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Co-authored-by: bot-backend <bot-backend@gendsgn.local> Co-committed-by: bot-backend <bot-backend@gendsgn.local>
620 lines
24 KiB
Python
620 lines
24 KiB
Python
"""Yandex.Недвижимость scraper (realty.yandex.ru) — DOM-based SERP parser.
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History: Yandex SSR used to embed full state in `<script id="initial_state_script">`.
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As of 2026-05, the state is chunked + evaporates after hydration. This version
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scrapes the rendered DOM via selectolax + helpers from yandex_helpers.py.
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Area extraction: DOM concat-text is empty pre-hydration (~82% NULL). Fix: extract
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area from the page-level embedded JSON state (script[id="initial_state_script"] or
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application/json script), keyed by offerId. DOM regex is kept as fallback.
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Transport (T4): curl_cffi AsyncSession(impersonate="chrome120") — Chrome TLS
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fingerprint bypasses Yandex anti-bot gate that returns captcha/shell HTML for plain
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httpx. Optional cookies loaded from YANDEX_COOKIES_FILE env path.
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Combos (T5): fetch_around_multi_room supports rooms × price-range combinations to
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work around Yandex SERP ~575-card cap per query. Full combos → ~4000 unique listings.
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URL pattern (path-based, no geo radius):
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https://realty.yandex.ru/{city}/kupit/kvartira/[{room-slug}/]vtorichniy-rynok/?...
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"""
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from __future__ import annotations
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import json
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import logging
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import re
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from datetime import date # noqa: F401 (used in type hints / future helpers)
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from pathlib import Path
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from typing import Any
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from urllib.parse import urlencode
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from curl_cffi.requests import AsyncSession as _CurlCffiSession
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from selectolax.parser import HTMLParser, Node
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from app.services.scraper_settings import get_scraper_delay
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from app.services.scrapers.base import BaseScraper, ScrapedLot
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from app.services.scrapers.repair_state_normalizer import infer_repair_state_from_text
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from app.services.scrapers.yandex_helpers import (
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RE_FLOOR,
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RE_JK_ID,
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RE_OFFER_ID,
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RE_PPM2,
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RE_PRICE,
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RE_TITLE_AREA,
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RE_TITLE_ROOMS,
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parse_listing_date,
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parse_rub,
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)
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logger = logging.getLogger(__name__)
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DEFAULT_CITY = "ekaterinburg"
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MAX_PAGES = 3
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PHOTO_DOMAIN = "avatars.mds.yandex"
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PHOTO_SIZE_FROM = "app_snippet_small"
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PHOTO_SIZE_TO = "main"
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# Address container wraps street link + house number text node.
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# Class is hashed but always starts with "AddressWithGeoLinks__addressContainer".
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ADDRESS_CONTAINER_SELECTOR = '[class*="AddressWithGeoLinks__addressContainer"]'
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_RE_WS = re.compile(r"\s+")
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# Yandex SERP embeds offer data in a <script id="initial_state_script"> as JSON,
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# or (since 2026-05) in <script type="application/json" ...> chunks.
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# We look for these selectors in priority order.
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_STATE_SCRIPT_SELECTORS = [
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'script[id="initial_state_script"]',
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'script[type="application/json"]',
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]
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# Area field candidates in a Yandex offer object (tried in order).
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_AREA_FIELDS = ("totalArea", "area", "spaceTotal", "spaceAll", "squareTotal")
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# Captcha detection markers (checked in first 5000 chars, lowercased).
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_CAPTCHA_MARKERS = ("/showcaptcha", "smartcaptcha", "checkboxcaptcha")
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# Path segments for room buckets (Yandex URL canonical slugs).
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# Key matches the rooms label used in combos; value = URL path segment.
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ROOM_PATH: dict[str, str] = {
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"studio": "studiya",
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"1": "odnokomnatnaya",
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"2": "dvuhkomnatnaya",
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"3": "trehkomnatnaya",
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"4+": "4-i-bolee",
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}
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# Default price ranges (price_min, price_max) in rubles. None = open-ended.
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DEFAULT_PRICE_RANGES: list[tuple[int | None, int | None]] = [
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(None, 5_000_000),
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(5_000_000, 7_000_000),
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(7_000_000, 10_000_000),
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(10_000_000, 15_000_000),
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(15_000_000, 25_000_000),
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(25_000_000, None),
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]
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def _load_cookies_from_file(path: str | None) -> dict[str, str]:
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"""Load Yandex cookies from JSON file path (Netscape/browser export format).
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Format: [{name: str, value: str, ...}, ...].
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Returns empty dict if path is None, missing, or unparseable — not a failure.
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"""
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if not path:
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return {}
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p = Path(path)
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if not p.exists():
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logger.warning("yandex cookies file not found: %s — running without cookies", path)
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return {}
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try:
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raw = json.loads(p.read_text(encoding="utf-8"))
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result = {
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item["name"]: item["value"]
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for item in raw
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if isinstance(item, dict) and "name" in item and "value" in item
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}
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logger.info("yandex: loaded %d cookies from %s", len(result), path)
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return result
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except Exception:
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logger.warning("yandex: failed to parse cookies file %s — running without", path)
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return {}
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def _is_captcha(html: str) -> bool:
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"""Return True if the response looks like a Yandex captcha page."""
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head = html[:5000].lower()
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return any(m in head for m in _CAPTCHA_MARKERS) or "докажите, что вы не робот" in head
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def _extract_offer_areas_from_state(html: str) -> dict[str, float]:
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"""Extract {offer_id: area_m2} map from Yandex SERP embedded JSON state.
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Tries each known script selector, parses JSON, then traverses known
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offer-array paths looking for offer objects with an id + area field.
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Returns empty dict if state is absent or unparseable.
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"""
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tree = HTMLParser(html)
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candidates: list[str] = []
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for selector in _STATE_SCRIPT_SELECTORS:
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for node in tree.css(selector):
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text = node.text() or ""
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text = text.strip()
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if text:
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candidates.append(text)
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result: dict[str, float] = {}
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for text in candidates:
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try:
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state = json.loads(text)
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except (json.JSONDecodeError, ValueError):
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continue
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if not isinstance(state, dict):
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continue
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_collect_areas_from_state(state, result)
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if result:
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break # успешно извлекли из первого валидного blob'а
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return result
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def _collect_areas_from_state(state: dict[str, Any], out: dict[str, float]) -> None:
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"""Walk known Yandex state paths to find offer objects and extract area.
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Known paths (tried in order):
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- state["offers"] (flat list)
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- state["pageData"]["offers"] (SERP v2)
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- state["listing"]["offers"] (SERP v3)
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- state["serpData"]["items"] (SERP v4 chunks)
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"""
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offer_lists: list[Any] = []
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for path in (
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["offers"],
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["pageData", "offers"],
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["listing", "offers"],
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["serpData", "items"],
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):
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node: Any = state
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for key in path:
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if not isinstance(node, dict):
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node = None
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break
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node = node.get(key)
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if isinstance(node, list):
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offer_lists.append(node)
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for offer_list in offer_lists:
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for offer in offer_list:
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if not isinstance(offer, dict):
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continue
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# Flatten one level of nesting (some Yandex shapes wrap the offer)
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inner = offer.get("offer") or offer
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if not isinstance(inner, dict):
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continue
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oid = inner.get("offerId") or inner.get("id")
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if oid is None:
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continue
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area = _read_area_field(inner)
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if area is not None:
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out[str(oid)] = area
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def _read_area_field(offer: dict[str, Any]) -> float | None:
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"""Try known field names to read area (м²) from a Yandex offer dict."""
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for field in _AREA_FIELDS:
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val = offer.get(field)
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if val is None:
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continue
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# Some fields are nested dicts: {"value": 52.0, "unit": "SQM"}
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if isinstance(val, dict):
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val = val.get("value")
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if val is not None:
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try:
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result = float(val)
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if result > 0:
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return result
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except (TypeError, ValueError):
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continue
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return None
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class YandexRealtyScraper(BaseScraper):
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name = "yandex"
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base_url = "https://realty.yandex.ru"
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request_delay_sec = 5.0
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def __init__(self, city: str = DEFAULT_CITY) -> None:
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super().__init__()
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self.city = city
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# Load global Yandex delay from DB at instantiation
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self.request_delay_sec = get_scraper_delay(self.name)
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self._cffi_session: _CurlCffiSession | None = None
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self._cookies: dict[str, str] = {}
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async def __aenter__(self) -> YandexRealtyScraper: # type: ignore[override]
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"""Override: Chrome120 TLS impersonation bypasses Yandex anti-bot gate.
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Plain httpx returns captcha/shell-HTML on datacenter IPs.
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Sibling pattern: yandex_valuation.py.
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Cookies loaded from YANDEX_COOKIES_FILE settings path (optional).
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"""
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# Deferred import to avoid circular / settings-at-import-time issues
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from app.core.config import settings
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self._cookies = _load_cookies_from_file(settings.yandex_cookies_file)
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# Mobile proxy wiring (#806 follow-up): Yandex blocks datacenter IPs with
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# captcha/shell HTML even with Chrome TLS fingerprint. Route via mobile proxy.
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# proxy=None → curl_cffi ходит напрямую (dev без прокси — не падаем).
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_proxy_url = settings.scraper_proxy_url
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_proxies = {"http": _proxy_url, "https": _proxy_url} if _proxy_url else None
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self._cffi_session = _CurlCffiSession(
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impersonate="chrome120",
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cookies=self._cookies or {},
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proxies=_proxies,
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headers={
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"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
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"Accept-Language": "ru-RU,ru;q=0.9,en;q=0.8",
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"Accept-Encoding": "gzip, deflate, br",
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"Connection": "keep-alive",
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"Upgrade-Insecure-Requests": "1",
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},
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)
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return self
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async def __aexit__(self, *args: object) -> None: # type: ignore[override]
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if self._cffi_session is not None:
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await self._cffi_session.close()
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self._cffi_session = None
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async def _http_get(self, url: str, **kwargs: object) -> object: # type: ignore[override]
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"""curl_cffi-based GET with Chrome120 impersonation.
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Returns curl_cffi Response (compatible API: .status_code, .text).
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Caller must check status_code; no automatic retry (BaseScraper.retry
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decorator is per-method and not inherited cleanly when overridden).
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"""
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if self._cffi_session is None:
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raise RuntimeError("YandexRealtyScraper must be used as async context manager")
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kwargs.setdefault("timeout", 30)
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return await self._cffi_session.get(url, **kwargs)
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async def fetch_around(
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self,
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lat: float,
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lon: float,
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radius_m: int = 1000,
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page: int = 0,
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rooms: str | None = None,
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price_min: int | None = None,
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price_max: int | None = None,
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) -> list[ScrapedLot]:
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"""Fetch ONE page of SERP cards.
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lat/lon/radius_m ignored (Yandex uses path-based vtorichka URL);
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kept for BaseScraper compat + logging.
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rooms: room-bucket slug (one of ROOM_PATH keys) or None = all rooms.
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price_min/price_max: price filters in rubles (None = open-ended).
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"""
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url = self._build_url(page=page, rooms=rooms, price_min=price_min, price_max=price_max)
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try:
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response = await self._http_get(url)
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except Exception:
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logger.exception("yandex serp fetch failed: %s", url)
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return []
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if response.status_code != 200:
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logger.warning("yandex serp returned %d for %s", response.status_code, url)
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return []
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# NBSP → space: parse_rub() buggy on \xa0 in capture groups → price=None (T4)
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html = response.text.replace("\xa0", " ")
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if _is_captcha(html):
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logger.warning(
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"yandex serp: captcha detected on page=%d url=%s — returning empty",
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page,
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url,
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)
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return []
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lots = self._parse_html(html, page=page)
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logger.info(
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"yandex serp page=%d city=%s rooms=%s price=[%s-%s]: %d cards",
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page,
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self.city,
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rooms or "all",
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price_min,
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price_max,
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len(lots),
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)
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await self.sleep_between_requests()
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return lots
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async def fetch_around_multi_room(
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self,
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lat: float,
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lon: float,
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radius_m: int = 1000,
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max_pages: int = MAX_PAGES,
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rooms_list: list[str] | None = None,
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price_ranges: list[tuple[int | None, int | None]] | None = None,
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**_legacy_kwargs: Any, # swallow old callers' kwargs
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) -> list[ScrapedLot]:
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"""Fetch SERP via rooms × price-range combos to bypass SERP ~575-card cap.
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When rooms_list/price_ranges are provided (T5 combos mode), iterates all
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(room, price_min, price_max) combinations, each up to max_pages pages,
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deduplicating by source_id/source_url across combos.
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When both are None (legacy mode), falls back to single citywide sweep
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(original behaviour — up to max_pages pages, no filtering).
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"""
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seen: dict[str, ScrapedLot] = {}
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if rooms_list is None and price_ranges is None:
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# Legacy / citywide mode — no combos
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combos: list[tuple[str | None, int | None, int | None]] = [(None, None, None)]
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else:
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r_list = rooms_list or list(ROOM_PATH.keys())
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p_ranges = price_ranges or DEFAULT_PRICE_RANGES
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combos = [(r, lo, hi) for r in r_list for lo, hi in p_ranges]
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for rooms, price_min, price_max in combos:
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combo_label = _combo_label(rooms, price_min, price_max)
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for page in range(max_pages):
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lots = await self.fetch_around(
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lat,
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lon,
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radius_m,
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page=page,
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rooms=rooms,
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price_min=price_min,
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price_max=price_max,
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)
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if not lots:
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logger.debug(
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"yandex combos [%s] page=%d: empty — stopping combo",
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combo_label,
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page,
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)
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break
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for lot in lots:
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key = lot.source_id or lot.source_url
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if key and key not in seen:
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seen[key] = lot
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logger.info(
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"yandex serp aggregate: %d unique lots (city=%s, %d combos)",
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len(seen),
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self.city,
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len(combos),
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)
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return list(seen.values())
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def _build_url(
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self,
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page: int = 0,
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rooms: str | None = None,
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price_min: int | None = None,
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price_max: int | None = None,
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) -> str:
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"""Build Yandex SERP URL.
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rooms: key from ROOM_PATH for path-based room bucket; None = all rooms.
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price_min/price_max: optional price filters in rubles.
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newFlat=NO_DEAL is added when any price filter is set — prevents Yandex
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from canonicalizing away /vtorichniy-rynok/ for some room slugs.
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"""
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if rooms and rooms in ROOM_PATH:
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path = f"/{self.city}/kupit/kvartira/{ROOM_PATH[rooms]}/vtorichniy-rynok/"
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else:
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path = f"/{self.city}/kupit/kvartira/vtorichniy-rynok/"
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base = f"{self.base_url}{path}"
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params: dict[str, str | int] = {}
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if price_min is not None:
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params["priceMin"] = price_min
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if price_max is not None:
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params["priceMax"] = price_max
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if price_min is not None or price_max is not None:
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# Guarantee vtorichka — Yandex sometimes drops /vtorichniy-rynok/ on canonicalize
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params["newFlat"] = "NO_DEAL"
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if page > 0:
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params["page"] = page
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if params:
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return f"{base}?{urlencode(params)}"
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return base
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def _parse_html(self, html: str, page: int = 0) -> list[ScrapedLot]:
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# NBSP-fix applied by caller (fetch_around) before _parse_html;
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# also applied here as a safety net for direct callers (tests, scripts).
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html = html.replace("\xa0", " ")
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# Extract offer-level area from embedded JSON state first (covers ~82% of
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# cards where DOM text is empty pre-hydration). Falls back to DOM regex per card.
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state_areas = _extract_offer_areas_from_state(html)
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if state_areas:
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logger.debug("yandex serp: state areas extracted for %d offers", len(state_areas))
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tree = HTMLParser(html)
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cards = tree.css('[data-test="OffersSerpItem"]')
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lots: list[ScrapedLot] = []
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for card in cards:
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lot = self._card_to_lot(card, page=page, state_areas=state_areas)
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if lot is not None:
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lots.append(lot)
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return lots
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def _card_to_lot(
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self,
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card: Node,
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page: int = 0,
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state_areas: dict[str, float] | None = None,
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) -> ScrapedLot | None:
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try:
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# offer_id — required
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offer_link = card.css_first('a[href^="/offer/"]')
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if offer_link is None:
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return None
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href = offer_link.attributes.get("href", "")
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id_match = RE_OFFER_ID.search(href)
|
||
if not id_match:
|
||
return None
|
||
offer_id = id_match.group(1)
|
||
|
||
text = card.text(strip=True)
|
||
|
||
# Price — required (ScrapedLot.price_rub > 0)
|
||
price_m = RE_PRICE.search(text)
|
||
price_rub = parse_rub(price_m.group(1)) if price_m else None
|
||
if not price_rub or price_rub <= 0:
|
||
return None
|
||
|
||
# Area: prefer JSON state (covers pre-hydration DOM where text is empty),
|
||
# fall back to DOM regex.
|
||
area_m2: float | None = (state_areas or {}).get(offer_id)
|
||
if area_m2 is None:
|
||
area_m = RE_TITLE_AREA.search(text)
|
||
area_m2 = float(area_m.group(1).replace(",", ".")) if area_m else None
|
||
|
||
rooms = self._parse_rooms(text)
|
||
|
||
floor_m = RE_FLOOR.search(text)
|
||
floor = int(floor_m.group(1)) if floor_m else None
|
||
total_floors = int(floor_m.group(2)) if floor_m else None
|
||
|
||
ppm2_m = RE_PPM2.search(text)
|
||
price_per_m2 = parse_rub(ppm2_m.group(1)) if ppm2_m else None
|
||
|
||
bargain = "торг" in text.lower()
|
||
listing_date = parse_listing_date(text)
|
||
|
||
# Repair state — инференс из текста карточки (#622). Yandex SERP не
|
||
# отдаёт структурного поля ремонта; берём сигнал из текста сниппета.
|
||
repair_state = infer_repair_state_from_text(text)
|
||
|
||
# Address — prefer the full address container (street + house number);
|
||
# fall back to the street aggregator link (street name only) if absent.
|
||
# See _extract_address for details.
|
||
address = self._extract_address(card)
|
||
|
||
# Photos
|
||
photo_urls = self._extract_photos(card)
|
||
|
||
# Newbuilding linkage
|
||
house_source: str | None = None
|
||
house_ext_id: str | None = None
|
||
house_url: str | None = None
|
||
nb_link = card.css_first('a[href*="/kupit/novostrojka/"]')
|
||
if nb_link is not None:
|
||
nb_href = nb_link.attributes.get("href", "")
|
||
nb_match = RE_JK_ID.search(nb_href)
|
||
if nb_match:
|
||
house_source = "yandex_realty_nb"
|
||
house_ext_id = nb_match.group(2)
|
||
house_url = (
|
||
nb_href
|
||
if nb_href.startswith("http")
|
||
else f"https://realty.yandex.ru{nb_href}"
|
||
)
|
||
|
||
return ScrapedLot(
|
||
source=self.name,
|
||
source_url=f"https://realty.yandex.ru/offer/{offer_id}/",
|
||
source_id=offer_id,
|
||
address=address,
|
||
lat=None,
|
||
lon=None,
|
||
rooms=rooms,
|
||
area_m2=area_m2,
|
||
floor=floor,
|
||
total_floors=total_floors,
|
||
repair_state=repair_state,
|
||
price_rub=price_rub,
|
||
price_per_m2=price_per_m2,
|
||
bargain_allowed=bargain,
|
||
listing_date=listing_date,
|
||
photo_urls=photo_urls,
|
||
house_source=house_source,
|
||
house_ext_id=house_ext_id,
|
||
house_url=house_url,
|
||
listing_segment="vtorichka",
|
||
raw_payload={
|
||
"card_text": text[:1000],
|
||
"page": page,
|
||
"city": self.city,
|
||
},
|
||
)
|
||
except Exception:
|
||
logger.exception("yandex card parse failed (page=%d)", page)
|
||
return None
|
||
|
||
@staticmethod
|
||
def _extract_address(card: Node) -> str | None:
|
||
"""Extract full address (street + house number) from a SERP card.
|
||
|
||
Yandex renders the address inside a container like:
|
||
<div class="AddressWithGeoLinks__addressContainer--XXXX">
|
||
<a href="/.../kupit/kvartira/st-...">улица Энгельса</a>, 38
|
||
</div>
|
||
|
||
The street-only `<a>` tag was used historically — it gave just the
|
||
street name and broke forward-geocoding precision (street-level only,
|
||
not exact house). Reading the container's text yields the full
|
||
"<street>, <house>" pair, including letter/fraction suffixes
|
||
(e.g. "2В", "2/2", "14к2"). Some cards prefix district/city info
|
||
(e.g. "Берёзовский, Александровский проспект, 5А") — that's still
|
||
a valid, more specific address for the geocoder.
|
||
|
||
Falls back to the street-only link when the container is missing
|
||
(older layout / unexpected DOM) so we never regress to NULL.
|
||
"""
|
||
addr_div = card.css_first(ADDRESS_CONTAINER_SELECTOR)
|
||
if addr_div is not None:
|
||
# text(strip=False) preserves spaces between text nodes and
|
||
# the anchor's text (selectolax with strip=True collapses them
|
||
# and yields "улица Энгельса,38" instead of "улица Энгельса, 38").
|
||
raw = addr_div.text(strip=False) or ""
|
||
normalized = _RE_WS.sub(" ", raw).strip().strip(",").strip()
|
||
if normalized:
|
||
return normalized
|
||
street_link = card.css_first('a[href*="/kupit/kvartira/st-"]')
|
||
return street_link.text(strip=True) if street_link else None
|
||
|
||
@staticmethod
|
||
def _parse_rooms(text: str) -> int | None:
|
||
m = RE_TITLE_ROOMS.search(text)
|
||
if not m:
|
||
return None
|
||
if m.group(2): # studio
|
||
return 0
|
||
if m.group(1): # numbered
|
||
try:
|
||
return int(m.group(1))
|
||
except ValueError:
|
||
return None
|
||
return None
|
||
|
||
@staticmethod
|
||
def _extract_photos(card: Node) -> list[str]:
|
||
urls: list[str] = []
|
||
for img in card.css("img"):
|
||
src = img.attributes.get("src", "") or ""
|
||
if PHOTO_DOMAIN in src:
|
||
urls.append(src.replace(PHOTO_SIZE_FROM, PHOTO_SIZE_TO))
|
||
if len(urls) >= 5:
|
||
break
|
||
return urls
|
||
|
||
|
||
def _combo_label(
|
||
rooms: str | None,
|
||
price_min: int | None,
|
||
price_max: int | None,
|
||
) -> str:
|
||
"""Human-readable label for a (rooms, price_min, price_max) combo."""
|
||
r = rooms or "all-rooms"
|
||
if price_min is None and price_max is None:
|
||
return f"{r}/any-price"
|
||
lo = f"{price_min // 1_000_000}M" if price_min is not None else "0"
|
||
hi = f"{price_max // 1_000_000}M" if price_max is not None else "inf"
|
||
return f"{r}/{lo}-{hi}"
|