tradein-mvp/backend/tests/test_scraper_kit_yandex_golden_parity.py

@@ -0,0 +1,364 @@
+"""Golden-parity: `scraper_kit.providers.yandex.*` парсинг ≡ `app.services.scrapers.yandex_*`.
+
+Strangler-инвариант (#2133): новая scraper_kit-копия yandex-провайдера должна давать
+БАЙТ-ИДЕНТИЧНЫЙ результат парсинга старому боевому коду на одинаковом входе.
+Развязка (settings→ScraperConfig, get_scraper_delay→delay_provider,
+house_type_normalizer→providers.yandex.shared, base/browser_fetcher/helpers→scraper_kit.*)
+НЕ меняет распарсенные данные.
+
+Гоняем ОБА модуля на одних фикстурах и сравниваем результат:
+  - SERP `_entity_to_lot` (gate-API entity → ScrapedLot) на репрезентативных entity;
+  - SERP `_parse_gate_json` (payload → list[ScrapedLot]) с новостройкой/вторичкой;
+  - `normalize_house_type` (SCREAMING/camelCase → канон);
+  - detail `parse` (INITIAL_STATE.offerCard.card + JSON-LD → DetailEnrichment) на
+    реальных offer-HTML фикстурах;
+  - valuation `parse` (house-meta + history → YandexValuationResult) на синтетике;
+  - newbuilding `parse` (ЖК-лендинг → YandexNewbuildingInfo) на синтетике;
+  - `_build_url` (gate-API URL builder) — детерминированность.
+
+Идентичность результата = kit-парсер верно скопирован (развязка не задела логику).
+"""
+
+from __future__ import annotations
+
+import inspect
+import os
+from pathlib import Path
+from types import SimpleNamespace
+from typing import Any
+
+# Старый app.services.scrapers.yandex_* импортирует app.core.config.settings=Settings(),
+# которому нужен DATABASE_URL. Офлайн-парсинг БД не трогает — фиктивный DSN достаточен.
+os.environ.setdefault("DATABASE_URL", "postgresql+psycopg://test:test@localhost/test_db")
+
+# НОВЫЙ (scraper_kit) и СТАРЫЙ (app.services.scrapers) yandex-парсеры — оба в одном
+# тесте; ruff сортирует scraper_kit (first-party) выше app-импортов.
+from scraper_kit.providers.yandex.detail import YandexDetailScraper as NewDetailScraper
+from scraper_kit.providers.yandex.newbuilding import (
+    YandexNewbuildingScraper as NewNewbuildingScraper,
+)
+from scraper_kit.providers.yandex.serp import YandexRealtyScraper as NewRealtyScraper
+from scraper_kit.providers.yandex.serp import _entity_to_lot as new_entity_to_lot
+from scraper_kit.providers.yandex.serp import _parse_gate_json as new_parse_gate_json
+from scraper_kit.providers.yandex.shared import normalize_house_type as new_normalize_house_type
+from scraper_kit.providers.yandex.valuation import (
+    YandexValuationScraper as NewValuationScraper,
+)
+
+from app.services.scrapers.house_type_normalizer import (
+    normalize_house_type as old_normalize_house_type,
+)
+from app.services.scrapers.yandex_detail import YandexDetailScraper as OldDetailScraper
+from app.services.scrapers.yandex_newbuilding import (
+    YandexNewbuildingScraper as OldNewbuildingScraper,
+)
+from app.services.scrapers.yandex_realty import YandexRealtyScraper as OldRealtyScraper
+from app.services.scrapers.yandex_realty import _entity_to_lot as old_entity_to_lot
+from app.services.scrapers.yandex_realty import _parse_gate_json as old_parse_gate_json
+from app.services.scrapers.yandex_valuation import (
+    YandexValuationScraper as OldValuationScraper,
+)
+
+_FIXTURES = Path(__file__).parent / "fixtures"
+
+# Инжектируемый конфиг для kit-скрапперов (duck-typed namespace, structurally
+# удовлетворяет scraper_kit.contracts.ScraperConfig в объёме читаемых полей).
+_KIT_CONFIG = SimpleNamespace(
+    scraper_proxy_url=None,
+    yandex_proxy_rotate_url=None,
+    avito_proxy_rotate_url=None,
+)
+
+
+# ── Fixtures: gate-API entities (mirror test_yandex_realty_serp) ─────────────
+
+_ENTITY_FULL: dict = {
+    "offerId": 4740475460451078271,
+    "url": "//realty.yandex.ru/offer/4740475460451078271",
+    "price": {"currency": "RUR", "value": 4500000, "valuePerPart": 119048},
+    "area": {"value": 37.8, "unit": "SQUARE_METER"},
+    "livingSpace": {"value": 20, "unit": "SQUARE_METER"},
+    "kitchenSpace": {"value": 12.7, "unit": "SQUARE_METER"},
+    "roomsTotal": 1,
+    "floorsOffered": [8],
+    "floorsTotal": 25,
+    "ceilingHeight": 2.7,
+    "building": {
+        "builtYear": 2016,
+        "buildingType": "MONOLIT",
+        "siteId": 280938,
+        "siteName": "Peremen",
+    },
+    "location": {
+        "geocoderAddress": "Ekaterinburg, ulitsa Evgenia Savkova, 8",
+        "point": {"latitude": 56.79512, "longitude": 60.49186},
+    },
+    "mainImages": [
+        "//avatars.mds.yandex.net/get-realty-offers/11904018/abc/main",
+        "//avatars.mds.yandex.net/get-realty-offers/14717586/def/main",
+    ],
+}
+
+_ENTITY_STUDIO: dict = {
+    "offerId": 9999999,
+    "url": "//realty.yandex.ru/offer/9999999",
+    "price": {"value": 3200000, "valuePerPart": 114285},
+    "area": {"value": 28.0},
+    "livingSpace": None,
+    "kitchenSpace": None,
+    "roomsTotal": None,  # studio -> rooms=0
+    "floorsOffered": [2],
+    "floorsTotal": 9,
+    "ceilingHeight": None,
+    "building": {"builtYear": 2010, "buildingType": "PANEL", "siteId": None, "siteName": None},
+    "location": {
+        "geocoderAddress": "Ekaterinburg, ulitsa Lenina, 5",
+        "point": {"latitude": 56.838, "longitude": 60.597},
+    },
+    "mainImages": [],
+}
+
+_ENTITY_RICH_OWNER: dict = {
+    "offerId": 5500000000000000001,
+    "url": "//realty.yandex.ru/offer/5500000000000000001",
+    "creationDate": "2026-05-24T15:10:27Z",
+    "description": "Продаётся светлая квартира с видом на парк.",
+    "author": {"category": "OWNER", "agentName": "Иван", "organization": None},
+    "price": {"value": 7200000, "valuePerPart": 150000, "trend": "DECREASED", "previous": 7500000},
+    "predictions": {"predictedPrice": {"value": "7554000", "min": "7100000", "max": "8000000"}},
+    "area": {"value": 48.0},
+    "roomsTotal": 2,
+    "floorsOffered": [5],
+    "floorsTotal": 12,
+    "building": {"builtYear": 2018, "buildingType": "MONOLIT"},
+    "location": {
+        "geocoderAddress": "Ekaterinburg, ulitsa Mira, 10",
+        "point": {"latitude": 56.84, "longitude": 60.61},
+        "metroList": [
+            {"name": "Ploshchad 1905 goda", "timeToMetro": 7},
+            {"name": "Geologicheskaya", "timeToMetro": 12},
+        ],
+    },
+    "mainImages": [],
+}
+
+_ENTITY_RICH_AGENCY: dict = {
+    "offerId": 5500000000000000002,
+    "url": "//realty.yandex.ru/offer/5500000000000000002",
+    "creationDate": "2026-06-01T09:00:00Z",
+    "description": "Агентская продажа.",
+    "author": {"category": "AGENCY", "agentName": "Петров", "organization": "Агентство «Диал»"},
+    "price": {"value": 9900000, "trend": "UNCHANGED"},
+    "area": {"value": 60.0},
+    "roomsTotal": 3,
+    "floorsOffered": [3],
+    "floorsTotal": 9,
+    "building": {"builtYear": 2012, "buildingType": "BRICK"},
+    "location": {
+        "geocoderAddress": "Ekaterinburg, ulitsa Lenina, 1",
+        "point": {"latitude": 56.83, "longitude": 60.6},
+        "metro": {"name": "Dinamo", "timeToMetro": 4},
+    },
+    "mainImages": [],
+}
+
+_ALL_ENTITIES = [_ENTITY_FULL, _ENTITY_STUDIO, _ENTITY_RICH_OWNER, _ENTITY_RICH_AGENCY]
+
+
+def _make_gate_payload(entities: list, pager: dict | None = None) -> dict:
+    if pager is None:
+        pager = {"page": 0, "pageSize": 20, "totalItems": len(entities), "totalPages": 1}
+    return {"response": {"search": {"offers": {"entities": entities, "pager": pager}}}}
+
+
+def _dump_lots(lots: list[Any]) -> list[dict[str, Any]]:
+    return [lot.model_dump() for lot in lots]
+
+
+# ── SERP _entity_to_lot parity ───────────────────────────────────────────────
+
+
+def test_entity_to_lot_parity_all_entities() -> None:
+    """gate-API entity → ScrapedLot идентичен на всех репрезентативных entity."""
+    for entity in _ALL_ENTITIES:
+        old_lot = old_entity_to_lot(entity)
+        new_lot = new_entity_to_lot(entity)
+        assert (old_lot is None) == (new_lot is None)
+        assert old_lot is not None and new_lot is not None
+        assert old_lot.model_dump() == new_lot.model_dump()
+
+
+def test_entity_to_lot_parity_new_flat_segments() -> None:
+    """new_flat=YES/NO → listing_segment идентичен (новостройка/вторичка)."""
+    for new_flat in ("NO", "YES"):
+        old_lot = old_entity_to_lot(_ENTITY_FULL, new_flat=new_flat)
+        new_lot = new_entity_to_lot(_ENTITY_FULL, new_flat=new_flat)
+        assert old_lot is not None and new_lot is not None
+        assert old_lot.model_dump() == new_lot.model_dump()
+
+
+def test_entity_to_lot_parity_ceiling_out_of_range() -> None:
+    """ceilingHeight мусор (18 / 1.6) → одинаково дропается в None (#2007)."""
+    for bad_ceiling in (18, 1.6):
+        entity = {**_ENTITY_FULL, "ceilingHeight": bad_ceiling}
+        old_lot = old_entity_to_lot(entity)
+        new_lot = new_entity_to_lot(entity)
+        assert old_lot is not None and new_lot is not None
+        assert old_lot.model_dump() == new_lot.model_dump()
+
+
+# ── SERP _parse_gate_json parity ─────────────────────────────────────────────
+
+
+def test_parse_gate_json_parity() -> None:
+    """payload → list[ScrapedLot] идентичен (вторичка и новостройка)."""
+    payload = _make_gate_payload(_ALL_ENTITIES)
+    for new_flat in ("NO", "YES"):
+        old_lots = old_parse_gate_json(payload, page_param=2, new_flat=new_flat)
+        new_lots = new_parse_gate_json(payload, page_param=2, new_flat=new_flat)
+        assert len(old_lots) == len(new_lots) > 0
+        assert _dump_lots(old_lots) == _dump_lots(new_lots)
+
+
+# ── normalize_house_type parity ──────────────────────────────────────────────
+
+
+def test_normalize_house_type_parity() -> None:
+    """SCREAMING / camelCase / канон / мусор → идентичный результат."""
+    raws = [
+        None,
+        "",
+        "MONOLIT",
+        "BRICK",
+        "PANEL",
+        "MONOLIT_BRICK",
+        "monolithBrick",
+        "gasSilicateBlock",
+        "monolith_brick",
+        "monolith",
+        "stalin",
+        "OTHER",
+        "  MONOLIT  ",
+    ]
+    for raw in raws:
+        assert old_normalize_house_type(raw) == new_normalize_house_type(raw)
+
+
+# ── detail parse parity (реальные offer-HTML фикстуры) ───────────────────────
+
+_SECONDARY_ID = "3402418396407468801"
+_STUDIO_ID = "7811691822126445498"
+
+
+def _load_offer(offer_id: str) -> str:
+    return (_FIXTURES / f"yandex_offer_{offer_id}.html").read_text(encoding="utf-8")
+
+
+def _offer_url(offer_id: str) -> str:
+    return f"https://realty.yandex.ru/offer/{offer_id}/"
+
+
+def test_detail_parse_parity() -> None:
+    """INITIAL_STATE.offerCard.card + JSON-LD → DetailEnrichment идентичен."""
+    old_scraper = OldDetailScraper()
+    new_scraper = NewDetailScraper()
+    for offer_id in (_SECONDARY_ID, _STUDIO_ID):
+        html = _load_offer(offer_id)
+        url = _offer_url(offer_id)
+        old_res = old_scraper.parse(html, offer_url=url)
+        new_res = new_scraper.parse(html, offer_url=url)
+        assert old_res is not None and new_res is not None
+        assert old_res.model_dump() == new_res.model_dump()
+
+
+# ── valuation parse parity (синтетика) ───────────────────────────────────────
+
+_VALUATION_HTML = """
+<html><body>
+Дом 2016 года 25 этажей 2,7 м потолки Лифт 42 объекта Панорама
+48,5 м², 1-комнатная, 5 этаж 5,1 млн ₽ 105 155 ₽ за м² 23.10.2023
+В экспозиции 945 дней Снято 24.05.2024
+32 м², студия, 2 этаж 3,2 млн ₽ 100 000 ₽ за м² 01.02.2024 В продаже
+</body></html>
+"""
+
+
+def test_valuation_parse_parity() -> None:
+    """house-meta + history (chunked-text fallback) → идентичный результат."""
+    old_scraper = OldValuationScraper()
+    new_scraper = NewValuationScraper(config=_KIT_CONFIG)
+    kwargs = dict(
+        address="Екатеринбург, ул. Ленина, 5",
+        offer_category="APARTMENT",
+        offer_type="SELL",
+        page=1,
+        source_url="https://realty.yandex.ru/otsenka-kvartiry-po-adresu-onlayn/?address=test",
+    )
+    old_res = old_scraper.parse(_VALUATION_HTML, **kwargs)
+    new_res = new_scraper.parse(_VALUATION_HTML, **kwargs)
+    assert old_res.model_dump() == new_res.model_dump()
+
+
+# ── newbuilding parse parity (синтетика) ─────────────────────────────────────
+
+_NEWBUILDING_HTML = """
+<html><body>
+<h1>ЖК «Татлин»</h1>
+Екатеринбург, ул. Черепанова 4.3 из 5 1505 оценок Смотреть все 353 отзыва
+56.855312 60.576668
+<h2>О комплексе</h2>
+<div>Дом комфорт-класса, монолитный. Введён в эксплуатацию в июнь 2023.
+35-этажные башни на участке 1,5 га. Три корпуса.</div>
+</body></html>
+"""
+
+
+def test_newbuilding_parse_parity() -> None:
+    """ЖК-лендинг → YandexNewbuildingInfo идентичен."""
+    old_scraper = OldNewbuildingScraper()
+    new_scraper = NewNewbuildingScraper()
+    old_res = old_scraper.parse(
+        _NEWBUILDING_HTML,
+        jk_slug="tatlin",
+        jk_id="1592987",
+        source_url="https://realty.yandex.ru/ekaterinburg/kupit/novostrojka/tatlin-1592987/",
+    )
+    new_res = new_scraper.parse(
+        _NEWBUILDING_HTML,
+        jk_slug="tatlin",
+        jk_id="1592987",
+        source_url="https://realty.yandex.ru/ekaterinburg/kupit/novostrojka/tatlin-1592987/",
+    )
+    assert old_res.model_dump() == new_res.model_dump()
+
+
+# ── _build_url parity ────────────────────────────────────────────────────────
+
+
+def test_build_url_parity() -> None:
+    """gate-API URL builder идентичен на репрезентативных комбо."""
+    old_scraper = OldRealtyScraper()
+    new_scraper = NewRealtyScraper(config=_KIT_CONFIG)
+    combos = [
+        dict(page=1),
+        dict(page=3, rooms="2", price_min=5_000_000, price_max=7_000_000),
+        dict(page=1, rooms="studio", new_flat="YES"),
+        dict(page=2, rooms="4+", price_min=25_000_000),
+    ]
+    for combo in combos:
+        assert old_scraper._build_url(**combo) == new_scraper._build_url(**combo)
+
+
+# ── strangler-guard: kit-провайдер не импортирует app.* ──────────────────────
+
+
+def test_kit_yandex_has_no_app_imports() -> None:
+    """Ни один модуль scraper_kit.providers.yandex.* не импортирует app.* (развязка)."""
+    from scraper_kit.providers.yandex import detail, newbuilding, serp, shared, valuation
+
+    for mod in (serp, detail, valuation, newbuilding, shared):
+        source = inspect.getsource(mod)
+        for line in source.splitlines():
+            stripped = line.strip()
+            assert not stripped.startswith("from app"), f"{mod.__name__}: {line!r}"
+            assert not stripped.startswith("import app"), f"{mod.__name__}: {line!r}"

tradein-mvp/packages/scraper-kit/src/scraper_kit/providers/yandex/__init__.py

@@ -0,0 +1,21 @@
+"""Yandex-провайдер scraper_kit — strangler-копия `app.services.scrapers.yandex_*`.
+
+Модули:
+  - serp        — SERP-sweep ядро (YandexRealtyScraper, gate-API JSON → ScrapedLot,
+                  price-range walk, combos)
+  - detail      — detail-страница объявления (INITIAL_STATE.offerCard.card парс →
+                  DetailEnrichment)
+  - valuation   — анонимная оценка/история дома (/otsenka-...)
+  - newbuilding — ЖК-лендинг (YandexNewbuildingScraper, slug-resolve через SERP)
+  - shared      — локальная копия normalize_house_type (канон house_type)
+
+Развязка от `app.*`:
+  - `app.core.config.settings` → инжектируемый `ScraperConfig` (scraper_kit.contracts)
+  - `app.services.scraper_settings.get_scraper_delay` → инжектируемый `delay_provider`
+  - `app.services.scrapers.base` → `scraper_kit.base`
+  - `app.services.scrapers.browser_fetcher` → `scraper_kit.browser_fetcher`
+  - `app.services.scrapers.price_brackets` → `scraper_kit.price_brackets`
+  - `app.services.scrapers.repair_state_normalizer` → `scraper_kit.repair_state_normalizer`
+  - `app.services.scrapers.yandex_helpers` → `scraper_kit.yandex_helpers`
+  - `app.services.scrapers.house_type_normalizer` → локальный `scraper_kit.providers.yandex.shared`
+"""

tradein-mvp/packages/scraper-kit/src/scraper_kit/providers/yandex/detail.py

@@ -0,0 +1,671 @@
+"""Yandex Realty detail page scraper.
+
+Fetches /offer/<id>/ and extracts Product JSON-LD + DOM sections into
+a DetailEnrichment Pydantic model. Used by enrichment pipeline
+(Wave 5+ matching / Wave 6 estimator).
+
+Strangler-копия `app.services.scrapers.yandex_detail` (#2133). Развязка от `app.*`:
+  - `app.services.scraper_settings.get_scraper_delay` → инжектируемый `delay_provider`
+  - `app.services.scrapers.base` → `scraper_kit.base`
+  - `app.services.scrapers.repair_state_normalizer` → `scraper_kit.repair_state_normalizer`
+  - `app.services.scrapers.yandex_helpers` → `scraper_kit.yandex_helpers`
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import re
+from collections.abc import Callable
+from datetime import date
+from typing import Any
+
+from pydantic import BaseModel, Field
+from selectolax.parser import HTMLParser, Node
+from sqlalchemy import text
+from sqlalchemy.orm import Session
+
+from scraper_kit.base import BaseScraper
+from scraper_kit.repair_state_normalizer import infer_repair_state_from_text
+from scraper_kit.yandex_helpers import (
+    RE_AGENCY_FOUNDED,
+    RE_AGENCY_OBJECTS,
+    RE_METRO_WALK,
+    RE_VIEWS,
+    RE_YEAR,
+    find_ld_by_type,
+    parse_house_type,
+    parse_ru_date,
+    parse_rub,
+)
+
+logger = logging.getLogger(__name__)
+
+
+# ── Pydantic models ───────────────────────────────────────────────────────────
+
+
+class MetroStation(BaseModel):
+    name: str
+    walk_min: int | None = None
+
+
+class DetailEnrichment(BaseModel):
+    """Enrichment payload from a Yandex detail page."""
+
+    offer_id: str
+    source_url: str
+
+    # Pricing — Product JSON-LD `offers.price` is the exact int
+    price_rub: int | None = None
+    price_per_m2: int | None = None
+
+    # Title + basic params
+    title: str | None = None
+    rooms: int | None = None
+    area_m2: float | None = None
+    living_area_m2: float | None = None
+    kitchen_area_m2: float | None = None
+    ceiling_height: float | None = None  # meters, e.g. 2.55
+    floor: int | None = None
+    total_floors: int | None = None
+
+    # Address (full)
+    address: str | None = None
+
+    # Description (full text)
+    description: str | None = None
+
+    # Repair state — enum, inferred from description text (#622).
+    # Yandex не отдаёт структурного поля ремонта, поэтому только инференс.
+    repair_state: str | None = None
+
+    # Stats
+    views_total: int | None = None
+    publish_date: date | None = None
+    publish_date_relative: str | None = None
+
+    # Agency block (OfferCardAuthorInfo)
+    agency_name: str | None = None
+    agency_founded_year: int | None = None
+    agency_objects_count: int | None = None
+    seller_name: str | None = None  # last text line before "Агентство «...»"
+
+    # Metro stations from "Расположение" section
+    metro_stations: list[MetroStation] = Field(default_factory=list)
+
+    # Photos — 8 sizes from Product.image[]
+    photo_urls: list[str] = Field(default_factory=list)
+
+    # Newbuilding linkage
+    newbuilding_url: str | None = None
+    newbuilding_id: str | None = None
+
+    # NLP from description (best-effort)
+    house_type_nlp: str | None = None
+    year_built_hint: int | None = None
+    metro_walk_min: int | None = None
+
+    # Raw payload (trimmed)
+    raw_payload: dict[str, Any] | None = None
+
+
+# ── Scraper ───────────────────────────────────────────────────────────────────
+
+
+class YandexDetailScraper(BaseScraper):
+    """Detail page scraper for realty.yandex.ru."""
+
+    name = "yandex_detail"
+    base_url = "https://realty.yandex.ru"
+    request_delay_sec = 5.0  # class default; instance value injected via delay_provider
+
+    def __init__(self, *, delay_provider: Callable[[str], float] | None = None) -> None:
+        super().__init__()
+        # Strangler-инжекция (#2133): провайдер задержки приходит снаружи вместо
+        # прямого импорта app.services.scraper_settings.get_scraper_delay.
+        if delay_provider is not None:
+            self.request_delay_sec = delay_provider(self.name)
+
+    # BaseScraper requires fetch_around — detail isn't geo-based, raise NotImplementedError
+    async def fetch_around(self, lat: float, lon: float, radius_m: int = 1000) -> list:  # type: ignore[override]
+        raise NotImplementedError(
+            "YandexDetailScraper is offer-id-based; use fetch_detail(offer_url) instead."
+        )
+
+    async def fetch_detail(self, offer_url: str) -> DetailEnrichment | None:
+        try:
+            response = await self._http_get(offer_url)
+        except Exception:
+            logger.exception("yandex detail fetch failed: %s", offer_url)
+            return None
+        if response.status_code != 200:
+            logger.warning("yandex detail returned %d for %s", response.status_code, offer_url)
+            return None
+        result = self.parse(response.text, offer_url=offer_url)
+        await self.sleep_between_requests()
+        return result
+
+    def parse(self, html: str, offer_url: str) -> DetailEnrichment | None:
+        offer_id_match = re.search(r"/offer/(\d+)/?", offer_url)
+        if not offer_id_match:
+            logger.warning("offer_url has no /offer/<id>/: %s", offer_url)
+            return None
+        offer_id = offer_id_match.group(1)
+
+        tree = HTMLParser(html)
+
+        # --- Product JSON-LD (authoritative price) ---
+        product = find_ld_by_type(html, "Product") or {}
+        offers_ld = product.get("offers") or {}
+        if isinstance(offers_ld, list) and offers_ld:
+            offers_ld = offers_ld[0]
+        price_ld = offers_ld.get("price") if isinstance(offers_ld, dict) else None
+        try:
+            price_rub = int(price_ld) if price_ld else None
+        except (TypeError, ValueError):
+            price_rub = None
+
+        # Photos from JSON-LD image[] (typically 8 size variants)
+        images = product.get("image") or []
+        if isinstance(images, str):
+            images = [images]
+        photo_urls = [u for u in images if isinstance(u, str)]
+
+        # --- Title + summary ---
+        title_node = tree.css_first("h1")
+        title = title_node.text(strip=True) if title_node else None
+
+        rooms, area_m2, floor, total_floors = _parse_title(title or "")
+
+        # --- Structural offer card (window.INITIAL_STATE → offerCard.card) ---
+        # Authoritative source for area/floor/ceiling/kitchen — the h1 title
+        # misses non-standard layouts (студия / свободная планировка) and never
+        # carries ceiling/kitchen/living. Title stays as fallback below.
+        living_area_m2: float | None = None
+        kitchen_area_m2: float | None = None
+        ceiling_height: float | None = None
+        card = _extract_offer_card(html, offer_id)
+        if card is not None:
+            (
+                c_rooms,
+                c_area,
+                c_living,
+                c_kitchen,
+                c_ceiling,
+                c_floor,
+                c_total_floors,
+            ) = _parse_card_fields(card)
+            # Structural source wins; title only fills the gaps it left.
+            rooms = c_rooms if c_rooms is not None else rooms
+            area_m2 = c_area if c_area is not None else area_m2
+            living_area_m2 = c_living
+            kitchen_area_m2 = c_kitchen
+            ceiling_height = c_ceiling
+            floor = c_floor if c_floor is not None else floor
+            total_floors = c_total_floors if c_total_floors is not None else total_floors
+
+        # --- OfferCardSummary text block ---
+        summary_node = tree.css_first('[data-test="OfferCardSummary"]')
+        summary_text = summary_node.text(strip=True) if summary_node else ""
+
+        # Views + relative publish date from summary text
+        views_match = RE_VIEWS.search(summary_text)
+        views_total = int(views_match.group(1)) if views_match else None
+        publish_date = parse_ru_date(summary_text)
+        publish_date_relative = _extract_relative_date(summary_text)
+
+        # price_per_m2 — from summary text if absent in LD
+        price_per_m2: int | None = None
+        ppm2_match = re.search(r"(\d[\d\s]+)\s*₽\s*за\s*м²", summary_text)
+        if ppm2_match:
+            price_per_m2 = parse_rub(ppm2_match.group(1))
+
+        # --- OfferCardAuthorInfo (agency block) ---
+        author_node = tree.css_first('[data-test="OfferCardAuthorInfo"]')
+        agency_name: str | None = None
+        agency_founded_year: int | None = None
+        agency_objects_count: int | None = None
+        seller_name: str | None = None
+        if author_node is not None:
+            author_text = author_node.text(strip=True)
+            agency_h2 = author_node.css_first("h2")
+            agency_name = agency_h2.text(strip=True) if agency_h2 else None
+            founded_m = RE_AGENCY_FOUNDED.search(author_text)
+            if founded_m:
+                agency_founded_year = int(founded_m.group(1))
+            objects_m = RE_AGENCY_OBJECTS.search(author_text)
+            if objects_m:
+                agency_objects_count = int(objects_m.group(1))
+            # seller_name — last text line before "Агентство"
+            seller_name = _extract_seller_name(summary_text, agency_name)
+
+        # --- Description section (after H2 "Описание") ---
+        description = _find_section_text(tree, "Описание")
+
+        # --- Repair state: инференс из описания (#622), Yandex без структурного поля ---
+        repair_state = infer_repair_state_from_text(description or summary_text)
+
+        # --- Address ---
+        address = _extract_address(summary_text)
+
+        # --- Metro stations from "Расположение" section ---
+        location_text = _find_section_text(tree, "Расположение") or ""
+        metro_stations = _parse_metro_stations(location_text)
+
+        # --- Newbuilding link ---
+        nb_url: str | None = None
+        nb_id: str | None = None
+        nb_link = tree.css_first('a[href*="/kupit/novostrojka/"]')
+        if nb_link is not None:
+            nb_href = nb_link.attributes.get("href", "")
+            nb_match = re.search(r"/novostrojka/[\w-]+?-(\d+)/?", nb_href)
+            if nb_match:
+                nb_id = nb_match.group(1)
+                nb_url = (
+                    nb_href if nb_href.startswith("http") else f"https://realty.yandex.ru{nb_href}"
+                )
+
+        # --- NLP best-effort from description ---
+        nlp_text = description or summary_text
+        house_type_nlp = parse_house_type(nlp_text)
+        year_hint_m = RE_YEAR.search(nlp_text or "")
+        year_built_hint = int(year_hint_m.group(1)) if year_hint_m else None
+        walk_m = RE_METRO_WALK.search(nlp_text or "")
+        metro_walk_min = int(walk_m.group(1)) if walk_m else None
+
+        return DetailEnrichment(
+            offer_id=offer_id,
+            source_url=offer_url,
+            price_rub=price_rub,
+            price_per_m2=price_per_m2,
+            title=title,
+            rooms=rooms,
+            area_m2=area_m2,
+            living_area_m2=living_area_m2,
+            kitchen_area_m2=kitchen_area_m2,
+            ceiling_height=ceiling_height,
+            floor=floor,
+            total_floors=total_floors,
+            address=address,
+            description=description,
+            repair_state=repair_state,
+            views_total=views_total,
+            publish_date=publish_date,
+            publish_date_relative=publish_date_relative,
+            agency_name=agency_name,
+            agency_founded_year=agency_founded_year,
+            agency_objects_count=agency_objects_count,
+            seller_name=seller_name,
+            metro_stations=metro_stations,
+            photo_urls=photo_urls,
+            newbuilding_url=nb_url,
+            newbuilding_id=nb_id,
+            house_type_nlp=house_type_nlp,
+            year_built_hint=year_built_hint,
+            metro_walk_min=metro_walk_min,
+            raw_payload={
+                "summary_text": summary_text[:1000],
+                "description_len": len(description) if description else 0,
+                "photo_count": len(photo_urls),
+            },
+        )
+
+
+# ── Helpers ───────────────────────────────────────────────────────────────────
+
+
+def _parse_title(title: str) -> tuple[int | None, float | None, int | None, int | None]:
+    """Extract (rooms, area_m2, floor, total_floors) from h1 text."""
+    rooms: int | None = None
+    area_m2: float | None = None
+    floor: int | None = None
+    total_floors: int | None = None
+
+    area_m = re.search(r"(\d+[.,]?\d*)\s*м²", title)
+    if area_m:
+        area_m2 = float(area_m.group(1).replace(",", "."))
+
+    if re.search(r"студи[яюй]", title, re.IGNORECASE):
+        rooms = 0
+    else:
+        rooms_m = re.search(r"(\d+)\s*-?\s*комнатн", title, re.IGNORECASE)
+        if rooms_m:
+            try:
+                rooms = int(rooms_m.group(1))
+            except ValueError:
+                pass
+
+    floor_m = re.search(r"(\d+)\s+этаж\s+из\s+(\d+)", title, re.IGNORECASE)
+    if floor_m:
+        floor = int(floor_m.group(1))
+        total_floors = int(floor_m.group(2))
+
+    return rooms, area_m2, floor, total_floors
+
+
+def _extract_js_object(html: str, marker: str) -> str | None:
+    """Return the JSON object literal assigned to `marker` (e.g. window.INITIAL_STATE).
+
+    Brace-matches from the first ``{`` after ``marker = ...`` to its balanced
+    close, respecting string literals/escapes. Returns the raw JSON text or None.
+    """
+    i = html.find(marker)
+    if i < 0:
+        return None
+    eq = html.find("=", i)
+    if eq < 0:
+        return None
+    start = html.find("{", eq)
+    if start < 0:
+        return None
+    bal = 0
+    in_str = False
+    esc = False
+    k = start
+    n = len(html)
+    while k < n:
+        c = html[k]
+        if in_str:
+            if esc:
+                esc = False
+            elif c == "\\":
+                esc = True
+            elif c == '"':
+                in_str = False
+        else:
+            if c == '"':
+                in_str = True
+            elif c == "{":
+                bal += 1
+            elif c == "}":
+                bal -= 1
+                if bal == 0:
+                    return html[start : k + 1]
+        k += 1
+    return None
+
+
+def _find_card_by_offer_id(obj: Any, offer_id: str) -> dict[str, Any] | None:
+    """Recursively locate the offer dict whose offerId matches and carries `area`."""
+    if isinstance(obj, dict):
+        if obj.get("offerId") == offer_id and "area" in obj:
+            return obj
+        for v in obj.values():
+            found = _find_card_by_offer_id(v, offer_id)
+            if found is not None:
+                return found
+    elif isinstance(obj, list):
+        for v in obj:
+            found = _find_card_by_offer_id(v, offer_id)
+            if found is not None:
+                return found
+    return None
+
+
+def _extract_offer_card(html: str, offer_id: str) -> dict[str, Any] | None:
+    """Extract the offer card object from window.INITIAL_STATE.
+
+    Yandex embeds full structured offer data in ``window.INITIAL_STATE`` under
+    ``offerCard.card``. This is the authoritative source for area / floor /
+    ceiling / kitchen — unlike the h1 title which misses non-standard layouts
+    and never carries ceiling/kitchen. Returns the card dict or None.
+    """
+    blob = _extract_js_object(html, "window.INITIAL_STATE")
+    if not blob:
+        return None
+    try:
+        state = json.loads(blob)
+    except (json.JSONDecodeError, ValueError):
+        logger.warning("yandex detail: INITIAL_STATE failed to parse for offer %s", offer_id)
+        return None
+    # Fast path: canonical location.
+    offer_card = state.get("offerCard") if isinstance(state, dict) else None
+    if isinstance(offer_card, dict):
+        card = offer_card.get("card")
+        if isinstance(card, dict) and card.get("offerId") == offer_id:
+            return card
+    # Fallback: deep search (page structure may differ).
+    return _find_card_by_offer_id(state, offer_id)
+
+
+def _space_value(node: Any) -> float | None:
+    """Yandex area fields are ``{"value": N, "unit": "SQUARE_METER"}`` → float."""
+    if isinstance(node, dict):
+        val = node.get("value")
+        if isinstance(val, int | float):
+            return float(val)
+    elif isinstance(node, int | float):
+        return float(node)
+    return None
+
+
+def _parse_card_fields(
+    card: dict[str, Any],
+) -> tuple[
+    int | None,
+    float | None,
+    float | None,
+    float | None,
+    float | None,
+    int | None,
+    int | None,
+]:
+    """Extract (rooms, area, living, kitchen, ceiling, floor, total_floors) from card.
+
+    rooms: ``roomsTotal``, or 0 when ``house.studio`` is truthy (студии не
+    несут roomsTotal). floor: first element of ``floorsOffered``.
+    """
+    area = _space_value(card.get("area"))
+    living = _space_value(card.get("livingSpace"))
+    kitchen = _space_value(card.get("kitchenSpace"))
+
+    ceiling_raw = card.get("ceilingHeight")
+    ceiling: float | None = None
+    if isinstance(ceiling_raw, int | float):
+        ceiling = float(ceiling_raw)
+
+    rooms_raw = card.get("roomsTotal")
+    rooms: int | None = None
+    if isinstance(rooms_raw, int):
+        rooms = rooms_raw
+    house = card.get("house")
+    if isinstance(house, dict) and house.get("studio"):
+        rooms = 0
+
+    total_floors_raw = card.get("floorsTotal")
+    total_floors = total_floors_raw if isinstance(total_floors_raw, int) else None
+
+    floor: int | None = None
+    floors_offered = card.get("floorsOffered")
+    if isinstance(floors_offered, list) and floors_offered:
+        first = floors_offered[0]
+        if isinstance(first, int):
+            floor = first
+
+    return rooms, area, living, kitchen, ceiling, floor, total_floors
+
+
+def _find_section_text(tree: HTMLParser, heading: str) -> str | None:
+    """Find the text content of a <section>/<div> whose preceding h2/h3 matches heading.
+
+    Yandex page structure varies; this scans h2/h3 nodes, then returns the
+    concatenated text of subsequent sibling blocks until the next heading.
+    """
+    for h in tree.css("h2, h3"):
+        if heading.lower() in (h.text(strip=True) or "").lower():
+            # collect subsequent siblings until the next h2/h3
+            parts: list[str] = []
+            node: Node | None = h.next
+            while node is not None:
+                tag = (node.tag or "").lower()
+                if tag in {"h2", "h3"}:
+                    break
+                txt = node.text(strip=True) if hasattr(node, "text") else ""
+                if txt:
+                    parts.append(txt)
+                node = node.next
+            return " ".join(parts).strip() or None
+    return None
+
+
+def _extract_address(summary_text: str) -> str | None:
+    """Best-effort address extraction from summary block."""
+    # Pattern: "Россия, Свердловская область, Екатеринбург, улица Х, д. N"
+    m = re.search(r"(Россия[^•]+?)(?:•|\d+\s+просмотр|$)", summary_text)
+    if m:
+        addr = m.group(1).strip().rstrip(",").strip()
+        return addr if len(addr) > 10 else None
+    return None
+
+
+def _parse_metro_stations(location_text: str) -> list[MetroStation]:
+    """Parse 'Уральская 11 мин. Динамо 16 мин.' → list of MetroStation."""
+    stations: list[MetroStation] = []
+    # name (1+ Cyrillic words) + space + N + space + мин(.|у|ут)
+    for m in re.finditer(r"([А-ЯЁ][А-Яа-яё\s-]+?)\s+(\d+)\s*мин", location_text):
+        name = m.group(1).strip()
+        if 2 <= len(name) <= 40:
+            stations.append(MetroStation(name=name, walk_min=int(m.group(2))))
+        if len(stations) >= 5:
+            break
+    return stations
+
+
+def _extract_relative_date(summary_text: str) -> str | None:
+    """Capture phrases like '6 часов назад' / 'вчера' / '3 дня назад'."""
+    m = re.search(
+        r"(\d+\s+(?:минут|час|часов|часа|день|дня|дней|недел[ьюи])\s+назад"
+        r"|вчера|сегодня|позавчера)",
+        summary_text,
+        re.IGNORECASE,
+    )
+    return m.group(1).strip() if m else None
+
+
+def _extract_seller_name(summary_text: str, agency_name: str | None) -> str | None:
+    """Heuristic: line right before 'Агентство ...' in summary text."""
+    if not agency_name or agency_name not in summary_text:
+        return None
+    head = summary_text.split(agency_name, 1)[0]
+    # last short token sequence (likely "Имя Фамилия")
+    m = re.findall(r"([А-ЯЁ][а-яё]+(?:\s+[А-ЯЁ][а-яё]+){1,2})", head)
+    return m[-1] if m else None
+
+
+# ── Save helper ───────────────────────────────────────────────────────────────
+
+
+def save_detail_enrichment(db: Session, listing_id: int, e: DetailEnrichment) -> bool:
+    """Persist Yandex DetailEnrichment to listings row.
+
+    UPDATE listings SET <col> = COALESCE(:val, <col>), ..., detail_enriched_at = NOW()
+    WHERE id = listing_id.
+
+    COALESCE semantics: keeps existing non-NULL value if new value is NULL (never
+    overwrites a populated column with NULL). area_m2 from detail is more accurate
+    than SERP, but COALESCE preserves SERP value if detail returns NULL — acceptable.
+
+    Returns True if the UPDATE touched at least one row (listing_id found in DB).
+    """
+    metro_json: str | None = None
+    if e.metro_stations:
+        metro_json = json.dumps(
+            [s.model_dump(exclude_none=True) for s in e.metro_stations],
+            ensure_ascii=False,
+        )
+
+    photo_json: str | None = None
+    if e.photo_urls:
+        photo_json = json.dumps(e.photo_urls, ensure_ascii=False)
+
+    result = db.execute(
+        text("""
+            UPDATE listings SET
+                rooms                = COALESCE(CAST(:rooms AS int),        rooms),
+                area_m2              = COALESCE(CAST(:area_m2 AS numeric),  area_m2),
+                living_area_m2       = COALESCE(
+                                           CAST(:living_area_m2 AS numeric),
+                                           living_area_m2
+                                       ),
+                kitchen_area_m2      = COALESCE(
+                                           CAST(:kitchen_area_m2 AS numeric),
+                                           kitchen_area_m2
+                                       ),
+                ceiling_height       = COALESCE(
+                                           CAST(:ceiling_height AS numeric),
+                                           ceiling_height
+                                       ),
+                floor                = COALESCE(CAST(:floor AS int),        floor),
+                total_floors         = COALESCE(CAST(:total_floors AS int), total_floors),
+                address              = COALESCE(CAST(:address AS text),     address),
+                description          = COALESCE(CAST(:description AS text), description),
+                repair_state         = COALESCE(CAST(:repair_state AS text),repair_state),
+                publish_date         = COALESCE(CAST(:publish_date AS date),publish_date),
+                views_total_yandex   = COALESCE(CAST(:views_total AS int),  views_total_yandex),
+                publish_date_relative= COALESCE(
+                                           CAST(:pub_date_rel AS text),
+                                           publish_date_relative
+                                       ),
+                agency_name          = COALESCE(CAST(:agency_name AS text), agency_name),
+                agency_founded_year  = COALESCE(
+                                           CAST(:agency_founded_year AS int),
+                                           agency_founded_year
+                                       ),
+                agency_objects_count = COALESCE(
+                                           CAST(:agency_objects_count AS int),
+                                           agency_objects_count
+                                       ),
+                metro_stations       = COALESCE(
+                                           CAST(:metro_stations AS jsonb),
+                                           metro_stations
+                                       ),
+                photo_urls           = COALESCE(
+                                           CAST(:photo_urls AS jsonb),
+                                           photo_urls
+                                       ),
+                newbuilding_url      = COALESCE(
+                                           CAST(:newbuilding_url AS text),
+                                           newbuilding_url
+                                       ),
+                newbuilding_id       = COALESCE(
+                                           CAST(:newbuilding_id AS text),
+                                           newbuilding_id
+                                       ),
+                detail_enriched_at   = NOW()
+            WHERE id = CAST(:listing_id AS bigint)
+        """),
+        {
+            "listing_id": listing_id,
+            "rooms": e.rooms,
+            "area_m2": e.area_m2,
+            "living_area_m2": e.living_area_m2,
+            "kitchen_area_m2": e.kitchen_area_m2,
+            "ceiling_height": e.ceiling_height,
+            "floor": e.floor,
+            "total_floors": e.total_floors,
+            "address": e.address,
+            "description": e.description,
+            "repair_state": e.repair_state,
+            "publish_date": e.publish_date,
+            "views_total": e.views_total,
+            "pub_date_rel": e.publish_date_relative,
+            "agency_name": e.agency_name,
+            "agency_founded_year": e.agency_founded_year,
+            "agency_objects_count": e.agency_objects_count,
+            "metro_stations": metro_json,
+            "photo_urls": photo_json,
+            "newbuilding_url": e.newbuilding_url,
+            "newbuilding_id": e.newbuilding_id,
+        },
+    )
+    db.commit()
+    saved = (result.rowcount or 0) > 0
+    logger.info(
+        "yandex detail enrichment saved listing_id=%s (metro=%d photos=%d saved=%s)",
+        listing_id,
+        len(e.metro_stations),
+        len(e.photo_urls),
+        saved,
+    )
+    return saved

tradein-mvp/packages/scraper-kit/src/scraper_kit/providers/yandex/newbuilding.py

@@ -0,0 +1,438 @@
+"""Yandex Realty ЖК landing page parser.
+
+URL pattern: /{city}/kupit/novostrojka/<slug>-<id>/
+Reference target: ЖК Татлин (id=1592987, slug=tatlin) — comfort+, June 2023,
+PRINZIP, rating 4.3, 1505 ratings, 353 text reviews, coords (56.855312, 60.576668).
+
+Fetch strategy (#974):
+  - Все network-запросы (ЖК-лендинг + SERP slug-resolve) идут через BrowserFetcher
+    (tradein-browser camoufox), а НЕ через httpx/_http_get.
+  - Yandex Realty — JS-heavy / anti-bot; curl_cffi / httpx не получают данные.
+  - BrowserFetcher.fetch(url) → str (полный HTML); вызывающий код парсит через parse().
+
+Strangler-копия `app.services.scrapers.yandex_newbuilding` (#2133). Развязка от `app.*`:
+  - `app.services.scraper_settings.get_scraper_delay` → инжектируемый `delay_provider`
+  - `app.services.scrapers.base` → `scraper_kit.base`
+  - `app.services.scrapers.browser_fetcher` → `scraper_kit.browser_fetcher`
+  - `app.services.scrapers.yandex_helpers` → `scraper_kit.yandex_helpers`
+"""
+
+from __future__ import annotations
+
+import logging
+import re
+from collections.abc import Callable
+from typing import Any
+
+from pydantic import BaseModel, Field
+from selectolax.parser import HTMLParser, Node
+
+from scraper_kit.base import BaseScraper
+from scraper_kit.browser_fetcher import BrowserFetcher
+from scraper_kit.yandex_helpers import (
+    RE_JK_ID,
+    parse_house_class,
+    parse_house_type,
+)
+
+logger = logging.getLogger(__name__)
+
+
+# ── Models ───────────────────────────────────────────────────────────────────
+
+
+class JKMetroStation(BaseModel):
+    name: str
+    walk_min: int | None = None
+
+
+class YandexNewbuildingInfo(BaseModel):
+    """ЖК landing scrape payload."""
+
+    ext_id: str  # '1592987'
+    ext_slug: str  # 'tatlin'
+    source_url: str
+
+    # Identification
+    name: str | None = None  # 'ЖК «Татлин»'
+    address: str | None = None  # 'Екатеринбург, ул. Черепанова / ул. Готвальда'
+
+    # Coords (inline in HTML — Yandex unique vs Avito/Cian)
+    lat: float | None = None
+    lon: float | None = None
+
+    # Classification + commission
+    house_class: str | None = None  # 'comfort_plus' etc.
+    commission_year: int | None = None
+    commission_month: str | None = None  # 'июнь' (RU)
+
+    # Footprint
+    total_floors: int | None = None  # 35
+    corpus_count: int | None = None  # 3
+    total_area_ha: float | None = None  # 1.5
+
+    # Developer
+    developer_name: str | None = None  # 'PRINZIP'
+    developer_url: str | None = None
+    developer_other_jk: list[str] = Field(default_factory=list)
+
+    # Reviews
+    rating: float | None = None  # 4.3
+    ratings_count: int | None = None  # 1505 — оценок
+    text_reviews_count: int | None = None  # 353 — текстовых отзывов
+
+    # NLP / description
+    description: str | None = None
+
+    # Metro
+    metro_stations: list[JKMetroStation] = Field(default_factory=list)
+
+    # House type (best-effort NLP from description)
+    house_type: str | None = None
+
+    raw_payload: dict[str, Any] | None = None
+
+
+# ── Regex constants ───────────────────────────────────────────────────────────
+
+RE_FLOORS_TOWERS = re.compile(r"(\d+)-этажн\w+\s+башн", re.IGNORECASE)
+RE_AREA_HA = re.compile(r"участке\s+([\d,]+)\s*га", re.IGNORECASE)
+RE_COMMISSION = re.compile(
+    r"(?:введ[её]н|сдан)\s+в\s+эксплуатацию\s+в\s+(\w+)\s+(\d{4})", re.IGNORECASE
+)
+# Yandex drift (#974 follow-up): рейтинг рендерится без пробела перед «из»
+# ("4.3из 5" / "4,5из 5", nbsp внутри) → \s* (а не \s+) перед «из», иначе rating=NULL
+# при заполненных ratings_count/text_reviews (verified live 2026-06-15, ЖК Татлин/Рио).
+RE_RATING = re.compile(r"(\d[.,]\d)\s*из\s+5")
+RE_RATINGS_COUNT = re.compile(r"(\d+)\s+оценок", re.IGNORECASE)
+RE_TEXT_REVIEWS = re.compile(r"Смотреть\s+все\s+(\d+)\s+отзыв", re.IGNORECASE)
+RE_CORPUS_COUNT_WORD = re.compile(
+    r"(одн[ау]|две|три|четыре|пять|шесть|семь|восемь|\d+)\s+(?:[\d\s-]*)\s*-?\s*этажн",
+    re.IGNORECASE,
+)
+RE_METRO_INLINE = re.compile(
+    r"([А-ЯЁ][А-Яа-яё\s-]{2,30}?)\s+(\d+)\s*мин",
+)
+
+# Slug из href: /{city}/kupit/novostrojka/<slug>-<id>/
+# Используется в resolve_yandex_jk_slug для извлечения slug из SERP href.
+_JK_SLUG_RE = re.compile(
+    r"/(?:ekaterinburg|moskva|spb|[a-z-]+)/kupit/novostrojka/([a-z0-9-]+)-(\d+)/"
+)
+
+# Ekb-specific coord ranges (extend per-city later)
+LAT_RANGE = (55.5, 57.5)
+LON_RANGE = (59.5, 61.5)
+
+# Word → number map
+_WORD_NUM: dict[str, int] = {
+    "одна": 1,
+    "одну": 1,
+    "одной": 1,
+    "две": 2,
+    "три": 3,
+    "четыре": 4,
+    "пять": 5,
+    "шесть": 6,
+    "семь": 7,
+    "восемь": 8,
+}
+
+
+# ── Scraper class ─────────────────────────────────────────────────────────────
+
+
+class YandexNewbuildingScraper(BaseScraper):
+    name = "yandex_realty_nb"
+    base_url = "https://realty.yandex.ru"
+    request_delay_sec = 5.0  # class default; instance value injected via delay_provider
+
+    def __init__(self, *, delay_provider: Callable[[str], float] | None = None) -> None:
+        super().__init__()
+        # Strangler-инжекция (#2133): провайдер задержки приходит снаружи вместо
+        # прямого импорта app.services.scraper_settings.get_scraper_delay.
+        if delay_provider is not None:
+            self.request_delay_sec = delay_provider(self.name)
+
+    async def fetch_around(self, lat: float, lon: float, radius_m: int = 1000) -> list:  # type: ignore[override]
+        raise NotImplementedError(
+            "YandexNewbuildingScraper is JK-slug-based; use fetch_jk(slug, id) instead."
+        )
+
+    async def fetch_jk(
+        self, jk_slug: str, jk_id: str, city: str = "ekaterinburg"
+    ) -> YandexNewbuildingInfo | None:
+        """Загрузить ЖК-лендинг через BrowserFetcher и распарсить.
+
+        Yandex Realty — JS/anti-bot: curl/httpx не получают данные. Запрос идёт
+        через tradein-browser (camoufox) контейнер — единственный рабочий путь (#974).
+        """
+        url = f"{self.base_url}/{city}/kupit/novostrojka/{jk_slug}-{jk_id}/"
+        try:
+            async with BrowserFetcher(source="yandex") as fetcher:
+                html = await fetcher.fetch(url)
+        except Exception:
+            logger.exception("yandex nb browser fetch failed: %s", url)
+            return None
+        if not html or len(html) < 500:
+            logger.warning(
+                "yandex nb browser returned empty/tiny HTML (%d bytes): %s",
+                len(html) if html else 0,
+                url,
+            )
+            return None
+        result = self.parse(html, jk_slug=jk_slug, jk_id=jk_id, source_url=url)
+        return result
+
+    def parse(self, html: str, jk_slug: str, jk_id: str, source_url: str) -> YandexNewbuildingInfo:
+        tree = HTMLParser(html)
+        body = tree.body
+        body_text = body.text(strip=True) if body else ""
+
+        # Header
+        h1 = tree.css_first("h1")
+        name = h1.text(strip=True) if h1 else None
+
+        # Sections (heading-based extraction)
+        location_text = _find_section_text(tree, "Расположение") or ""
+        description_section = (
+            _find_section_text(tree, "О комплексе")
+            or _find_section_text(tree, "Расположение, транспортная доступность")
+            or location_text
+        )
+
+        # Coords — inline scan within plausible range
+        lat, lon = _extract_coords(html)
+
+        # Class
+        house_class = parse_house_class(description_section) or parse_house_class(body_text)
+
+        # Commission
+        commission_year: int | None = None
+        commission_month: str | None = None
+        c_m = RE_COMMISSION.search(description_section) or RE_COMMISSION.search(body_text)
+        if c_m:
+            commission_month = c_m.group(1).lower()
+            try:
+                commission_year = int(c_m.group(2))
+            except ValueError:
+                pass
+
+        # Floors + corpus + area
+        floors_m = RE_FLOORS_TOWERS.search(description_section) or RE_FLOORS_TOWERS.search(
+            body_text
+        )
+        total_floors = int(floors_m.group(1)) if floors_m else None
+
+        corpus_count = _parse_corpus_count(description_section or body_text)
+
+        area_m = RE_AREA_HA.search(description_section) or RE_AREA_HA.search(body_text)
+        total_area_ha = float(area_m.group(1).replace(",", ".")) if area_m else None
+
+        # Developer
+        dev_link = tree.css_first('[data-test="CARD_DEV_BADGE_DEVELOPER_LINK"]')
+        developer_name: str | None = None
+        developer_url: str | None = None
+        if dev_link is not None:
+            developer_name = dev_link.text(strip=True) or None
+            href = dev_link.attributes.get("href", "")
+            if href:
+                developer_url = (
+                    href if href.startswith("http") else f"https://realty.yandex.ru{href}"
+                )
+
+        # Developer's other JKs
+        other_jk_block = tree.css_first('[data-test="CardDevSites"]')
+        developer_other_jk: list[str] = []
+        if other_jk_block is not None:
+            for jk_a in other_jk_block.css("a"):
+                t = jk_a.text(strip=True)
+                if t and t not in developer_other_jk:
+                    developer_other_jk.append(t)
+
+        # Reviews
+        rating_m = RE_RATING.search(body_text)
+        rating = float(rating_m.group(1).replace(",", ".")) if rating_m else None
+        rcount_m = RE_RATINGS_COUNT.search(body_text)
+        ratings_count = int(rcount_m.group(1)) if rcount_m else None
+        treviews_m = RE_TEXT_REVIEWS.search(body_text)
+        text_reviews_count = int(treviews_m.group(1)) if treviews_m else None
+
+        # Address (header area before lat/lon block)
+        address = _extract_jk_address(body_text, name)
+
+        # Metro stations
+        metro_stations = _parse_metro(body_text)
+
+        # NLP house_type fallback
+        house_type = parse_house_type(description_section) or parse_house_type(body_text)
+
+        return YandexNewbuildingInfo(
+            ext_id=jk_id,
+            ext_slug=jk_slug,
+            source_url=source_url,
+            name=name,
+            address=address,
+            lat=lat,
+            lon=lon,
+            house_class=house_class,
+            commission_year=commission_year,
+            commission_month=commission_month,
+            total_floors=total_floors,
+            corpus_count=corpus_count,
+            total_area_ha=total_area_ha,
+            developer_name=developer_name,
+            developer_url=developer_url,
+            developer_other_jk=developer_other_jk[:10],
+            rating=rating,
+            ratings_count=ratings_count,
+            text_reviews_count=text_reviews_count,
+            description=description_section or None,
+            metro_stations=metro_stations,
+            house_type=house_type,
+            raw_payload={
+                "description_len": len(description_section or ""),
+                "body_len": len(body_text),
+            },
+        )
+
+
+# ── Slug resolution via SERP ──────────────────────────────────────────────────
+
+
+async def resolve_yandex_jk_slug(
+    jk_id: str,
+    city: str = "ekaterinburg",
+) -> str | None:
+    """Найти Yandex Realty slug для ЖК по его ext_id (jk_id) через SERP.
+
+    Стратегия (#974 — зеркало resolve_cian_zhk_url_via_search):
+      1. Запросить поисковую страницу Yandex Realty через BrowserFetcher.
+         URL: /ekaterinburg/kupit/novostrojka/?siteId=<jk_id>
+      2. В HTML найти первую ссылку вида /<city>/kupit/novostrojka/<slug>-<jk_id>/
+         через regex _JK_SLUG_RE.
+      3. Вернуть slug или None при любой ошибке.
+
+    Caller несёт ответственность за anti-bot sleep (зеркало cian_newbuilding.py).
+    BrowserFetcher обязателен — Yandex Realty JS/anti-bot, httpx/curl не работают.
+
+    Returns:
+        slug (str без id-суффикса), или None при ошибке / не найден.
+    """
+    # Yandex Realty SERP: фильтр по siteId → первый результат = нужный ЖК.
+    # Альтернативный путь через Яндекс Поиск (web SERP) менее надёжен из-за
+    # вариативности разметки. Прямой realty.yandex.ru SERP — стабильнее.
+    serp_url = f"https://realty.yandex.ru/{city}/kupit/novostrojka/?siteId={jk_id}"
+    try:
+        async with BrowserFetcher(source="yandex") as fetcher:
+            html = await fetcher.fetch(serp_url)
+    except Exception as exc:
+        logger.warning("resolve_yandex_jk_slug jk_id=%s browser fetch failed: %s", jk_id, exc)
+        return None
+
+    if not html:
+        logger.warning("resolve_yandex_jk_slug jk_id=%s: empty HTML from browser", jk_id)
+        return None
+
+    # Ищем ссылку вида /{city}/kupit/novostrojka/<slug>-<id>/
+    # Ограничиваем: id в ссылке должен совпадать с искомым jk_id.
+    for m in _JK_SLUG_RE.finditer(html):
+        if m.group(2) == str(jk_id):
+            slug = m.group(1)
+            logger.info("resolve_yandex_jk_slug jk_id=%s → slug=%s", jk_id, slug)
+            return slug
+
+    logger.warning(
+        "resolve_yandex_jk_slug jk_id=%s: no matching slug in SERP HTML (markup drift?)",
+        jk_id,
+    )
+    return None
+
+
+# ── helpers ───────────────────────────────────────────────────────────────────
+
+
+def _extract_coords(html: str) -> tuple[float | None, float | None]:
+    """Scan HTML for any `<lat>.\\d+` and `<lon>.\\d+` matching plausible city range."""
+    lats = [
+        float(m)
+        for m in re.findall(r"\b(\d{2}\.\d{4,8})\b", html)
+        if LAT_RANGE[0] <= float(m) <= LAT_RANGE[1]
+    ]
+    lons = [
+        float(m)
+        for m in re.findall(r"\b(\d{2}\.\d{4,8})\b", html)
+        if LON_RANGE[0] <= float(m) <= LON_RANGE[1]
+    ]
+    lat = lats[0] if lats else None
+    lon = lons[0] if lons else None
+    return lat, lon
+
+
+def _find_section_text(tree: HTMLParser, heading: str) -> str | None:
+    for h in tree.css("h2, h3"):
+        if heading.lower() in (h.text(strip=True) or "").lower():
+            parts: list[str] = []
+            node: Node | None = h.next
+            while node is not None:
+                tag = (node.tag or "").lower()
+                if tag in {"h2", "h3"}:
+                    break
+                txt = node.text(strip=True) if hasattr(node, "text") else ""
+                if txt:
+                    parts.append(txt)
+                node = node.next
+            return " ".join(parts).strip() or None
+    return None
+
+
+def _parse_corpus_count(text: str) -> int | None:
+    m = RE_CORPUS_COUNT_WORD.search(text)
+    if not m:
+        return None
+    token = m.group(1).lower()
+    if token.isdigit():
+        return int(token)
+    return _WORD_NUM.get(token)
+
+
+def _parse_metro(text: str) -> list[JKMetroStation]:
+    stations: list[JKMetroStation] = []
+    for m in RE_METRO_INLINE.finditer(text):
+        name = m.group(1).strip()
+        # filter common noise
+        if not 2 <= len(name) <= 40 or "ходьб" in name.lower() or "минут" in name.lower():
+            continue
+        try:
+            stations.append(JKMetroStation(name=name, walk_min=int(m.group(2))))
+        except ValueError:
+            continue
+        if len(stations) >= 5:
+            break
+    return stations
+
+
+def _extract_jk_address(body_text: str, name: str | None) -> str | None:
+    """Find address line — typically right after JK name, before metro entries."""
+    if name and name in body_text:
+        after_name = body_text.split(name, 1)[1]
+        # Match 'Город, ул. X / ул. Y' until first metro mention
+        m = re.match(
+            r"\s*([А-ЯЁ][^•]{5,150}?)(?:\s+[А-ЯЁ][а-яё]+\s+\d+\s*мин|\d+\s+оценок|$)",
+            after_name,
+        )
+        if m:
+            addr = m.group(1).strip().rstrip(",").strip()
+            if 10 < len(addr) < 200:
+                return addr
+    return None
+
+
+# Expose RE_JK_ID at module level for external use (e.g. SERP link → newbuilding detail)
+__all__ = [
+    "RE_JK_ID",
+    "JKMetroStation",
+    "YandexNewbuildingInfo",
+    "YandexNewbuildingScraper",
+    "resolve_yandex_jk_slug",
+]

tradein-mvp/packages/scraper-kit/src/scraper_kit/providers/yandex/shared.py

@@ -0,0 +1,95 @@
+"""Нормализация house_type → каноничный enum для listings.house_type.
+
+Strangler-копия `app.services.scrapers.house_type_normalizer` (#2133). Локальная в
+yandex-провайдере, потому что house_type_normalizer ещё не перенесён в core-слой
+scraper_kit (это отдельный шаг консолидации E). Копия — pure-функция без `app.*`
+зависимостей; идентична источнику.
+
+Целевой канон (сверено с estimator._IMV_HOUSE_TYPE_MAP, estimator.py:146):
+  panel / brick / monolith / monolith_brick / block / wood.
+
+Зачем (#2007): estimator применяет soft-penalty по house_type — аналог с
+house_type != target штрафуется. Yandex SERP отдаёт SCREAMING-значения
+(MONOLIT / BRICK / PANEL / ...), которые НИКОГДА не равны каноничным
+(monolith / brick / panel / ...) → ~70% yandex-аналогов получали ложный штраф
+и фактически выпадали из скоринга. Нормализация на ингесте чинит это.
+
+Важно про None: неизвестное / 'other' / '' → None, НЕ 'other'. В estimator
+`house_type IS NULL` нейтрально (без штрафа), а любое не-канон значение всегда
+!= target → ложный штраф. Поэтому unknown лучше схлопнуть в NULL.
+
+Источники raw-значений:
+- yandex SERP: building.buildingType — SCREAMING_SNAKE (MONOLIT, MONOLIT_BRICK, ...)
+- cian SERP: building.materialType — camelCase (monolith, monolithBrick,
+  gasSilicateBlock, ...) — переиспользуется в #2008 (cian.py:815).
+"""
+
+from __future__ import annotations
+
+import logging
+
+logger = logging.getLogger(__name__)
+
+# Канон listings.house_type — выровнен по estimator._IMV_HOUSE_TYPE_MAP.
+_CANON: frozenset[str] = frozenset(
+    {"panel", "brick", "monolith", "monolith_brick", "block", "wood"}
+)
+
+# raw-токен → канон. Ключи — точные значения вокабуляров источников; сравнение
+# регистронезависимое (см. _LOOKUP ниже), но строго по полному токену енума,
+# без fuzzy-матчинга. Неизвестные токены сюда НЕ попадают → normalize вернёт None.
+_RAW_TO_CANON: dict[str, str] = {
+    # ── yandex SERP (SCREAMING_SNAKE buildingType) ───────────────────────────
+    "MONOLIT": "monolith",
+    "BRICK": "brick",
+    "PANEL": "panel",
+    "MONOLIT_BRICK": "monolith_brick",
+    "BLOCK": "block",
+    "WOOD": "wood",
+    # ── cian SERP (camelCase materialType) — reuse в #2008 ───────────────────
+    "monolith": "monolith",
+    "brick": "brick",
+    "panel": "panel",
+    "block": "block",
+    "wood": "wood",
+    "monolithBrick": "monolith_brick",
+    "gasSilicateBlock": "block",
+    "aerocreteBlock": "block",
+    "foamConcreteBlock": "block",
+    "stalin": "brick",  # «сталинка» — кирпич
+}
+
+# Регистронезависимый lookup. Лоуэркейс-ключи не коллизят между вокабулярами:
+# 'MONOLIT'→'monolit' и 'monolith'→'monolith' — разные ключи.
+_LOOKUP: dict[str, str] = {k.lower(): v for k, v in _RAW_TO_CANON.items()}
+
+
+def normalize_house_type(raw: str | None) -> str | None:
+    """Преобразовать raw house_type в каноничный enum.
+
+    Уже-каноничное значение возвращается as-is (идемпотентность — нужна при
+    ре-обработке и для backfill-миграции). Неизвестное / 'other' / пустое /
+    None → None (НЕ 'other': см. docstring модуля про estimator soft-penalty).
+
+    Args:
+        raw: сырое значение из парсера (e.g. «MONOLIT», «monolithBrick») или None.
+
+    Returns:
+        Одно из panel / brick / monolith / monolith_brick / block / wood, либо None.
+    """
+    if raw is None:
+        return None
+    stripped = raw.strip()
+    if not stripped:
+        return None
+    # Pass-through: уже каноничное значение (idempotency — в т.ч. 'monolith_brick',
+    # которого нет среди raw-ключей карты).
+    if stripped in _CANON:
+        return stripped
+    # Регистронезависимый exact-token lookup по обоим вокабулярам.
+    canon = _LOOKUP.get(stripped) or _LOOKUP.get(stripped.lower())
+    if canon is None:
+        # Неизвестное / 'other' — нормально (NULL нейтрально для estimator).
+        # debug, не warning: 'other' встречается массово, warning засорил бы лог.
+        logger.debug("house_type_normalizer: unmapped raw value %r — stored as NULL", raw)
+    return canon

tradein-mvp/packages/scraper-kit/src/scraper_kit/providers/yandex/valuation.py

@@ -0,0 +1,543 @@
+"""Yandex Realty anonymous valuation/history scraper.
+
+URL pattern:
+  GET /otsenka-kvartiry-po-adresu-onlayn/?address=...&offerCategory=...&offerType=...&page=N
+
+No cookies, no auth required (unlike Cian Calculator or Avito IMV).
+
+Extracts:
+- House metadata: year_built, total_floors, house_type, ceiling_height, has_lift, total_objects
+- Historical offers: area, rooms, floor, start/last price + per-m2, publish_date DMY, exposure
+
+Two-strategy history extraction:
+1. data-test container selectors (CSS, if Yandex adds them)
+2. Fallback: text chunks around DD.MM.YYYY date matches with dedup by (date, area, floor)
+
+Strangler-копия `app.services.scrapers.yandex_valuation` (#2133). Развязка от `app.*`:
+  - `app.core.config.settings` → инжектируемый `ScraperConfig` (scraper_proxy_url)
+  - `app.services.scraper_settings.get_scraper_delay` → инжектируемый `delay_provider`
+  - `app.services.scrapers.base` → `scraper_kit.base`
+  - `app.services.scrapers.yandex_helpers` → `scraper_kit.yandex_helpers`
+"""
+
+from __future__ import annotations
+
+import logging
+import re
+from collections.abc import Callable
+from datetime import date
+from typing import TYPE_CHECKING, Any
+from urllib.parse import urlencode
+
+from curl_cffi.requests import AsyncSession as _CurlCffiSession
+from pydantic import BaseModel, Field
+from selectolax.parser import HTMLParser
+
+from scraper_kit.base import BaseScraper
+from scraper_kit.yandex_helpers import (
+    parse_dmy,
+    parse_house_type,
+    parse_rub,
+)
+
+if TYPE_CHECKING:
+    from scraper_kit.contracts import ScraperConfig
+
+logger = logging.getLogger(__name__)
+
+
+# ---------------------------------------------------------------------------
+# Models
+# ---------------------------------------------------------------------------
+
+
+class ValuationHouseMeta(BaseModel):
+    """House metadata extracted from Yandex valuation page."""
+
+    year_built: int | None = None
+    total_floors: int | None = None
+    house_type: str | None = None  # panel/brick/monolith/...
+    ceiling_height: float | None = None  # in meters, e.g. 2.5
+    has_lift: bool | None = None
+    total_objects: int | None = None  # 'N объектов' (full archive count)
+    has_panorama: bool = False  # 'Панорама' label present
+
+    def validate_match(
+        self,
+        expected_year_built: int | None = None,
+        expected_total_floors: int | None = None,
+    ) -> float:
+        """Return confidence 0..1 that this house meta matches expected values.
+
+        Used after fetching valuation by address to detect when Yandex returned a
+        different house (ambiguous address geocoding). Tolerance ±1 year, ±1 floor.
+
+        Both expected=None → 1.0 (no check). Mismatch on any dimension → 0.0 for it.
+        """
+        score = 0.0
+        checks = 0
+        if expected_year_built is not None:
+            checks += 1
+            if self.year_built is not None and abs(self.year_built - expected_year_built) <= 1:
+                score += 1.0
+        if expected_total_floors is not None:
+            checks += 1
+            if (
+                self.total_floors is not None
+                and abs(self.total_floors - expected_total_floors) <= 1
+            ):
+                score += 1.0
+        if checks == 0:
+            return 1.0
+        return score / checks
+
+
+class ValuationHistoryItem(BaseModel):
+    """One historical offer entry from the valuation page."""
+
+    area_m2: float | None = None
+    rooms: int | None = None
+    floor: int | None = None
+    start_price: int | None = None
+    start_price_per_m2: int | None = None
+    last_price: int | None = None
+    last_price_per_m2: int | None = None
+    publish_date: date | None = None
+    removed_date: date | None = None  # ← NEW
+    exposure_days: int | None = None
+    status: str | None = None  # 'В продаже' / 'Снято'
+
+
+class YandexValuationResult(BaseModel):
+    """Full result of one /otsenka-... GET."""
+
+    address: str
+    offer_category: str
+    offer_type: str
+    page: int
+    source_url: str
+    house: ValuationHouseMeta
+    history_items: list[ValuationHistoryItem] = Field(default_factory=list)
+    raw_payload: dict[str, Any] | None = None
+
+
+# ---------------------------------------------------------------------------
+# Regex constants
+# ---------------------------------------------------------------------------
+
+RE_YEAR_BUILT = re.compile(r"Дом\s+(\d{4})\s+года", re.IGNORECASE)
+RE_FLOORS = re.compile(r"(\d+)\s+этажей", re.IGNORECASE)
+RE_CEILING = re.compile(r"([\d,]+)\s*м\s+потолки", re.IGNORECASE)
+RE_TOTAL_OBJECTS = re.compile(r"(\d+)\s+объект", re.IGNORECASE)
+
+# Lookbehind blocks digit-only adjacency (rejects year-concat like '20244,6')
+# while still allowing tokens preceded by punctuation/letter. Min 2 digits
+# rejects sub-fragments like '2,2' that come from inside '52,2'. Max 4 digits
+# whole part catches obvious junk (penthouse extremes are <500 m² in practice;
+# sanity cap from PR #538 backs this up).
+RE_ITEM_AREA = re.compile(r"(?<!\d)(\d{2,4}(?:[.,]\d{1,2})?)\s*м²")
+RE_ITEM_ROOMS = re.compile(r"(\d+)\s*-\s*комнатн", re.IGNORECASE)
+RE_ITEM_STUDIO = re.compile(r"студи[яюй]", re.IGNORECASE)
+RE_ITEM_FLOOR = re.compile(r"(\d+)\s*этаж", re.IGNORECASE)
+RE_ITEM_EXPOSURE = re.compile(r"экспозиции\s+(\d+)\s+дн", re.IGNORECASE)
+RE_ITEM_STATUS = re.compile(r"(В\s+продаже|Снят[оа])", re.IGNORECASE)
+
+# Matches total-price tokens (rubles) — excludes per-m2 tokens by negative lookahead
+_RE_PRICE_TOKEN = re.compile(r"(?:\d[\d\s]*\d|\d)(?:[.,]\d+)?\s*(?:млн)?\s*₽(?!\s*за\s*м²)")
+_RE_PPM2_TOKEN = re.compile(r"\d[\d\s]*\s*₽\s*за\s*м²")
+
+
+# ---------------------------------------------------------------------------
+# Scraper
+# ---------------------------------------------------------------------------
+
+
+class YandexValuationScraper(BaseScraper):
+    """Anonymous Yandex valuation/history scraper.
+
+    Fetches https://realty.yandex.ru/otsenka-kvartiry-po-adresu-onlayn/ by address.
+    Pagination via ?page=N. Use fetch_house_history() directly;
+    fetch_around() is not applicable to this tool.
+    """
+
+    name = "yandex_valuation"
+    base_url = "https://realty.yandex.ru"
+    valuation_path = "/otsenka-kvartiry-po-adresu-onlayn/"
+    request_delay_sec = 5.0  # class default; instance value injected via delay_provider
+
+    def __init__(
+        self,
+        config: ScraperConfig,
+        *,
+        delay_provider: Callable[[str], float] | None = None,
+    ) -> None:
+        super().__init__()
+        # Strangler-инжекция (#2133): конфиг (прокси-egress) и провайдер задержки
+        # приходят снаружи вместо app.core.config.settings /
+        # app.services.scraper_settings.get_scraper_delay.
+        self._config = config
+        if delay_provider is not None:
+            self.request_delay_sec = delay_provider(self.name)
+        self._cffi_session: _CurlCffiSession | None = None
+
+    async def __aenter__(self) -> YandexValuationScraper:  # type: ignore[override]
+        # Override: Yandex valuation endpoint gates SSR data on Chrome TLS
+        # fingerprint. Plain httpx returns shell HTML (CSR-only).
+        # Sibling: yandex_realty.py / scripts/local-sweep-ekb-yandex.py
+        # Mobile proxy wiring (#806 follow-up): route via mobile proxy to avoid
+        # datacenter-IP blocks. proxy=None → прямое подключение (dev).
+        _proxy_url = self._config.scraper_proxy_url
+        _proxies = {"http": _proxy_url, "https": _proxy_url} if _proxy_url else None
+        self._cffi_session = _CurlCffiSession(impersonate="chrome120", proxies=_proxies)
+        return self
+
+    async def __aexit__(self, *args: object) -> None:  # type: ignore[override]
+        if self._cffi_session is not None:
+            await self._cffi_session.close()
+            self._cffi_session = None
+
+    async def _http_get(self, url: str, **kwargs: object) -> object:  # type: ignore[override]
+        """curl_cffi-based GET with Chrome120 impersonation.
+
+        Returns curl_cffi Response (compatible API: .status_code, .text).
+        Caller must check status_code; no automatic retry (BaseScraper.retry
+        decorator is per-method and not inherited cleanly when overridden).
+        """
+        if self._cffi_session is None:
+            raise RuntimeError("YandexValuationScraper must be used as async context manager")
+        kwargs.setdefault("timeout", 30)
+        return await self._cffi_session.get(url, **kwargs)
+
+    async def fetch_around(self, lat: float, lon: float, radius_m: int = 1000) -> list:  # type: ignore[override]
+        raise NotImplementedError(
+            "YandexValuationScraper is address-based; use fetch_house_history() instead."
+        )
+
+    async def fetch_house_history(
+        self,
+        address: str,
+        offer_category: str = "APARTMENT",
+        offer_type: str = "SELL",
+        page: int = 1,
+    ) -> YandexValuationResult | None:
+        """Fetch and parse one page of house history for the given address.
+
+        Args:
+            address: Postal address string (will be URL-encoded).
+            offer_category: 'APARTMENT' / 'ROOMS' / etc.
+            offer_type: 'SELL' / 'RENT'.
+            page: 1-based pagination index.
+
+        Returns:
+            YandexValuationResult or None on HTTP error / network failure.
+        """
+        params = {
+            "address": address,
+            "offerCategory": offer_category,
+            "offerType": offer_type,
+            "page": page,
+        }
+        url = f"{self.base_url}{self.valuation_path}?{urlencode(params)}"
+        try:
+            response = await self._http_get(url)
+        except Exception:
+            logger.exception("yandex valuation fetch failed: %s", url)
+            return None
+        if response.status_code != 200:
+            logger.warning("yandex valuation returned %d for %s", response.status_code, url)
+            return None
+        result = self.parse(
+            response.text,
+            address=address,
+            offer_category=offer_category,
+            offer_type=offer_type,
+            page=page,
+            source_url=url,
+        )
+        await self.sleep_between_requests()
+        return result
+
+    def parse(
+        self,
+        html: str,
+        address: str,
+        offer_category: str,
+        offer_type: str,
+        page: int,
+        source_url: str,
+    ) -> YandexValuationResult:
+        """Parse raw HTML into YandexValuationResult. Pure function — usable in unit tests."""
+        html_normalized = html.replace("\xa0", " ")
+        tree = HTMLParser(html_normalized)
+        body = tree.body
+        body_text = (body.text(strip=True) if body else "").replace("\xa0", " ")
+
+        house = self._parse_house_meta(body_text)
+        history_items = self._parse_history_items(tree, body_text)
+
+        return YandexValuationResult(
+            address=address,
+            offer_category=offer_category,
+            offer_type=offer_type,
+            page=page,
+            source_url=source_url,
+            house=house,
+            history_items=history_items,
+            raw_payload={
+                "body_len": len(body_text),
+                "items_count": len(history_items),
+            },
+        )
+
+    @staticmethod
+    def _parse_house_meta(body_text: str) -> ValuationHouseMeta:
+        """Extract house-level metadata from page body text."""
+        year_m = RE_YEAR_BUILT.search(body_text)
+        floors_m = RE_FLOORS.search(body_text)
+        ceiling_m = RE_CEILING.search(body_text)
+        objects_m = RE_TOTAL_OBJECTS.search(body_text)
+        return ValuationHouseMeta(
+            year_built=int(year_m.group(1)) if year_m else None,
+            total_floors=int(floors_m.group(1)) if floors_m else None,
+            house_type=parse_house_type(body_text),
+            ceiling_height=(float(ceiling_m.group(1).replace(",", ".")) if ceiling_m else None),
+            has_lift="Лифт" in body_text,
+            total_objects=int(objects_m.group(1)) if objects_m else None,
+            has_panorama="Панорама" in body_text,
+        )
+
+    def _parse_history_items(self, tree: HTMLParser, body_text: str) -> list[ValuationHistoryItem]:
+        """Extract historical offer items.
+
+        Strategy 1 (preferred, structured): each row at .OffersArchiveSearchOffers__row,
+        with 6 cells (.OffersArchiveSearchOffers__cell) in fixed order:
+          [0] area+rooms, [1] floor, [2] start_price+ppm2, [3] last_price+ppm2,
+          [4] publish_date+exposure, [5] status/removed_date.
+        Yields per-cell parsing — no chunked-text ambiguity.
+
+        Strategy 2 (last-resort fallback): legacy chunked-text scan around
+        DD.MM.YYYY anchors. Kept for the rare case Yandex changes class names;
+        triggers a logger.warning so we notice.
+        """
+        items: list[ValuationHistoryItem] = []
+        for row in tree.css(".OffersArchiveSearchOffers__row"):
+            item = self._parse_row_cells(row)
+            if item:
+                items.append(item)
+        if items:
+            return items
+        # Fallback (only if structured selector failed)
+        logger.warning(
+            "yandex_valuation: .OffersArchiveSearchOffers__row matched 0 items — "
+            "falling back to chunked-text scan"
+        )
+        return self._parse_items_from_chunked_text(body_text)
+
+    @classmethod
+    def _parse_row_cells(cls, row) -> ValuationHistoryItem | None:
+        """Parse one .OffersArchiveSearchOffers__row into a ValuationHistoryItem.
+
+        Cell layout is positional (no labels). Returns None if the row doesn't
+        match the expected 6-cell structure (defensive — Yandex may A/B-test).
+        """
+        cells = row.css(".OffersArchiveSearchOffers__cell")
+        if len(cells) < 5:
+            return None
+        cell_texts = [(c.text(strip=True) or "").replace("\xa0", " ") for c in cells]
+
+        # [0] photo (skipped — empty cell)
+        # [1] title — single cell contains area + rooms + floor jammed together,
+        # e.g. "48,5 м², 1-комнатная19 этаж" (real Yandex layout, 2026-05-24)
+        title_text = cell_texts[1] if len(cell_texts) > 1 else ""
+
+        area_m = RE_ITEM_AREA.search(title_text)
+        area_m2: float | None = float(area_m.group(1).replace(",", ".")) if area_m else None
+        # Sanity drop (belt-and-suspenders from PR #538)
+        if area_m2 is not None and (area_m2 > 10_000 or area_m2 <= 0):
+            area_m2 = None
+
+        rooms: int | None = None
+        if RE_ITEM_STUDIO.search(title_text):
+            rooms = 0
+        else:
+            rooms_m = RE_ITEM_ROOMS.search(title_text)
+            if rooms_m:
+                rooms = int(rooms_m.group(1))
+
+        floor_m = RE_ITEM_FLOOR.search(title_text)
+        floor: int | None = int(floor_m.group(1)) if floor_m else None
+
+        # [2] start price + ppm2 — "5,1 млн ₽105 155 ₽ за м²" (no separator)
+        start_price: int | None = None
+        start_ppm2: int | None = None
+        if len(cell_texts) > 2:
+            tokens = _RE_PRICE_TOKEN.findall(cell_texts[2])
+            if tokens:
+                start_price = parse_rub(tokens[0])
+            ppm2_tokens = _RE_PPM2_TOKEN.findall(cell_texts[2])
+            if ppm2_tokens:
+                start_ppm2 = parse_rub(ppm2_tokens[0])
+
+        # [3] last price + ppm2
+        last_price: int | None = None
+        last_ppm2: int | None = None
+        if len(cell_texts) > 3:
+            tokens = _RE_PRICE_TOKEN.findall(cell_texts[3])
+            if tokens:
+                last_price = parse_rub(tokens[0])
+            ppm2_tokens = _RE_PPM2_TOKEN.findall(cell_texts[3])
+            if ppm2_tokens:
+                last_ppm2 = parse_rub(ppm2_tokens[0])
+
+        # [4] publish_date + exposure ("23.10.2023В экспозиции 945 дней")
+        publish_date = None
+        exposure_days: int | None = None
+        if len(cell_texts) > 4:
+            publish_date = parse_dmy(cell_texts[4])
+            expo_m = RE_ITEM_EXPOSURE.search(cell_texts[4])
+            if expo_m:
+                exposure_days = int(expo_m.group(1))
+
+        # [5] status or removed_date
+        removed_date = None
+        status: str | None = None
+        if len(cell_texts) > 5:
+            last_cell = cell_texts[5]
+            status_m = RE_ITEM_STATUS.search(last_cell)
+            if status_m:
+                status = status_m.group(1)
+            removed_date = parse_dmy(last_cell)
+
+        # Sort dates chronologically (in case Yandex flips them — same fix as PR #541)
+        if publish_date and removed_date and removed_date < publish_date:
+            publish_date, removed_date = removed_date, publish_date
+
+        # Row is valid only if we got area OR start_price
+        if area_m2 is None and start_price is None:
+            return None
+
+        return ValuationHistoryItem(
+            area_m2=area_m2,
+            rooms=rooms,
+            floor=floor,
+            start_price=start_price,
+            start_price_per_m2=start_ppm2,
+            last_price=last_price,
+            last_price_per_m2=last_ppm2,
+            publish_date=publish_date,
+            removed_date=removed_date,
+            exposure_days=exposure_days,
+            status=status,
+        )
+
+    @staticmethod
+    def _parse_item_text(text: str) -> ValuationHistoryItem | None:
+        """Parse a single text block into a ValuationHistoryItem.
+
+        Returns None if neither area nor start_price can be extracted
+        (item is considered invalid/noise).
+        """
+        if not text or len(text) < 20:
+            return None
+
+        # area + rooms
+        area_m = RE_ITEM_AREA.search(text)
+        area_m2: float | None = float(area_m.group(1).replace(",", ".")) if area_m else None
+        # Sanity cap — Yandex page text sometimes concatenates digits across DOM
+        # boundaries (e.g. "2025\xa0106,7 м²" → 2_025_106.7). Flats over 10_000 m²
+        # are impossible; DB column is NUMERIC(8,2) which overflows at 10^6.
+        # Drop the value rather than block the whole save batch.
+        if area_m2 is not None and (area_m2 > 10_000 or area_m2 <= 0):
+            logger.warning(
+                "yandex_valuation: dropping nonsensical area_m2=%s from item chunk",
+                area_m2,
+            )
+            area_m2 = None
+
+        rooms: int | None = None
+        if RE_ITEM_STUDIO.search(text):
+            rooms = 0
+        else:
+            rooms_m = RE_ITEM_ROOMS.search(text)
+            if rooms_m:
+                rooms = int(rooms_m.group(1))
+
+        floor_m = RE_ITEM_FLOOR.search(text)
+        floor = int(floor_m.group(1)) if floor_m else None
+
+        # Prices — find first 2 price tokens (start, last)
+        price_tokens = _RE_PRICE_TOKEN.findall(text)
+        start_price = parse_rub(price_tokens[0]) if len(price_tokens) >= 1 else None
+        last_price = parse_rub(price_tokens[1]) if len(price_tokens) >= 2 else None
+
+        ppm2_tokens = _RE_PPM2_TOKEN.findall(text)
+        start_ppm2 = parse_rub(ppm2_tokens[0]) if len(ppm2_tokens) >= 1 else None
+        last_ppm2 = parse_rub(ppm2_tokens[1]) if len(ppm2_tokens) >= 2 else None
+
+        # Extract ALL DD.MM.YYYY dates: first → publish_date, second → removed_date
+        date_matches = list(re.finditer(r"\d{2}\.\d{2}\.\d{4}", text))
+        dates_parsed: list[date] = []
+        for m in date_matches:
+            d = parse_dmy(m.group(0))
+            if d is not None:
+                dates_parsed.append(d)
+        # Sort dates chronologically — chunked-text scan returns them in page-text
+        # order, but semantically publish_date is earliest and removed_date is
+        # latest. Without this, ~1% of rows on prod show removed < publish.
+        if dates_parsed:
+            dates_sorted = sorted(d for d in dates_parsed if d is not None)
+            publish_date = dates_sorted[0] if dates_sorted else None
+            removed_date = dates_sorted[1] if len(dates_sorted) >= 2 else None
+        else:
+            publish_date = None
+            removed_date = None
+        expo_m = RE_ITEM_EXPOSURE.search(text)
+        exposure_days = int(expo_m.group(1)) if expo_m else None
+
+        status_m = RE_ITEM_STATUS.search(text)
+        status = status_m.group(1) if status_m else None
+
+        # Item is valid only if we got at least area or price
+        if area_m2 is None and start_price is None:
+            return None
+
+        return ValuationHistoryItem(
+            area_m2=area_m2,
+            rooms=rooms,
+            floor=floor,
+            start_price=start_price,
+            start_price_per_m2=start_ppm2,
+            last_price=last_price,
+            last_price_per_m2=last_ppm2,
+            publish_date=publish_date,
+            removed_date=removed_date,
+            exposure_days=exposure_days,
+            status=status,
+        )
+
+    @classmethod
+    def _parse_items_from_chunked_text(cls, body_text: str) -> list[ValuationHistoryItem]:
+        """Fallback: split body text into chunks around DD.MM.YYYY dates and parse each chunk.
+
+        Window: 200 chars before + 100 chars after each date match.
+        Deduplicates by (publish_date, area_m2, floor).
+        Caps output at 30 items per page to avoid runaway extraction.
+        """
+        items: list[ValuationHistoryItem] = []
+        for m in re.finditer(r"\d{2}\.\d{2}\.\d{4}", body_text):
+            start = max(0, m.start() - 200)
+            end = min(len(body_text), m.end() + 100)
+            chunk = body_text[start:end]
+            item = cls._parse_item_text(chunk)
+            if item:
+                items.append(item)
+
+        # Dedup by (publish_date, area_m2, floor)
+        seen: set[tuple[Any, Any, Any]] = set()
+        deduped: list[ValuationHistoryItem] = []
+        for item in items:
+            key = (item.publish_date, item.area_m2, item.floor)
+            if key not in seen:
+                seen.add(key)
+                deduped.append(item)
+        return deduped[:30]