13 commits

Author	SHA1	Message	Date
Light1YT	0acd72a325	fix(best-layouts): per-object latest snapshot for supply (#1956) ... _SUPPLY_BATCH_SQL джойнил domrf_kn_flats по ОДНОЙ глобальной дате (f.snapshot_date = MAX(snapshot_date) по всей таблице). Но domrf_kn_flats — ПО-ОБЪЕКТНЫЙ time-series: каждый ЖК скрейпится в свой день. На единственной глобал-max дате присутствует обычно 1 объект → у остальных 0 квартир → supply_units_in_radius=0 для всех строк 4.2 Планировки → frontend показывал «Срок продажи 0 мес» и «% продано —». Регрессия от #1944 (objects-first дедуп snapshot'ов объектов, который сам по себе корректен). Фикс: flats_latest CTE (DISTINCT ON (obj_id) ... ORDER BY obj_id, snapshot_date DESC, id DESC) берёт для КАЖДОГО obj_id его собственный последний снимок и джойнится к nearby. objects-first MATERIALIZED дедуп (#1944) сохранён → fan-out по снимкам не возвращается. Глобальный db.scalar(MAX(snapshot_date)) + :latest_snap bind удалены. Прод (66:41:0205010:287, r=1км, 9 объектов): supply 0 (global-max) → 2675 (per-object, 4 объекта имеют flats на разных датах 2026-05-17/05-05; ни один не на глобал-max 2026-06-22). Данные flats частично сломаны (#1945, отдельно), но фикс корректно двигает supply с 0 к реальным per-object числам. Тесты: новый guard test_supply_joins_flats_per_object_latest_snapshot; обновлены mock-фабрики (db.scalar больше не вызывается).	2026-06-27 23:24:28 +05:00
Light1YT	7533bc333b	fix(site_finder): correct best-layouts supply fan-out + objects-first perf ... domrf_kn_objects is a snapshot dimension (UNIQUE (obj_id, snapshot_date), ~8 snapshots/obj_id). _SUPPLY_BATCH_SQL joined flats to ALL object-snapshot rows (no o.snapshot_date filter), counting each flat ~8.5x → supply_units_in_radius inflated ~8.5x, sold_pct_of_supply deflated ~8.5x, is_oversold under-fired (all user-facing, best_layouts.py:571-611; sold_pct=deals/supply is a raw ratio so no canceling). Fix: dedup objects to one row per obj_id (latest-snapshot coords) via DISTINCT ON in an objects-first MATERIALIZED CTE, then join domrf_kn_flats via idx_kn_flats_obj. units now = one count per flat (prod cross-check at radius 1.5km: units == count(*) == count(DISTINCT f.id) == 9612 for 65 objects; correction factor 8.56x at 1.5km, 9.13x at 1.0km). This also aligns the supply denominator with the deals numerator (_COMPETITORS_IN_RADIUS_SQL already uses DISTINCT ON latest snapshot). Perf bonus: objects-first avoids the parallel seq scan of the ~376k-row flats snapshot. radius 1.5km / snapshot 2026-05-17: 240ms/~28k buffers/6712 disk reads -> 49ms/1554 buffers/0 disk reads (~5x). Tests: add SQL-text fan-out guard (DISTINCT ON + MATERIALIZED, no bare flats->objects join); update stale EXPLAIN mirror in test_phantom_columns. USER-FACING: best-layouts supply/sold_pct/is_oversold/sell-out-months shift ~8.5x toward correct (frontend BestLayoutsBlock only; ТЗ recommendation + PDF unchanged — they derive from sum_deals, not supply). Deep-reviewed (APPROVE).	2026-06-27 10:45:19 +05:00
Light1YT	86e9ea2937	fix(week-review): автофиксы код-ревью — 169 issue (label «week ревью 1») ... Многоагентный аудит + имплементация: один воркер на файл, точечные правки. Верификация: py_compile (47/47 .py) + tsc --noEmit (0 ошибок). Unit-тесты не прогонялись (окружение не поднято: rollup native dep / нет pytest-venv). Полностью исправлено (169): #1336, #1337, #1339, #1340, #1341, #1342, #1343, #1345, #1346, #1348, #1349, #1350, #1351, #1354, #1356, #1358, #1359, #1360, #1362, #1364, #1365, #1366, #1367, #1368, #1369, #1370, #1371, #1372, #1373, #1374, #1375, #1376, #1377, #1378, #1379, #1380, #1381, #1382, #1384, #1385, #1386, #1387, #1388, #1389, #1390, #1391, #1392, #1394, #1395, #1396, #1397, #1399, #1400, #1401, #1402, #1403, #1404, #1408, #1409, #1410, #1411, #1412, #1413, #1414, #1415, #1416, #1417, #1418, #1420, #1423, #1425, #1426, #1427, #1428, #1429, #1430, #1431, #1432, #1433, #1434, #1435, #1437, #1438, #1439, #1440, #1441, #1442, #1443, #1444, #1445, #1446, #1447, #1448, #1449, #1450, #1451, #1452, #1453, #1454, #1455, #1456, #1457, #1458, #1459, #1460, #1461, #1462, #1463, #1464, #1465, #1466, #1467, #1468, #1469, #1471, #1472, #1473, #1474, #1476, #1478, #1479, #1481, #1482, #1483, #1484, #1485, #1487, #1488, #1489, #1490, #1491, #1492, #1493, #1494, #1495, #1496, #1497, #1499, #1500, #1501, #1502, #1504, #1505, #1506, #1507, #1510, #1514, #1515, #1516, #1517, #1518, #1519, #1521, #1522, #1523, #1524, #1525, #1526, #1527, #1528, #1529, #1531, #1532, #1533, #1534, #1535, #1536, #1537, #1538 Частично (9, in-file часть, остаток cross-file): #1361, #1419, #1422, #1424, #1470, #1475, #1477, #1480, #1498 Требуют cross-file (3, не тронуты): #1338, #1363, #1421 Пропущено (1): #1539 Не входило в партию: 22 needs-Leha issue (нужны решения владельца). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>	2026-06-15 20:21:11 +05:00
Light1YT	703d3905b8	fix(site-finder): normalize supply room_bucket vocabulary to velocity side (#1229) ... best_layouts._SUPPLY_BATCH_SQL эмитил {studio,euro-1,euro-2,1,2,3,4+}, а _INLINE_VELOCITY_SQL читает {студия,1,2,3,4+} из objective_corpus_room_month (prod check: 'euro-*' rows отсутствуют). Эффект: rooms=2 + area<50 уходили в euro-1/euro-2 supply-стороной → выпадали из знаменателя bucket '2' → sold_pct_of_supply двушек завышен, is_oversold ложно True. (rb='euro-*') dead lookups в supply_map. Patch: убраны euro-* WHEN в supply CASE. SF-08 euro-биннинг отложен до момента когда velocity-сторона начнёт его отдавать. +2 regression теста (bucket match, string guard). 35 best_layouts тестов зелёные. Closes #1229	2026-06-13 15:02:50 +05:00
lekss361	2104ed879b	fix(sf-21b): weighted AVG in _INLINE_VELOCITY_SQL (best_layouts.py) ... Replace unweighted AVG(deals_total_avg_area_m2) and AVG(deals_total_avg_price_thousand_rub_per_m2) with SUM(x * count) / NULLIF(SUM(count), 0) pattern in _INLINE_VELOCITY_SQL. Months with zero deals no longer dilute the weighted mean 2-4x. P0 follow-up to PR #290 (mv fix, issue #21).	2026-05-17 16:56:22 +03:00
lekss361	689327909c	fix(sf-09): capacity-aware redistribute (round 2) — bounded + correct invariant ... Round 1 (commit bcd7dc8) был broken: на 2-bucket входах surplus уходил в free полностью без учёта capacity → free превышал cap → следующая итерация clamp'ировала его и наоборот. Infinite oscillation в FastAPI handler. Round 2 fix per review BLOCK (#282 comment): - Surplus распределяется пропорционально available capacity (cap - v), не текущему v. Free никогда не вылетит выше cap. - free = строго < cap (не <=) — иначе деление на 0 capacity. - Hard guard `for _ in range(N+1)` — гарантированно завершается. - Pathological (surplus > total_capacity): возвращаем оригинальный pct_map + cap_skipped=True (sum=100 invariant сохранён). - Hamilton round вынесен в _hamilton_round() helper. Tests: - 2-bucket cases (90/10, 70/30, 99/1) expected cap_skipped=True - test_cap_iteration_count_bounded — все pathological завершаются < 100ms - All 13 cases verified standalone (3 fast-path + 7 reproduced + 3 pathological)	2026-05-17 15:30:50 +03:00
lekss361	bcd7dc8f75	fix(sf-09): iterative cap algorithm + cap_skipped flag + unit tests ... Review verdict MINOR (PR #282) — single-pass cap_and_redistribute не гарантировал invariant max ≤ MAX_BUCKET_SHARE_PCT. Surplus от clamped поднимал free выше cap (например {1k:75, studio:15, 2k:10} → studio=39). - backend/app/services/site_finder/best_layouts.py - _cap_and_redistribute → iterative while-loop до сходимости - Returns (result_map, cap_skipped) — флаг для pathological all-clamped - Float work map, Hamilton финальный pass для invariant sum=100 - backend/app/schemas/parcel.py - LayoutTzRecommendation.cap_skipped: bool = False - backend/tests/services/site_finder/test_best_layouts.py - 6 parametrized tests: invariants, 7 failing cases from review, no-dominant unchanged, empty, cap_skipped propagation, normal-case - frontend/src/types/best-layouts.ts — cap_skipped: boolean - frontend/src/components/site-finder/BestLayoutsBlock.tsx - banner условие сменилось с maxPct > 60 на rec.cap_skipped (honest signal)	2026-05-17 15:21:51 +03:00
lekss361	0d11f426b2	fix(sf-09): MAX_BUCKET_SHARE 35% cap + frontend warning banner ... _build_recommendation зеркалило рынок через чистый Hamilton apportionment. Добавлен _cap_and_redistribute: bucket >35% clamp к 35%, surplus пропорционально перераспределяется в остальные bucket'ы (Hamilton финальный pass гарантирует sum=100). Pathological case (все bucket'ы >35%) — warning в лог, cap пропускается. Frontend: warning banner при maxPct>60 в RecommendationCard (Tailwind amber utilities, без inline hex).	2026-05-17 14:49:56 +03:00
lekss361	b9259cd8ed	fix(sf-08): add euro-1/euro-2 room_bucket for small-format rooms=2 flats ... DOM.РФ API classifies euro-format flats (26-50м²) as rooms=2. _SUPPLY_BATCH_SQL now maps: rooms=2 + area<35 → 'euro-1' rooms=2 + area<50 → 'euro-2' before the generic rooms IN (1,2,3) branch. Audit: 4 140 units rooms=2 + area<35 in domrf_kn_flats were inflating the supply count for genuine 2-room apartments (median 57м²). euro buckets have no velocity counterpart in objective_corpus_room_month so they are filtered out of top_layouts by min_velocity. Also extends RoomBucket Literal and room_bucket_from_flat() in layout_signature.py with the new euro-1/euro-2 values. Closes #271 item 8	2026-05-17 14:38:48 +03:00
lekss361	c701636515	Merge forgejo/main into fix/sf-01-velocity-time-window ... Resolve conflict in best_layouts.py: keep SF-01 inline velocity (deals_window numerator) + add SF-05 sold_pct clamp at 100% and is_oversold flag from main.	2026-05-17 12:15:40 +03:00
lekss361	5a4408e0ab	fix(sf-01): time_window honest velocity — inline SQL с реальным фильтром report_month ... Раньше _VELOCITY_DIVISORS делил агрегаты mv_layout_velocity (24 мес) на 4/12 для quarter/year, не меняя реальное окно данных. Теперь inline SQL из objective_corpus_room_month с CAST(:window_interval AS interval). velocity_per_month = deals_window / months_in_window (1.0/3.0/12.0). Разные time_window → разные строки из БД → разный mix/velocity/jk_count. Closes (epic part) #271 item 1	2026-05-17 12:12:19 +03:00
lekss361	247c252b04	fix(sf-05): clamp sold_pct_of_supply at 100% + add is_oversold flag ... Symptom: sold_pct_of_supply = sum_deals_24mo / supply_count_snapshot * 100 yields >100% (e.g. 199%) for fast-selling small formats due to incompatible time windows (24-month deals vs point-in-time supply snapshot). Option A (hotfix): clamp to 100.0, expose is_oversold=True for UI badge. - best_layouts.py: compute sold_pct_raw, clamp with min(..., 100.0), set is_oversold = raw > 100% - parcel.py TopLayoutRow: add is_oversold: bool field - best-layouts.ts TopLayoutRow: add is_oversold: boolean - BestLayoutsBlock.tsx: show warn badge ">100%" when is_oversold=True - tests: two new cases — raw 199% clamps + is_oversold=True; raw 50% passes through + is_oversold=False Closes (epic part) #271 item 5	2026-05-17 11:57:29 +03:00
lekss361	ad16fc0e42	feat(parcels): best-layouts endpoint + service (#113 PR C) (#196)	2026-05-16 09:10:06 +00:00