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bc2d393b05 fix(market_metrics): disambiguate ROLLUP grand-total via GROUPING() (#1214)
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_SALES_WINDOW_SQL делал GROUP BY ROLLUP (rooms_int), rooms_int nullable
(ETL пишет NULL для «неопределённого типа», sales_series.py:399 явно
обрабатывает None). Проданный лот с rooms_int IS NULL даёт ДВЕ строки
rooms_int IS NULL (NULL-группа + grand-total итог), неразличимые в
Python (оба if r["rooms_int"] is None).

MixedAggregate-план PG16 эмитит grand-total ПЕРВЫМ (среди hash-строк),
NULL-группа после → loop затирает units_total частичным счётом (живой
тест на PG16: 2000 → 200). Эффект: unit_velocity / absorption_rate
занижены, months_of_supply завышен → base_pace в demand_supply_forecast
неверный (recommendation.py:586) → reports/scoring врёт.

Patch:
- SQL: добавить GROUPING(rooms_int) AS is_total (=1 для grand-total).
- Python: ветвить по is_total, NULL-комнатную группу класть в
  by_room['unknown'] (отдельный бакет), аккумулировать через +=
  вместо assign (защита от будущих NULL-вариантов).
- Тесты: моки получили "is_total" поле (1 для grand-total, 0 иначе).

71/71 market_metrics тестов зелёные. ruff clean.

Closes #1214
2026-06-13 05:57:19 +00:00
8206a0b067 perf(forecast): per-request memoization cache for §22 cold build (#1129)
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Cold §22 forecast measured ~215-233s on prod: §9.x layers re-execute the same
horizon/segment-invariant DB loads with identical args hundreds of times per
report (profiled: get_competitors x69, market_metrics x124, get_monthly_macro
x290). Add a per-report ContextVar cache (forecast_cache(), opened once in the
orchestrator) + @cached(key_builder) on the expensive §9.x loaders so each
unique load runs ONCE and reuses the same frozen, read-only instance.

Output is byte-identical (memoized producers are frozen dataclasses / read-only
Pydantic, callers never mutate; cache is per-report, discarded on exit; no-op
outside the report build). No concurrency, no signature changes.

- forecast_request_cache.py: ContextVar cache + cached() decorator (no-op
  outside context, reentrant, _MISS sentinel for cached None)
- @cached on competitors/future_supply/market_metrics/macro_series/
  sales_series/macro_coefficient/demand_normalization/regression loaders
- orchestrator: wrap build_site_finder_report in forecast_cache()
- 58 tests: key discrimination (call-counting regression guard), no-op-outside,
  per-report isolation, reentrancy, frozen-producer canary, amplification proof
  (real get_monthly_macro xN->1)

code-reviewer APPROVE (keys correct, mutation-safe, output identical). 1265
forecast/cache tests green. No new deps. Refs #1129.
2026-06-08 05:26:27 +00:00
681a922d99 feat(forecast): resolve admin district -> micro set in §9.x market/supply/sales filters
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/analyze passes the official ЕКБ admin district (ekb_districts polygon, e.g.
'Кировский'), but objective_lots/corpus_room_month store informal micro-districts
('Втузгородок','ЖБИ') -> admin name matched 0 rows -> silent empty forecast.

Add resolve_objective_districts() (site_finder/district_resolver.py) mapping an
admin name to its clean micros via ekb_district_alias (note IS NULL), with
None -> EKB-wide fallback and raw-micro pass-through. Wire into the objective_lots
district filters of market_metrics (§9.2 stock+sales), supply_layers L1 (§9.3),
and sales_series Sources A+B (crm shares the micro vocab, prod-verified),
switching the scalar filter to psycopg3-safe = ANY(CAST(:districts AS text[])).
supply_layers L2/L3 keep the admin name (domrf_kn_objects.district_name is admin vocab).

Prod: Кировский/Ленинский/Орджоникидзевский obj_count 0 -> 32/64/31.
Tests mutation-verified non-vacuous. 192 module tests pass; ruff clean. Refs #969 #949.
2026-06-05 07:03:37 +05:00
2b3759af6a fix(market-metrics): count window sales by contract_date, not 17-day history (#949 CRITICAL)
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REOPENED. _SALES_WINDOW_SQL derived "sales in window" from objective_lots_history
snapshots, but history is only ~17 days deep — every currently-sold lot had a
sold-snapshot in the window, so window-sales collapsed into the entire cumulative
sold stock (Автовокзал 6mo: 33,245 vs real ~2,308). Inflated absorption_rate
(~235%/mo with confidence=high), months_of_supply, unit_velocity, liquidity,
demand_concentration → contaminated forecast #950/#952.

Count window sales directly from objective_lots by contract_date in the window
(the real sale date — present on 100% of sold lots: 41,091/41,091). Return
contract of _query_sales_window unchanged (units/area/by-room ROLLUP); downstream
formulas untouched. Removed the now-dead objective_lots_history JOIN/CTE.
Regression test: lots sold outside window (contract_date out of range) not counted
(41,091 cumulative vs 2,308 window → absorption 2.35→0.04). 288 tests green.

Verification = prod compute_market_metrics(Автовокзал) post-deploy. Refs #949
2026-06-04 10:46:50 +05:00
45d61ecff0 feat(site_finder): market-metrics service (#949 PR A, §9.2) (#997)
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2026-06-02 19:26:26 +00:00