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Author SHA1 Message Date
lekss361
6fce81e10c
feat(db): add nspd_quarter_dumps table for PKK harvest persistence (#94 pt.3/4) (#110)
Sprint 1.1 item #2 из плана #94 part 2. Persistent storage для QuarterDump
snapshots (PR #109). Foundation для Celery harvest_quarter task (next PR)
и analyze_parcel integration (после).

Schema (data/sql/88_nspd_quarter_dumps.sql):
- Table `nspd_quarter_dumps`: 17 columns matching QuarterDump dataclass.
  - PK quarter_cad (natural key, one row per quarter)
  - quarter_geom (MultiPolygon, 4326) + bbox_3857 (Polygon, 3857) — dual-index
    стратегия: bbox для scheduler queries без transform, geom для joins с
    PZZ/district в 4326
  - 7 per-layer count columns + total_features (computed denorm для быстрых
    статистических queries без распаковки JSON)
  - features_json JSONB — array of ~117 NSPDFeature objects (~120KB per row,
    TOAST handles transparently). Geometry в raw EPSG:3857 — caller transforms.
  - layers_fetched TEXT[] mirrors QuarterDump.layers_fetched tuple
  - harvest_duration_ms (nullable — NULL = "not measured"), harvest_error TEXT
  - region_code SMALLINT NOT NULL (no DEFAULT — explicit per insert)
- 6 indexes: PK, GIST(bbox_3857), GIST(quarter_geom), B-tree(fetched_at_utc DESC),
  B-tree(region_code), partial B-tree(fetched_at_utc WHERE harvest_error IS NULL)
- View v_quarter_dumps_freshness — admin monitoring (AGE + is_failed flag)

Конвенции:
- BEGIN/COMMIT atomic
- IF NOT EXISTS на каждом CREATE — idempotent
- COMMENT ON TABLE + 7 COMMENT ON COLUMN + comments на каждом index
- psycopg v3 compatible (DDL only, no %s)

Применено к prod в рамках database-expert verification (DDL only, idempotent).

Vault entry: code/schemas/Schema_Nspd_Quarter_Dumps.md (upsert template +
EXPLAIN plans + cross-refs).

Code review (code-reviewer pre-push): APPROVE, 2 minor non-blocking:
- MINOR-1 quarter_geom MultiPolygon vs Polygon — resolved в Celery PR via
  ST_Multi(ST_Transform(...)) на ingest contract
- MINOR-2 layers_fetched default '{}' — documented в comment как
  partial-failure path для error rows

Next: Celery harvest_quarter task + beat schedule.

Part of #94 Sprint 1.1.

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 18:22:50 +03:00
lekss361
9ee0b07003
feat(scrapers): search_by_quarter orchestrator + QuarterDump (#94 pt.2/4) (#109)
Sprint 1.1 item #1 из плана #94 part 2. Foundation для PKK harvest pipeline —
1 vacuum (search) + N layer fetches → comprehensive snapshot всех NSPD данных
в пределах квартала. Базис для G1 #28 ПЗЗ, G3 #30 ЗОУИТ, P2 #46 neighbors,
E1 #51 parcels backfill, #96 ЕГРН помещения.

Backend (nspd_client.py):
- New QuarterDump frozen dataclass (slots=True): quarter + per-layer feature
  lists (parcels/buildings/territorial_zones/red_lines/engineering + zouit
  dict + risks dict) + bbox_3857 + layers_fetched (immutable tuple) +
  fetched_at_utc + total_features property.
- New NSPDClient.search_by_quarter(quarter_cad, include_zouit=True,
  include_risks=False): search → bbox → bulk fetch per layer phase.
  Cost 6/11/22 requests.
- New _geojson_bbox_3857() module-level helper — recursive coord walker.
- Class constants QUARTER_CORE_LAYERS / QUARTER_ZOUIT_LAYERS /
  QUARTER_RISK_LAYERS.

Empty-quarter (NSPD не нашёл cad): quarter=None, bbox=None, all lists empty,
zouit/risks dicts populated с пустыми lists (структурно стабильно),
layers_fetched=('search',).

Tests: +12 tests (31 total, no network).

Code review (code-reviewer pre-push): MINOR, fixed 3 of 5:
- datetime import → module-level
- layers_fetched → tuple[str, ...] (immutable in frozen dataclass)
- docstring clarified empty-quarter semantics
Bonus: ruff UP038 isinstance tuple → union syntax.

Part of #94. Sprint 1.1: 4 PRs total. Next: migration → Celery → integration.

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 18:11:30 +03:00
lekss361
bc092b58f1
feat(scrapers): NSPD client foundation (#94) — search + WMS + layers (#98)
* feat(scrapers): NSPD client foundation (#94) — search_by_cad + WMS + layers

Foundation для G1 #28 ПЗЗ, G2 #29 ВРИ, G3 #30 ЗОУИТ, E1 #51 cad_parcels,
I3 #44 engineering, и поддержки on-demand #93.

Backend (`app/services/scrapers/nspd_client.py`):
- `NSPDClient` с 4 core методами:
  - `search_by_cad(cad, thematic_id)` — REST /api/geoportal/v2/search
    возвращает GeoJSON + ВРИ + land_category + cost_value за 1 запрос
  - `get_feature_info(layer_id, lon, lat, buffer_m=100)` — WMS GetFeatureInfo
    на точке: какие feature'ы layer'а покрывают (lon,lat)
  - `get_features_in_bbox(layer_id, bbox_3857)` — bulk через WMS workaround
    (WFS GetCapabilities → 404, поэтому большой bbox + центральная I/J точка)
  - `list_layers(theme_id)` — каталог слоёв в теме (PKK=1, ARN=665)
- Typed responses: NSPDFeature, NSPDSearchResult, NSPDLayer (frozen dataclasses)
- LAYERS catalog: 32 layer-id с семантическими именами (territorial_zones=875838,
  zouit_engineering=37578, risk_flooding=872205, etc) — TIER 1-6 per #94
- Coordinate helpers: lonlat_to_3857(), bbox_around_point_m()
- Reuse: HEADERS + SSL ctx + fetch_geoportal из existing nspd_lite (WAF-compatible
  urllib trick). Rate limit через rate_ms.
- WAF/Rate-limit: raises NspdLiteWafError на 403/429 — caller backoff.

Tests (`backend/tests/test_nspd_client.py`): 14 unit tests, no network.
- LAYERS catalog sanity (territorial_zones=875838 закрывает G1)
- Coordinate transforms (zero, ЕКБ center, bbox)
- NSPDFeature.from_raw parsing (full / missing fields)
- NSPDSearchResult helpers (empty/first)
- _walk_layer_tree (flat / nested / empty)
- search_by_cad через monkeypatch fetch_geoportal

Также включён micro-fix из PR #95 review (cosmetic):
- parcels.py inline comment "до 25s" → "до 15s" (matched _INLINE_FETCH_WAIT_S)

Scope NOT в этом PR (отдельные follow-up issues, sequential rule):
- Schema migrations (cad_parcels_geom +columns, nspd_territorial_zones,
  nspd_zouit, nspd_red_lines, nspd_risk_zones tables) → отдельный PR
- Celery tasks (sync_territorial_zones_bbox, sync_zouit_*, sync_risk_*) →
  отдельный PR использует client
- Admin endpoints (trigger / status) → отдельный PR
- Замена on-demand fetch на nspd_client → PR after schema ready

Closes part of #94 (foundation only — sub-issues for schema/tasks).

* fix(scrapers): address PR #98 auto-review minor feedback

Backend (nspd_client.py):
1. (line 100+) bbox_around_point_m signature split на multi-line.
2. (lazy imports) import json, time → module-level.
3. (duplicate SSL ctx) Reuse _SSL_CTX из nspd_lite через explicit import.
4. (shape defense) list_layers чекает {"data": [...]} wrapper + non-dict/list garbage → warning + empty.
5. (cad_num docstring) search_by_cad документирует формат + ссылку на validate_cad_format.

Tests: +5 mock тестов (19/19 passed):
- get_feature_info URL builder + parsing
- get_features_in_bbox bbox propagation
- list_layers_walks_tree_response
- list_layers_handles_data_wrapper
- list_layers_handles_garbage_response

Backend (parcels.py): docstring '~25с' → '~15с'.

Per auto-review on be14388.

---------

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 09:47:45 +03:00
lekss361
49fac806fc
feat(site-finder): auto-fetch cadastre geometry on-demand (#93) (#95)
* feat(site-finder): auto-fetch cadastre geometry on-demand (#93)

Когда пользователь вводит cad-номер которого нет в БД (cad_quarters_geom /
cad_buildings / cad_parcels_geom), вместо 404 «Загрузи через NSPD geo» (dead-
end для non-admin) — теперь backend автоматически инициирует NSPD fetch,
frontend показывает loading state с polling /fetch-status каждые 2с.

Backend:
- Новый модуль app/services/site_finder/cadastre_fetch.py с helpers:
  find_or_enqueue_fetch (atomic check + enqueue с дедупликацией по cad),
  fetch_status (smart polling endpoint — отличает not_in_nspd от failed),
  detect_thematic_id (3-сегм quarter / 4-сегм parcel / 5-сегм building),
  validate_cad_format.
- Reuse: enqueue_geo_job + process_nspd_geo_job (workers/tasks/nspd_geo).
  source_kind='auto_on_demand' отличает от bulk; rate_ms=200, priority=9.
- POST /parcels/{cad}/analyze graceful fallback: inline await до 25s
  (fast path), затем 202 + job_id + eta_seconds для polling, либо
  400/404/503 в зависимости от статуса (с Retry-After 60s на 503).
- GET /parcels/{cad}/fetch-status новый endpoint для polling.

Frontend:
- useSiteAnalysis расширен: fetchingState + cancel(). POST analyze + при 202
  polling каждые 2с (max 60 итераций = 2 мин cap). status=ready → re-trigger
  analyze; not_in_nspd/failed/invalid_format → typed errors.
- apiFetchWithStatus<T> + HTTPError в lib/api.ts — status-aware variant
  для 200 vs 202.
- FetchingState.tsx: animated spinner, progress bar (linear до etaSeconds,
  asymptote после), elapsed counter, cancel button. Светло-голубая
  scheme отличается от обычного pending skeleton.
- site-finder/page.tsx: FetchingState когда fetchingState активен; обычный
  pending skeleton — только при первичном analyze без 202.

Edge cases (per #93 acceptance):
- cad валидный в НСПД, fetch <25s → inline 200 OK
- cad валидный, fetch >25s → 202 + frontend polls → ready → analyze
- cad валидный, не в НСПД → 404 с понятным сообщением + формат hint
- cad invalid format → 400 + формат hint
- NSPD rate-limited / failed → 503 + Retry-After 60s
- Параллельные запросы на тот же cad → один job, оба клиента poll'ят (дедуп
  через find_active_on_demand_job).

Closes #93.

* fix(site-finder): address PR #95 auto-review minor feedback

Backend (cadastre_fetch.py):
1. (race condition) Advisory lock `pg_try_advisory_xact_lock(hashtext(cad_num))`
   обёрнут вокруг шагов "check active job → enqueue" в find_or_enqueue_fetch.
   Lock transaction-scoped, released at COMMIT. Параллельные запросы на тот
   же cad: первый получает lock и enqueue; второй lock=false → re-check
   active job (уже виден после первого COMMIT) → возвращает тот же job_id.
   Docstring обновлён, упоминание SELECT FOR UPDATE удалено.

Backend (parcels.py):
3. (threadpool exhaustion) _INLINE_FETCH_WAIT_S снижен 25 → 15s с подробным
   комментарием: tradeoff про default Starlette anyio threadpool (40 slots)
   и concurrent burst saturation. 15s баланс: НСПД avg 5-15s для quarter,
   ~70% fast path; остальные 30% получают 202 + polling без блока.

Data (87_on_demand_indexes.sql):
2. (missing index) New migration:
   - `nspd_geo_targets_cad_num_idx ON nspd_geo_targets(cad_num)` — для
     find_active/recent_completed_job (existing UNIQUE composite не покрывает
     WHERE cad_num=:c).
   - `nspd_geo_jobs_source_status_idx ON nspd_geo_jobs(source_kind, status)`
     composite для filter auto_on_demand + queued/running.
   Idempotent (CREATE INDEX IF NOT EXISTS), не блокер при текущем размере,
   критично при росте on-demand traffic.

Frontend (useSiteAnalysis.ts):
4. (UI flicker) setFetchingState(null) перемещён ПОСЛЕ `await second
   apiFetch`. Иначе между clear и resolve есть момент когда mutation
   isPending=true + fetchingState=null → пустой экран ~1 RTT.

NOT addressed (rebuttal):
5. (Tailwind convention) — проверил: в проекте нет ни globals.css, ни
   @tailwind directives. ВСЕ существующие site-finder components используют
   inline styles (ConfidenceBadge, GeotechRiskBlock, ScoreBreakdownPanel etc).
   Tailwind в deps но не wired up. Keep inline styles для consistency.
6. (animate-spin) — требует Tailwind globals (см. #5). `<style jsx>`
   keyframes — built-in Next.js, работает.

Per auto-review on 2252236.

---------

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 09:02:17 +03:00
lekss361
f4a865060f
feat(site-finder): D4 pipeline 24mo — future competition (#36) (#90)
* feat(site-finder): D4 pipeline 24mo — future competition (#36)

Backend (parcels.py):
- Запрос к domrf_kn_objects в радиусе 5км с ready_dt BETWEEN NOW() AND NOW()+24mo.
- _aggregate_pipeline() — сводка: objects_count, flats_total, by_class (эконом/
  комфорт/бизнес/...), by_quarter (хронологически, для UI bar), severity
  (low <500 / medium <3000 / high) per spec, top_objects (десятка по flat_count desc).
- Поле analyze.pipeline_24mo. Backward-compat — optional.

Frontend:
- Pipeline24moBlock.tsx — severity badge + 3 summary numbers (объектов, квартир,
  горизонт/радиус), by-class chips, гистограмма bar по кварталам сдачи
  (нормирована на max), разворачиваемый top-N список с классом + датой сдачи.
- Добавлен в MarketTab выше "Market trend".
- TS типы: Pipeline24mo, PipelineObject, PipelineQuarterSlot.

Closes #36. Relates to #19 (Конкурентный 360 — закрыт ранее в #36 scope).

* fix(site-finder): address PR #90 auto-review feedback

Must-fix (3):
1. distance_m falsy guard: `if obj.get("distance_m") is not None` вместо
   `if obj.get("distance_m")` — centroid-on-building даёт 0.0 (falsy float),
   raw Decimal иначе упал бы в JSON serialization.
2. SQL plan note добавлен про seq scan ~3000 строк OK; при росте — нужен
   GIST/index на (latitude, longitude) — отдельный issue для database-expert
   (будет создан separately).
3. obj_class NULL bug помечен в docstring _aggregate_pipeline с reference на
   fixes/Bug_Kn_API_Obj_Class_Always_Null_OPEN. D6/#38 — fix плановый.

Cleanup (3 из 5):
4. CLASS_LABEL.null dead key убран — JSON null приходит as absent key, не
   "null" string.
6. Magic numbers вынесены: PIPELINE_RADIUS_M=5000, PIPELINE_HORIZON_MONTHS=24,
   PIPELINE_SEVERITY_MEDIUM_THRESHOLD=500, PIPELINE_SEVERITY_HIGH_THRESHOLD=3000,
   PIPELINE_TOP_OBJECTS_LIMIT=10. SQL query теперь через f-string подставляет
   их (защищённое от injection — это int литералы).
8. obj.ready_dt formatting через fmtMonth() с new Date + toLocaleDateString —
   robust к datetime suffix vs date-only, fallback к substring(0,7) при NaN.

Не сделано (defer):
5. Async 3 HTTP calls (pre-existing pattern, нужен ThreadPoolExecutor refactor
   отдельным PR — затрагивает weather/air_quality fetch architecture).
7. ST_GeomFromText дважды — CSE справляется на этом масштабе.

Per auto-review on ade511b.

* fix(site-finder): address PR #90 auto-review minor feedback

1. TS PipelineObject.distance_m — `number | null` для отражения defensive
   Python guard (`if obj.get("distance_m") is not None`). Comment объясняет
   почему.
2. Pipeline SQL: `text(f"...")` → `text("...")` + parameters. radius_m и
   horizon_months через `:param` placeholders + `cast(:horizon_months || ' months'
   AS interval)`. Consistency с остальными SQL в файле, plus защита от
   accidental injection при будущих изменениях.
3. top_objects: explicit field selection вместо `dict(r) for r in rows`.
   Раньше leak'ило все колонки из CTE `SELECT *` (latitude/longitude/
   snapshot_date/region_cd/dev_id) в API response. Теперь только nominated
   fields: obj_id, comm_name, dev_name, obj_class, flat_count, ready_dt,
   distance_m. Schema clean.

Per auto-review on 4e431bf.

---------

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 08:34:02 +03:00
lekss361
1f8fd77825
feat(site-finder): X1 score breakdown + verbal explain (#47) (#92)
Backend (parcels.py):
- POI scoring loop teper строит score_breakdown_detailed: per-factor list с
  verbal explain (через _verbal_for_poi helper) и группировкой
  (_POI_GROUP: Социалка / Торговля / Парки / Транспорт / Шум/трамвай / Локация).
- center_bonus добавлен как synthetic factor группы "Локация" с weight=1.0
  (decay не применяется — bonus IS the value).
- factor key включает enumerate idx — prevents React key collision когда
  два POI одной категории совпадают по округлённому расстоянию.
- Skip факторов с |contribution| < 0.01 (POI > 1км) — UI шуму не нужен.
- abs_total fallback на 1.0 — защита от division-by-zero для empty factors.
- Top-3 positives/negatives: explicit ascending sort для негативов
  ("most-negative first" очевидно из кода).
- score_by_group: stacked-bar данные с count + contribution_pct.
- group_totals type: dict[str, dict[str, float | int]] (count это int).

Frontend:
- Новый ScoreBreakdownPanel.tsx: stacked-bar по группам с tooltip + legend,
  топ-3 плюса (▲ зелёный) / топ-3 минуса (▼ красный) с verbal, отдельная
  строка "Снижают балл — Шум/трамвай: ..." для negative groups, разворачиваемая
  таблица всех факторов (sticky thead, scrollable).
- Интегрирован в OverviewTab под секцией "Балл".
- TS типы: FactorContribution, ScoreGroupTotal.

Closes #47.

NB: branch создан заново из-за rebase mess (см. PR #87 comments). Логически
эквивалентно но history clean.

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 08:17:00 +03:00
lekss361
09611dc690
feat(site-finder): P1 geometry suitability score (#45) (#89)
* feat(site-finder): P1 geometry suitability score (#45)

Backend (parcels.py):
- _polygon_suitability() — Shapely metrics on parcel WGS84 polygon:
  area_ha/m2 (projected via cos(lat) к UTM-like meters), perimeter_m,
  aspect_ratio (long/short side of MABR), convex_hull_ratio (area / hull area),
  min_inscribed_rect_dim_m.
- Composite suitability score 0..1:
  base = area_subscore (0 при <0.2 ha, linear → 1 при ≥0.5 ha)
  −0.3 если aspect_ratio > 5 (вытянутый)
  −0.3 если convex_hull_ratio < 0.65 (изрезанный)
  −0.5 если min_inscribed_rect_dim_m < 30 (узкий)
- Label: микро / подходящий / сложная форма / слабо подходит
- Recommendation: "для МКД 16+ нужно >0.3 ha + минимум 40м"
- В analyze response → geometry_suitability.

Frontend:
- Новый GeometrySuitabilityBlock.tsx с color-coded badge + метрики grid +
  penalties + recommendation
- Добавлен в LandTab (выше "Зонирование (ПЗЗ)")
- TS типы расширены: GeometrySuitability

Closes #45.

* fix(site-finder): address PR #89 auto-review minor feedback

Backend (parcels.py):
1. Фактическая ошибка фикс: recommendation теперь различает "строительный
   минимум 30м" (physical penalty trigger) и "комфорт МКД 12-16эт 40м"
   (recommendation level). Пользователю чётко видны 2 порога.
2. Lazy imports → module-level: `from shapely import wkt as _shp_wkt`,
   `from shapely.geometry import Polygon`.
3. MABR inner exception теперь логирует: `logger.debug("MABR computation
   failed, falling back to sqrt(area): %s", mabr_err)`.
4. Magic numbers вынесены в константы: _GEOM_MIN_AREA_HA, _GEOM_AREA_SCORE_FULL_HA,
   _GEOM_ASPECT_PENALTY_THRESHOLD, _GEOM_CONVEX_PENALTY_THRESHOLD,
   _GEOM_MIN_WIDTH_PHYSICAL_M, _GEOM_MIN_WIDTH_COMFORT_M, _GEOM_LABEL_MICRO_HA,
   _GEOM_LABEL_GOOD, _GEOM_LABEL_MEDIUM, плюс penalty константы.
5. Label "микро" теперь комбинируется с penalties: "микро, узкий" — UI видит
   обе проблемы. Pure "микро" остаётся когда нет penalty.

Frontend (GeometrySuitabilityBlock.tsx + types):
6. Заменил emoji ⚠ (U+26A0) на текстовый <strong>"Проблемы формы:"</strong> —
   стабильнее в WeasyPrint PDF-экспорте и cross-platform.
- TS типы: GeometrySuitabilityBaseLabel экспортирован, label расширен до
  `string` для допуска combo-labels; helper colorForLabel() парсит base часть.

Per auto-review on f4e7491.

* fix(site-finder): P1 #45 — extract 0.3 ha to _GEOM_AREA_COMFORT_HA

Auto-review нашёл: recommendation упоминала "от 0.3 га" но в constants block
не было 0.3 — magic literal в строке. Тот же класс проблемы что 30/40м inconsistency
из прошлого review, только в другом поле.

Fix: новая константа `_GEOM_AREA_COMFORT_HA = 0.3` с комментарием
"рекомендуемая комфортная площадь МКД (recommendation)". Размещена между
_GEOM_MIN_AREA_HA (физический минимум) и _GEOM_AREA_SCORE_FULL_HA (premium) —
третий semantic threshold. Recommendation теперь f-string использует константу.

Per auto-review on ae5e8de.

---------

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 08:00:12 +03:00
lekss361
843314c040
feat(site-finder): P2 cad_buildings соседи + overlap check (#46) (#91)
* feat(site-finder): P2 cad_buildings соседи + overlap check (#46)

Backend (parcels.py):
- _parse_floors() helper для TEXT column (cad_buildings.floors хранится как
  строка, могут быть диапазоны "5-7"). Возвращает верхнюю границу.
- _neighbors_summary(db, geom_wkt, our_cad) — query соседей в 100м (GIST):
  cad_num, building_name, floors, year_built, cost_value, area, address, distance.
  Aggregate: avg_floors_100m, max_floors_100m, median_cost_per_m2_100m,
  count_buildings_100m. Outliers cost/m² фильтруются (1k < x < 500k).
- Overlap check: ST_Intersects + ST_Area(ST_Intersection) > 50 m² (transformed
  to UTM 32641 для метров). Если есть → has_existing_buildings: true +
  overlap_buildings list.
- В response → neighbors_summary.

Frontend:
- Новый NeighborsBlock.tsx: hard red warn block для overlap (с building names +
  overlap_m2 + "Инвестиции невозможны без сноса"); summary metrics (avg/max
  floors, median price); toggle "Показать N ближайших" → таблица.
- Border меняется на красный при has_existing_buildings — visual cue.
- Добавлен в LandTab выше "Зонирование (ПЗЗ)".
- TS типы: NeighborBuilding, OverlapBuilding, NeighborsSummary.

Closes #46. Closes #21 (cad_buildings в Site Finder фильтрах).

* fix(site-finder): address PR #91 auto-review minor feedback

Backend (parcels.py):
1. (medium) Aggregation loop _neighbors_summary теперь обёрнут в try/except
   (ValueError, TypeError) с fallback к data_available:False + log warning.
   Защищает от non-numeric cost_value/area придёт в строке (e.g. "N/A") —
   ранее весь endpoint падал 500.
2. Magic numbers вынесены: _COST_PER_M2_MIN=1000, _COST_PER_M2_MAX=500_000.
3. _parse_floors docstring + inline note про malformed parts ("5а-7" filter,
   multi-range "1-2-3" max acceptable degradation).

Frontend (NeighborsBlock.tsx):
5. Русский plural fix: pluralBuildings(n) helper — 1 здание, 2-4 здания,
   5+/11-14 зданий. Раньше "3 зданий" — теперь "3 здания".

Не сделано (defer):
4. ST_Area для overlap query — практически 0-5 buildings в ЕКБ, GIST scan OK.
6. Discriminated union для NeighborsSummary — refactor а не bug.
7. Vault entry для P2 — добавится batch'ем после merge всех текущих PR.

Per auto-review on 60d53bb.

---------

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 01:30:53 +03:00
lekss361
3777a77a42
feat(site-finder): X2 confidence indicator + caveats (#48) (#88)
Backend (parcels.py):
- _compute_confidence() composite score 0..1 from 7 subscores: poi_freshness,
  geom_source (parcel vs quarter), district, market_trend (rosreestr_deals depth),
  competitors, environment (noise/air/weather availability), zoning (placeholder
  до G1).
- confidence_label: high (>0.75) / medium (0.4-0.75) / low (<0.4)
- confidence_caveats: list of конкретных проблем для UI
- confidence_breakdown: per-subscore 0..1 для прозрачности

Это stub-версия (полная — после G1/G2/D1/D2). Использует только текущие сигналы.

Frontend:
- Новый ConfidenceBadge.tsx — color-coded (green/yellow/red) badge с %
- Caveats для low — показываются сразу; для medium/high — под toggle
- Toggle "Подробнее" → breakdown per-subscore + полный список caveats
- Размещён в начале OverviewTab (выше "Район")
- TS типы расширены: confidence, confidence_label, confidence_breakdown, confidence_caveats

Closes #48.

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 01:04:25 +03:00
lekss361
485c221c3b
docs(claude): formalize Auto-review passed as approval signal (#85)
* docs(claude): formalize "Auto-review passed" as approval signal + polling loop

Per user feedback after PR #84 merge:
- Critical rule 5: "Auto-review passed" / "LGTM" от auto-review bot = approval
  (наряду с явным "merge it" / "approved" от human user)
- Add "Polling loop для PR" section: 60s ScheduleWakeup pattern,
  decisive states (merged / approved / changes / no-news), cap 30 iters

This formalizes what main session already did: after fixup commit, poll
comments, detect auto-review verdict, and auto-merge if passed.

* fix(claude): address PR #85 auto-review feedback

- Fix cyrillic/latin typo (rule 5 second sub-bullet)
- Add SHA marker validation to polling loop (race condition on stale LGTM after fixup-push)
- Add explicit "Auto-merge scope" rule 6 — allowlist (docs/UI/.claude) vs blocklist (migrations/API/infra/secrets)
- Sync "Когда auto-mode" section with new merge approval signals
- Lower cap to 5 iters for scope-blocked PRs (human required anyway)
- Self-modifying CLAUDE.md rules → always require human

Per auto-review on e66e1ea.

---------

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 00:43:25 +03:00
lekss361
a35a3d02ea
feat(site-finder): deep-link tabs via ?tab= URL param (#86)
* feat(site-finder): deep-link tabs via ?tab=env|land|market URL param

Tab state now syncs with URL — можно поделиться ссылкой на конкретный
таб (например /site-finder?tab=market для тренда цен по последнему cad).

- useRouter + useSearchParams (Next 15 app router, client-component)
- router.replace (не push) чтобы tab switches не засоряли history
- useEffect on searchParams → back/forward работают
- overview = default, не пишется в URL (clean)
- Type-guard isTabId(): только valid values из URL переключают state

* fix(site-finder): address PR #86 auto-review minor recommendations

- Use usePathname() for router.replace fallback (avoid dangling "?" in Next 15)
- Remove stale-closure guard in useEffect — React bails Object.is, no eslint-disable
- Wrap page in <Suspense> for useSearchParams (Next 15 App Router req for static)
- Lazy useState initializer — skip wasted CPU on re-renders

Per auto-review on c47e56b.

---------

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 00:33:49 +03:00
lekss361
aadf47709b
docs(claude): mandate branch+PR workflow, ban direct push to main (#84)
* docs(claude): mandate branch+PR workflow, ban direct push to main

* docs(claude): sync TL;DR + Don't-do-these with new PR workflow

Address auto-review feedback:
- TL;DR rule 5 → branch+PR mandate (was: "user commits themselves")
- TL;DR rule 6 → no --no-verify/--force/--amend (split from rule 5)
- Don't-do-these → drop conflicting "no auto-commit" line, add
  "no direct push to main" + "no merge without approval"
- Critical workflow rules: add explicit rule 2 — worker-agents don't
  commit themselves; main session commits on feature branch
- Restore "Squash on merge" wording in PR section (was dropped)
- Auto-mode section: clarify that main session does commits on feature
  branch (worker-agents leave changes staged)

* fix(claude): Code-reviewer diagram had stale 'push origin HEAD:main' — replace with branch+PR flow

---------

Co-authored-by: lekss361 <claudestars@proton.me>
2026-05-12 00:16:06 +03:00
lekss361
053ce29a40 docs(claude): add code-reviewer agent — review workflow before push 2026-05-11 23:44:32 +03:00
lekss361
13119f9cb5 feat(docs): /docs/b2b-channels (rendered) + /docs/b2b-channels.md (raw) for sharing 2026-05-11 23:36:02 +03:00
lekss361
59466de811 fix(deploy): aggressive docker image prune (drop until=72h filter to avoid 50GB buildup) 2026-05-11 23:26:31 +03:00
lekss361
a1201aa94e feat(site-finder): tabbed UX - hero KPI band + 4 tabs (Overview/Env/Land/Market) + sticky map 2026-05-11 23:21:39 +03:00
lekss361
199adc31e6 fix(site-finder): UX - sticky map, collapsible sections, score header sticky 2026-05-11 23:10:56 +03:00
lekss361
99ca42e5d0 fix(site-finder): isochrones map re-renders on mode change (key includes coords hash) 2026-05-11 23:03:25 +03:00
lekss361
2cbcea9e73 fix(zoning): NSPD blocks bot access — fallback to deep-links (PKK6 API closed 2024) 2026-05-11 22:56:50 +03:00
lekss361
49eadeb9ce fix(pzz-sync): follow_redirects=True (PKK6 returns 301) 2026-05-11 22:50:46 +03:00
lekss361
1c1ecad8b8 fix(pzz-sync): disable SSL verify for Rosreestr PKK6 (self-signed cert chain) 2026-05-11 22:44:53 +03:00
lekss361
2e83d62237 feat(site-finder): center distance bonus display + success_recommendation block 2026-05-11 22:40:46 +03:00
lekss361
ab0647e4d5 feat(site-finder): distance to EKB center + success quartirography recommendation 2026-05-11 22:35:21 +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
369b5a4706 feat(db): v_bucket_success_score view (success-driven mix #25) 2026-05-11 22:04:22 +03:00
lekss361
8be539ddc6 feat(site-finder): ПЗЗ territorial zones from Rosreestr PKK6 + zoning in analyze 2026-05-11 21:51:51 +03:00
lekss361
5b03d6d799 feat(site-finder): isochrones UI + networks VKH + OSM substations 2026-05-11 21:48:21 +03:00
lekss361
923f250926 feat(site-finder): /parcels/{cad}/isochrones via OpenRouteService 2026-05-11 21:44:22 +03:00
lekss361
6ce634a9b9 feat(site-finder): utilities (power/pipeline) + fix Внешние факторы layout 2026-05-11 21:38:20 +03:00
lekss361
2855a01ca7 feat(site-finder): v3.5 - seasonal weather + hydrology + geotech risk 2026-05-11 21:32:07 +03:00
lekss361
7bb51aa838 feat(site-finder): v3.4 - weather enrichment (temp/precip/UV) + geology stub 2026-05-11 21:17:57 +03:00
lekss361
7900dc5238 fix(site-finder): WKT LINESTRING needs commas + rosreestr_deals real column names 2026-05-11 20:58:49 +03:00
lekss361
232c81eae9 feat(site-finder): v3.3 - score label + market_trend + multi-thematic bulk 2026-05-11 20:51:59 +03:00
lekss361
1e9d32ee3c feat(site-finder): v3.2 — noise + air quality + wind analytics 2026-05-11 20:42:37 +03:00
lekss361
a2e8a49e6d feat(db): osm_noise_sources_ekb for site-finder noise scoring 2026-05-11 20:35:27 +03:00
lekss361
d08d06d8a8 fix(geo): parcels (thematic_id=1) come from rosreestr2coord in WGS84 — drop ST_Transform 2026-05-11 20:09:58 +03:00
lekss361
81cd7499f6 feat(site-finder): cad_parcels_geom migration + POI markers on map + bulk-job UX 2026-05-11 19:54:56 +03:00
lekss361
f419900968 feat(site-finder): v3.1 — cad_parcels_geom, analyze fallback, POI lat/lon, OSM expand
- nspd_geo: add _save_parcel() for thematic_id=1 → cad_parcels_geom (UPSERT,
  ST_Transform from Web Mercator); _persist_target now handles 1/2/5
- parcels.py: analyze endpoint geom lookup extended with cad_parcels_geom as
  3rd fallback source (after cad_quarters_geom, cad_buildings); both SELECT
  and WKT subqueries updated
- parcels.py: POI score_breakdown items now include lat/lon for map markers
- poi_loader: OSM_CATEGORIES expanded — college+university→school,
  hypermarket→shop_supermarket; coverage +3 tag pairs
2026-05-11 19:52:19 +03:00
lekss361
ea3d58fa7d feat(routing): /sf -> /site-finder permanent redirect (short URL alias) 2026-05-11 19:49:26 +03:00
lekss361
e6c062cc5b feat(home): site-finder no longer WIP + admin/scrape/all + buildings in object card desc 2026-05-11 19:36:43 +03:00
lekss361
a7d7dc9667 fix(site-finder): dedupe competitors — same domrf_kn_objects 3x snapshots bug 2026-05-11 19:04:29 +03:00
lekss361
3aeda297ee fix(poi-sync): split Overpass query per category (504 Gateway Timeout) 2026-05-11 18:54:28 +03:00
lekss361
93f13795bb fix(poi-sync): add User-Agent header — Overpass returns 406 for python-httpx default UA 2026-05-11 18:46:47 +03:00
lekss361
9742219ef6 debug(poi-sync): DB breadcrumbs to nspd_geo_log for silent-fail diagnosis 2026-05-11 18:37:43 +03:00
lekss361
f81bd710c0 feat(api): POST /admin/scrape/poi-sync — manual OSM POI sync trigger 2026-05-11 18:12:37 +03:00
lekss361
a4e8fff5ac feat(site-finder): POST /parcels/{cad}/analyze endpoint + UI
Backend:
- analyze endpoint: cad → geom lookup → POI within 1km → district
  context → competitors within 3km. Tram_stop carries negative weight.

Frontend /site-finder:
- CadInput regex-validated (default 66:41:0204016:10)
- SiteMap (Leaflet via next/dynamic) with parcel polygon + legend
- ScoreCard color-coded (>5 green, 2-5 yellow, <2 red) with tram-warning
- CompetitorTable top-20 with same-district highlight
- useSiteAnalysis hook + TS types
2026-05-11 18:11:58 +03:00
lekss361
6dea34186b feat(site-finder): OSM POI loader + Celery weekly sync
- New poi_loader.py: Overpass QL query for 13 POI categories in EKB bbox,
  UPSERT into osm_poi_ekb with soft 2-year filter tracking (skipped_old counter)
- New poi_sync.py Celery task wrapping sync_poi_to_db()
- celery_app.py: include poi_sync module, add poi-sync-weekly beat entry (Mon 03:00 MSK)
2026-05-11 18:08:34 +03:00
lekss361
688e094844 feat(db): osm_poi_ekb table for site-finder POI analysis 2026-05-11 18:06:28 +03:00
lekss361
ceaf553eb7 fix(analytics): recommend page UI — caveat badge wrap + headline baseline label
Two UX nits:
- Caveats badge had whiteSpace:nowrap on a 250-char data_caveat → overflowed
  visibly outside the section in the screenshot. Drop nowrap, keep small
  font + light grey background. Reads as a compact note.
- Headline KPIs (369 млн ₽ · 19.4 мес · темп 6.0 · ликв 97/100) are
  computed by backend at price_factor=1.0, while live KPI cards below
  recompute with the current slider position. When user moves price to
  +40% the discrepancy is confusing. Append small grey '(базовая цена)'
  marker after headline with a tooltip explaining baseline vs live.
2026-05-11 17:53:35 +03:00
lekss361
0de32cd2ce fix(analytics): dedupe comparables — domrf_kn_objects has 3x snapshots per obj_id
The comparables block on /analytics/recommend was showing the same ЖК
multiple times (ЖК СТАРТ × 3, ЭХО ЛЕСА × 2 etc) because domrf_kn_objects
has ~3 historical snapshots per obj_id. The previous query joined all
rows and LIMIT 5 cherry-picked duplicates by flat_count.

Fix: wrap base in CTE `latest_obj` with `DISTINCT ON (obj_id) ORDER BY
obj_id, snapshot_date DESC` to pick only the latest snapshot per object
before sorting by flat_count.
2026-05-11 17:52:37 +03:00