feat(analyze): add market_price из mv_quarter_price_per_m2 (#33 PR B)

POST /analyze returns market_price из mv_quarter_price_per_m2 (52K quarters).
Fields: p25/median/p75/mean/median_{6,12,24}m/deals_count/last_deal_date.
source='quarter_mv' либо 'no_data'. district.median_price_per_m2 kept для backward-compat.

MarketPrice BaseModel в schemas. 3 mock tests.

backend/app/api/v1/parcels.py

@@ -1800,6 +1800,55 @@ def analyze_parcel(
             logger.warning("success_recommendation query failed for %s: %s", cad_num, e)
             success_recommendation = None
 
+    # 10d-pre) Market price — ценовая статистика квартала из mv_quarter_price_per_m2 (#33)
+    # quarter_cad_number — первые три части кад. номера: "66:41:0204016:10" → "66:41:0204016"
+    _cad_parts = cad_num.split(":")
+    _quarter_cad = ":".join(_cad_parts[:3]) if len(_cad_parts) >= 3 else cad_num
+    market_price: dict[str, Any]
+    try:
+        with db.begin_nested():
+            mp_row = (
+                db.execute(
+                    text("""
+                        SELECT p25, median, p75, mean, deals_count,
+                               median_6m, median_12m, median_24m, last_deal_date
+                          FROM mv_quarter_price_per_m2
+                         WHERE quarter_cad_number = :q
+                    """),
+                    {"q": _quarter_cad},
+                )
+                .mappings()
+                .first()
+            )
+        if mp_row:
+            market_price = {
+                "p25": float(mp_row["p25"]) if mp_row["p25"] is not None else None,
+                "median": float(mp_row["median"]) if mp_row["median"] is not None else None,
+                "p75": float(mp_row["p75"]) if mp_row["p75"] is not None else None,
+                "mean": float(mp_row["mean"]) if mp_row["mean"] is not None else None,
+                "deals_count": int(mp_row["deals_count"]),
+                "median_6m": (
+                    float(mp_row["median_6m"]) if mp_row["median_6m"] is not None else None
+                ),
+                "median_12m": (
+                    float(mp_row["median_12m"]) if mp_row["median_12m"] is not None else None
+                ),
+                "median_24m": (
+                    float(mp_row["median_24m"]) if mp_row["median_24m"] is not None else None
+                ),
+                "last_deal_date": (
+                    mp_row["last_deal_date"].isoformat()
+                    if mp_row["last_deal_date"] is not None
+                    else None
+                ),
+                "source": "quarter_mv",
+            }
+        else:
+            market_price = {"deals_count": 0, "source": "no_data"}
+    except Exception as e:
+        logger.warning("market_price query failed for %s: %s", cad_num, e)
+        market_price = {"deals_count": 0, "source": "no_data"}
+
     # 10d) Geology stub — реальные данные требуют ВСЕГЕИ-200/1000 шейпы в PostGIS
     karpinsky_url = (
         f"https://www.karpinskyinstitute.ru/ru/gisatlas/web-gisatlas/"
@@ -1935,6 +1984,8 @@ def analyze_parcel(
         # P2 (#46) — соседи-здания + overlap check
         "neighbors_summary": _neighbors_summary(db, geom_wkt, cad_num),
         "market_trend": market_trend,
+        # #33 D2: квартальная ценовая статистика из mv_quarter_price_per_m2
+        "market_price": market_price,
         "zoning": zoning,
         "success_recommendation": success_recommendation,
         "isochrones_available": bool(settings.openrouteservice_api_key),

backend/app/schemas/parcel.py

@@ -215,6 +215,28 @@ class BestLayoutsResponse(BaseModel):
     data_quality: LayoutDataQuality
 
 
+# ── Analyze endpoint market price (#33) ──────────────────────────────────────
+
+
+class MarketPrice(BaseModel):
+    """Ценовая статистика квартала из mv_quarter_price_per_m2 (Issue #33).
+
+    Источник: rosreestr_deals, фильтр realestate_type_code='002001003000' (ДДУ),
+    скользящее окно 24 мес., 30K–800K руб/м², HAVING >= 3 сделок.
+    """
+
+    p25: float | None = None
+    median: float | None = None
+    p75: float | None = None
+    mean: float | None = None
+    deals_count: int = 0
+    median_6m: float | None = None
+    median_12m: float | None = None
+    median_24m: float | None = None
+    last_deal_date: str | None = None  # ISO date
+    source: Literal["quarter_mv", "no_data"] = "no_data"
+
+
 # ── Analyze endpoint inline weights (#201) ────────────────────────────────────
 
 

backend/tests/api/v1/test_analyze_market_price.py

@@ -0,0 +1,263 @@
+"""Тесты для market_price в POST /api/v1/parcels/{cad_num}/analyze (#33).
+
+Покрывает:
+1. analyze с known quarter в mv_quarter_price_per_m2 → возвращает median/p25/p75/source='quarter_mv'
+2. analyze с quarter которого нет в MV → deals_count=0, source='no_data'
+3. analyze с invalid cad → 404 (no regression)
+
+Стратегия mock: аналогична test_analyze_inline_weights.py — DB mock через
+dependency_overrides, тяжёлые сервисы патчим через unittest.mock.patch.
+
+Порядок db.execute calls в analyze_parcel (v3.7 + #33):
+  0. UNION ALL geom + source → .mappings().first()
+  1. WKT query → .mappings().first()
+  2. District → .mappings().first()
+  3. POI rows → .mappings().all()
+  4. Competitor rows → .mappings().all()
+  5. Pipeline rows → .mappings().all()
+  6. Centroid lat/lon → .mappings().first()
+  7. Noise rows → .mappings().all()
+  8. Hydrology → .mappings().all()
+  9. Utilities → .mappings().all()
+  10. Market trend → .mappings().first()
+  11. Zoning (begin_nested) → .mappings().first()
+  12. Success recommendation (begin_nested) → .mappings().all()
+  13. Market price (begin_nested) → .mappings().first()   ← NEW #33
+  14. _geotech_risk (industrial count) → .scalar()
+  15. _neighbors_summary (neighbor_rows) → .mappings().all()
+  16. _neighbors_summary (overlap_row) → .mappings().first()
+"""
+
+from __future__ import annotations
+
+import datetime as dt
+from decimal import Decimal
+from typing import Any
+from unittest.mock import MagicMock, patch
+
+import pytest
+from fastapi.testclient import TestClient
+
+from app.main import app
+
+# ── Константы ─────────────────────────────────────────────────────────────────
+
+_CAD = "66:41:0204016:10"  # cad_num с 4 частями — quarter = "66:41:0204016"
+_CAD_3PARTS = "66:41:0204016"  # cad_num уже является quarter
+_WKT = "POLYGON((60.6 56.838, 60.61 56.838, 60.61 56.845, 60.6 56.845, 60.6 56.838))"
+_GEOJSON = '{"type":"Polygon","coordinates":[[[60.6,56.838],[60.61,56.838]]]}'
+
+# ── Mock factories ─────────────────────────────────────────────────────────────
+
+
+def _make_mapping(data: dict[str, Any]) -> MagicMock:
+    """Создать mock-строку (mapping) с __getitem__ + .get() для dict-like доступа."""
+    m = MagicMock()
+    m.__getitem__ = lambda self, k: data[k]
+    m.get = lambda k, default=None: data.get(k, default)
+    return m
+
+
+def _make_db_for_analyze(
+    geom_found: bool = True,
+    district_found: bool = True,
+    market_price_row: dict[str, Any] | None = None,
+) -> MagicMock:
+    """Сконструировать mock DB Session для analyze_parcel.
+
+    market_price_row=None → имитирует "нет данных в MV" (mp_row is None → source='no_data').
+    market_price_row={...} → имитирует найденную строку в MV.
+    """
+    db = MagicMock()
+
+    geom_row = (
+        _make_mapping({"geom_geojson": _GEOJSON, "geom_wkb": None, "source": "cad_quarter"})
+        if geom_found
+        else None
+    )
+    wkt_row = _make_mapping({"wkt": _WKT}) if geom_found else None
+    district_row = (
+        _make_mapping(
+            {
+                "district_name": "Октябрьский",
+                "median_price_per_m2": 120000,
+                "dist_to_center": 1500.0,
+            }
+        )
+        if district_found
+        else None
+    )
+    centroid_row = _make_mapping({"lat": 56.84, "lon": 60.605})
+
+    mp_mock = _make_mapping(market_price_row) if market_price_row is not None else None
+
+    call_idx = [0]
+    responses: list[Any] = [
+        ("first", geom_row),  # 0: geom UNION ALL
+        ("first", wkt_row),  # 1: WKT
+        ("first", district_row),  # 2: district
+        ("all", []),  # 3: POI rows
+        ("all", []),  # 4: competitor rows
+        ("all", []),  # 5: pipeline rows
+        ("first", centroid_row),  # 6: centroid
+        ("all", []),  # 7: noise rows
+        ("all", []),  # 8: hydrology rows
+        ("all", []),  # 9: utilities rows
+        ("first", None),  # 10: market trend
+        ("first", None),  # 11: zoning (begin_nested)
+        ("all", []),  # 12: success recommendation (begin_nested)
+        ("first", mp_mock),  # 13: market price (begin_nested) ← #33
+        ("scalar", 0),  # 14: geotech_risk
+        ("all", []),  # 15: neighbors
+        ("first", None),  # 16: overlap
+    ]
+
+    def _execute_side_effect(*args: Any, **kwargs: Any) -> MagicMock:
+        idx = call_idx[0]
+        call_idx[0] += 1
+        if idx >= len(responses):
+            r = MagicMock()
+            r.mappings.return_value.first.return_value = None
+            r.mappings.return_value.all.return_value = []
+            r.scalar.return_value = 0
+            return r
+        kind, data = responses[idx]
+        r = MagicMock()
+        r.mappings.return_value.first.return_value = data
+        r.mappings.return_value.all.return_value = data if isinstance(data, list) else []
+        r.scalar.return_value = data if kind == "scalar" else 0
+        return r
+
+    db.execute.side_effect = _execute_side_effect
+
+    ctx = MagicMock()
+    ctx.__enter__ = MagicMock(return_value=ctx)
+    ctx.__exit__ = MagicMock(return_value=False)
+    db.begin_nested.return_value = ctx
+
+    return db
+
+
+def _override_db(db: MagicMock):
+    def _get_db_override():
+        yield db
+
+    return _get_db_override
+
+
+_PATCHES = [
+    patch("app.api.v1.parcels._fetch_air_quality_sync", return_value=None),
+    patch("app.api.v1.parcels._fetch_weather_sync", return_value=None),
+    patch("app.api.v1.parcels._fetch_seasonal_weather_sync", return_value=None),
+    patch(
+        "app.api.v1.parcels.get_quarter_dump_data",
+        return_value={
+            "nspd_zoning": None,
+            "nspd_zouit_overlaps": [],
+            "nspd_engineering_nearby": [],
+            "nspd_dump": {"available": False, "stale": False, "harvest_triggered": False},
+        },
+    ),
+    patch("app.api.v1.parcels.compute_velocity", return_value=None),
+    patch("app.api.v1.parcels.compute_gate_verdict", return_value={"verdict": "unknown"}),
+]
+
+
+def _start_patches() -> None:
+    for p in _PATCHES:
+        p.start()
+
+
+def _stop_patches() -> None:
+    for p in _PATCHES:
+        p.stop()
+
+
+# ── Тесты ─────────────────────────────────────────────────────────────────────
+
+
+def test_market_price_found_in_mv() -> None:
+    """analyze с known quarter → market_price содержит median/p25/p75, source='quarter_mv'."""
+    from app.core.db import get_db
+
+    mv_data: dict[str, Any] = {
+        "p25": Decimal("85000.00"),
+        "median": Decimal("102000.00"),
+        "p75": Decimal("118000.00"),
+        "mean": Decimal("103500.00"),
+        "deals_count": 47,
+        "median_6m": Decimal("105000.00"),
+        "median_12m": Decimal("100000.00"),
+        "median_24m": Decimal("102000.00"),
+        "last_deal_date": dt.date(2026, 3, 15),
+    }
+    db = _make_db_for_analyze(market_price_row=mv_data)
+    app.dependency_overrides[get_db] = _override_db(db)
+    _start_patches()
+    try:
+        client = TestClient(app)
+        resp = client.post(f"/api/v1/parcels/{_CAD}/analyze")
+        assert resp.status_code == 200, resp.text
+        body = resp.json()
+        assert "market_price" in body, "market_price отсутствует в ответе"
+        mp = body["market_price"]
+        assert mp["source"] == "quarter_mv"
+        assert mp["deals_count"] == 47
+        assert mp["median"] == pytest.approx(102000.0)
+        assert mp["p25"] == pytest.approx(85000.0)
+        assert mp["p75"] == pytest.approx(118000.0)
+        assert mp["mean"] == pytest.approx(103500.0)
+        assert mp["median_6m"] == pytest.approx(105000.0)
+        assert mp["median_12m"] == pytest.approx(100000.0)
+        assert mp["median_24m"] == pytest.approx(102000.0)
+        assert mp["last_deal_date"] == "2026-03-15"
+    finally:
+        app.dependency_overrides.clear()
+        _stop_patches()
+
+
+def test_market_price_quarter_not_in_mv() -> None:
+    """analyze с quarter которого нет в MV → deals_count=0, source='no_data'."""
+    from app.core.db import get_db
+
+    # market_price_row=None → mp_mock=None → ветка else {"deals_count": 0, "source": "no_data"}
+    db = _make_db_for_analyze(market_price_row=None)
+    app.dependency_overrides[get_db] = _override_db(db)
+    _start_patches()
+    try:
+        client = TestClient(app)
+        resp = client.post(f"/api/v1/parcels/{_CAD}/analyze")
+        assert resp.status_code == 200, resp.text
+        body = resp.json()
+        assert "market_price" in body
+        mp = body["market_price"]
+        assert mp["source"] == "no_data"
+        assert mp["deals_count"] == 0
+        # price fields absent или None
+        assert mp.get("median") is None
+        assert mp.get("p25") is None
+    finally:
+        app.dependency_overrides.clear()
+        _stop_patches()
+
+
+def test_market_price_invalid_cad_returns_404() -> None:
+    """analyze с несуществующим cad → 404 (no regression)."""
+    from app.core.db import get_db
+
+    # geom_found=False → geom_row=None → endpoint вернёт 202 (inline fetch) или 404
+    # В тестовой среде on-demand fetch задизейблен (нет Celery/Redis) → 404 expected
+    db = _make_db_for_analyze(geom_found=False)
+    app.dependency_overrides[get_db] = _override_db(db)
+    _start_patches()
+    try:
+        client = TestClient(app)
+        resp = client.post("/api/v1/parcels/00:00:0000000:0/analyze")
+        # При отсутствии геометрии возвращается 202 (on-demand fetch enqueue) или 404
+        assert resp.status_code in (
+            202,
+            404,
+        ), f"Ожидали 202 или 404 для неизвестного cad, получили {resp.status_code}: {resp.text}"
+    finally:
+        app.dependency_overrides.clear()
+        _stop_patches()