d350d27325
feat(finmodel): financing overlay (кредит 15%) поверх unlevered DCF (epic #1881 PR-5)
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Финансирование как ДОПОЛНИТЕЛЬНЫЙ overlay поверх готового unlevered cashflow:
кредитная линия покрывает накопительный кассовый разрыв, проценты капитализируются
(compound), ставка _CREDIT_RATE_ANNUAL=15% (норматив, ОТДЕЛЬНО от ставки
дисконтирования — разная семантика: стоимость долга vs требуемая доходность).
Backend (financial.py):
- _compute_financing(operating_cf, annual_rate) — чистая (READ-ONLY вход, не
мутирует): процент на остаток на начало месяца ДО движений → капитализация;
draw=-cf при оттоке, repay=min(cf,debt) при притоке (долг не уходит в минус).
Возвращает peak_debt_rub / total_interest_rub / ending_debt_rub.
- compute_financial: вызов после DCF, net_profit_after_financing = net − interest.
- _build_monthly_cashflow и unlevered NPV/IRR/PBP НЕ ТРОНУТЫ → инвариант
Σ unlevered cashflow == net_profit сохранён (регресс-тест).
- FinancialModel +6 полей (financing_enabled/annual_rate_used/peak_debt_rub/
total_interest_rub/net_profit_after_financing_rub/financing_is_simplified).
Frontend: ParcelFinancialEstimate +6 полей; adaptFinanceDrawer + concept-каскад
показывают пиковый долг/проценты/чистую прибыль после финанс. (когда enabled).
MVP: только агрегаты, БЕЗ levered IRR (хрупко на хардкод-100%-долге — отдельный
PR). HEAVY caveat: проценты — реальная стоимость (net после < net до); 100%
покрытие разрыва (нет equity/LTC); compound; эскроу не моделируется; unlevered
headline не затронут. financing_is_simplified=True флаг.
mypy strict clean, +9 backend + 3 frontend тестов (compound точное значение,
no-mutation, инвариант-регресс, монотонность, net_after<net), api-types
регенерён авторитетно, deps не тронуты (hand-roll).
Refs #1881
2026-06-24 01:12:47 +05:00
d4068a255b
feat(finmodel): monthly DCF — real NPV/IRR/PBP, replace IRR-proxy (epic #1881 PR-3)
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Hand-rolled детерминированный DCF (без numpy-financial/новых deps): _npv /
_irr_monthly (bisection с bracket-guard) / _payback_months над помесячным
cashflow, построенным из статического каскада (PR-1) + калиброванной цены
(PR-2) по дефолтным нормативам фаз (ПИР 6мес → СМР по development_type
24/36/48 → распродажа, дисконт 15%).
- Налоги прорейтятся на признание выручки → Σ недисконтированного cashflow ==
net_profit (ИНВАРИАНТ, тест — гарантия что DCF не разошёлся со статикой).
- IRR настоящий когда есть смена знака; вырожденный поток → fallback на
roi-proxy (irr_is_proxy=True). Честно помечено.
- График продаж привязан к завершению стройки: sales_end = max(sales_start +
длительность, construction_end) — продажи не заканчиваются раньше ввода
(РФ ДДУ/эскроу). Без этого high_rise распродавался за 12 мес ДО ввода →
двойная смена знака → profitable-проект молча падал в proxy + инверсия NPV.
- FinancialModel +npv_rub/payback_months/discount_rate_used/schedule_is_default
(additive). development_type проброшен через placement.
- UI/PDF: NPV/IRR/PBP + честный caveat «график — типовое допущение, точность
зависит от него». api-types регенерён авторитетно.
mypy strict clean (generative.*), +15 тестов (DCF helpers на учебных значениях,
ИНВАРИАНТ, IRR real-vs-proxy обе ветки, PBP, sales≥construction для всех типов,
profitable high_rise → настоящий IRR). 48 passed.
Refs #1881
2026-06-23 21:52:04 +05:00
b1332d6b55
feat(generative): calibrate finmodel sale price from Objective market data (epic #1881 PR-2)
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Заменяет хардкод-цену продажи жилья (класс-норма) на реальную рыночную
медиану из Objective по локации участка. compute_financial остаётся ЧИСТЫМ
(без БД) — DB-lookup в API-слое, цена прокидывается параметром.
- compute_financial: +optional market_price_per_sqm/price_source; цена =
рынок если есть, иначе класс-норма. Паркинг/СМР НЕ калибруем (только жильё).
- concepts.py _lookup_market_price(db, lon, lat): центроид → ближайший
ekb_district (ST_DWithin 5км) → медиана objective_lots.price_per_m2_rub
(n>=10, фильтр 30k-600k) → fallback ekb_districts.median_price_per_m2 →
None. try/except → graceful (None, class_norm) при любой ошибке (вне ЕКБ/
нет гео/SQL) без краха генерации. psycopg3 CAST.
- FinancialModel +price_per_sqm_used/price_is_calibrated/price_source (additive).
- Threading market_price через generate→placement→compute_financial (optional
kwargs, backward-compat).
- UI/CSV: честный caption источника (рынок Objective / справочник района /
норматив класса). Старый лживый footnote «не калиброванная модель» → условный.
Prod-verified: калибруется 4 главных ЕКБ-района по name-match (Академический
204k лотов, Ленинский 38k, Кировский, Орджоникидзевский); остальные 5 admin-
районов честно → district_reference. Гео-радиус matching (полное покрытие) —
follow-up.
api-types.ts регенерён авторитетно. mypy strict clean (generative.*), +14
тестов (калибровка/lookup 4 ветки/SQL-ошибки graceful/backward-compat).
Refs #1881
2026-06-23 21:10:25 +05:00
65bab902e1
feat(generative): full static developer financial cascade (epic #1881 PR-1)
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Объединяет наше (площади из реальной геометрии teap) + полноту девелоперской
Excel-модели (каскад затрат + БДР с налогами). Расширяет financial.py из
статического GDV−COST в полный статический расчёт. БЕЗ DCF (PR-3), БЕЗ новых
вводных от пользователя — только нормативы + существующий TEAP.
Каскад (financial.py):
- Выручка: жильё (residential×price) + ПАРКИНГ (spaces×1.9М)
- Затраты: СМР(резид+паркинг) + ПИР 2.5% + сети/ТУ 6000₽/м² + услуги заказчика
1.5% + резерв 3% + маркетинг/риэлтор 7% выручки + земля
- БДР: валовая маржа → НДС (упрощённо) → прибыль до налога → налог 25% (ФЗ
176-ФЗ) → ЧИСТАЯ прибыль → ROI + чистая маржа%
- Нормативы документированы (источник: Excel-эталон «Авангардная 13» + RU-рынок)
FinancialModel (concept.py): +16 additive-полей (revenue breakdown, cost cascade,
БДР/налоги, roi, margin_pct, irr_is_proxy). Старые 4 поля сохранены (backward-compat).
IRR честно помечен irr_is_proxy=True (annualized net ROI, не DCF) — настоящий
IRR/NPV/PBP в PR-3 (помесячный cashflow). НДС — документированное упрощение, не
точный НК РФ. Офисы пропущены (нет площади в TEAP).
PDF + concept UI: полный БДР-каскад + чистая прибыль/ROI + честные сноски.
api-types.ts регенерён авторитетно (openapi-typescript + prettier, как CI).
mypy strict clean (generative.*), +тесты (каскад/паркинг/налоги/backward-compat/
edge cost=0), 36 passed.
Refs #1881
2026-06-23 16:45:58 +05:00
14f3ef2019
fix(week-review): backend-аудит v2 — 82 фиксов ( #1660 )
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Co-authored-by: bot-backend <bot-backend@gendsgn.local>
Co-committed-by: bot-backend <bot-backend@gendsgn.local>
2026-06-17 17:13:38 +00:00
479f01ae1a
Merge remote-tracking branch 'forgejo/main' into HEAD
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# Conflicts:
# backend/app/services/site_finder/gate_verdict.py
2026-06-15 21:07:05 +03:00
86e9ea2937
fix(week-review): автофиксы код-ревью — 169 issue (label «week ревью 1»)
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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
b405ae291d
feat(site-finder): additive objective_lots price fallback for competitors ( #307 OBJ-3) ( #1332 )
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2026-06-14 16:10:02 +00:00
5507bbc1a4
feat(site-finder): domrf→cad geom-match + parking_ratio конкурентов ( #96 ) ( #1327 )
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2026-06-14 14:49:28 +00:00
2c22c3f7ea
feat(site-finder): per-building помещения/машино-места + parking_ratio (on-demand MVP, #96 )
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Оживляет мёртвый foundation list_objects_in_building (#168 Q3-deferred). Fix реального
блокера: NSPDOptions не парсил objdocId (camelCase из NSPD search) → objdoc_id всегда None,
метод нельзя было вызвать. AliasChoices(objdoc_id, objdocId) + registers.
premises_lookup.get_building_premises(cad_num) — резолв objdoc → list_objects_in_building,
graceful (WAF/сеть/not-found → None). parking_ratio = машино-места/помещения (None при 0
помещений, 0.0 при реальном отсутствии паркинга). Verified live 66:41:0106036:183.
MVP on-demand (без bulk/схемы/prod-записей). parking_ratio готов, но НЕ wired в analyze:
конкуренты приходят из ДОМ.РФ без cad_num → нужен domrf↔cad_buildings geom-match (отдельная
задача). Сервис примет cad_num как только matching появится. 11 тестов, ruff clean.
Refs #96
2026-06-14 18:48:16 +05:00
658d724075
feat(analytics): velocity-anomaly alerts ( #17 ) + ARN ДДУ price indicator ( #99 )
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#17 : detect_velocity_anomalies + GET /analytics/velocity-alerts — z-score drop-detection
на domrf_kn_sale_graph (double-gate z≤-2 AND drop≤-30%, starvation-guards). Snapshot=richest
(не MAX — prod новейшие частичные), lookback anchored на latest report_month (scrape лаг ~4мес).
Prod: ЖК Центральный Парк -69%, ~14ms.
#99 : mv_ddu_price_indicator (миграция 152) + POST /market/ddu-indicator — ARN-mirror
ценовой индекс per quarter×area_bucket из rosreestr_deals (ДДУ регион 66). MVP: subject-level,
period Q, window 2025-Q2+, methods 1/2 (basis/previous, prev_period_value honesty). Q1-2026
headline 1.0185 vs ARN 1.03 (±5%). Method 3 blocked (нет pre-2025-Q2 данных) — задокументировано.
Closes #17
Closes #99
2026-06-13 22:04:49 +05:00
84d08940c6
fix(analytics): свежая ипотечная ставка + recommend last_updated + drop dead route ( #236 #237 #251 )
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#236 : _current_mortgage_rate сортировал cbr_mortgage_series по TEXT-полю period
лексикографически ('Январь'>'Февраль') → возвращал stale-точку. Сортировка по
parsed (year, month) + regex-guard на malformed period-строки. Остаётся на
subsidized weighted series (НЕ domrf market — иная метрика). Verified prod:
Февраль 2026 (было Январь 2026).
#237 : scope.last_updated = MAX(snapshot_date) domrf_kn_objects в recommend_mix +
подпись «данные на <дата>» в recommend page.
#251 : удалён never-implemented GET /parcels/{parcel_id} (501) + ParcelDetail схема
(frontend bare 1-сегментный route не зовёт).
Closes #236
Closes #237
Closes #251
2026-06-13 15:22:22 +00:00
b211183940
feat(site-finder): детерминированная атрибуция застройщика в analyze ( #1088 )
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Сервис get_developer_attribution поверх fn_developer_for_parcel (миграция 149):
топ-1 застройщик участка + track-record (РНС/РВЭ + домрф) + nearby_developers.
Дедуп по норм-ИНН (лучший match_method первым). Wire в analyze additive без флага
(чистый DB-резолвер по индексам, graceful → None). Beat-refresh developer_registry
ежемесячно 05:30 МСК после ekburg-permits. Pydantic-схемы + 18 тестов.
Источники: ekburg_construction_permits (РНС, ИНН) ⋈ domrf_kn_objects по
нормализованному ИНН + spatial/quarter fallback. 68% domrf-застройщиков имеют РНС.
EXPLAIN: point-lookup 0.06ms, резолвер ~30ms (functional/GIST индексы в миграции).
Closes #1088
2026-06-13 16:13:45 +05:00
4648e1aee7
fix(schemas): expose per-bucket elasticity + velocity_source в RecommendBucket ( #1204 )
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recommend_mix кладёт в bucket поля elasticity / elasticity_r2 / elasticity_n /
elasticity_source / velocity_source (analytics_queries.py:2592-2606), но
RecommendBucket их не объявляет и не имеет extra='allow' → Pydantic v2 молча
выкидывает их из response. Фронт (RecommendVelocityPanel.tsx:68
`r.elasticity ?? elasticity`) при движении price-слайдера всегда падает на
ГЛОБАЛЬНУЮ эластичность — live what-if расходится и с серверным
months_to_sellout (тот считается per-bucket), и с UI-таблицей «Эластичность
по сегментам».
Patch: добавлены 5 опциональных полей в схему. Совместимость: фронт уже
читает их с `?? globalFallback`, поэтому non-breaking. Producer/consumer-
контракт восстановлен. 113/113 recommend-тестов зелёные.
Closes #1204
2026-06-13 05:14:05 +00:00
4847a2eb01
feat(chat): deterministic §22 chat foundation — POST /api/v1/chat/ask (no LLM)
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Step 1 of #957 . Answers parcel questions by reading the already-persisted
§22 SiteFinderReport (latest_run_for, schema "1.0", read-only) and returning
templated RU answers with engine numbers verbatim (§16, never fabricated).
Intent routing (explicit or RU keyword match) -> per-section renderers;
graceful on partial/missing sections and pending (no run / DB error) without
500s. Works with llm_enabled=False (llm_used always False); LLM composition
is Step 2. Mounted off /api/v1/chat so rbac_guard auto-requires an authed
known user.
Refs #957
2026-06-08 17:21:51 +05:00
df34e55ab4
feat(site-finder): own-portfolio data source for §25.3 cannibalization ( #1169 PR1)
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Foundation PR: unified "our projects" source the §25.3 overlap engine (PR2)
will consume. Two origins normalized to OwnProject (class/timing/price/unit-mix):
- current <- domrf_kn_objects filtered by settings.own_developer_ids (numeric
prefix of composite dev_id; empty -> [] graceful, no DB hit, no hardcoded id)
- future <- new manual-entry own_planned_project entity (migration 148)
Adds OWN_DEVELOPER_IDS config (comma-sep -> list[int], default []),
own_planned_project table (range/unit_mix CHECKs via IMMUTABLE helper, generated
geom), /api/v1/own-projects CRUD (created_by from X-Authenticated-User), and
get_own_portfolio(db). Per-source graceful degradation; psycopg-v3 CAST clean.
Does not touch special_indices.py or parcels.py (out of scope).
Refs #1169
2026-06-08 16:21:53 +05:00
8da1c00138
feat(location): district-level Location entity + indices ( #948 part B)
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Promote district to a first-class `location` entity (ТЗ §8.2), ADDITIVE — no
district->FK refactor. New `location` table keyed by district_name (joinable by
string), carrying 4 normalized [0,1] indices (NULL when no data, never 0):
- infra: _district_poi_score / _city_avg_poi_score (per-district POI aggregate)
- competition: market_metrics.overstock_index (available/stuck competing supply
— orthogonal to demand; NOT sell-through, which is market-heat correlated w/ demand)
- demand: market_metrics.unit_velocity (saturating /50)
- future_supply: future_supply_pressure.index (passthrough, already 0..1)
- data/sql/146_location.sql: idempotent table + UNIQUE(district_name) + range
CHECK + centroid GIST
- services/site_finder/locations.py: compute_location_indices (reuses forecast
per-district fns) + refresh_locations (SAVEPOINT per-row, CAST, ON CONFLICT)
- workers/tasks/location_refresh.py + beat (Mon 07:00 MSK, after supply-layers)
- api/v1/locations.py: read-only GET list + GET by name (analyst+admin via rbac,
frontend pilot-gated)
- tests: 34 (normalization 0..1/null, competition⊥demand orthogonality, idempotent
upsert, read API list/by-name/404)
Part of #948 (Part A insight shipped #1164 ).
2026-06-08 13:28:19 +05:00
6400ebde24
feat(insights): manual-entry Insight entity CRUD + §19 audit ( #948 part A)
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Insight = аналитик пишет free-form intel про локацию/участок с пометкой
«непублично» (is_confidential, §7.13/§8.9). CRUD под /api/v1/insights;
created_by из X-Authenticated-User (не из тела — спуфинг автора невозможен).
Зеркало custom_pois: raw-SQL service + Pydantic v2 schemas, sync def handlers
(threadpool, off event loop).
- data/sql/145_insight.sql: table insight (idempotent, geom GENERATED из lon/lat,
индексы district/cad_num/is_confidential/created_by/GIST); аддитивно расширяет
CHECK audit_log.action += insight_write (тот же constraint ck_audit_log_action,
to_regclass-guarded, superset — не ломает #962-аудит; НЕ правит applied 144).
- audit_middleware.classify_path: method-aware insight_write для POST/PUT/DELETE
/api/v1/insights (GET-чтения не аудируются); обратно совместимо с parcels.
- ACL: backend rbac_guard hard-блокирует только /api/v1/admin/*; pilot отсекается
frontend RouteGuard + Caddy (как parcels/custom_pois). is_confidential — стораемая
пометка без per-record backend-гейта (analyst видит, per #962-политике).
- tests: 28 insight (CRUD+filters+required+#261 commit) + 5 audit. 86 зелёных, ruff.
Part B (Location first-class, §8.2) — отдельный follow-up.
Refs #948 .
2026-06-08 12:41:39 +05:00
7b40e7e480
feat(sf): wire ИРД-слой в analyze за флагом enable_ird_analyze ( #1101 )
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D9b capstone — поле `ird` в ответе analyze за флагом enable_ird_analyze (default OFF): parcel_ird_overlaps (м.132, incl opportunity) + функц.зона/КРТ (геопортал WFS) + ПЗЗ-регламент (C8b cache-first). Логика в self-contained ird_analyze.py; parcels.py +13 строк flag-gated, defense-in-depth ×3 graceful. Schema additive (ird Optional). Замыкает ИРД-эпик #1067 (#1078/#1090/#1092/#1099/#1100/#1058/#1060). 4 теста.
Refs #1067 .
Co-authored-by: lekss361 <lekss361@gendsgn.local>
Co-committed-by: lekss361 <lekss361@gendsgn.local>
2026-06-06 19:50:57 +00:00
22fffb9878
feat(parcels): typed AnalyzeResponse + run-history read endpoints ( #961 )
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#992 : attach response_model=AnalyzeResponse to POST /{cad_num}/analyze. Model
uses extra="allow" so any result_payload key not explicitly modeled is preserved
in the 200 response (no silent drops that would break Site Finder), and ALL
fields are Optional so the #93 202 fetch-stub serializes without a 500.
#994 : add GET /{cad_num}/runs (light summary list, empty 200 not 404) and
GET /runs/{run_id} (full row incl result, 404 if missing), backed by
list_runs_for/get_run in analysis_runs.repository (psycopg v3 CAST(:x AS type)).
Routes ordered before /{parcel_id} so /runs/{run_id} is not shadowed.
Closes #992 . Closes #994 . Refs #961 .
2026-06-06 18:13:34 +00:00
691ccef4b7
feat(forecasting): class/commercial/USP §10.2/10.4/10.5 + §16 ( #983 , 953-B) ( #1015 )
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2026-06-03 07:52:24 +00:00
72e9b24f2c
feat(recommend): horizon-aware recommend_mix opt-in overlay ( #982 , 953-A) ( #1014 )
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2026-06-03 07:40:33 +00:00
59be55f80e
feat(site-finder): per-competitor relevance_weight ( #949 PR B) ( #1000 )
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2026-06-02 19:45:38 +00:00
c61c8c86af
feat(sf-b1): GET /parcels/by-bbox — map entry endpoint + parcel_user_status table ( #336 )
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2026-05-17 21:25:48 +00:00
29dbbee2ac
feat(trade-in): TI-1 mock /trade-in/estimate endpoint + Pydantic + SQL migration ( #316 )
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2026-05-17 16:45:06 +00:00
lekss361
bcd7dc8f75
fix(sf-09): iterative cap algorithm + cap_skipped flag + unit tests
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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
247c252b04
fix(sf-05): clamp sold_pct_of_supply at 100% + add is_oversold flag
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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
485f489bd2
feat( #254 ): user_custom_pois — backend schema + CRUD + scoring integration
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- SQL migration 101_user_custom_pois.sql: table with GEOGRAPHY(POINT) + GIST index
- Pydantic schemas: CustomPoiCreate / CustomPoiUpdate / CustomPoiOut
- Service custom_pois.py: CRUD + get_overlaps_for_scoring (1km radius, psycopg v3 CAST)
- API /api/v1/custom-pois: POST(201)/GET/PATCH/DELETE, X-Session-Id header auth
- Scoring in analyze_parcel: custom POI block after OSM POI loop,
decay weight * max(0, 1 - dist/1000), custom_poi_score_items in response
- Tests: CRUD + validation (weight/lon/lat 422) + scoring integration (mock-based)
- Vault: Schema_User_Custom_Pois.md + Endpoint_Parcel_Analyze v3.9 section
2026-05-17 09:34:33 +03:00
lekss361
f70be684da
feat(#29,#232): wire cad_parcels.permitted_use in analyze + cad_zouit fallback (G2+G3)
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TASK A (#29 G2): add parcel_meta to analyze response
- New ParcelMeta Pydantic schema in app/schemas/parcel.py
- SELECT from cad_parcels WHERE cad_num=:c in analyze_parcel() (step 9f)
- Returns permitted_use_established_by_document, land_record_category_type,
land_record_subtype, cost_value; None when row absent
- Tests: test_analyze_parcel_meta.py (found + not-found cases)
TASK B (#232 G3): cad_zouit fallback in _get_zouit_overlaps
- When nspd_quarter_dumps has zouit_count==0, fall back to ST_Intersects
query on cad_zouit (3483 rows, GIST indexed)
- Overlaps tagged with source='cad_zouit'; format compatible with NSPD path
- gate_verdict.py: BLOCKER_TYPE_ZONE_KEYWORDS tuple for keyword-based
classification (охранная зона / трубопровод / электр / газ -> blocker;
СЗЗ -> warning); NSPD subcategory path preserved backward-compat
- Tests: 6 new test cases in test_gate_verdict.py covering cad_zouit path
and backward-compat for NSPD subcategory path
Updated db.execute call sequence in test_analyze_*.py (index shift +1 at pos 10).
2026-05-17 08:17:22 +03:00
lekss361
fdb54834e5
fix(nspd): rename migration 89→98, fix red lines ST_Area→ST_Length ( #220 )
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- data/sql/98_*: rename from 89 to avoid collision with existing 89_drop_dead_brin
- _get_red_lines: ST_Length(ST_Intersection(planar)::geography) instead of
ST_Area(ST_Intersection(::geography, ::geography)) — fixes PostGIS 3.4
tolerance error and returns correct non-zero length for LINESTRING intersections
- Rename intersection_area_sqm → intersection_length_m across schema, TS types,
frontend component, and tests; add test_get_red_lines_db_exception_returns_empty
Addresses review-bot feedback on PR #220 .
2026-05-16 19:33:14 +03:00
lekss361
ed3c128528
feat(nspd): TIER 4 opportunity layers + red lines ( #94 PR2 of 4)
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- NSPDClient: QUARTER_OPPORTUNITY_LAYERS (auction/scheme/free/future/oopt)
+ QuarterDump.opportunity field
- nspd_sync: harvest_quarter accepts include_opportunity, denorm cols
has_auction_parcels + opportunity_count in UPSERT
- quarter_dump_lookup:
- _get_opportunity_parcels (sort by distance, early-exit on count=0)
- _get_red_lines (query existing dump.red_lines core path, layer='red_lines')
- SQL 89_*: has_auction_parcels + opportunity_count + partial index
- Pydantic: OpportunityParcel + RedLine schemas
- /analyze: nspd_opportunity_parcels + nspd_red_lines fields
- Frontend: NspdOpportunityBlock + NspdRedLinesBlock + LandTab integration
- Tests: 28 total (11 PR1 + 17 PR2), all pass
Red lines uses existing core harvest path (layer 879243 already in dump.red_lines
from PR1+core) — no duplicate harvest, no red_lines_count_v2 column needed.
Part of #94
2026-05-16 19:06:22 +03:00
lekss361
1595157ebf
feat(nspd): enable TIER 3 risk zones harvest + extract in analyze ( #94 PR1)
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- harvest_stale_quarters fanout passes include_risks=True to all queued tasks
- _get_risk_zones() with ST_Intersects + ST_Area intersection calc
- _extract_features_by_layer() generic helper for future PR2+ reuse
- RiskZone Pydantic schema; /analyze returns nspd_risk_zones list
- NspdRiskZonesBlock component with severity color-coding (red/yellow/orange)
- 11 unit tests for extract/intersect/null-area/db-exception paths
Part of #94 (TIER 3 risk layers — flooding, landslide, burns, erosion etc)
2026-05-16 16:11:59 +03:00
46203ab365
feat(permits): Celery beat monthly + analyze recent_permits ( #105 Phase 4+5) ( #213 )
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2026-05-16 12:23:52 +00:00
27a0957bb5
feat(analyze): add market_price из mv_quarter_price_per_m2 ( #33 PR B) ( #210 )
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2026-05-16 11:28:16 +00:00
092976f656
feat(site-finder): inline POI weights pass-through в /analyze ( #201 Phase 1) ( #206 )
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2026-05-16 11:00:41 +00:00
e673811a20
feat(parcels): layout signature schemas + extractor ( #113 PR A) ( #193 )
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2026-05-16 07:52:34 +00:00
4deb1b0284
feat(parcels): connection-points endpoint (Forgejo #115 Phase 1 backend) ( #190 )
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2026-05-16 05:58:27 +00:00
e561df1b55
feat(parcels): competitors endpoint (Forgejo #112 Phase 1 backend) ( #191 )
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2026-05-15 22:21:05 +00:00
lekss361
99e2210919
fix(cadastre): NSPD response parse — properties.category + top-level meta ( #168 ) ( #177 )
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* fix(cadastre): NSPD response parse — properties.category + top-level meta (#168 )
* fix(cadastre): test fixtures use real NSPD shape — properties.category + top-level meta (#168 )
Bot review of #177 flagged that fixtures still used legacy properties.categoryId
+ data.meta — meaning CI exercised only fallback branches, not primary paths
where the actual bug lived. Pattern of 3 consecutive "live-only" parse fixes
(#175 verify, #176 headers, #177 parse) confirmed need for test coverage.
Changes:
- test_nspd_bulk_client.py: sample_quarter_response → properties.category +
meta moved to top-level (real NSPD shape verified live)
- test_cadastre_bulk.py: 7 fixtures categoryId → category (regex replace)
- test_nspd_bulk_feature_parse_basic: primary path now exercised
Plus schema hardening per bot review:
- NSPDBulkFeature.category_id: `is not None` check (not truthy `or`)
to avoid edge case category=0; int() wrapped in try/except so
non-numeric ID (e.g. "ЗУ") doesn't crash upsert_features loop.
35/35 tests pass locally.
---------
Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-15 15:40:01 +03:00
lekss361
b7889d113b
feat(cadastre): NSPDBulkClient + schemas for bulk ingest ( #168 PR2/5) ( #170 )
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Add async NSPD client (nspd_bulk_client.py) with 3 new methods:
- search_by_quarter: REST /api/geoportal/v2/search/geoportal — snapshot 20 per cat + meta totals
- wms_feature_info: WMS GetFeatureInfo для grid-walk discovery
- list_objects_in_building: tab-group-data (Q3 deferred — код ready)
Rate limit: asyncio.Semaphore(3) + 0.05s jitter.
429 → exponential backoff 2→4→8s, max 3 retries.
403 (WAF) → raise immediately, no retry.
Pydantic schemas (nspd_bulk.py): NSPDBulkFeature, QuarterSnapshot, ObjectsListing
with extra='allow' to preserve unknown fields → raw_props JSONB downstream.
15 unit tests + 4 e2e (real NSPD, skipped in CI by default).
Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-15 12:50:41 +03:00
lekss361
c31da62e8d
feat(analytics): recommend_mix v3.1-v3.4 - noise + 2D competitors + 24m cap + success-driven
2026-05-11 22:19:41 +03:00
lekss361
2847262953
feat(analytics): extend recommend comparables with cad_quarter, lat/lon, buildings_n
2026-05-11 17:30:09 +03:00
lekss361
fe2a881cec
feat(api,analytics): bulk geo backfill + complex_buildings query
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- POST /api/v1/admin/scrape/geo/bulk — splits pending Sverdlovsk cad-nums
into N chunks (parallelism 1..10, default 5), creates N jobs and enqueues
each in queue=geo. source_kind='rosreestr_pending_chunk' for tracking.
- analytics_queries.complex_buildings(db, obj_id) — returns list of buildings
from cad_buildings (cad_num, floors, area, purpose, name, address, geom).
- object_detail: LEFT JOIN v_complex_buildings, adds buildings_count.
- top_developers: adds complexes_count via correlated subquery.
- GET /api/v1/analytics/object/{obj_id}/buildings → list[ComplexBuilding].
2026-05-11 15:56:17 +03:00
lekss361
2fee7739e8
feat(jobs): centralized job_settings API + DB-driven beat schedule
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- JobSetting ORM model (JSONB extra_config) + Pydantic schemas
- GET/PUT /api/v1/admin/jobs/settings + /{job_type} (X-Admin-Token auth)
- celery_app.py builds beat_schedule from job_settings DB (env fallback
retained for safety on first deploy / DB unreachable)
- nspd_geo task reads rate_ms from job_settings when per-job row has
no override
- enqueue/resume geo jobs route to queue_name from job_settings
- Worker container: --queues=celery,scrape_kn,geo (one container,
three named queues — kn sweep no longer blocks nspd_geo)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 15:38:13 +03:00
lekss361
132d57a3f3
fix recommend page
2026-04-29 08:16:22 +03:00
lekss361
7a23aa9edc
fix: heartbeat-based zombie autoclean (10min) + Phase A heartbeats; ship recommend velocity calculator
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Scraper resume:
- /admin/scrape/queue autoclean уменьшен с 60min started_at до 10min
COALESCE(heartbeat_at, started_at). Не режет валидные long sweeps.
- Phase A пишет heartbeat после каждого objStatus fetch (3min Phase A
больше не рискует быть отмеченной как zombie при новом 10min threshold).
Recommend (Уровень 1 калькулятор):
- POST /api/v1/analytics/recommend/mix с velocity baseline (sale_graph),
price elasticity (regr_slope/r2 на sale_graph, fallback -1.5),
inverse mode (target_months → required price_factor), liquidity score
24mo, headline.
- /analytics/recommend: RecommendVelocityPanel (price slider 0.85..1.15
+ 4 KPI Чек/Срок/Темп/Ликвидность + методология эластичности),
RecommendLiquidityChart (cumulative 0..36 mo с пунктиром на 24).
- BucketsTable: +колонки Темп и Срок, цены/выручка масштабируются по
priceFactor live.
- Все слайдеры и target_months считаются клиентски — никаких round-trip.
Fix: SQLAlchemy не парсит :cls::text — заменено на CAST(:cls AS TEXT).
2026-04-28 22:54:03 +03:00
lekss361
ecc0dbafd5
add predict
2026-04-27 21:28:02 +03:00
lekss361
6c4ba1777a
deploy.yml: sync compose+Caddyfile from git, reload caddy after up
2026-04-26 13:31:26 +03:00
lekss361
b95559eac9
init
2026-04-25 13:45:19 +03:00