"""Regression checks for OpenAlex workqueue counts. Run from the repository root with: python3 -m unittest scripts.test_workqueue_counts """ from __future__ import annotations import csv import json import sys import tempfile import unittest from pathlib import Path sys.path.insert(0, str(Path(__file__).resolve().parent)) import workqueue_counts # noqa: E402 ROOT = Path(__file__).resolve().parents[1] COUNT_FIELDS = workqueue_counts.QUEUE_FIELDS CATALOG_FIELDS = [ "record_id", "work_id", "collection", "group", "title", "authors", "year", "work_type", "pages", "pdf_url", "source_url", "identifier", "status", "checked_at", "sha256", "verification_note", "source_notes", ] def _write_jsonl(path: Path, rows: list[dict]) -> None: path.parent.mkdir(parents=True, exist_ok=True) path.write_text("".join(json.dumps(row) + "\n" for row in rows), encoding="utf-8") def _record(record_id: str, collection: str, digest: str, **changes) -> dict: row = dict.fromkeys(CATALOG_FIELDS, "") row.update({ "record_id": record_id, "work_id": "sha256:" + digest, "collection": collection, "group": "test", "title": record_id, "year": "2020", "work_type": "scholarly_book", "pages": "100", "pdf_url": "https://example.org/book.pdf", "source_url": "https://example.org/book", "status": "downloaded_and_screened", "checked_at": "2026-10-12T00:00:00Z", "sha256": digest, }) row.update(changes) return row class WorkqueueCountTests(unittest.TestCase): def test_real_export_has_one_row_per_openalex_subfield(self): with tempfile.TemporaryDirectory(prefix="workqueue-counts-real-") as tmp: # Rendering writes two planning outputs; copy only authoritative inputs. root = Path(tmp) for rel in ( "planning/subfield_jobs.jsonl", "planning/collection_subfield_map.json", "taxonomy/openalex_subfields.csv", "collections.json", "data/verified_links.jsonl", "data/legacy_candidates.jsonl", "planning/workqueue_state.json", ): source = ROOT / rel if source.exists(): destination = root / rel destination.parent.mkdir(parents=True, exist_ok=True) destination.write_bytes(source.read_bytes()) for source in (ROOT / "planning").glob("*search_progress.jsonl"): destination = root / "planning" / source.name destination.parent.mkdir(parents=True, exist_ok=True) destination.write_bytes(source.read_bytes()) summary = workqueue_counts.render(root, now="2026-10-12T12:00:00Z") with (root / "planning/openalex_workqueue.csv").open(newline="", encoding="utf-8") as f: rows = list(csv.DictReader(f)) self.assertEqual(list(rows[0]), COUNT_FIELDS) self.assertEqual(len(rows), 252) self.assertEqual(len({row["subfield_id"] for row in rows}), 252) self.assertTrue(all(all(isinstance(v, str) for v in row.values()) for row in rows)) self.assertEqual(summary["global_verified_entries"], 3530) self.assertEqual(summary["global_distinct_pdfs"], 3171) self.assertEqual(summary["unassigned_verified_entries"], 277) self.assertEqual(summary["zero_pdf_subfields"], 184) self.assertEqual(summary["subfield_pdf_assignments"], 3209) self.assertEqual(workqueue_counts.validate(root), summary) canonical = [ json.loads(line) for line in (ROOT / "data/verified_links.jsonl").read_text(encoding="utf-8").splitlines() if line.strip() ] self.assertEqual(len(canonical), 3530) for record in canonical: self.assertEqual(set(record), set(CATALOG_FIELDS)) self.assertTrue(all(isinstance(record[k], str) for k in CATALOG_FIELDS if k not in {"year", "pages"})) self.assertTrue(record["year"] is None or type(record["year"]) is int) self.assertTrue(type(record["pages"]) is int and record["pages"] > 0) self.assertEqual(record["status"], "downloaded_and_screened") self.assertRegex(record["sha256"], r"^[0-9a-f]{64}$") with (ROOT / "data/verified_links.csv").open(newline="", encoding="utf-8") as f: canonical_csv = list(csv.DictReader(f)) self.assertEqual(len(canonical_csv), 3530) self.assertEqual(list(canonical_csv[0]), CATALOG_FIELDS) self.assertTrue(all(all(isinstance(v, str) for v in r.values()) for r in canonical_csv)) def test_hash_dedup_assignment_and_unmapped_collection(self): with tempfile.TemporaryDirectory(prefix="workqueue-counts-fixture-") as tmp: root = Path(tmp) jobs = [ { "subfield_id": sid, "subfield_name": name, "domain_id": "1", "domain_name": "Test", "field_id": "10", "field_name": "Test Field", "topic_count": "1", "prompt_file": "test.txt", } for sid, name in (("100", "One"), ("200", "Two"), ("300", "Unmapped")) ] _write_jsonl(root / "planning/subfield_jobs.jsonl", jobs) definitions = [ {"collection": key, "group": "test", "path": "test/" + key} for key in ("a", "b", "c", "unmapped") ] (root / "collections.json").write_text(json.dumps(definitions), encoding="utf-8") taxonomy = root / "taxonomy/openalex_subfields.csv" taxonomy.parent.mkdir(parents=True) with taxonomy.open("w", newline="", encoding="utf-8") as f: writer = csv.DictWriter(f, fieldnames=list(jobs[0])) writer.writeheader() writer.writerows(jobs) mapping = { "schema_version": 1, "mapping_basis": "editorial_collection_level_not_per_work_classification", "collections": { "a": {"subfield_ids": ["100"], "basis": "test", "rationale": "a"}, "b": {"subfield_ids": ["100"], "basis": "test", "rationale": "b"}, "c": {"subfield_ids": ["200"], "basis": "test", "rationale": "c"}, "unmapped": {"subfield_ids": [], "basis": "test", "rationale": "ambiguous"}, }, } (root / "planning/collection_subfield_map.json").parent.mkdir(parents=True, exist_ok=True) (root / "planning/collection_subfield_map.json").write_text(json.dumps(mapping), encoding="utf-8") _write_jsonl(root / "data/verified_links.jsonl", [ _record("a1", "a", "a" * 64), _record("b1", "b", "a" * 64), # same PDF in a second collection, same subfield _record("b2", "b", "b" * 64), _record("c1", "c", "a" * 64), # same PDF may count in another assigned subfield _record("u1", "unmapped", "c" * 64), _record("paper", "a", "e" * 64, work_type="research_article"), ]) _write_jsonl(root / "data/legacy_candidates.jsonl", []) (root / "planning/workqueue_state.json").write_text( json.dumps({"schema_version": 1, "tasks": {}}), encoding="utf-8" ) workqueue_counts.render(root, now="2026-10-12T12:00:00Z") with (root / "planning/openalex_workqueue.csv").open(newline="", encoding="utf-8") as f: rows = {r["subfield_id"]: r for r in csv.DictReader(f)} self.assertEqual(set(rows), {"100", "200", "300"}) self.assertEqual(rows["100"]["valid_pdf_count"], "3") self.assertEqual(rows["100"]["book_scope_pdf_count"], "2") self.assertEqual(rows["200"]["valid_pdf_count"], "1") self.assertEqual(rows["300"]["valid_pdf_count"], "0") self.assertEqual(rows["300"]["collection_ids"], "") self.assertEqual(rows["300"]["availability"], "available") summary = json.loads((root / "planning/workqueue_summary.json").read_text(encoding="utf-8")) self.assertEqual(summary["global_distinct_pdfs"], 4) self.assertEqual(summary["subfield_pdf_assignments"], 4) self.assertEqual(summary["unassigned_distinct_pdfs"], 1) self.assertEqual(summary["unassigned_collections"][0]["collection"], "unmapped") def test_invalid_verified_rows_fail_closed(self): with tempfile.TemporaryDirectory(prefix="workqueue-counts-invalid-") as tmp: root = Path(tmp) jobs = [{ "subfield_id": "100", "subfield_name": "One", "domain_id": "1", "domain_name": "Test", "field_id": "10", "field_name": "Test Field", "topic_count": "1", "prompt_file": "test.txt", }] _write_jsonl(root / "planning/subfield_jobs.jsonl", jobs) (root / "collections.json").write_text(json.dumps([{"collection": "a"}]), encoding="utf-8") taxonomy = root / "taxonomy/openalex_subfields.csv" taxonomy.parent.mkdir(parents=True) with taxonomy.open("w", newline="", encoding="utf-8") as f: writer = csv.DictWriter(f, fieldnames=list(jobs[0])) writer.writeheader() writer.writerows(jobs) (root / "planning/collection_subfield_map.json").write_text(json.dumps({ "schema_version": 1, "collections": {"a": {"subfield_ids": ["100"], "basis": "test", "rationale": "test"}}, }), encoding="utf-8") _write_jsonl(root / "data/verified_links.jsonl", [ _record("bad", "a", "f" * 64, status="legacy_not_rechecked"), ]) with self.assertRaises(ValueError): workqueue_counts.render(root) def test_public_inputs_preserve_mixed_medical_collection_as_unmapped(self): mapping = json.loads((ROOT / "planning/collection_subfield_map.json").read_text(encoding="utf-8")) self.assertEqual(mapping["mapping_basis"], "editorial_collection_level_not_per_work_classification") self.assertEqual(mapping["collections"]["medical_sciences"]["subfield_ids"], []) if __name__ == "__main__": unittest.main()