deep-review #1964: v_objective_lots_latest has NO premise/district filter inside,
so a consumer's outer WHERE cannot push below DISTINCT ON → the view materializes
the WHOLE table (Parallel Seq Scan + external Sort 1.76M rows, ~55MB spill) on
every query. For REQUEST-PATH consumers inside analyze_parcel this is a ~19x latency
regression vs the pre-#1964 raw-table plan.
DISPROVEN remedy (NOT applied): a full index on the physflat-key does NOT help —
DISTINCT ON selects ol.* (51 cols, width≈945) so index-only-unique is impossible;
the planner ignores the index (seq-scan+sort still cheaper) and even forced it is
~3.9 s. A 142MB index for zero request-path benefit + slower bulk-INSERT during
objective-scrape is wrong. Honors original #1964 decision "no new index".
Prod EXPLAIN (Академический / 3km radius, 2026-06-28):
consumer via view inline (this commit)
concepts median 5854 ms 1640 ms (bitmap district + sort)
parcels district 5854 ms 1640 ms
parcels geo-median 6443 ms 122 ms (NestedLoop geo->complex bitmap)
parcels obj_pricing 5721 ms 441 ms (project bitmap per nearby ЖК)
FIX: keep v_objective_lots_latest ONLY for batch/background/cached consumers
(supply_layers L1, competitors._SOLD_COUNT_SQL, special_indices [/forecast bg task
30-180s], admin, landing). Revert the 4 request-path consumers inside analyze_parcel
to inline DISTINCT ON (physflat-key, latest snapshot) with the filter pushed INTO the
CTE so the district/spatial/project index applies:
- concepts._OBJECTIVE_MEDIAN_SQL
- parcels.py district price block
- parcels.py geo-radius median (complex_id-scoped)
- parcels.py obj_pricing CTE (project_name-scoped; aggregates over deduped set)
Migration 175 header CORRECTED: accurately states the partial mig-173 index does NOT
serve the view (qual can't push below DISTINCT ON), the full index is disproven/not
added, and which consumers use the view vs inline. No DDL change (still view-only).
Tests: +guards (concepts/obj_pricing dedup inline, not view; obj_pricing physflat
DISTINCT ON; perf-pushdown scope preserved). 965 passed.
Финальная часть эпика #1953: пользователь выбирает типовые дома
(тип × этажность × число секций) вместо авто max-FAR раскладки, формируя
building_program из Stage 3a.
Бэкенд:
- GET /api/v1/concepts/house-types — read-only каталог HOUSE_TYPES
(section_type, label_ru, footprint w×d + sqm, default_floors, housing_class)
как single source of truth; фронт ничего не хардкодит.
- Схема HouseTypeCatalog / HouseTypeCatalogItem в schemas/concept.py.
- Тесты эндпоинта: полнота каталога + совпадение ключей с available_section_types.
Кодген: api-types.ts перегенерён (dump OpenAPI → openapi-typescript →
project-local prettier 3.9.0); 2-й прогон без диффа.
Фронтенд:
- useHouseTypes() (TanStack useQuery, staleTime Infinity) в concept-api.ts;
building_program в ConceptInput, placed_count/requested_count в ConceptVariant.
- HouseProgramPicker: toggle «Авто (max-FAR)» (default, program omit → greedy)
vs «Выбрать дома» (список каталожных типов, count 1-50 / floors 1-40, дефолт
из каталога; габариты/этажность/класс как подсказка). Смонтирован в
Section7Concept и на странице /concept.
- Partial-fit заметка в ConceptVariantsResult: при placed<requested честное
«Разместилось N из M секций — участок вмещает меньше» (нейтрально, не ошибка).
Extend the concept generator so ConceptInput can carry an optional
building_program (list of typed houses from a catalog). When present,
placement lays out EXACTLY that program — for each item, place `count`
sections of the catalog footprint at the item's floors — instead of the
greedy max-FAR coverage-cap sweep. When absent, the existing greedy
behavior is unchanged (byte-for-byte backward-compatible).
- catalog.py: hardcoded HOUSE_TYPES (panel_econom, monolith_comfort,
tower_business, lowrise_comfort, townhouse) — sane-default catalog,
promote to DB later; get_house_type / available_section_types lookups.
- schema: additive BuildingProgramItem {section_type, floors, count} and
ConceptInput.building_program (default None -> greedy). ConceptVariant
gains optional placed_count / requested_count (partial-fit signal).
- placement: shared _Placer (collision/STRtree/setback machine extracted
from greedy sweep, reused — no duplication); place_program +
place_program_variant; branch in place_all_strategies on
building_program. Mixed-floor TEAP via exact per-floor-group aggregation
(GFA = sum(area_i * floors_i), no rounding drift).
- partial fit: when the parcel can't fit all sections, place as many as
fit and report placed_count < requested_count (no hard-422); zero-fit
still raises ParcelGeometryError (-> 422).
- API: validate program section_type keys against the catalog (unknown ->
422) before placement.
- tests: catalog integrity, greedy backward-compat, exact 2-item program +
TEAP reflection, over-packed partial placement, API program path.
- regenerate frontend api-types.ts (OpenAPI codegen gate stays green).
Code-review follow-up: /recompute hardcoded price_source="objective_district_median"
for any body-supplied market_price_per_sqm, mislabeling the honesty-flag once
Stage 2b forwards a price whose genuine source differs (objective_geo_radius /
district_reference / class_norm from financial_estimate).
- schemas/concept.py: add optional price_source: str | None to MassingProgram.
- api/v1/concepts.py: on FAST path use payload.price_source if provided, else the
default label (now a module-level constant _DEFAULT_PRERESOLVED_SOURCE). DB-fallback
and class-norm paths keep their own resolved source unchanged.
- tests: assert body-provided price_source echoes through to financial.price_source
(not overwritten), and the default label applies when the front omits it.
Stage 2a of epic #1953: backend service + endpoint for live economic recompute
driven by the interactive 3D massing (Stage 2b debounced sliders).
- teap.py: add pure synthesize_teap_from_program(total_footprint_sqm, floors,
site_area_sqm, housing_class, sections) — builds a TEAP from the SCALAR
aggregate footprint × floors, mirroring synthesize_teap_from_buildability and
reusing the same shared norm constants (_OFFICE_SHARE_OF_GFA / _EFFICIENCY_BY_CLASS
/ _AVG_APARTMENT_SQM / _PARKING_PER_APARTMENT) — single source of truth.
- schemas/concept.py: add MassingProgram (program contract, optional pre-resolved
market_price_per_sqm + parcel_centroid_wkt) and MassingRecomputeOutput (teap + financial).
- api/v1/concepts.py: add POST /api/v1/concepts/recompute — synthesize TEAP → run
the existing pure compute_financial. FAST path uses body market_price_per_sqm
(no DB); else _lookup_market_price by centroid via run_in_threadpool; else class norm.
- tests: synthesize_teap_from_program (gfa math, parity with compute_teap, class
efficiency, sections no-op) + endpoint (200, coherent output, price passthrough
skips DB, DB fallback, class-norm default, floors validation).
FIX A (#1955) «Что хорошо продаётся»: убран фантомный класс 'Comfort'.
- Миграция 172: v_bucket_success_score COALESCE(obj_class,'Comfort')
→ COALESCE(obj_class,'не указан'). Английский литерал заполнял 397 NULL
и сливался отдельным классом от русского 'Комфорт' → визуальные дубли
бакетов в UI. Источник уже канонически-русский (проверено на проде),
synonym-mapping не нужен.
- parcels.py: obj_class протаскивается в success-ranking query + dict.
- TS SuccessRankingBucket.obj_class добавлен.
FIX B (#1960) «Медиана рынка» = 64k (квартальная росреестровская n=1 ДКП):
- district.median_price_per_m2 больше не COALESCE(median_12m, ekb_ref) в SQL.
Basis-приоритет (newbuild-first): Objective по имени района →
geo_radius (Objective в 3км) → ekb_districts reference →
квартальная росреестровская медиана ТОЛЬКО при deals_count≥5.
Для 66:41:0205010:287: 64k → 132690 (geo_radius, newbuild-consistent).
- median_price_basis добавлен в payload + TS type (nullable median).
- Frontend null-guards для нового nullable median.
Tests: +4 (geo_radius basis, objective-приоритет, deals-guard, obj_class
passthrough); обновлены district-моки в 9 analyze-тестах под новую
SQL-сигнатуру.
#1954 — площадь «—»: COALESCE(land_record_area, specified_area, declared_area)
в EGRN-блоке analyze (land_record_area NULL у 12809/42233 участков, но
specified_area заполнена). area_m2 для 66:41:0205010:287 теперь 106378 (был NULL).
#1954 — «Обновлено» сломано: cost_registration_date — мёртвая колонка (0/42233);
репойнт на updated_at (42233/42233 заполнено). Ключ ответа last_egrn_update_date
не меняется (additive value fix).
#1958 — confidence-фактор «Прогноз спрос/предложение» дублировался ×4
(по фактору на горизонт). Сворачиваем в один weakest-link'ом (MIN ранга
по горизонтам) в _component_confidences до confidence-движка (#990).
#1957 — ЗОУИТ backend:
- _get_cad_zouit_overlaps: DISTINCT ON (reg_numb_border) — дедуп дубль-строк
(одна физ. зона 2× с разным category_name). group_key cad_zouit→protected.
- _get_zouit_overlaps (dump path): subcategory→RU-тип карта (26→СЗЗ и др.,
коды сверены кросс-джойном dump↔cad_zouit на проде); type_zone из карты,
reg из props.options.reg_numb_border. Раньше отдавал blank-строки.
- унификация group_key (protected/engineering/okn/natural/other) + top-level
reg_numb_border в обоих путях.
UP038-модернизация isinstance в report_assembler (pre-commit ruff 0.7.4).
Frontend note (#1957): nspd_zouit_overlaps теперь всегда group_key из набора
{protected,engineering,okn,natural,other} — сырой 'cad_zouit' больше не отдаётся;
оба пути несут type_zone + reg_numb_border.
Tests: +4 _component_confidences collapse, +6 ЗОУИТ (subcategory map, dump
typing, DISTINCT ON), schema-test обновлён на protected. 451 passed targeted.
The data-freshness monitor classified by run RECENCY only, so the domrf_kn
FLATS loader running status=done but extracting 0 flats for ~5 weeks went
undetected — and the kn source watched objects_count (healthy ~1548), not
flats_count (the broken =0 metric).
Add an opt-in zero-output check: an otherwise-fresh run-ledger source (recent
success, would-be fresh by age) that produced 0 work-rows in the 7d window is
downgraded to status="failed" (so scrape_freshness_check alerts), with an
additive "reason". Guards: alert_on_zero_output flag, run-ledger only
(timestamp_col is None), status=="ok" (age-stale/failed already covered), and
upd_7d==0 (SUM of the source's own work_col over done-runs).
Registry: new kn_flats source (kn_scrape_runs, work_col=flats_count, critical,
flag on) — watches the column that was broken; existing kn (objects_count)
unchanged. Flag also enabled on objective (rows_lots, critical). nspd/nspd_geo/
cadastre left unflagged (legitimate-0 / data-table).
JSON additive only (new nullable "reason" key; endpoint is dict[str,Any], no
frontend consumer / no codegen needed). 4 new tests (downgrade, no-false-
positive, age-precedence, registry). code-reviewer APPROVE.
Would have caught #1945 within ~8-14d instead of 5 weeks.
Walk-relevant POIs (school/shop/park/kindergarten/pharmacy/stops) now route
via a FOOT OSRM graph (osrm-walk service), car-relevant POIs (mall/hospital +
unknown) keep the DRIVING graph. Validation showed driving overstated
pedestrian-proximity distance — median 1.6-2.9x straight-line (#39).
- config: osrm_walk_local_url + osrm_walk_categories (frozenset, 9 walk cats)
- osrm_client_local: base_url override on get_road_distances_m (default unchanged)
- _apply_osrm_road_distances: split POIs by category, per-group OSRM call with
independent graceful fallback (one server down -> its group keeps straight-line),
in-place write-back by original index; never raises; flag-OFF byte-identical
- docker-compose: osrm-walk service (foot graph, internal, mem_limit 1.5g)
- build_osrm.sh: CAR=0 gate for foot-only refresh (doesn't touch live car graph)
- tests: per-category split, per-group fallback, asymmetric intra-group write-back
Still flag-gated (use_osrm_distances OFF) — enabling is a product decision.
Refs #39
kn (DOM.РФ ЖК) runs weekly (Mon cron) but thresholds were 2/5 → false "stale" every Wed-Sun. Recalibrate to 8/14 (weekly, mirrors objective) + regression test. Surfaced by the freshness monitor's first prod run. Refs #73
