLs, "all rights reserved", "photocopy"); **never drops**, only logged. - Banned list size: **{len(banned_terms):,} terms** (+ format-tell patterns) - Shards completed: {totals["n_shards_done"]:,} - Input documents: {totals["n_input"]:,} - Kept: {totals["n_kept"]:,} ({totals["docs_kept_pct"]:.2f}%) - Removed: {totals["n_removed"]:,} ({totals["docs_removed_pct"]:.2f}%) - Kept characters: {totals["chars_kept_pct"]:.2f}% ## Stage 0.5 — footer / boilerplate stripping (runs before the filter) Before the anachronism filter, a line-level pass removes reprint/OCR footer lines (URLs, "printed in the United States of America", "all rights reserved", photocopy / print-on-demand colophons, ISBN lines, bare page numbers, library stamps) from each document, writing the stripped corpus to `{config.STRIP_PREFIX}/`. Whole books are kept; only footer lines are removed. Docs that would lose more than {int(config.FOOTER_MAX_DOC_LINE_FRAC * 100)}% of their lines are kept unstripped and flagged. - Shards stripped: {st["n_shards_stripped"]:,} - Docs changed: {st["n_docs_changed"]:,} / {st["n_docs"]:,} - Docs flagged (kept unstripped): {st["n_docs_flagged_unstripped"]:,} - Footer lines removed: {st["n_lines_removed"]:,} - Characters removed: {st["chars_removed_pct"]:.2f}% Top footer patterns: {footer_lines} Artifacts: `_banned/` (list + allow-list + audit), `{config.STRIP_PREFIX}/` (footer-stripped corpus), `strip_stats/` + `strip_samples/` (footer audit), `stats/` (per-shard filter counts), `hits/` (per-shard hit log), `scripts/` (the pipeline). Top firing terms: {top_lines} """ readme_path = config.OUT_DIR / "README.md" with open(readme_path, "w", encoding="utf-8") as f: f.write(readme) api.create_commit( repo_id=config.DST_REPO, repo_type="dataset", operations=[ CommitOperationAdd("cleaning_report_1930s.json", str(report_path)), CommitOperationAdd("README.md", str(readme_path)), ], commit_message="update 1930s anachronism-filter report", ) print(f"\nUploaded report + README. Banned list: {len(banned_terms):,} terms. " f"Removed so far: {totals['n_removed']:,} ({totals['docs_removed_pct']:.2f}%).") if __name__ == "__main__": main()