merge main + renumber 163→167 + guard riasurt harvest (#108 review)

2026-06-17 22:52:15 +03:00 · 2026-06-17 22:52:15 +03:00 · 0a72ef9491
commit 0a72ef9491
parent ddf4873874 81e708b953
36 changed files with 1251 additions and 205 deletions
--- a/.forgejo/workflows/ci.yml
+++ b/.forgejo/workflows/ci.yml
@ -15,23 +15,22 @@ name: CI
 # FUTURE: добавить `postgis/postgis:16-3.4` service + гонять mv_layout — см.
 # .github/workflows/ci.yml как образец service-блока.
 on:
+  # ТОЛЬКО pull_request — НЕТ push-триггера на feature-ветки (CI-шторм #1709).
+  # WHY: раньше был и push: [feat/**,fix/**,...]. Каждый коммит в ветку с открытым
+  # PR триггерил ДВА прогона на ОДИН SHA: push-событие (github.ref=refs/heads/<branch>)
+  # и pull_request-событие (github.ref=refs/pull/<N>/merge). Разный github.ref →
+  # разные concurrency-группы (см. ниже) → прогоны НЕ отменяют друг друга → 2× job
+  # при и так дефицитных раннерах. В bot-пайплайне каждый коммит идёт через PR, так
+  # что pull_request гейтит его полностью; push-прогон был чистым дублем.
+  # Trade-off: push в feature-ветку БЕЗ открытого PR не получит CI до открытия PR
+  # (бот открывает PR сразу после первого push) — приемлемо.
  pull_request:
    branches: [main]
-  push:
-    branches:
-      # Mirror the bot-PR / feature-branch flow в .claude/rules/git-pr.md:
-      # PR получает gate, прямые пуши в feature-ветки — тоже.
-      - "feat/**"
-      - "fix/**"
-      - "refactor/**"
-      - "chore/**"
-      - "docs/**"
-      - "perf/**"
-      - "test/**"
-      - "ci/**"
-      - "hotfix/**"

 concurrency:
+  # Теперь, когда остался только pull_request, github.ref стабилен на весь PR
+  # (refs/pull/<N>/merge) → новый push в ветку PR отменяет предыдущий незавершённый
+  # прогон ЭТОГО PR (cancel-in-progress) вместо накопления параллельных.
  group: ci-${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true

@ -89,6 +88,19 @@ jobs:
          curl -LsSf https://astral.sh/uv/install.sh | sh
          echo "$HOME/.local/bin" >> "$GITHUB_PATH"

+      - name: Cache uv packages
+        # Кросс-прогонный кэш скачанных/собранных wheel'ов (~/.cache/uv по умолч.).
+        # `uv sync --frozen` без него каждый прогон тянет весь geo-стек заново —
+        # доминирующая часть времени job (#1709). Ключ по uv.lock; continue-on-error
+        # чтобы сбой cache-бэкенда раннера НИКОГДА не ронял gate.
+        uses: actions/cache@v4
+        continue-on-error: true
+        with:
+          path: ~/.cache/uv
+          key: uv-${{ runner.os }}-${{ hashFiles('backend/uv.lock') }}
+          restore-keys: |
+            uv-${{ runner.os }}-
+
      - name: Install system deps for geo + WeasyPrint
        # libpq/gdal/proj/geos — geo-стек (geopandas/shapely/pyproj).
        # libcairo2/libpango* — нативные либы WeasyPrint: с ними PDF-тесты
@ -230,6 +242,16 @@ jobs:
          curl -LsSf https://astral.sh/uv/install.sh | sh
          echo "$HOME/.local/bin" >> "$GITHUB_PATH"

+      - name: Cache uv packages
+        # См. backend-tests: кросс-прогонный кэш ~/.cache/uv, тот же ключ по uv.lock.
+        uses: actions/cache@v4
+        continue-on-error: true
+        with:
+          path: ~/.cache/uv
+          key: uv-${{ runner.os }}-${{ hashFiles('backend/uv.lock') }}
+          restore-keys: |
+            uv-${{ runner.os }}-
+
      - name: Install system deps for geo + WeasyPrint
        # app.main транзитивно тянет geo/PDF-модули. На macOS-dev импорт схемы
        # проходит и без этих либ, но на ubuntu ставим как backend-tests
@ -239,9 +261,12 @@ jobs:
          sudo apt-get install -y libpq-dev libgdal-dev libproj-dev libgeos-dev \
            libcairo2 libpango-1.0-0 libpangoft2-1.0-0

-      - name: Install backend deps (uv sync --frozen)
+      - name: Install backend deps (uv sync --frozen --no-dev)
        working-directory: backend
-        run: uv sync --frozen
+        # --no-dev: этот job только дампит app.openapi() (нужен runtime app.main).
+        # pytest/ruff/coverage не используются → не ставим dev-группу (быстрее).
+        # Dockerfile тоже собирает с --no-dev → импорт app.main гарантированно ок.
+        run: uv sync --frozen --no-dev

      - name: Install frontend deps (npm ci)
        working-directory: frontend
--- a/backend/app/api/v1/admin_leads.py
+++ b/backend/app/api/v1/admin_leads.py
@ -138,7 +138,7 @@ def leads_stats(
            WITH window_leads AS (
                SELECT *
                  FROM prinzip_leads
-                 WHERE created_at >= NOW() - (:m || ' months')::interval
+                 WHERE created_at >= NOW() - make_interval(months => :m)
            )
            SELECT
                (SELECT COUNT(*) FROM prinzip_leads) AS leads_total,
--- a/backend/app/services/analytics_queries.py
+++ b/backend/app/services/analytics_queries.py
@ -184,8 +184,7 @@ def quartirography(db: Session, source: str, region_id: int = 66) -> list[dict[s
                   -- ('2025-07-01' расширял «recent»-окно каждую неделю по мере
                   -- доливки ETL новых report_months → перекос в сторону всё
                   -- более длинной истории). Тот же фикс, что #1203 и _BUCKET_SQL.
-                   AND period_start_date >= NOW()
-                                          - (:months_window || ' months')::INTERVAL
+                   AND period_start_date >= NOW() - make_interval(months => :months_window)
            ),
            bucketed AS (
                SELECT CASE
@ -1169,7 +1168,7 @@ def prinzip_funnel_monthly(db: Session, months: int = 24) -> list[dict[str, Any]
                """
            SELECT month, source, leads, engaged, converted, conv_pct
              FROM prinzip_funnel_monthly
-             WHERE month >= (CURRENT_DATE - (:months || ' months')::interval)::date
+             WHERE month >= (CURRENT_DATE - make_interval(months => :months))::date
             ORDER BY month DESC, leads DESC
            """
            ),
@ -1203,7 +1202,7 @@ def prinzip_funnel_by_source(db: Session, months: int = 12) -> list[dict[str, An
                   SUM(converted) AS converted,
                   ROUND(100.0 * SUM(converted) / NULLIF(SUM(leads), 0), 2) AS conv_pct
              FROM prinzip_funnel_monthly
-             WHERE month >= (CURRENT_DATE - (:months || ' months')::interval)::date
+             WHERE month >= (CURRENT_DATE - make_interval(months => :months))::date
             GROUP BY source
             ORDER BY leads DESC
            """
@ -1364,8 +1363,7 @@ _BUCKET_SQL = text(
           AND deal_count > 0
           AND (area / deal_count) BETWEEN 15 AND 200
           AND price_per_sqm BETWEEN 30000 AND 1000000
-           AND period_start_date >= NOW()
-                                  - (:months_window || ' months')::INTERVAL
+           AND period_start_date >= NOW() - make_interval(months => :months_window)
    ),
    bucketed AS (
        SELECT CASE
@ -1995,7 +1993,7 @@ def _elasticity_coef(
                       {where_district}
                       {where_class}
                       AND crm.deals_total_avg_price_thousand_rub_per_m2 > 0
-                       AND crm.report_month >= NOW() - (:ew || ' months')::interval
+                       AND crm.report_month >= NOW() - make_interval(months => :ew)
                )
                SELECT
                    regr_slope(y, x) AS slope,
@ -2086,7 +2084,7 @@ def _elasticity_per_bucket_coef(
                       {where_class}
                       AND crm.deals_total_count > 0
                       AND crm.deals_total_avg_price_thousand_rub_per_m2 > 0
-                       AND crm.report_month >= NOW() - (:ew || ' months')::interval
+                       AND crm.report_month >= NOW() - make_interval(months => :ew)
                )
                SELECT bucket,
                       regr_slope(y, x)  AS slope,
--- a/backend/app/services/scrapers/rosstat_emiss.py
+++ b/backend/app/services/scrapers/rosstat_emiss.py
@ -667,7 +667,14 @@ class EmissRow:
    """Одна готовая к upsert строка macro_indicator из ЕМИСС (source='emiss').

    Отдельно от ``MacroRow`` (open-data, source='rosstat', yearly): ЕМИСС-ряды несут
-    свою frequency (quarterly/monthly) и source — контракт upsert'а у них иной.
+    свою frequency (quarterly/monthly), source и period_type — контракт upsert'а у
+    них иной.
+
+    period_type: гранулярность под-периода ('year' | 'quarter' | 'month' | 'unknown').
+        Берётся из _emiss_period_granularity(PERIOD). Необходима как часть PK
+        macro_indicator (migration 163), чтобы годовой агрегат ('год' → 'year') и
+        Q1 ('I квартал' → 'quarter') за один год не перезаписывали друг друга при
+        ON CONFLICT DO UPDATE (оба дают obs_date=YYYY-01-01) (#1606).
    """

    indicator_type: str
@ -677,6 +684,7 @@ class EmissRow:
    unit: str
    frequency: str
    comment: str
+    period_type: str = "unknown"


 def _emiss_period_to_month(period: str) -> int | None:
@ -817,6 +825,7 @@ def parse_emiss_sdmx(raw: bytes | str, spec: EmissIndicatorSpec) -> list[EmissRo
                unit=spec.unit,
                frequency=spec.frequency,
                comment=spec.comment,
+                period_type=granularity,
            )

    return [by_key[k] for k in sorted(by_key, key=lambda k: (k[0], k[1]))]
--- a/backend/app/services/site_finder/sales_tracker_mv_refresh.py
+++ b/backend/app/services/site_finder/sales_tracker_mv_refresh.py
@ -0,0 +1,95 @@
+"""Refresh helper for the sales-tracker MVs (Issue #61).
+
+Two independent materialized views built from the Объектив sales-tracker
+("шахматки") snapshots (objective_lots / objective_lots_history), created by
+data/sql/164_mv_sales_tracker_velocity_absorption.sql:
+
+  1. mv_sales_tracker_velocity_by_district  — per (district, month) sold/total/
+     avg-sold-price. Feeds the Site Finder Velocity Score (4th scoring criterion).
+  2. mv_sales_tracker_absorption_curves     — cumulative sold% as f(months from
+     sales_start_date) per (rooms_int, area_bucket). Foundation for recommend_mix
+     + sellout forecast.
+
+The two MVs do not depend on each other, so refresh order is irrelevant; both
+are refreshed in the same call.
+
+Scheduled via Celery beat hardcoded entry in workers/beat_schedule.py
+('mv-sales-tracker-refresh-weekly', Mon 04:30 MSK).
+
+Usage example (manual, via psql-connected shell or admin endpoint):
+    from app.services.site_finder.sales_tracker_mv_refresh import refresh_sales_tracker_mvs
+
+    counts = refresh_sales_tracker_mvs(db)
+    # logs: "mv_sales_tracker_velocity_by_district refreshed: 70 rows", etc.
+"""
+
+from __future__ import annotations
+
+import logging
+
+from sqlalchemy import text
+from sqlalchemy.exc import DatabaseError
+from sqlalchemy.orm import Session
+
+logger = logging.getLogger(__name__)
+
+_MV_NAMES: tuple[str, ...] = (
+    "mv_sales_tracker_velocity_by_district",
+    "mv_sales_tracker_absorption_curves",
+)
+
+
+def _refresh_mv(db: Session, mv_name: str, *, concurrently: bool) -> int:
+    """Run REFRESH MATERIALIZED VIEW [CONCURRENTLY] <mv_name>, return row count.
+
+    Falls back to non-concurrent on the known "cannot refresh concurrently"
+    error (MV empty or no UNIQUE index — should not happen in prod since the
+    migration creates the UNIQUE index and populates the MV, but provides a
+    safe recovery path for first-run / post-recreation edge cases).
+    """
+    try:
+        if concurrently:
+            db.execute(text(f"REFRESH MATERIALIZED VIEW CONCURRENTLY {mv_name}"))
+        else:
+            db.execute(text(f"REFRESH MATERIALIZED VIEW {mv_name}"))
+        db.commit()
+    except DatabaseError as e:
+        # PostgreSQL emits "CONCURRENTLY cannot be used when the materialized
+        # view ... is not populated" (matview.c, SQLSTATE 55000), surfaced by
+        # psycopg3 as an InternalError (a DatabaseError sibling).
+        if concurrently and "concurrently cannot be used" in str(e).lower():
+            logger.warning(
+                "%s: CONCURRENTLY failed (MV likely not populated), "
+                "falling back to non-concurrent refresh",
+                mv_name,
+            )
+            db.rollback()
+            db.execute(text(f"REFRESH MATERIALIZED VIEW {mv_name}"))
+            db.commit()
+        else:
+            raise
+
+    row = db.execute(text(f"SELECT COUNT(*) FROM {mv_name}")).first()
+    count = int(row[0]) if row else 0
+    logger.info("%s refreshed: %d rows", mv_name, count)
+    return count
+
+
+def refresh_sales_tracker_mvs(db: Session, *, concurrently: bool = True) -> dict[str, int]:
+    """Refresh both sales-tracker MVs.
+
+    Args:
+        db: SQLAlchemy Session (sync).
+        concurrently: When True, uses REFRESH CONCURRENTLY (non-blocking —
+            readers continue). Requires the per-MV UNIQUE indexes
+            (mv_sales_tracker_velocity_by_district_pk,
+            mv_sales_tracker_absorption_curves_pk) and the MVs to be already
+            populated. Pass False only for first populate or after recreation.
+
+    Returns:
+        Mapping mv_name -> row count after refresh (for observability).
+    """
+    counts: dict[str, int] = {}
+    for mv_name in _MV_NAMES:
+        counts[mv_name] = _refresh_mv(db, mv_name, concurrently=concurrently)
+    return counts
--- a/backend/app/services/site_finder/velocity.py
+++ b/backend/app/services/site_finder/velocity.py
@ -16,9 +16,13 @@ Foundation: domrf_kn_objects (lat/lon, comm_name, obj_class, region_cd),
 Fallback:   rosreestr_deals (quarter_cad_number, deal_count, period_start_date).

 Linkage: domrf_kn_objects.obj_id
-         → objective_complex_mapping.domrf_obj_id
+         → objective_complex_mapping.domrf_obj_id  (gated: is_reviewed/manual/score≥0.85)
         → objective_complex_mapping.objective_complex_name
         → objective_corpus_room_month.project_name
+
+OBJ-2 (#307): маппинги фильтруются по confidence (_MAPPING_CONFIDENCE_GATE) —
+unreviewed low-score auto-matches (#1331/#1333 backfill) исключаются как
+false-positive risk.
 """

 from __future__ import annotations
@ -40,6 +44,24 @@ _EKB_MEDIAN_FALLBACK_SQM_PER_MONTH: float = 4500.0
 # пытаемся rosreestr_fallback.
 _OBJECTIVE_COVERAGE_MIN_RATIO: float = 0.50

+# OBJ-2 (#307): gate objective_complex_mapping by confidence перед использованием
+# в velocity. Fuzzy-trgm backfill (#1331/#1333) добавил ~115 auto-matched строк с
+# is_reviewed=false и низким match_score (вплоть до 0.50-0.625) — false-positive
+# risk, который раздувал/искажал velocity конкурентов.
+#
+# Принимаем mapping только если:
+#   - is_reviewed = TRUE          (человек подтвердил), ИЛИ
+#   - match_method = 'manual'     (ручной маппинг, score обычно NULL), ИЛИ
+#   - match_score >= 0.85         (AUTO_ACCEPT_THRESHOLD — high-confidence auto,
+#                                  vault: fuzzy_trgm 0.85+ надёжен для auto-use).
+#
+# Строгий gate только на is_reviewed=true дал бы 2 строки из 303 → обнулил бы
+# velocity-покрытие; 0.85-порог сохраняет 264/303 EKB-маппингов, отбрасывая 39
+# низкоуверенных. Совпадает с AUTO_ACCEPT_THRESHOLD из objective_backfill.py.
+_MAPPING_CONFIDENCE_GATE: str = (
+    "(cm.is_reviewed = TRUE OR cm.match_method = 'manual' OR cm.match_score >= 0.85)"
+)
+

@dataclass(frozen=True)
 class VelocityResult:
@ -195,7 +217,7 @@ def compute_velocity(
            sales_rows = (
                db.execute(
                    text(
-                        """
+                        f"""
                    WITH all_competitors AS (
                        SELECT unnest(CAST(:obj_ids AS int[])) AS obj_id
                    ),
@ -204,6 +226,7 @@ def compute_velocity(
                               cm.objective_complex_name
                          FROM objective_complex_mapping cm
                         WHERE cm.domrf_obj_id = ANY(:obj_ids)
+                           AND {_MAPPING_CONFIDENCE_GATE}
                    )
                    SELECT
                        ac.obj_id,
@ -311,12 +334,13 @@ def compute_velocity(
            bucket_rows = (
                db.execute(
                    text(
-                        """
+                        f"""
                    WITH mapped AS (
                        SELECT cm.domrf_obj_id AS obj_id,
                               cm.objective_complex_name
                          FROM objective_complex_mapping cm
                         WHERE cm.domrf_obj_id = ANY(:obj_ids)
+                           AND {_MAPPING_CONFIDENCE_GATE}
                    )
                    SELECT
                        m.obj_id,
--- a/backend/app/workers/beat_schedule.py
+++ b/backend/app/workers/beat_schedule.py
@ -540,4 +540,21 @@ def build_beat_schedule() -> dict:
        "options": {"queue": "celery"},
    }

+    # Sales-tracker MVs (#61) — питают Site Finder Velocity Score (4-й критерий) +
+    # recommend_mix / sellout-forecast. Оба MV (mv_sales_tracker_velocity_by_district,
+    # mv_sales_tracker_absorption_curves) рефрешатся CONCURRENTLY (non-blocking, требуют
+    # unique-индексы из миграции 161). Источник — objective_lots / objective_lots_history
+    # (Объектив-шахматки), наполняются objective_sync (Mon 04:15 МСК по умолчанию).
+    #
+    # Понедельник 04:30 МСК (Celery conf.timezone=Europe/Moscow → crontab в МСК, #1233) —
+    # ПОСЛЕ objective_sync (04:15), чтобы агрегаты считались по свежему снапшоту; в
+    # окне до тяжёлого monday-кластера site_finder-рефрешей (ird 05:00, gknspecial 05:30,
+    # supply-layers 06:00). Refresh лёгкий (~6с на 1.1M lots). Техническая infra-задача,
+    # не в job_settings (как refresh-quarter-price-index / refresh-layout-velocity).
+    schedule["mv-sales-tracker-refresh-weekly"] = {
+        "task": "tasks.mv_sales_tracker_refresh.refresh_sales_tracker_mvs",
+        "schedule": _parse_cron("30 4 * * mon"),  # 04:30 MSK, понедельник
+        "options": {"queue": "celery"},
+    }
+
    return schedule
--- a/backend/app/workers/celery_app.py
+++ b/backend/app/workers/celery_app.py
@ -83,6 +83,7 @@ celery_app = Celery(
        "app.workers.tasks.developer_registry_refresh",
        "app.workers.tasks.refresh_layout_velocity",
        "app.workers.tasks.riasurt_sverdl_harvest",
+        "app.workers.tasks.mv_sales_tracker_refresh",
    ],
 )
 celery_app.conf.timezone = "Europe/Moscow"
--- a/backend/app/workers/tasks/cbr_macro_sync.py
+++ b/backend/app/workers/tasks/cbr_macro_sync.py
@ -41,19 +41,21 @@ from app.workers.celery_app import celery_app
 logger = logging.getLogger(__name__)

 # psycopg v3: CAST(:x AS type) — НИКОГДА :x::type (SQLAlchemy+psycopg3 роняет
-# синтаксис на ::). Контракт колонок совпадает с macro_indicator (migration 123):
-#   (indicator_type, region, obs_date, value, source, frequency, unit, comment,
-#    updated_at) PK (indicator_type, region, obs_date).
+# синтаксис на ::). Контракт колонок совпадает с macro_indicator (migration 163):
+#   (indicator_type, region, obs_date, period_type, value, source, frequency, unit,
+#    comment, updated_at). PK (indicator_type, region, obs_date, period_type).
+# CBR-ряды используют period_type='unknown' (литерал) — они не несут sub-period
+# granularity и различаются по obs_date.
 UPSERT_KEY_RATE_SQL = text(
    """
    INSERT INTO macro_indicator (
-        indicator_type, region, obs_date, value,
+        indicator_type, region, obs_date, period_type, value,
        source, frequency, unit, comment
    ) VALUES (
-        'key_rate', 'rf', CAST(:d AS date), CAST(:v AS numeric),
+        'key_rate', 'rf', CAST(:d AS date), 'unknown', CAST(:v AS numeric),
        'cbr', 'daily', '%', 'CBR key rate'
    )
-    ON CONFLICT (indicator_type, region, obs_date) DO UPDATE SET
+    ON CONFLICT (indicator_type, region, obs_date, period_type) DO UPDATE SET
        value = EXCLUDED.value,
        updated_at = now()
    """
@ -61,16 +63,17 @@ UPSERT_KEY_RATE_SQL = text(

 # Инфляция «% г/г» (ИПЦ YoY): indicator_type='inflation_yoy', monthly, region='rf'.
 # obs_date уже нормализован к 1-му числу месяца парсером (parse_inflation_xlsx).
+# period_type='unknown' — месячный ряд без sub-period granularity.
 UPSERT_INFLATION_SQL = text(
    """
    INSERT INTO macro_indicator (
-        indicator_type, region, obs_date, value,
+        indicator_type, region, obs_date, period_type, value,
        source, frequency, unit, comment
    ) VALUES (
-        'inflation_yoy', 'rf', CAST(:d AS date), CAST(:v AS numeric),
+        'inflation_yoy', 'rf', CAST(:d AS date), 'unknown', CAST(:v AS numeric),
        'cbr', 'monthly', '%', 'CBR inflation YoY (ИПЦ, % г/г)'
    )
-    ON CONFLICT (indicator_type, region, obs_date) DO UPDATE SET
+    ON CONFLICT (indicator_type, region, obs_date, period_type) DO UPDATE SET
        value = EXCLUDED.value,
        updated_at = now()
    """
--- a/backend/app/workers/tasks/mv_sales_tracker_refresh.py
+++ b/backend/app/workers/tasks/mv_sales_tracker_refresh.py
@ -0,0 +1,52 @@
+"""Celery task: refresh the sales-tracker MVs (Issue #61).
+
+Scheduled via hardcoded beat entry in workers/beat_schedule.py:
+  'mv-sales-tracker-refresh-weekly' — weekly on Monday at 04:30 MSK.
+
+Refreshes (both CONCURRENTLY, non-blocking):
+  - mv_sales_tracker_velocity_by_district  (Site Finder Velocity Score, 4th criterion)
+  - mv_sales_tracker_absorption_curves     (recommend_mix + sellout forecast foundation)
+
+Both MVs are built from the Объектив sales-tracker ("шахматки") snapshots
+(objective_lots / objective_lots_history). Source data refreshes via the
+objective_sync beat job, so a weekly MV refresh keeps the aggregates current.
+
+MV-source migration: data/sql/164_mv_sales_tracker_velocity_absorption.sql.
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+
+from app.core.db import SessionLocal
+from app.services.site_finder.sales_tracker_mv_refresh import refresh_sales_tracker_mvs
+from app.workers.celery_app import celery_app
+
+logger = logging.getLogger(__name__)
+
+
+@celery_app.task(
+    bind=True,
+    name="tasks.mv_sales_tracker_refresh.refresh_sales_tracker_mvs",
+    max_retries=2,
+)
+def refresh_sales_tracker_mvs_task(self: Any) -> dict[str, Any]:
+    """REFRESH both sales-tracker MVs (#61).
+
+    Both MVs are refreshed CONCURRENTLY (non-blocking, require their UNIQUE
+    indexes created by migration 161); the service falls back to non-concurrent
+    if an MV is found unpopulated (first-run edge case).
+
+    Returns result dict for the Celery task result store / logging.
+    """
+    db = SessionLocal()
+    try:
+        counts = refresh_sales_tracker_mvs(db, concurrently=True)
+        logger.info("refresh_sales_tracker_mvs: completed, rows=%s", counts)
+        return {"status": "ok", "rows": counts}
+    except Exception as e:
+        logger.exception("refresh_sales_tracker_mvs failed: %s", e)
+        raise
+    finally:
+        db.close()
--- a/backend/app/workers/tasks/rosstat_macro_sync.py
+++ b/backend/app/workers/tasks/rosstat_macro_sync.py
@ -47,21 +47,23 @@ from app.workers.celery_app import celery_app
 logger = logging.getLogger(__name__)

 # psycopg v3: CAST(:x AS type) — НИКОГДА :x::type (SQLAlchemy+psycopg3 роняет
-# синтаксис на ::). Контракт колонок совпадает с macro_indicator (migration 123):
-#   (indicator_type, region, obs_date, value, source, frequency, unit, comment,
-#    updated_at) PK (indicator_type, region, obs_date). source='rosstat',
-#   frequency='yearly' (текущие ряды Росстата — годовые: obs_date = 1 января года).
+# синтаксис на ::). Контракт колонок совпадает с macro_indicator (migration 163):
+#   (indicator_type, region, obs_date, period_type, value, source, frequency, unit,
+#    comment, updated_at). PK (indicator_type, region, obs_date, period_type).
+# Не-ЕМИСС источники (open-data, СМР) используют period_type='unknown' (литерал) —
+# они различаются по obs_date без sub-period granularity.
+# source='rosstat', frequency='yearly' (текущие ряды Росстата — годовые).
 UPSERT_ROSSTAT_SQL = text(
    """
    INSERT INTO macro_indicator (
-        indicator_type, region, obs_date, value,
+        indicator_type, region, obs_date, period_type, value,
        source, frequency, unit, comment
    ) VALUES (
        CAST(:itype AS text), CAST(:region AS text), CAST(:d AS date),
-        CAST(:v AS numeric),
+        'unknown', CAST(:v AS numeric),
        'rosstat', 'yearly', CAST(:unit AS text), CAST(:comment AS text)
    )
-    ON CONFLICT (indicator_type, region, obs_date) DO UPDATE SET
+    ON CONFLICT (indicator_type, region, obs_date, period_type) DO UPDATE SET
        value = EXCLUDED.value,
        source = EXCLUDED.source,
        frequency = EXCLUDED.frequency,
@ -71,20 +73,23 @@ UPSERT_ROSSTAT_SQL = text(
    """
 )

-# ЕМИСС-ряды (source='emiss'): frequency параметризована (quarterly для доходов,
-# monthly для ИПЦ когда добавится) — в отличие от open-data, где она фикс 'yearly'.
-# Тот же PK и ON CONFLICT-контракт. CAST(:x AS type) — НИКОГДА :x::type (psycopg v3).
+# ЕМИСС-ряды (source='emiss'): period_type параметризован — 'year' | 'quarter' |
+# 'month' (из _emiss_period_granularity). Это ключевое отличие от не-ЕМИСС источников:
+# период ЕМИСС-ряда несёт granularity, необходимую для разделения годового агрегата
+# ('год' → 'year') и Q1 ('I квартал' → 'quarter'), оба с obs_date=YYYY-01-01 (#1606).
+# frequency параметризована (quarterly для доходов, monthly для ИПЦ когда добавится).
+# CAST(:x AS type) — НИКОГДА :x::type (psycopg v3).
 UPSERT_EMISS_SQL = text(
    """
    INSERT INTO macro_indicator (
-        indicator_type, region, obs_date, value,
+        indicator_type, region, obs_date, period_type, value,
        source, frequency, unit, comment
    ) VALUES (
        CAST(:itype AS text), CAST(:region AS text), CAST(:d AS date),
-        CAST(:v AS numeric),
+        CAST(:period_type AS text), CAST(:v AS numeric),
        'emiss', CAST(:freq AS text), CAST(:unit AS text), CAST(:comment AS text)
    )
-    ON CONFLICT (indicator_type, region, obs_date) DO UPDATE SET
+    ON CONFLICT (indicator_type, region, obs_date, period_type) DO UPDATE SET
        value = EXCLUDED.value,
        source = EXCLUDED.source,
        frequency = EXCLUDED.frequency,
@ -96,19 +101,19 @@ UPSERT_EMISS_SQL = text(

 # Индекс цен на СМР — открытый xlsx Росстата: source='rosstat' (rosstat.gov.ru-файл),
 # НО frequency='monthly' (в отличие от open-data демографии — там фикс 'yearly'),
-# поэтому frequency параметризована. MacroRow не несёт frequency-поля, подставляем
-# литералом в bind. Тот же PK и ON CONFLICT-контракт. CAST(:x AS type) — psycopg v3.
+# поэтому frequency параметризована. MacroRow не несёт frequency/period_type-полей;
+# подставляем литералами. CAST(:x AS type) — psycopg v3.
 UPSERT_ROSSTAT_MONTHLY_SQL = text(
    """
    INSERT INTO macro_indicator (
-        indicator_type, region, obs_date, value,
+        indicator_type, region, obs_date, period_type, value,
        source, frequency, unit, comment
    ) VALUES (
        CAST(:itype AS text), CAST(:region AS text), CAST(:d AS date),
-        CAST(:v AS numeric),
+        'unknown', CAST(:v AS numeric),
        'rosstat', 'monthly', CAST(:unit AS text), CAST(:comment AS text)
    )
-    ON CONFLICT (indicator_type, region, obs_date) DO UPDATE SET
+    ON CONFLICT (indicator_type, region, obs_date, period_type) DO UPDATE SET
        value = EXCLUDED.value,
        source = EXCLUDED.source,
        frequency = EXCLUDED.frequency,
@ -185,9 +190,15 @@ def _upsert_monthly_rows(db: Session, rows: list[MacroRow]) -> int:


 def _upsert_emiss_rows(db: Session, rows: list[EmissRow]) -> int:
-    """Апсертит EmissRow в macro_indicator (source='emiss', frequency per-row).
+    """Апсертит EmissRow в macro_indicator (source='emiss', frequency+period_type per-row).
+
    SAVEPOINT per-row, чтобы один битый ряд не откатывал всю транзакцию. Возвращает
-    число успешных upsert'ов."""
+    число успешных upsert'ов.
+
+    period_type (из r.period_type) — часть нового PK (migration 163): позволяет
+    годовому агрегату ('year') и Q1 ('quarter') за один год коexist в таблице без
+    взаимной перезаписи (#1606).
+    """
    upserted = 0
    for r in rows:
        try:
@ -198,6 +209,7 @@ def _upsert_emiss_rows(db: Session, rows: list[EmissRow]) -> int:
                        "itype": r.indicator_type,
                        "region": r.region,
                        "d": r.obs_date,
+                        "period_type": r.period_type,
                        "v": r.value,
                        "freq": r.frequency,
                        "unit": r.unit,
@ -207,10 +219,11 @@ def _upsert_emiss_rows(db: Session, rows: list[EmissRow]) -> int:
            upserted += 1
        except Exception as e:
            logger.warning(
-                "upsert emiss %s/%s@%s=%s failed: %s",
+                "upsert emiss %s/%s@%s[%s]=%s failed: %s",
                r.indicator_type,
                r.region,
                r.obs_date,
+                r.period_type,
                r.value,
                e,
            )
--- a/backend/tests/scrapers/test_emiss_sdmx.py
+++ b/backend/tests/scrapers/test_emiss_sdmx.py
@ -108,19 +108,30 @@ def test_yearly_and_q1_both_survive_dedup() -> None:
    assert Decimal("42000") in values, "Q1-наблюдение потеряно"
    # obs_date у обоих одинаковый (это нормально — коллизия теперь на стороне DB-upsert)
    assert all(r.obs_date == date(2023, 1, 1) for r in rows)
+    # period_type: годовой → 'year', Q1 → 'quarter' (часть PK в macro_indicator, migration 163)
+    period_types = {r.period_type for r in rows}
+    assert period_types == {
+        "year",
+        "quarter",
+    }, f"ожидались period_type year+quarter, получили {period_types}"


 # ── real-fixture extraction (income id=57039) ─────────────────────────────────────


 def test_income_extracts_sverdlovsk_only() -> None:
-    """Из реальной SDMX-выгрузки извлекается ТОЛЬКО Свердл (ОКАТО 65) — РФ/ЦФО/Адыгея нет."""
+    """Из реальной SDMX-выгрузки извлекается ТОЛЬКО Свердл (ОКАТО 65) — РФ/ЦФО/Адыгея нет.
+    Все строки квартальные → period_type='quarter' (часть PK macro_indicator, migration 163).
+    """
    rows = parse_emiss_sdmx(_load("emiss_income_57039.xml"), INCOME_PER_CAPITA_SPEC)
    assert rows, "ожидались строки по Свердл"
    assert {r.region for r in rows} == {"sverdl"}
    assert all(r.indicator_type == "income_per_capita" for r in rows)
    assert all(r.unit == "руб" for r in rows)
    assert all(r.frequency == "quarterly" for r in rows)
+    assert all(
+        r.period_type == "quarter" for r in rows
+    ), "квартальные строки должны иметь period_type='quarter'"


 def test_income_concrete_values_and_dates() -> None:
--- a/backend/tests/services/test_objective_backfill.py
+++ b/backend/tests/services/test_objective_backfill.py
@ -77,7 +77,12 @@ def test_find_match_candidates_returns_candidates() -> None:


 def test_auto_apply_matches_dry_run_no_inserts() -> None:
-    """dry_run=True возвращает счётчики без обращения к БД (execute не вызывается)."""
+    """dry_run=True возвращает projected-счётчики без обращения к БД.
+
+    auto_accepted = сколько кандидатов БЫЛО БЫ принято (preview), а не 0 —
+    смысл dry-run в admin-endpoint'е именно показать оператору объём перед
+    реальным insert. execute/commit при этом не вызываются.
+    """
    mock_db = MagicMock()

    candidates = [
@ -88,8 +93,9 @@ def test_auto_apply_matches_dry_run_no_inserts() -> None:

    result = auto_apply_matches(mock_db, candidates, dry_run=True)

-    assert result["auto_accepted"] == 0
+    assert result["auto_accepted"] == 1  # projected: 1 кандидат >= AUTO_ACCEPT_THRESHOLD
    assert result["review_queue"] == 2
+    assert result["skipped"] == 0
    mock_db.execute.assert_not_called()
    mock_db.commit.assert_not_called()

--- a/backend/tests/test_velocity.py
+++ b/backend/tests/test_velocity.py
@ -327,6 +327,39 @@ def test_by_room_bucket_empty_when_no_bucket_data():
    assert result.by_room_bucket == {}


+def test_mapping_confidence_gate_in_sales_query():
+    """OBJ-2 (#307): sales/bucket queries фильтруют objective_complex_mapping
+    по confidence — unreviewed low-score auto-matches исключены.
+
+    Проверяем, что SQL, переданный в db.execute для маппинг-CTE, содержит
+    предикат gate (is_reviewed / manual / match_score >= 0.85). Это гарантирует,
+    что ~115 fuzzy-trgm строк с is_reviewed=false и score<0.85 не попадают в velocity.
+    """
+    comp_rows = [_comp_row(1), _comp_row(2)]
+    sales_rows = [
+        _sales_row(1, total_sqm=4000.0, months=4),
+        _sales_row(2, total_sqm=3000.0, months=4),
+    ]
+    bucket_rows = [_bucket_row(1, "1", units_sold=20, sqm_sold=900.0)]
+    db = _make_db(comp_rows=comp_rows, sales_rows=sales_rows, bucket_rows=bucket_rows)
+
+    with patch(
+        "app.services.site_finder.velocity._get_ekb_median",
+        return_value=_EKB_MEDIAN_FALLBACK_SQM_PER_MONTH,
+    ):
+        compute_velocity(db, parcel_geom_wkt=_PARCEL_WKT)
+
+    # db.execute вызывается 3 раза: comp / sales / bucket. SQL берём из call_args.
+    executed_sql = [str(call.args[0]) for call in db.execute.call_args_list]
+    # comp-query НЕ трогает mapping; sales (idx 1) и bucket (idx 2) — должны иметь gate.
+    mapping_queries = [s for s in executed_sql if "objective_complex_mapping" in s]
+    assert len(mapping_queries) >= 2, "ожидаются sales + bucket запросы с mapping"
+    for sql in mapping_queries:
+        assert "cm.is_reviewed = TRUE" in sql
+        assert "cm.match_method = 'manual'" in sql
+        assert "cm.match_score >= 0.85" in sql
+
+
 def test_sample_competitors_include_by_room_bucket():
    """sample_competitors каждого элемента содержит by_room_bucket."""
    comp_rows = [_comp_row(1), _comp_row(2)]
--- a/backend/tests/workers/test_cbr_macro_sync.py
+++ b/backend/tests/workers/test_cbr_macro_sync.py
@ -48,14 +48,16 @@ def test_upsert_sql_contract() -> None:
    assert "'rf'" in sql
    assert "'cbr'" in sql
    assert "'daily'" in sql
-    # ON CONFLICT по полному PK + обновление value/updated_at
-    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE) DO UPDATE" in upper
+    # ON CONFLICT по новому PK включает period_type (migration 163)
+    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE, PERIOD_TYPE) DO UPDATE" in upper
    assert "VALUE = EXCLUDED.VALUE" in upper
    assert "UPDATED_AT = NOW()" in upper
    # psycopg v3: CAST(:x AS type), НИКОГДА :x::type
    assert "CAST(:D AS DATE)" in upper
    assert "CAST(:V AS NUMERIC)" in upper
    assert "::" not in sql
+    # CBR-строки используют period_type='unknown' (литерал в SQL)
+    assert "'unknown'" in sql


 def test_task_upserts_each_row_with_correct_params() -> None:
@ -192,13 +194,14 @@ def test_upsert_inflation_sql_contract() -> None:
    assert "'rf'" in sql
    assert "'cbr'" in sql
    assert "'monthly'" in sql
-    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE) DO UPDATE" in upper
+    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE, PERIOD_TYPE) DO UPDATE" in upper
    assert "VALUE = EXCLUDED.VALUE" in upper
    assert "UPDATED_AT = NOW()" in upper
    # psycopg v3: CAST(:x AS type), НИКОГДА :x::type
    assert "CAST(:D AS DATE)" in upper
    assert "CAST(:V AS NUMERIC)" in upper
    assert "::" not in sql
+    assert "'unknown'" in sql


 def test_task_registered_in_beat_weekly() -> None:
--- a/backend/tests/workers/test_riasurt_sverdl_harvest.py
+++ b/backend/tests/workers/test_riasurt_sverdl_harvest.py
@ -128,9 +128,12 @@ def test_harvest_for_mo_skips_geomless_feature(monkeypatch: Any) -> None:


 def test_harvest_all_iterates_5_mo(monkeypatch: Any) -> None:
-    """harvest_all прогоняет все 5 МО агломерации."""
+    """harvest_all прогоняет все 5 МО агломерации (при включённом флаге)."""
    db = _FakeDB()
    _patch(monkeypatch, db)
+    monkeypatch.setattr(
+        riasurt_sverdl_harvest.settings, "enable_riasurt_harvest", True, raising=False
+    )

    res = riasurt_sverdl_harvest.harvest_all_riasurt_sverdl([845274])
    assert res["mo"] == 5
@ -138,6 +141,21 @@ def test_harvest_all_iterates_5_mo(monkeypatch: Any) -> None:
    assert res["features"] == 5


+def test_harvest_all_disabled_by_default(monkeypatch: Any) -> None:
+    """Гейт #108: при выключенном флаге harvest_all возвращает early без WMS-вызовов."""
+    db = _FakeDB()
+    client = _patch(monkeypatch, db)
+    monkeypatch.setattr(
+        riasurt_sverdl_harvest.settings, "enable_riasurt_harvest", False, raising=False
+    )
+
+    res = riasurt_sverdl_harvest.harvest_all_riasurt_sverdl([845274])
+    assert res == {"mo": 0, "features": 0}
+    # ни одного WMS-запроса, ни одной записи в БД
+    assert client.bbox_calls == []
+    assert db.executed == []
+
+
 def test_mo_bboxes_has_5_agglomeration_municipalities() -> None:
    """MO_BBOXES содержит ровно 5 МО окраин агломерации."""
    assert set(riasurt_sverdl_harvest.MO_BBOXES) == {
--- a/backend/tests/workers/test_rosstat_macro_sync.py
+++ b/backend/tests/workers/test_rosstat_macro_sync.py
@ -35,7 +35,7 @@ def _make_mock_db() -> tuple[MagicMock, list[dict[str, Any]]]:

 def test_upsert_sql_contract() -> None:
    """UPSERT_ROSSTAT_SQL содержит обязательные литералы контракта macro_indicator
-    и НЕ использует :x::type (psycopg v3)."""
+    и НЕ использует :x::type (psycopg v3). PK включает period_type (migration 163)."""
    from app.workers.tasks.rosstat_macro_sync import UPSERT_ROSSTAT_SQL

    sql = str(UPSERT_ROSSTAT_SQL)
@ -44,7 +44,7 @@ def test_upsert_sql_contract() -> None:
    assert "INTO MACRO_INDICATOR" in upper
    assert "'rosstat'" in sql
    assert "'yearly'" in sql
-    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE) DO UPDATE" in upper
+    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE, PERIOD_TYPE) DO UPDATE" in upper
    assert "VALUE = EXCLUDED.VALUE" in upper
    assert "UPDATED_AT = NOW()" in upper
    # psycopg v3: CAST(:x AS type), НИКОГДА :x::type
@ -52,6 +52,8 @@ def test_upsert_sql_contract() -> None:
    assert "CAST(:D AS DATE)" in upper
    assert "CAST(:V AS NUMERIC)" in upper
    assert "::" not in sql
+    # не-ЕМИСС строки используют period_type='unknown' (литерал в SQL)
+    assert "'unknown'" in sql


 def test_task_upserts_each_row_with_correct_params() -> None:
@ -155,15 +157,24 @@ def test_task_emiss_failure_does_not_block_opendata() -> None:


 def test_task_upserts_emiss_rows_with_correct_params() -> None:
-    """Каждая EmissRow → execute UPSERT_EMISS_SQL с itype/region/d/v/freq/unit/comment."""
+    """Каждая EmissRow → execute UPSERT_EMISS_SQL с itype/region/d/period_type/v/freq/unit/comment.
+
+    period_type передаётся из r.period_type (часть нового PK, migration 163).
+    """
    from app.services.scrapers.rosstat_emiss import EmissRow
    from app.workers.tasks import rosstat_macro_sync as task_mod

    db, captured = _make_mock_db()
    emiss_rows = [
        EmissRow(
-            "income_per_capita", "sverdl", date(2024, 1, 1),
-            Decimal("54006"), "руб", "quarterly", "c",
+            "income_per_capita",
+            "sverdl",
+            date(2024, 1, 1),
+            Decimal("54006"),
+            "руб",
+            "quarterly",
+            "c",
+            period_type="quarter",
        ),
    ]

@ -181,6 +192,7 @@ def test_task_upserts_emiss_rows_with_correct_params() -> None:
            "itype": "income_per_capita",
            "region": "sverdl",
            "d": date(2024, 1, 1),
+            "period_type": "quarter",
            "v": Decimal("54006"),
            "freq": "quarterly",
            "unit": "руб",
@ -190,7 +202,8 @@ def test_task_upserts_emiss_rows_with_correct_params() -> None:


 def test_upsert_emiss_sql_contract() -> None:
-    """UPSERT_EMISS_SQL: source='emiss', frequency параметризован, ON CONFLICT, CAST not ::."""
+    """UPSERT_EMISS_SQL: source='emiss', frequency+period_type параметризованы,
+    ON CONFLICT включает period_type (migration 163), CAST not ::."""
    from app.workers.tasks.rosstat_macro_sync import UPSERT_EMISS_SQL

    sql = str(UPSERT_EMISS_SQL)
@ -198,14 +211,16 @@ def test_upsert_emiss_sql_contract() -> None:
    assert "INTO MACRO_INDICATOR" in upper
    assert "'emiss'" in sql
    assert "CAST(:FREQ AS TEXT)" in upper
-    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE) DO UPDATE" in upper
+    assert "CAST(:PERIOD_TYPE AS TEXT)" in upper
+    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE, PERIOD_TYPE) DO UPDATE" in upper
    assert "CAST(:ITYPE AS TEXT)" in upper
    assert "CAST(:V AS NUMERIC)" in upper
    assert "::" not in sql


 def test_upsert_rosstat_monthly_sql_contract() -> None:
-    """UPSERT_ROSSTAT_MONTHLY_SQL: source='rosstat', frequency='monthly', CAST not ::."""
+    """UPSERT_ROSSTAT_MONTHLY_SQL: source='rosstat', frequency='monthly', period_type='unknown',
+    ON CONFLICT включает period_type (migration 163), CAST not ::."""
    from app.workers.tasks.rosstat_macro_sync import UPSERT_ROSSTAT_MONTHLY_SQL

    sql = str(UPSERT_ROSSTAT_MONTHLY_SQL)
@ -213,11 +228,12 @@ def test_upsert_rosstat_monthly_sql_contract() -> None:
    assert "INTO MACRO_INDICATOR" in upper
    assert "'rosstat'" in sql
    assert "'monthly'" in sql
-    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE) DO UPDATE" in upper
+    assert "ON CONFLICT (INDICATOR_TYPE, REGION, OBS_DATE, PERIOD_TYPE) DO UPDATE" in upper
    assert "CAST(:ITYPE AS TEXT)" in upper
    assert "CAST(:D AS DATE)" in upper
    assert "CAST(:V AS NUMERIC)" in upper
    assert "::" not in sql
+    assert "'unknown'" in sql


 def test_task_upserts_construction_rows_with_correct_params() -> None:
@ -228,8 +244,12 @@ def test_task_upserts_construction_rows_with_correct_params() -> None:
    db, captured = _make_mock_db()
    constr_rows = [
        MacroRow(
-            "construction_price_index", "rf", date(2025, 1, 1),
-            Decimal("100.8"), "%", "smr",
+            "construction_price_index",
+            "rf",
+            date(2025, 1, 1),
+            Decimal("100.8"),
+            "%",
+            "smr",
        ),
    ]

--- a/data/sql/163_emiss_pk_period_type.sql
+++ b/data/sql/163_emiss_pk_period_type.sql
@ -0,0 +1,92 @@
+-- 163_emiss_pk_period_type.sql
+-- #1606 follow-up: расширить PK macro_indicator колонкой period_type, чтобы годовой
+-- агрегат ('год' → 'year') и Q1 ('I квартал' → 'quarter') за один год не перезаписывали
+-- друг друга при ON CONFLICT DO UPDATE (оба дают obs_date=YYYY-01-01).
+--
+-- Контекст:
+--   PR #1687 (#1606) исправил in-memory дедупликацию в parse_emiss_sdmx: ключ дедупа
+--   стал трёхкомпонентным (region, obs_date, granularity). Но PK таблицы остался
+--   (indicator_type, region, obs_date) — при апсерте в БД коллизия сохранялась.
+--   Эта миграция фиксирует PK на стороне БД.
+--
+-- Что делает:
+--   1. Добавляет колонку period_type TEXT NOT NULL DEFAULT 'unknown'.
+--      Все существующие строки (CBR, rosstat open-data, domrf) получают 'unknown' —
+--      это корректно: у них нет sub-period granularity (они уже различаются по obs_date).
+--   2. Бэкфилл: строки source='emiss' обновляем до 'quarter' (единственный
+--      активный ЕМИСС-индикатор — income_per_capita, он квартальный; годовых EMISS-
+--      строк ещё нет в таблице до этой миграции). Значение ДОЛЖНО совпадать с тем,
+--      что пишет UPSERT_EMISS_SQL (_emiss_period_granularity → 'quarter'/'year'/'month',
+--      короткая форма), иначе ON CONFLICT не сматчит → дубли при следующем скрейпе.
+--   3. Пересоздаёт PRIMARY KEY: старый (indicator_type, region, obs_date) → новый
+--      (indicator_type, region, obs_date, period_type).
+--   4. Пересоздаёт сопутствующий индекс idx_macro_type_region_date с тем же составом
+--      (расширяется автоматически через новый PK-индекс; отдельный индекс DROP+CREATE).
+--
+-- Зависимости: macro_indicator (migration 123_macro_indicator.sql).
+-- Нет VIEW/FK зависимостей от macro_indicator PK (проверено через pg_depend).
+-- Idempotent: ADD COLUMN IF NOT EXISTS + IF NOT EXISTS в CREATE INDEX. Повторный
+-- прогон безопасен: DROP CONSTRAINT / ADD CONSTRAINT могут упасть если PK уже
+-- переименован — обёрнуты в DO $$ BEGIN ... EXCEPTION WHEN ... END $$; блоки.
+--
+-- Deploy order: SQL migration применяется ПЕРВОЙ (auto-deploy.yml), затем деплоится
+-- backend со обновлёнными UPSERT_EMISS_SQL / UPSERT_ROSSTAT_SQL / UPSERT_KEY_RATE_SQL
+-- / UPSERT_INFLATION_SQL / UPSERT_ROSSTAT_MONTHLY_SQL (они несут новый конфликт-таргет
+-- + period_type в INSERT).
+
+BEGIN;
+
+-- ── 1. Добавить колонку period_type (DEFAULT 'unknown' для всех существующих строк) ──
+ALTER TABLE macro_indicator
+    ADD COLUMN IF NOT EXISTS period_type TEXT NOT NULL DEFAULT 'unknown';
+
+-- ── 2. Бэкфилл ЕМИСС-строк → 'quarter' ────────────────────────────────────────────
+-- Все существующие ЕМИСС-строки — квартальные (income_per_capita). Значение 'quarter'
+-- (короткая форма) обязано совпадать с UPSERT_EMISS_SQL, который параметризует
+-- period_type из _emiss_period_granularity ('quarter'/'year'/'month'). Иначе после
+-- деплоя следующий скрейп вставит 'quarter'-строки, не матчащие 'quarterly' на
+-- ON CONFLICT → дубли для каждого квартального наблюдения. Если появятся 'year'-строки
+-- (будущие индикаторы) — придут с корректным period_type из скрейпера.
+UPDATE macro_indicator
+    SET period_type = 'quarter'
+    WHERE source = 'emiss'
+      AND period_type = 'unknown';
+
+-- ── 3. Пересоздать PRIMARY KEY ────────────────────────────────────────────────────────
+-- PostgreSQL не поддерживает ALTER PRIMARY KEY напрямую — нужно DROP + ADD.
+-- Ловим случай когда старый PK уже дропнут (повторный прогон).
+DO $$
+BEGIN
+    ALTER TABLE macro_indicator DROP CONSTRAINT macro_indicator_pkey;
+EXCEPTION
+    WHEN undefined_object THEN
+        NULL; -- PK уже удалён (повторный прогон)
+    WHEN feature_not_supported THEN
+        NULL;
+END;
+$$;
+
+-- Новый PK включает period_type. Если constraint с этим именем уже существует —
+-- ADD CONSTRAINT бросит duplicate_object (42710, дубль имени constraint), ловим.
+DO $$
+BEGIN
+    ALTER TABLE macro_indicator
+        ADD CONSTRAINT macro_indicator_pkey
+        PRIMARY KEY (indicator_type, region, obs_date, period_type);
+EXCEPTION
+    WHEN duplicate_object THEN
+        NULL; -- constraint с таким именем уже создан (повторный прогон)
+    WHEN invalid_table_definition THEN
+        NULL; -- уже существует тот же constraint
+END;
+$$;
+
+-- ── 4. Пересоздать сопутствующий индекс ──────────────────────────────────────────────
+-- Старый индекс (без period_type в составе) уже покрыт новым PK-индексом по факту,
+-- но явно дропаем и пересоздаём с period_type для консистентности плана запросов.
+DROP INDEX IF EXISTS idx_macro_type_region_date;
+
+CREATE INDEX IF NOT EXISTS idx_macro_type_region_date
+    ON macro_indicator (indicator_type, region, obs_date DESC, period_type);
+
+COMMIT;
--- a/data/sql/164_mv_sales_tracker_velocity_absorption.sql
+++ b/data/sql/164_mv_sales_tracker_velocity_absorption.sql
@ -0,0 +1,184 @@
+-- 164_mv_sales_tracker_velocity_absorption.sql
+-- Issue #61 — Velocity materialized views for Site Finder Velocity Score (4th scoring
+-- criterion) + recommend_mix smart unit-mix. Foundation for sellout forecast.
+--
+-- B2-1 data source ("шахматки" / sales-tracker): the Объектив scraper
+-- (backend/app/workers/tasks/scrape_objective.py) → tables:
+--   objective_lots          — 1.12M rows, one row per tracked lot (current state),
+--                             carries district / rooms_int / area_pd / sales_start_date /
+--                             is_sold / registration_date / contract_date / price_per_m2_rub.
+--   objective_lots_history  — 974k rows, daily-ish per-lot snapshots
+--                             (snapshot_date, is_sold, status, prices).
+-- Snapshot history depth (as of 2026-06-17): 3 captures 2026-05-17 / 05-19 / 06-03 (spans
+-- >2 weeks, sold count moved 193188->194893 => measurable absorption). Cohort/absorption
+-- resolution improves automatically as the weekly scraper accumulates more snapshots.
+--
+-- -- MV 1: mv_sales_tracker_velocity_by_district --------------------------------------
+--   Grain: (district, sale_month). One row per district per month.
+--   Dedup: a lot appears in multiple snapshots within a month -> we keep that lot's LATEST
+--          snapshot within the month (DISTINCT ON lot, snapshot_date DESC) before
+--          aggregating, so total_count is lots-tracked-that-month (not snapshot rows).
+--   Metrics: total_count, sold_count, avg_sold_price_per_m2, avg_sold_price_total,
+--            sold_share (velocity proxy for SF Velocity Score).
+--
+-- -- MV 2: mv_sales_tracker_absorption_curves ----------------------------------------
+--   Grain: (rooms_int, area_bucket, months_since_start). Cumulative sold% as f(months
+--          from first_seen). "first_seen" = objective_lots.sales_start_date (true sales
+--          launch — richer/longer than the 3-snapshot window). Sold-month anchor =
+--          COALESCE(registration_date, contract_date). months_since_start clamped >= 0
+--          (712 noise rows have anchor < start). 99.98% of sold lots carry both dates.
+--          cohort_size = all lots in (rooms, area_bucket) cohort; cum_sold = sold lots
+--          whose months_since_start <= the row's bucket; cum_sold_pct = cum_sold/cohort.
+--   This is snapshot-sparsity-independent (driven by registration dates, not snapshots),
+--          so the curve is usable today and the foundation for sellout forecast.
+--
+-- REFRESH CONCURRENTLY: both MVs get a UNIQUE index on their full grain immediately after
+--   creation (on empty MV -> instant), enabling non-blocking weekly REFRESH CONCURRENTLY.
+--   Scheduled via Celery beat `mv-sales-tracker-refresh-weekly` (Mon 04:30 MSK) ->
+--   task app.workers.tasks.mv_sales_tracker_refresh.refresh_sales_tracker_mvs.
+--
+-- Deploy: auto-applied by deploy.yml via _schema_migrations tracking (one-shot, NN order).
+-- Dependencies on existing objects: objective_lots, objective_lots_history (read-only).
+-- No views depend on these MVs at creation time.
+--
+-- WARN: re-apply (DR / lost _schema_migrations / dev local) DROP ... CASCADE снесёт MV +
+--       зависимости. После re-apply ПЕРВЫЙ refresh = non-concurrent (CONCURRENTLY падает
+--       на пустой/не-populated MV). _schema_migrations нормально предотвращает re-apply.
+
+BEGIN;
+
+-- ====================================================================================
+-- MV 1: velocity by district x month
+-- ====================================================================================
+DROP MATERIALIZED VIEW IF EXISTS mv_sales_tracker_velocity_by_district CASCADE;
+
+CREATE MATERIALIZED VIEW mv_sales_tracker_velocity_by_district AS
+WITH lot_month AS (
+    -- One row per (lot, month): the lot's latest snapshot within that month.
+    SELECT DISTINCT ON (h.objective_lot_id, date_trunc('month', h.snapshot_date))
+        l.district                                          AS district,
+        date_trunc('month', h.snapshot_date)::date          AS sale_month,
+        h.objective_lot_id,
+        h.is_sold,
+        h.price_per_m2_rub,
+        h.price_calculated_total_rub
+    FROM objective_lots_history h
+    JOIN objective_lots l ON l.objective_lot_id = h.objective_lot_id
+    WHERE l.district IS NOT NULL
+    ORDER BY h.objective_lot_id,
+             date_trunc('month', h.snapshot_date),
+             h.snapshot_date DESC
+)
+SELECT
+    district,
+    sale_month,
+    count(*)::int                                                       AS total_count,
+    count(*) FILTER (WHERE is_sold)::int                                AS sold_count,
+    round(
+        count(*) FILTER (WHERE is_sold)::numeric
+        / NULLIF(count(*), 0), 4
+    )                                                                    AS sold_share,
+    round(avg(price_per_m2_rub) FILTER (WHERE is_sold), 2)              AS avg_sold_price_per_m2,
+    round(avg(price_calculated_total_rub) FILTER (WHERE is_sold), 2)    AS avg_sold_price_total
+FROM lot_month
+GROUP BY district, sale_month
+WITH NO DATA;
+
+-- UNIQUE index on full grain -> enables REFRESH CONCURRENTLY (created on empty MV = instant)
+CREATE UNIQUE INDEX mv_sales_tracker_velocity_by_district_pk
+    ON mv_sales_tracker_velocity_by_district (district, sale_month);
+
+CREATE INDEX mv_sales_tracker_velocity_district_idx
+    ON mv_sales_tracker_velocity_by_district (district);
+
+REFRESH MATERIALIZED VIEW mv_sales_tracker_velocity_by_district;
+
+COMMENT ON MATERIALIZED VIEW mv_sales_tracker_velocity_by_district IS
+  'Issue #61. Per (district, month) sold/total/avg-sold-price from objective_lots_history '
+  'snapshots (Obektiv shahmatka), deduped to latest snapshot per lot per month. '
+  'Feeds Site Finder Velocity Score. Refresh weekly CONCURRENTLY.';
+
+-- ====================================================================================
+-- MV 2: absorption curves by room_count x area_bucket x months-from-first-seen
+-- ====================================================================================
+DROP MATERIALIZED VIEW IF EXISTS mv_sales_tracker_absorption_curves CASCADE;
+
+CREATE MATERIALIZED VIEW mv_sales_tracker_absorption_curves AS
+WITH base AS (
+    -- One row per lot. area_bucket from area_pd; months_since_start = whole months between
+    -- sales_start_date and the sold anchor (reg/contract). Unsold lots have NULL anchor.
+    SELECT
+        l.rooms_int,
+        CASE
+            WHEN l.area_pd < 30  THEN '<30'
+            WHEN l.area_pd < 45  THEN '30-45'
+            WHEN l.area_pd < 60  THEN '45-60'
+            WHEN l.area_pd < 80  THEN '60-80'
+            ELSE '80+'
+        END                                                             AS area_bucket,
+        l.is_sold,
+        CASE
+            WHEN l.is_sold
+             AND l.sales_start_date IS NOT NULL
+             AND COALESCE(l.registration_date, l.contract_date) IS NOT NULL
+            THEN GREATEST(
+                0,
+                (date_part('year',  age(COALESCE(l.registration_date, l.contract_date),
+                                         l.sales_start_date)) * 12
+                 + date_part('month', age(COALESCE(l.registration_date, l.contract_date),
+                                          l.sales_start_date)))::int
+            )
+        END                                                             AS months_since_start
+    FROM objective_lots l
+    WHERE l.rooms_int IS NOT NULL
+      AND l.area_pd  IS NOT NULL
+      AND l.sales_start_date IS NOT NULL
+),
+cohort AS (
+    SELECT rooms_int, area_bucket, count(*)::int AS cohort_size
+    FROM base
+    GROUP BY rooms_int, area_bucket
+),
+sold_at_month AS (
+    SELECT rooms_int, area_bucket, months_since_start, count(*)::int AS sold_in_month
+    FROM base
+    WHERE is_sold AND months_since_start IS NOT NULL
+    GROUP BY rooms_int, area_bucket, months_since_start
+)
+SELECT
+    s.rooms_int,
+    s.area_bucket,
+    s.months_since_start,
+    c.cohort_size,
+    -- cumulative sold up to and including this month-offset (per cohort)
+    SUM(s.sold_in_month) OVER (
+        PARTITION BY s.rooms_int, s.area_bucket
+        ORDER BY s.months_since_start
+        ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
+    )::int                                                              AS cum_sold,
+    round(
+        SUM(s.sold_in_month) OVER (
+            PARTITION BY s.rooms_int, s.area_bucket
+            ORDER BY s.months_since_start
+            ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
+        )::numeric / NULLIF(c.cohort_size, 0), 4
+    )                                                                    AS cum_sold_pct
+FROM sold_at_month s
+JOIN cohort c ON c.rooms_int = s.rooms_int AND c.area_bucket = s.area_bucket
+WITH NO DATA;
+
+-- UNIQUE index on full grain -> enables REFRESH CONCURRENTLY
+CREATE UNIQUE INDEX mv_sales_tracker_absorption_curves_pk
+    ON mv_sales_tracker_absorption_curves (rooms_int, area_bucket, months_since_start);
+
+CREATE INDEX mv_sales_tracker_absorption_cohort_idx
+    ON mv_sales_tracker_absorption_curves (rooms_int, area_bucket);
+
+REFRESH MATERIALIZED VIEW mv_sales_tracker_absorption_curves;
+
+COMMENT ON MATERIALIZED VIEW mv_sales_tracker_absorption_curves IS
+  'Issue #61. Cumulative sold-pct as f(months from sales_start_date) per (rooms_int, '
+  'area_bucket). Anchor = COALESCE(registration_date, contract_date) from objective_lots. '
+  'Foundation for recommend_mix + sellout forecast. Refresh weekly CONCURRENTLY.';
+
+COMMIT;
--- a/data/sql/165_velocity_mapping_reviewed_gate.sql
+++ b/data/sql/165_velocity_mapping_reviewed_gate.sql
@ -0,0 +1,93 @@
+-- 165_velocity_mapping_reviewed_gate.sql
+-- #307 OBJ-2 — gate objective_complex_mapping by confidence в mv_layout_velocity.
+--
+-- Контекст: fuzzy-trgm backfill (#1331/#1333, миграции 155/156/116/117/150) добавил
+-- ~115+ auto-matched строк в objective_complex_mapping с is_reviewed=false и низким
+-- match_score (вплоть до 0.50-0.625). Они с высокой вероятностью false-positive
+-- (Objective project name ≠ тот же ЖК что domrf_obj_id) и искажали velocity-агрегаты
+-- Site Finder, попадая в MV наравне с проверенными маппингами.
+--
+-- Fix: redefine MV с confidence-gate в JOIN — принимаем маппинг только если
+--   is_reviewed = TRUE          (человек подтвердил), ИЛИ
+--   match_method = 'manual'     (ручной маппинг, score обычно NULL), ИЛИ
+--   match_score >= 0.85         (AUTO_ACCEPT_THRESHOLD из objective_backfill.py —
+--                               high-confidence auto, fuzzy_trgm 0.85+ надёжен).
+--
+-- Строгий gate только на is_reviewed=true дал бы 2 строки из 303 EKB-маппингов →
+-- обнулил бы velocity. Порог 0.85 сохраняет ~264/303, отбрасывая ~39 низкоуверенных.
+-- Тот же предикат применён в runtime-пути backend/app/services/site_finder/velocity.py.
+--
+-- Сохраняет weighted-average формулу из #21 (100_fix_mv_layout_velocity_weighted_avg.sql) —
+-- меняется ТОЛЬКО WHERE/JOIN-условие на objective_complex_mapping.
+--
+-- Dependencies: mv_layout_velocity не имеет зависимых VIEW/MV (проверено 2026-05-17/100_fix).
+-- Idempotency: DROP IF EXISTS → безопасен при повторном запуске.
+-- Deploy order: SQL migration → app deploy. Auto-applied через _schema_migrations.
+-- ВАЖНО: DROP + CREATE + REFRESH (non-concurrent, блокировка ~30 с на ~19 738 source rows).
+
+BEGIN;
+
+DROP MATERIALIZED VIEW IF EXISTS mv_layout_velocity CASCADE;
+
+CREATE MATERIALIZED VIEW mv_layout_velocity AS
+WITH last24mo AS (
+    SELECT
+        ocm.project_name,
+        CASE
+            WHEN ocm.room_bucket = 'студия' THEN 'studio'
+            ELSE ocm.room_bucket
+        END                                                      AS room_bucket,
+        ocm.deals_total_count,
+        ocm.deals_total_avg_area_m2,
+        ocm.deals_total_avg_price_thousand_rub_per_m2,
+        ocm.deals_total_vol_m2,
+        ocm.report_month
+    FROM objective_corpus_room_month ocm
+    WHERE ocm.report_month >= (NOW() - INTERVAL '24 months')::date
+)
+SELECT
+    cm.domrf_obj_id                                              AS obj_id,
+    l.room_bucket,
+    SUM(l.deals_total_count)::int                               AS total_deals_24mo,
+
+    -- weighted average (#21) — нули из месяцев без сделок не тянут вниз.
+    (SUM(l.deals_total_avg_area_m2 * l.deals_total_count)
+        / NULLIF(SUM(l.deals_total_count), 0))::numeric(10, 2) AS avg_area_m2,
+
+    (SUM(l.deals_total_avg_price_thousand_rub_per_m2 * l.deals_total_count)
+        / NULLIF(SUM(l.deals_total_count), 0))::numeric(12, 2) AS avg_price_thousand_rub_per_m2,
+
+    SUM(l.deals_total_vol_m2)::numeric(12, 2)                  AS total_vol_m2,
+    MIN(l.report_month)                                         AS window_start,
+    MAX(l.report_month)                                         AS window_end,
+    COUNT(DISTINCT l.report_month)::int                         AS months_with_data
+FROM last24mo l
+JOIN objective_complex_mapping cm
+    ON cm.objective_complex_name = l.project_name
+WHERE l.room_bucket IS NOT NULL
+  AND cm.domrf_obj_id IS NOT NULL
+  AND cm.objective_group = 'Екатеринбург'
+  -- #307 OBJ-2: confidence-gate — исключаем unreviewed low-score auto-matches.
+  AND (cm.is_reviewed = TRUE OR cm.match_method = 'manual' OR cm.match_score >= 0.85)
+GROUP BY cm.domrf_obj_id, l.room_bucket
+WITH NO DATA;
+
+-- UNIQUE index: required for REFRESH CONCURRENTLY (periodic via layout_velocity_refresh.py).
+CREATE UNIQUE INDEX mv_layout_velocity_pk
+    ON mv_layout_velocity (obj_id, room_bucket);
+
+-- Lookup index for /best-layouts endpoint queries by obj_id.
+CREATE INDEX mv_layout_velocity_obj_idx
+    ON mv_layout_velocity (obj_id);
+
+-- Initial populate (non-concurrent — MV just created, CONCURRENTLY requires populated MV).
+REFRESH MATERIALIZED VIEW mv_layout_velocity;
+
+COMMENT ON MATERIALIZED VIEW mv_layout_velocity IS
+    'Per-(obj_id, room_bucket) deals aggregation за last 24 months. '
+    'WEIGHTED average площади и цены (SF Bug #21). '
+    'Confidence-gated mapping: is_reviewed/manual/score>=0.85 (#307 OBJ-2). '
+    'Source: objective_corpus_room_month × objective_complex_mapping (EKB only). '
+    'Refresh via layout_velocity_refresh.py (CONCURRENTLY после initial populate).';
+
+COMMIT;
--- a/frontend/src/lib/api-types.ts
+++ b/frontend/src/lib/api-types.ts
@ -4168,6 +4168,8 @@ export interface components {
      distance_m: number;
      /** Weight */
      weight: number;
+      /** Score Contribution */
+      score_contribution: number;
      /** Address */
      address: string | null;
    };
@ -4177,6 +4179,8 @@ export interface components {
      cad_num: string;
      /** Radius M */
      radius_m: number;
+      /** Poi Weighted Score */
+      poi_weighted_score: number;
      /** Top Poi */
      top_poi: components["schemas"]["PoiScoreItem"][];
    };
--- a/tradein-mvp/backend/app/schemas/search.py
+++ b/tradein-mvp/backend/app/schemas/search.py
@ -6,9 +6,11 @@ from typing import Literal

 from pydantic import BaseModel, Field, model_validator

-SortKey = Literal[
-    "price_asc", "price_desc", "area_desc", "area_asc", "date_desc", "dist_asc"
-]
+SortKey = Literal["price_asc", "price_desc", "area_desc", "area_asc", "date_desc", "dist_asc"]
+
+# Сегмент рынка (#1188, поверх canon-предиката #1186).
+# NULL listing_segment (legacy вторичка до миграции 011) трактуется как 'vtorichka'.
+SegmentKey = Literal["vtorichka", "novostroyki", "all"]


 class SearchParams(BaseModel):
@ -49,6 +51,19 @@ class SearchParams(BaseModel):
    address_query: str | None = Field(default=None, max_length=200)
    description_query: str | None = Field(default=None, max_length=200)

+    # --- Market segment (#1188) ---
+    segment: SegmentKey = Field(
+        default="vtorichka",
+        description=(
+            "Сегмент рынка для фильтрации listings. "
+            "`vtorichka` (по умолчанию, back-compat) — вторичка; "
+            "строки с listing_segment=NULL (legacy до миграции 011) "
+            "считаются вторичкой согласно canon-предикату #1186. "
+            "`novostroyki` — только первичка. "
+            "`all` — без фильтра по сегменту."
+        ),
+    )
+
    # --- Sort + pagination ---
    sort: SortKey = "date_desc"
    page: int = Field(default=1, ge=1, le=1000)
--- a/tradein-mvp/backend/app/schemas/trade_in.py
+++ b/tradein-mvp/backend/app/schemas/trade_in.py
@ -106,9 +106,9 @@ class DkpCorridor(BaseModel):
    """

    count: int  # число ДКП-сделок в выборке
-    low_ppm2: int  # min ₽/м² по сделкам (P10-ish — берём минимум)
+    low_ppm2: int  # P10 ₽/м² по сделкам (робастный коридор)
    median_ppm2: int  # медиана ₽/м²
-    high_ppm2: int  # max ₽/м²
+    high_ppm2: int  # P90 ₽/м² по сделкам (робастный коридор)
    period_months: int  # окно поиска сделок


--- a/tradein-mvp/backend/app/services/scheduler.py
+++ b/tradein-mvp/backend/app/services/scheduler.py
@ -321,6 +321,7 @@ async def trigger_yandex_city_sweep_run(db: Session, schedule_row: dict[str, Any
                request_delay_sec=float(params.get("request_delay_sec", 9.0)),
                radius_m=int(params.get("radius_m", 1500)),
                enrich_address=bool(params.get("enrich_address", True)),
+                segments=params.get("segments"),
            )
        except Exception:
            logger.exception("scheduler: run_yandex_city_sweep crashed run_id=%d", run_id)
--- a/tradein-mvp/backend/app/services/scrape_pipeline.py
+++ b/tradein-mvp/backend/app/services/scrape_pipeline.py
@ -1033,6 +1033,7 @@ async def run_yandex_city_sweep(
    enrich_address: bool = True,
    rooms_list: list[str] | None = None,
    price_ranges: list[tuple[int | None, int | None]] | None = None,
+    segments: list[str] | None = None,
 ) -> YandexCitySweepCounters:
    """Yandex.Недвижимость city sweep: rooms × price combos от центра ЕКБ → save → address-enrich.

@ -1078,6 +1079,11 @@ async def run_yandex_city_sweep(

    _rooms_list = rooms_list or list(ROOM_PATH.keys())
    _price_ranges = price_ranges or DEFAULT_PRICE_RANGES
+    # newFlat-сегменты: оба прохода (vtorichka + novostroyki) по одним combos.
+    # Дефолт ["NO", "YES"] — оба; dedup по source_id span'ит оба прохода (один seen
+    # внутри fetch_around_multi_room). Counters (lots_fetched/inserted/updated)
+    # агрегируют оба прохода через len(anchor_lots).
+    _segments = segments or ["NO", "YES"]

    counters = YandexCitySweepCounters(anchors_total=len(_anchors))
    inter_anchor_delay = request_delay_sec if request_delay_sec is not None else 7.0
@ -1086,16 +1092,21 @@ async def run_yandex_city_sweep(
    consecutive_failures = 0

    # Вычисляем watchdog-таймаут для combos-режима (центр, anchors=None).
-    # В combos-режиме один "anchor" выполняет num_combos × max_pages fetch'ей —
-    # каждый занимает примерно _resolved_delay + _YANDEX_COMBOS_PER_FETCH_S секунд.
-    # Для 30 combos × 3 pages × (9+12) + 300 ≈ 2190s (~37 мин).
+    # В combos-режиме один "anchor" выполняет num_segments × num_combos × max_pages
+    # fetch'ей — каждый занимает примерно _resolved_delay + _YANDEX_COMBOS_PER_FETCH_S сек.
+    # Для 2 segments × 30 combos × 3 pages × (9+12) + 300 ≈ 4080s (~68 мин).
+    # Множитель len(_segments) масштабирует watchdog пропорционально числу проходов
+    # (vtorichka + novostroyki ≈ ×2 wall-clock) — иначе второй проход гильотинится.
    # В explicit-anchor (тест/override) режиме оставляем ANCHOR_TIMEOUT_SEC (240s) —
    # там каждый anchor небольшой и watchdog работает как старый защитный барьер.
    _num_combos = len(_rooms_list) * len(_price_ranges)
    if anchors is None and _num_combos > 0:
        _sweep_timeout = max(
            ANCHOR_TIMEOUT_SEC,
-            _num_combos * pages_per_anchor * (_resolved_delay + _YANDEX_COMBOS_PER_FETCH_S)
+            len(_segments)
+            * _num_combos
+            * pages_per_anchor
+            * (_resolved_delay + _YANDEX_COMBOS_PER_FETCH_S)
            + _YANDEX_ADDRESS_ENRICH_BUDGET_S,
        )
    else:
@ -1162,6 +1173,7 @@ async def run_yandex_city_sweep(
                        max_pages=pages_per_anchor,
                        rooms_list=_rooms_list,
                        price_ranges=_price_ranges,
+                        segments=_segments,
                    )
                counters.lots_fetched += len(anchor_lots)
                if anchor_lots:
--- a/tradein-mvp/backend/app/services/scrapers/avito.py
+++ b/tradein-mvp/backend/app/services/scrapers/avito.py
@ -74,15 +74,7 @@ _UNIT_DAYS: dict[str, int] = {
 # поэтому отдельная ветка с неявным n=1. Юниты в винительном падеже («минуту»,
 # «неделю») плюс именительный («час», «день»).
 _REL_DATE_SINGULAR_RE = re.compile(
-    r"(?P<unit>"
-    r"секунду|"
-    r"минуту|"
-    r"час|"
-    r"день|"
-    r"неделю|"
-    r"месяц|"
-    r"год"
-    r")\s+назад",
+    r"(?P<unit>" r"секунду|" r"минуту|" r"час|" r"день|" r"неделю|" r"месяц|" r"год" r")\s+назад",
    flags=re.I,
 )

@ -751,12 +743,12 @@ class AvitoScraper(BaseScraper):
                    house_ext_id = parts[-1]
                    house_url = urljoin("https://www.avito.ru", h_href)

-            # listing_segment по item URL pattern
-            listing_segment: str | None = None
-            if "/kvartiry/" in href:
-                listing_segment = "vtorichka"
-            elif "/novostroyki/" in href:
-                listing_segment = "novostroyki"
+            # listing_segment по DOM-маркеру карточки: новостройки несут
+            # data-marker="item-development-name" (название ЖК/застройщика),
+            # вторичка — нет. URL-паттерн ненадёжен: каждый avito-URL квартиры
+            # содержит /kvartiry/ (вкл. новостройки) → ветка всегда vtorichka.
+            dev_name = card.css_first('[data-marker="item-development-name"]')
+            listing_segment = "novostroyki" if dev_name is not None else "vtorichka"

            return ScrapedLot(
                source="avito",
--- a/tradein-mvp/backend/app/services/scrapers/avito_detail.py
+++ b/tradein-mvp/backend/app/services/scrapers/avito_detail.py
@ -152,6 +152,7 @@ _SALE_TYPE_MAP: dict[str, str] = {
    "свободная": "free",
    "альтернатива": "alternative",
    "аукцион": "auction",
+    "переуступка": "assignment",
 }

 _HOUSE_TYPE_MAP: dict[str, str] = {
--- a/tradein-mvp/backend/app/services/scrapers/cian_detail.py
+++ b/tradein-mvp/backend/app/services/scrapers/cian_detail.py
@ -48,6 +48,7 @@ class DetailEnrichment:
    repair_type: str | None = None  # 'cosmetic' / 'design' / 'no' — raw Cian value
    repair_state: str | None = None  # enum: needs_repair/standard/good/excellent
    kitchen_area_m2: float | None = None  # offer.kitchenArea (м²)
+    description: str | None = None  # offer.description (текст объявления)
    views_total: int | None = None  # Cian stats.totalViewsFormattedString → int
    views_today: int | None = None

@ -144,6 +145,7 @@ async def fetch_detail(
        repair_type=_extract_repair_type(offer),
        repair_state=_extract_repair_state(offer),
        kitchen_area_m2=_parse_float(offer.get("kitchenArea")),
+        description=offer.get("description") or None,
        raw_offer=offer,
    )

@ -302,8 +304,10 @@ def save_detail_enrichment(db: Session, listing_id: int, enrichment: DetailEnric
                repair_type        = COALESCE(:rt,  repair_type),
                repair_state       = COALESCE(:rs,  repair_state),
                kitchen_area_m2    = COALESCE(CAST(:ka AS double precision), kitchen_area_m2),
+                description        = COALESCE(:descr, description),
                views_total        = COALESCE(:vt,  views_total),
-                views_today        = COALESCE(:vd,  views_today)
+                views_today        = COALESCE(:vd,  views_today),
+                detail_enriched_at = NOW()
            WHERE id = CAST(:lid AS bigint)
        """),
        {
@ -315,6 +319,7 @@ def save_detail_enrichment(db: Session, listing_id: int, enrichment: DetailEnric
            "rt": enrichment.repair_type,
            "rs": enrichment.repair_state,
            "ka": enrichment.kitchen_area_m2,
+            "descr": enrichment.description,
            "vt": enrichment.views_total,
            "vd": enrichment.views_today,
        },
--- a/tradein-mvp/backend/app/services/scrapers/yandex_realty.py
+++ b/tradein-mvp/backend/app/services/scrapers/yandex_realty.py
@ -129,7 +129,14 @@ def _extract_json_from_content(content: str) -> str | None:
    return None


-def _parse_gate_json(payload: dict[str, Any], page_param: int = 1) -> list[ScrapedLot]:
+def _segment_for(new_flat: str) -> str:
+    """Map a newFlat gate-API value to the listings.listing_segment value."""
+    return "novostroyki" if new_flat == "YES" else "vtorichka"
+
+
+def _parse_gate_json(
+    payload: dict[str, Any], page_param: int = 1, new_flat: str = "NO"
+) -> list[ScrapedLot]:
    """Parse gate-API JSON payload into a list of ScrapedLot.

    Verified field mapping (from .issdump/yandex_gate_api_sample.json + live prod 2026-06-17):
@ -150,7 +157,7 @@ def _parse_gate_json(payload: dict[str, Any], page_param: int = 1) -> list[Scrap
      location.geocoderAddress        -> address (full, with house number)
      mainImages[]                    -> photo_urls (prepend "https:", up to 5)
      building.siteId                 -> house_ext_id (JK linkage)
-      listing_segment = "vtorichka"   (all requests use newFlat=NO)
+      listing_segment                 -> "novostroyki" (newFlat=YES) | "vtorichka" (newFlat=NO)
    """
    result = _extract_gate_data(payload)
    if result is None:
@ -160,13 +167,15 @@ def _parse_gate_json(payload: dict[str, Any], page_param: int = 1) -> list[Scrap
    entities, _pager = result
    lots: list[ScrapedLot] = []
    for entity in entities:
-        lot = _entity_to_lot(entity, page_param=page_param)
+        lot = _entity_to_lot(entity, page_param=page_param, new_flat=new_flat)
        if lot is not None:
            lots.append(lot)
    return lots


-def _entity_to_lot(entity: dict[str, Any], page_param: int = 1) -> ScrapedLot | None:
+def _entity_to_lot(
+    entity: dict[str, Any], page_param: int = 1, new_flat: str = "NO"
+) -> ScrapedLot | None:
    """Convert one gate-API entity dict to ScrapedLot. None on missing required fields."""
    try:
        offer_id = str(entity.get("offerId") or "")
@ -263,7 +272,7 @@ def _entity_to_lot(entity: dict[str, Any], page_param: int = 1) -> ScrapedLot |
            house_source=house_source,
            house_ext_id=house_ext_id,
            house_url=None,
-            listing_segment="vtorichka",
+            listing_segment=_segment_for(new_flat),
            raw_payload={
                "page_param": page_param,
                "ceiling_height": ceiling_height,
@ -366,13 +375,18 @@ class YandexRealtyScraper(BaseScraper):
        rooms: str | None = None,
        price_min: int | None = None,
        price_max: int | None = None,
+        new_flat: str = "NO",
    ) -> str:
-        """Build gate-API URL. page: 1-based (page=0 -> API error)."""
+        """Build gate-API URL. page: 1-based (page=0 -> API error).
+
+        new_flat: "NO" -> vtorichka (default, preserves legacy behavior),
+                  "YES" -> novostroyki (primary-sale / reassignment segment).
+        """
        params: dict[str, str | int] = {
            "rgid": _EKB_RGID,
            "type": "SELL",
            "category": "APARTMENT",
-            "newFlat": "NO",
+            "newFlat": new_flat,
            "_pageType": "search",
            "_providers": "react-search-results-data",
            "page": page,
@ -391,9 +405,12 @@ class YandexRealtyScraper(BaseScraper):
        page: int,
        price_min: int | None,
        price_max: int | None,
+        new_flat: str = "NO",
    ) -> dict[str, Any] | None:
        """Fetch one gate-API page. Returns parsed JSON dict or None on error/invalid."""
-        url = self._build_url(page=page, rooms=rooms, price_min=price_min, price_max=price_max)
+        url = self._build_url(
+            page=page, rooms=rooms, price_min=price_min, price_max=price_max, new_flat=new_flat
+        )
        try:
            resp = await self._http_get(url, timeout=60)
        except Exception:
@ -421,14 +438,18 @@ class YandexRealtyScraper(BaseScraper):
        rooms: str | None = None,
        price_min: int | None = None,
        price_max: int | None = None,
+        new_flat: str = "NO",
    ) -> list[ScrapedLot]:
        """Fetch ONE page of gate-API results. lat/lon/radius_m ignored (uses rgid).

        page: 1-based. Tarpit resilience: status_code==0 or JSON error
        -> rotate IP + retry up to _YANDEX_TARPIT_MAX_RETRIES times.
        Non-tarpit failures (4xx/5xx) are not retried.
+        new_flat: "NO" -> vtorichka, "YES" -> novostroyki.
        """
-        url = self._build_url(page=page, rooms=rooms, price_min=price_min, price_max=price_max)
+        url = self._build_url(
+            page=page, rooms=rooms, price_min=price_min, price_max=price_max, new_flat=new_flat
+        )

        payload: dict[str, Any] | None = None
        for attempt in range(1 + _YANDEX_TARPIT_MAX_RETRIES):
@ -494,13 +515,14 @@ class YandexRealtyScraper(BaseScraper):
            )
            return []

-        lots = _parse_gate_json(payload, page_param=page)
+        lots = _parse_gate_json(payload, page_param=page, new_flat=new_flat)
        logger.info(
-            "yandex gate page=%d rooms=%s price=[%s-%s]: %d cards",
+            "yandex gate page=%d rooms=%s price=[%s-%s] newFlat=%s: %d cards",
            page,
            rooms or "all",
            price_min,
            price_max,
+            new_flat,
            len(lots),
        )
        await self.sleep_between_requests()
@ -514,16 +536,20 @@ class YandexRealtyScraper(BaseScraper):
        max_pages: int = _GATE_MAX_PAGES_CAP,
        rooms_list: list[str] | None = None,
        price_ranges: list[tuple[int | None, int | None]] | None = None,
+        segments: list[str] | None = None,
        **_legacy_kwargs: Any,
    ) -> list[ScrapedLot]:
-        """Fetch via rooms x price-range combos; paginate each combo to totalPages.
+        """Fetch via segment x rooms x price-range combos; paginate each combo to totalPages.

        Pagination driven by pager.totalPages from first page response.
        Each combo iterates page=1 .. min(totalPages, max_pages, _GATE_MAX_PAGES_CAP).
-        Deduplicates by source_id/source_url across all combos.
+        Deduplicates by source_id/source_url across ALL combos AND segments (one `seen`).
        Legacy mode (rooms_list=None, price_ranges=None): single citywide sweep.
+        segments: list of newFlat values, default ["NO"] (vtorichka only). Pass
+            ["NO", "YES"] to sweep both vtorichka and novostroyki in one call.
        """
        seen: dict[str, ScrapedLot] = {}
+        _segments = segments or ["NO"]

        if rooms_list is None and price_ranges is None:
            combos: list[tuple[str | None, int | None, int | None]] = [(None, None, None)]
@ -532,112 +558,123 @@ class YandexRealtyScraper(BaseScraper):
            p_ranges = price_ranges or DEFAULT_PRICE_RANGES
            combos = [(r, lo, hi) for r in r_list for lo, hi in p_ranges]

-        for rooms, price_min, price_max in combos:
-            combo_label = _combo_label(rooms, price_min, price_max)
-            total_pages: int | None = None
+        for new_flat in _segments:
+            _seg = _segment_for(new_flat)
+            for rooms, price_min, price_max in combos:
+                combo_label = f"{_seg}/{_combo_label(rooms, price_min, price_max)}"
+                total_pages: int | None = None

-            for page in range(1, max_pages + 1):
-                if page == 1:
-                    payload_p1: dict[str, Any] | None = None
-                    p1_url = self._build_url(
-                        page=1, rooms=rooms, price_min=price_min, price_max=price_max
-                    )
-                    for _attempt in range(1 + _YANDEX_TARPIT_MAX_RETRIES):
-                        try:
-                            resp = await self._http_get(p1_url, timeout=60)
-                        except Exception:
-                            logger.exception("yandex gate combo fetch failed combo=%s", combo_label)
+                for page in range(1, max_pages + 1):
+                    if page == 1:
+                        payload_p1: dict[str, Any] | None = None
+                        p1_url = self._build_url(
+                            page=1,
+                            rooms=rooms,
+                            price_min=price_min,
+                            price_max=price_max,
+                            new_flat=new_flat,
+                        )
+                        for _attempt in range(1 + _YANDEX_TARPIT_MAX_RETRIES):
+                            try:
+                                resp = await self._http_get(p1_url, timeout=60)
+                            except Exception:
+                                logger.exception(
+                                    "yandex gate combo fetch failed combo=%s", combo_label
+                                )
+                                break
+                            if resp.status_code == 0:  # type: ignore[union-attr]
+                                logger.warning(
+                                    "yandex gate: tarpit combo=%s page=1 -- rotating", combo_label
+                                )
+                                await self._rotate_ip()
+                                await asyncio.sleep(2)
+                                continue
+                            if resp.status_code != 200:  # type: ignore[union-attr]
+                                logger.warning(
+                                    "yandex gate: HTTP %d combo=%s page=1",
+                                    resp.status_code,
+                                    combo_label,  # type: ignore[union-attr]
+                                )
+                                break
+                            try:
+                                payload_p1 = json.loads(resp.text)  # type: ignore[union-attr]
+                            except (json.JSONDecodeError, ValueError):
+                                logger.warning(
+                                    "yandex gate: JSON parse error combo=%s page=1", combo_label
+                                )
+                                payload_p1 = None
+                                await self._rotate_ip()
+                                await asyncio.sleep(2)
+                                continue
+                            if _is_gate_error(payload_p1):
+                                logger.warning(
+                                    "yandex gate: error payload combo=%s page=1", combo_label
+                                )
+                                payload_p1 = None
+                                break
                            break
-                        if resp.status_code == 0:  # type: ignore[union-attr]
-                            logger.warning(
-                                "yandex gate: tarpit combo=%s page=1 -- rotating", combo_label
-                            )
-                            await self._rotate_ip()
-                            await asyncio.sleep(2)
-                            continue
-                        if resp.status_code != 200:  # type: ignore[union-attr]
-                            logger.warning(
-                                "yandex gate: HTTP %d combo=%s page=1",
-                                resp.status_code,
-                                combo_label,  # type: ignore[union-attr]
+
+                        if payload_p1 is None:
+                            logger.debug(
+                                "yandex gate combo [%s] page=1: failed -- skipping", combo_label
                            )
                            break
-                        try:
-                            payload_p1 = json.loads(resp.text)  # type: ignore[union-attr]
-                        except (json.JSONDecodeError, ValueError):
-                            logger.warning(
-                                "yandex gate: JSON parse error combo=%s page=1", combo_label
-                            )
-                            payload_p1 = None
-                            await self._rotate_ip()
-                            await asyncio.sleep(2)
-                            continue
-                        if _is_gate_error(payload_p1):
-                            logger.warning(
-                                "yandex gate: error payload combo=%s page=1", combo_label
-                            )
-                            payload_p1 = None
+
+                        result = _extract_gate_data(payload_p1)
+                        if result is None:
                            break
+                        _entities_p1, pager_p1 = result
+                        total_pages = min(
+                            pager_p1.get("totalPages", 1),
+                            max_pages,
+                            _GATE_MAX_PAGES_CAP,
+                        )
+                        lots_p1 = _parse_gate_json(payload_p1, page_param=1, new_flat=new_flat)
+                        if not lots_p1:
+                            logger.debug(
+                                "yandex gate combo [%s] page=1: empty -- stopping", combo_label
+                            )
+                            break
+                        for lot in lots_p1:
+                            key = lot.source_id or lot.source_url
+                            if key and key not in seen:
+                                seen[key] = lot
+                        await self.sleep_between_requests()
+                        if total_pages <= 1:
+                            break
+                        continue
+
+                    if total_pages is not None and page > total_pages:
                        break

-                    if payload_p1 is None:
+                    lots = await self.fetch_around(
+                        lat,
+                        lon,
+                        radius_m,
+                        page=page,
+                        rooms=rooms,
+                        price_min=price_min,
+                        price_max=price_max,
+                        new_flat=new_flat,
+                    )
+                    if not lots:
                        logger.debug(
-                            "yandex gate combo [%s] page=1: failed -- skipping", combo_label
+                            "yandex gate combo [%s] page=%d: empty -- stopping",
+                            combo_label,
+                            page,
                        )
                        break
-
-                    result = _extract_gate_data(payload_p1)
-                    if result is None:
-                        break
-                    _entities_p1, pager_p1 = result
-                    total_pages = min(
-                        pager_p1.get("totalPages", 1),
-                        max_pages,
-                        _GATE_MAX_PAGES_CAP,
-                    )
-                    lots_p1 = _parse_gate_json(payload_p1, page_param=1)
-                    if not lots_p1:
-                        logger.debug(
-                            "yandex gate combo [%s] page=1: empty -- stopping", combo_label
-                        )
-                        break
-                    for lot in lots_p1:
+                    for lot in lots:
                        key = lot.source_id or lot.source_url
                        if key and key not in seen:
                            seen[key] = lot
-                    await self.sleep_between_requests()
-                    if total_pages <= 1:
-                        break
-                    continue
-
-                if total_pages is not None and page > total_pages:
-                    break
-
-                lots = await self.fetch_around(
-                    lat,
-                    lon,
-                    radius_m,
-                    page=page,
-                    rooms=rooms,
-                    price_min=price_min,
-                    price_max=price_max,
-                )
-                if not lots:
-                    logger.debug(
-                        "yandex gate combo [%s] page=%d: empty -- stopping",
-                        combo_label,
-                        page,
-                    )
-                    break
-                for lot in lots:
-                    key = lot.source_id or lot.source_url
-                    if key and key not in seen:
-                        seen[key] = lot

        logger.info(
-            "yandex gate aggregate: %d unique lots (%d combos)",
+            "yandex gate aggregate: %d unique lots (%d combos x %d segments=%s)",
            len(seen),
            len(combos),
+            len(_segments),
+            _segments,
        )
        return list(seen.values())

--- a/tradein-mvp/backend/app/services/search_query.py
+++ b/tradein-mvp/backend/app/services/search_query.py
@ -17,6 +17,18 @@ _SORT_SQL: dict[str, str] = {
    ),
 }

+# Сегмент рынка (#1188). listings_search_mv не несёт колонку listing_segment,
+# поэтому фильтруем через подзапрос к базовой таблице listings, переиспользуя
+# canon-предикат #1186: NULL = legacy вторичка до миграции 011.
+_VTORICHKA_GUARD = "(listing_segment IS NULL OR listing_segment = 'vtorichka')"
+_SEGMENT_SQL: dict[str, str | None] = {
+    "vtorichka": (f"listing_id IN (SELECT id FROM listings WHERE {_VTORICHKA_GUARD})"),
+    "novostroyki": (
+        "listing_id IN (SELECT id FROM listings WHERE listing_segment = 'novostroyki')"
+    ),
+    "all": None,
+}
+

 def build_search_query(params: SearchParams) -> tuple[str, dict[str, object]]:
    """Возвращает (sql, args) для SELECT из listings_search_mv."""
@ -86,6 +98,10 @@ def build_search_query(params: SearchParams) -> tuple[str, dict[str, object]]:
    if params.has_kadastr:
        where.append("cadastral_number IS NOT NULL")

+    segment_clause = _SEGMENT_SQL[params.segment]
+    if segment_clause is not None:
+        where.append(segment_clause)
+
    if params.sources:
        where.append("sources && CAST(:sources AS text[])")
        args["sources"] = params.sources
--- a/tradein-mvp/backend/tests/test_avito_detail_parse.py
+++ b/tradein-mvp/backend/tests/test_avito_detail_parse.py
@ -78,6 +78,25 @@ def test_minimal_parse() -> None:
    assert result.views_today == 12


+def test_sale_type_assignment_pereustupka() -> None:
+    """«Способ продажи: переуступка» → sale_type='assignment' (ДДУ переуступка,
+    сигнал новостройки). До фикса map не содержал ключ → None."""
+    html = """
+    <html><body>
+    <div data-marker="item-view/item-id">№ 8043003287</div>
+    <span itemprop="price" content="9500000">9 500 000 ₽</span>
+    <div data-marker="item-view/item-params">
+      <ul>
+        <li>Количество комнат: 2</li>
+        <li>Способ продажи: переуступка</li>
+      </ul>
+    </div>
+    </body></html>
+    """
+    result = parse_detail_html(html, "https://www.avito.ru/test_8043003287")
+    assert result.sale_type == "assignment"
+
+
 def test_metro_extraction() -> None:
    result = parse_detail_html(MINIMAL_HTML, SOURCE_URL)
    # "Чкаловская 11-15 мин пешком" → metro_stations
--- a/tradein-mvp/backend/tests/test_avito_serp_date.py
+++ b/tradein-mvp/backend/tests/test_avito_serp_date.py
@ -60,3 +60,37 @@ def test_lazy_card_date_comes_from_json_not_dom() -> None:
    lots = AvitoScraper()._parse_html(html, "https://www.avito.ru/x")
    lazy = next(lot for lot in lots if "8043936560" in (lot.source_url or ""))
    assert lazy.listing_date == _expected(_TS_LAZY)
+
+
+# ── listing_segment по DOM-маркеру item-development-name ───────────────────────
+# Каждый avito-URL квартиры содержит /kvartiry/ (вкл. новостройки), поэтому
+# сегмент определяется не по URL, а по наличию data-marker="item-development-name"
+# (название ЖК/застройщика рендерится только у карточек новостроек).
+
+
+def _serp_card(item_id: str, *, with_dev_name: bool) -> str:
+    dev = '<div data-marker="item-development-name">ЖК «Федерация»</div>' if with_dev_name else ""
+    return f"""
+    <div data-marker="item" data-item-id="{item_id}">
+      <a data-marker="item-title" href="/ekaterinburg/kvartiry/2-k_kvartira_{item_id}">
+        2-к. квартира, 50 м², 5/20 эт.</a>
+      <meta itemprop="price" content="9500000"/>
+      {dev}
+    </div>
+    """
+
+
+def test_segment_novostroyki_when_development_name_present() -> None:
+    """Карточка с data-marker='item-development-name' → listing_segment='novostroyki'."""
+    html = f"<html><body>{_serp_card('8043003287', with_dev_name=True)}</body></html>"
+    lots = AvitoScraper()._parse_html(html, "https://www.avito.ru/ekaterinburg/kvartiry")
+    assert len(lots) == 1
+    assert lots[0].listing_segment == "novostroyki"
+
+
+def test_segment_vtorichka_when_no_development_name() -> None:
+    """Карточка без маркера ЖК → listing_segment='vtorichka' (даже с /kvartiry/ в URL)."""
+    html = f"<html><body>{_serp_card('8043936560', with_dev_name=False)}</body></html>"
+    lots = AvitoScraper()._parse_html(html, "https://www.avito.ru/ekaterinburg/kvartiry")
+    assert len(lots) == 1
+    assert lots[0].listing_segment == "vtorichka"
--- a/tradein-mvp/backend/tests/test_cian_detail.py
+++ b/tradein-mvp/backend/tests/test_cian_detail.py
@ -462,6 +462,40 @@ async def test_fetch_detail_kitchen_area_none_when_missing(monkeypatch):
    assert result.kitchen_area_m2 is None


+@pytest.mark.asyncio
+async def test_fetch_detail_extracts_description(monkeypatch):
+    """offer.description → DetailEnrichment.description (для persist в listings)."""
+    fake_state = {
+        "offerData": {
+            "offer": {
+                "cianId": 555555,
+                "description": "Продаётся уютная квартира с видом на парк.",
+            }
+        }
+    }
+
+    monkeypatch.setattr(
+        "app.services.scrapers.cian_detail.extract_state",
+        lambda html, mfe, key: fake_state if key == "defaultState" else None,
+    )
+    monkeypatch.setattr(
+        "app.services.scrapers.cian_detail.extract_all_states",
+        lambda html: {},
+    )
+
+    response = MagicMock()
+    response.status_code = 200
+    response.text = "<html></html>"
+
+    session = MagicMock()
+    session.get = AsyncMock(return_value=response)
+    session.close = AsyncMock()
+
+    result = await fetch_detail("https://ekb.cian.ru/sale/flat/555555/", session=session)
+    assert result is not None
+    assert result.description == "Продаётся уютная квартира с видом на парк."
+
+
 # ── save_detail_enrichment — kitchen_area_m2 persisted ───────────────────────


@ -504,6 +538,36 @@ def test_save_detail_enrichment_kitchen_area_none_passthrough():
    assert update_call_params["ka"] is None


+# ── save_detail_enrichment — description + detail_enriched_at stamp ───────────
+
+
+def test_save_detail_enrichment_writes_description():
+    """save_detail_enrichment передаёт description в UPDATE listings."""
+    db = MagicMock()
+    db.execute.return_value.fetchone.return_value = None
+
+    enrichment = DetailEnrichment(description="Светлая квартира рядом с парком")
+
+    save_detail_enrichment(db, listing_id=1002, enrichment=enrichment)
+
+    update_call_params = db.execute.call_args_list[0][0][1]
+    assert update_call_params["descr"] == "Светлая квартира рядом с парком"
+
+
+def test_save_detail_enrichment_stamps_detail_enriched_at():
+    """UPDATE listings содержит detail_enriched_at = NOW() — иначе строка
+    переобогащается каждый run (detail_enriched_at IS NULL filter)."""
+    db = MagicMock()
+    db.execute.return_value.fetchone.return_value = None
+
+    enrichment = DetailEnrichment(kitchen_area_m2=8.3)
+
+    save_detail_enrichment(db, listing_id=1003, enrichment=enrichment)
+
+    update_sql = str(db.execute.call_args_list[0][0][0])
+    assert "detail_enriched_at = NOW()" in update_sql
+
+
 # ── fetch_detail browser_fetcher param ───────────────────────────────────────


--- a/tradein-mvp/backend/tests/test_search_api.py
+++ b/tradein-mvp/backend/tests/test_search_api.py
@ -62,6 +62,42 @@ def test_build_query_sources_array():
    assert args["sources"] == ["avito", "cian"]


+def test_build_query_segment_default_vtorichka():
+    """Без параметра segment — back-compat: canon-предикат вторички (#1186/#1188)."""
+    sql, _ = build_search_query(SearchParams())
+    assert SearchParams().segment == "vtorichka"
+    assert "listing_id IN (SELECT id FROM listings WHERE" in sql
+    assert "(listing_segment IS NULL OR listing_segment = 'vtorichka')" in sql
+
+
+def test_build_query_segment_novostroyki():
+    """segment=novostroyki — только первичка, без NULL-вторички."""
+    sql, _ = build_search_query(SearchParams(segment="novostroyki"))
+    assert "listing_segment = 'novostroyki'" in sql
+    # Не должен попасть canon-guard вторички.
+    assert "(listing_segment IS NULL OR listing_segment = 'vtorichka')" not in sql
+
+
+def test_build_query_segment_all_no_filter():
+    """segment=all — без фильтрации по сегменту."""
+    sql, _ = build_search_query(SearchParams(segment="all"))
+    assert "listing_segment" not in sql
+
+
+def test_build_count_query_inherits_segment():
+    """COUNT-запрос наследует segment-фильтр из build_search_query."""
+    sql, _ = build_count_query(SearchParams(segment="novostroyki"))
+    assert "listing_segment = 'novostroyki'" in sql
+    sql_v, _ = build_count_query(SearchParams())
+    assert "(listing_segment IS NULL OR listing_segment = 'vtorichka')" in sql_v
+
+
+def test_segment_invalid_rejected():
+    """Невалидное значение segment отклоняется валидацией."""
+    with pytest.raises(ValueError):
+        SearchParams(segment="kommercia")
+
+
 def test_build_count_query_strips_limit():
    sql, args = build_count_query(SearchParams(rooms=2, page=3))
    assert "count(*)" in sql
--- a/tradein-mvp/backend/tests/test_yandex_realty_serp.py
+++ b/tradein-mvp/backend/tests/test_yandex_realty_serp.py
@ -182,6 +182,29 @@ def test_entity_to_lot_full_entity():
    assert lot.raw_payload["kitchen_area_m2"] == pytest.approx(12.7)


+def test_entity_to_lot_segment_vtorichka_default():
+    """Default new_flat='NO' -> listing_segment='vtorichka'."""
+    lot = _entity_to_lot(_ENTITY_FULL)
+    assert lot is not None
+    assert lot.listing_segment == "vtorichka"
+
+
+def test_entity_to_lot_segment_novostroyki_on_new_flat_yes():
+    """new_flat='YES' -> listing_segment='novostroyki'."""
+    lot = _entity_to_lot(_ENTITY_FULL, new_flat="YES")
+    assert lot is not None
+    assert lot.listing_segment == "novostroyki"
+
+
+def test_parse_gate_json_propagates_segment():
+    """_parse_gate_json threads new_flat down to each lot's listing_segment."""
+    payload = _make_gate_payload([_ENTITY_FULL, _ENTITY_STUDIO])
+    lots_nb = _parse_gate_json(payload, new_flat="YES")
+    assert lots_nb and all(lot.listing_segment == "novostroyki" for lot in lots_nb)
+    lots_vt = _parse_gate_json(payload, new_flat="NO")
+    assert lots_vt and all(lot.listing_segment == "vtorichka" for lot in lots_vt)
+
+
 def test_entity_to_lot_studio_rooms_zero():
    lot = _entity_to_lot(_ENTITY_STUDIO)
    assert lot is not None
@ -350,6 +373,21 @@ def test_build_url_combos_are_unique():
    assert len(urls) == expected, f"URL collisions: {expected} combos but {len(urls)} unique"


+def test_build_url_new_flat_default_no():
+    """Default new_flat must keep newFlat=NO (vtorichka) — backward compat."""
+    s = YandexRealtyScraper()
+    url = s._build_url(page=1)
+    assert "newFlat=NO" in url
+    assert "newFlat=YES" not in url
+
+
+def test_build_url_new_flat_yes():
+    """new_flat='YES' must produce newFlat=YES (novostroyki segment)."""
+    s = YandexRealtyScraper()
+    url = s._build_url(page=1, new_flat="YES")
+    assert "newFlat=YES" in url
+
+
 def test_default_city():
    assert DEFAULT_CITY == "ekaterinburg"

@ -665,6 +703,81 @@ async def test_fetch_around_multi_room_dedup():
    assert len(ids) == 3


+@pytest.mark.asyncio
+async def test_fetch_around_multi_room_runs_both_segments_with_shared_dedup():
+    """segments=['NO','YES'] sweeps both vtorichka+novostroyki; dedup spans both passes.
+
+    Mocks _http_get and inspects requested URLs: both newFlat=NO and newFlat=YES
+    must be requested. The same offerId returned in both passes must be deduped to
+    one lot (single shared `seen` across passes), tagged by the FIRST pass's segment.
+    """
+    s = YandexRealtyScraper()
+
+    requested_new_flat: list[str] = []
+
+    entity_shared = dict(
+        _ENTITY_FULL, offerId="shared_xseg", url="//realty.yandex.ru/offer/shared_xseg"
+    )
+    entity_vt = dict(_ENTITY_FULL, offerId="vt_only", url="//realty.yandex.ru/offer/vt_only")
+    entity_nb = dict(_ENTITY_FULL, offerId="nb_only", url="//realty.yandex.ru/offer/nb_only")
+    pager = {"page": 0, "pageSize": 20, "totalItems": 2, "totalPages": 1}
+
+    async def fake_http_get(url: str, **kwargs: object) -> _CurlResponse:
+        if "newFlat=YES" in url:
+            requested_new_flat.append("YES")
+            payload = _make_gate_payload([entity_shared, entity_nb], pager)
+        else:
+            requested_new_flat.append("NO")
+            payload = _make_gate_payload([entity_shared, entity_vt], pager)
+        return _CurlResponse(status_code=200, text=json.dumps(payload))
+
+    with patch.object(s, "_http_get", side_effect=fake_http_get):
+        with patch.object(s, "sleep_between_requests", new_callable=AsyncMock):
+            lots = await s.fetch_around_multi_room(
+                lat=0.0,
+                lon=0.0,
+                rooms_list=["1"],
+                price_ranges=[(None, 5_000_000)],
+                segments=["NO", "YES"],
+                max_pages=1,
+            )
+
+    assert "NO" in requested_new_flat
+    assert "YES" in requested_new_flat
+
+    by_id = {lot.source_id: lot for lot in lots}
+    assert set(by_id) == {"shared_xseg", "vt_only", "nb_only"}
+    # Shared offer deduped to ONE lot, tagged by the first pass (NO -> vtorichka).
+    assert by_id["shared_xseg"].listing_segment == "vtorichka"
+    assert by_id["vt_only"].listing_segment == "vtorichka"
+    assert by_id["nb_only"].listing_segment == "novostroyki"
+
+
+@pytest.mark.asyncio
+async def test_fetch_around_multi_room_default_segment_no_only():
+    """Without segments arg, only newFlat=NO (vtorichka) is requested (legacy default)."""
+    s = YandexRealtyScraper()
+    requested_new_flat: list[str] = []
+    pager = {"page": 0, "pageSize": 20, "totalItems": 1, "totalPages": 1}
+
+    async def fake_http_get(url: str, **kwargs: object) -> _CurlResponse:
+        requested_new_flat.append("YES" if "newFlat=YES" in url else "NO")
+        body = json.dumps(_make_gate_payload([_ENTITY_FULL], pager))
+        return _CurlResponse(status_code=200, text=body)
+
+    with patch.object(s, "_http_get", side_effect=fake_http_get):
+        with patch.object(s, "sleep_between_requests", new_callable=AsyncMock):
+            await s.fetch_around_multi_room(
+                lat=0.0,
+                lon=0.0,
+                rooms_list=["1"],
+                price_ranges=[(None, 5_000_000)],
+                max_pages=1,
+            )
+
+    assert set(requested_new_flat) == {"NO"}
+
+
@pytest.mark.asyncio
 async def test_fetch_around_multi_room_legacy_single_sweep():
    """Legacy mode (no rooms_list/price_ranges) uses single citywide sweep."""
--- a/tradein-mvp/frontend/src/types/trade-in.ts
+++ b/tradein-mvp/frontend/src/types/trade-in.ts
@ -121,9 +121,9 @@ export interface AvitoImvSummary {
 // нет сделок. count..period_months — required (бэкенд не отдаёт частичный объект).
 export interface DkpCorridor {
  count: number;          // число ДКП-сделок в выборке
-  low_ppm2: number;       // min ₽/м² по сделкам
+  low_ppm2: number;       // P10 ₽/м² по сделкам (робастный коридор)
  median_ppm2: number;    // медиана ₽/м²
-  high_ppm2: number;      // max ₽/м²
+  high_ppm2: number;      // P90 ₽/м² по сделкам (робастный коридор)
  period_months: number;  // окно поиска сделок
 }