698ef4f003
Replaces tradein.cad_buildings manual snapshot (36k rows, frozen 2026-05-22) with live postgres_fdw foreign table reading gendesign.v_tradein_cad_buildings directly. Also reverts PR #492 HTTP-based cadastral.py — superseded by FDW. Architecture: - gendesign DB: new role tradein_fdw_reader + flat view v_tradein_cad_buildings (EKB-only slice of cad_buildings with lat/lon flattened from geom) - networks: gendesign-postgres added to gendesign_shared (alias); tradein-postgres added to gendesign_shared for FDW connect - tradein DB: postgres_fdw extension + FOREIGN TABLE gendesign_cad_buildings - tradein backend: startup hook creates/refreshes USER MAPPING with password from env GENDESIGN_FDW_PASSWORD (password rotation handled via restart) - geocoder.py: cadastral primary for forward + reverse + suggest; Yandex/Nominatim fallback. reverse_geocode wraps Nominatim in try/except — no more HTTPStatusError → 500. - house_metadata.py and trade_in.py admin stats switched to foreign table - DROP TABLE cad_buildings in tradein (legacy snapshot removed entirely) - import-cadastre.sh deleted (no manual sync needed) Fixes: - /trade-in/api/v1/geocode/reverse 500 (Nominatim ban → no fallback) - estimate confidence_explanation=address_not_geocoded for addresses in our cadastre (e.g. Хохрякова 81) that Nominatim doesn't return Deploy ordering: main migration 100_tradein_fdw_role.sql adds role+view first (strict deploy.yml). Tradein next deploy applies 060_postgres_fdw_extension.sql and 061_drop_legacy_cad_buildings.sql (idempotent, errors ignored). Tradein backend startup creates USER MAPPING when env var present. Verify post-deploy with: docker exec tradein-postgres psql -U tradein -d tradein -c \ "SELECT count(*) FROM gendesign_cad_buildings" # expect ~36k EKB buildings.
739 lines
26 KiB
Python
739 lines
26 KiB
Python
"""Trade-In Estimator — endpoints (TI-1 mock + TI-2 PDF).
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MOCK implementation: returns realistic ЕКБ price bands by rooms/floor/repair.
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TODO TI-1b: заменить _mock_estimate() на реальный SQL aggregation из
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objective_lots + rosreestr_deals после OBJ-1/2 merge.
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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 random
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from datetime import UTC, datetime, timedelta
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from typing import Annotated
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from uuid import UUID, uuid4
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from fastapi import APIRouter, Depends, File, HTTPException, Response, UploadFile
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from sqlalchemy import text
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from sqlalchemy.orm import Session
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from app.core.db import get_db
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from app.schemas.trade_in import (
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AggregatedEstimate,
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AnalogLot,
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HouseInfoForEstimate,
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IMVBenchmarkResponse,
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PhotoMeta,
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TradeInEstimateInput,
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)
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from app.services.exporters.trade_in_pdf import generate_trade_in_pdf
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logger = logging.getLogger(__name__)
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router = APIRouter()
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# ЕКБ-адреса для фейковых аналогов (реальные улицы центра)
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_EKB_STREETS = [
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"ул. Малышева",
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"ул. Куйбышева",
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"ул. 8 Марта",
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"ул. Белинского",
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"пр. Ленина",
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"ул. Толмачёва",
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"ул. Радищева",
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"ул. Мамина-Сибиряка",
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"ул. Луначарского",
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"ул. Первомайская",
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]
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# Базовые ценовые диапазоны по комнатности (ЕКБ, 2026)
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_PRICE_BANDS: dict[int, dict[str, int | float | str]] = {
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0: { # студия ~25 м²
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"median": 6_500_000,
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"low": 5_800_000,
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"high": 7_500_000,
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"ppm2": 260_000,
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"ref_area": 25.0,
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},
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1: { # 1к ~40 м²
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"median": 9_000_000,
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"low": 8_000_000,
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"high": 10_500_000,
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"ppm2": 225_000,
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"ref_area": 40.0,
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},
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2: { # 2к ~60 м²
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"median": 12_500_000,
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"low": 11_000_000,
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"high": 14_000_000,
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"ppm2": 208_000,
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"ref_area": 60.0,
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},
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3: { # 3к ~80 м²
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"median": 17_000_000,
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"low": 15_000_000,
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"high": 19_000_000,
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"ppm2": 213_000,
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"ref_area": 80.0,
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},
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}
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def _floor_factor(floor: int, total_floors: int) -> float:
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"""±5% поправка за этаж: 1й и последний этаж снижают цену."""
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if floor == 1:
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return 0.95
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if floor == total_floors:
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return 0.97
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return 1.0
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def _repair_factor(repair_state: str | None) -> float:
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"""±10% поправка за состояние отделки."""
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factors = {
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"needs_repair": 0.90,
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"standard": 1.00,
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"good": 1.05,
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"excellent": 1.10,
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}
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return factors.get(repair_state or "standard", 1.0)
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def _confidence(rooms: int) -> str:
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if 1 <= rooms <= 3:
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return "high"
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return "medium"
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def _gen_analogs(
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rooms: int,
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area_m2: float,
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base_ppm2: int,
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n: int,
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*,
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is_listing: bool,
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) -> list[AnalogLot]:
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"""Генерирует список фейковых аналогов (объявления или сделки)."""
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rng = random.Random(42 + rooms + n)
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result: list[AnalogLot] = []
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today = datetime.now(tz=UTC).date()
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for i in range(n):
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street = _EKB_STREETS[i % len(_EKB_STREETS)]
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building_no = rng.randint(1, 120)
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apt_no = rng.randint(1, 300)
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addr = f"г. Екатеринбург, {street}, {building_no}, кв. {apt_no}"
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area_jitter = area_m2 * rng.uniform(0.85, 1.15)
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ppm2_jitter = int(base_ppm2 * rng.uniform(0.90, 1.10))
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price = int(area_jitter * ppm2_jitter)
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floor_val = rng.randint(2, 16)
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total_fl = rng.randint(floor_val, 20)
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if is_listing:
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dom = rng.randint(5, 120)
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listing_dt = today - timedelta(days=dom)
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else:
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dom = rng.randint(10, 60)
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listing_dt = today - timedelta(days=rng.randint(30, 365))
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result.append(
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AnalogLot(
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address=addr,
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area_m2=round(area_jitter, 1),
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rooms=rooms if rooms > 0 else 0,
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floor=floor_val,
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total_floors=total_fl,
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price_rub=price,
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price_per_m2=ppm2_jitter,
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listing_date=listing_dt,
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days_on_market=dom,
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photo_url=None,
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)
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)
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return result
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def _mock_estimate(payload: TradeInEstimateInput) -> AggregatedEstimate:
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"""Возвращает mock-оценку на основе диапазонов ЕКБ 2026.
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Логика:
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- Берём базовый band по rooms (0-3+).
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- Масштабируем на фактическую площадь относительно референсной.
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- Применяем поправку за этаж (±5%) и отделку (±10%).
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- Генерируем 7-10 аналогов (листинги) и 3-5 actual_deals.
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"""
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rooms_key = min(payload.rooms, 3) # 4к+ → диапазон 3к
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band = _PRICE_BANDS[rooms_key]
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# Масштаб по площади
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ref_area: float = band["ref_area"] # type: ignore[assignment]
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area_scale = payload.area_m2 / ref_area
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ff = _floor_factor(payload.floor, payload.total_floors)
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rf = _repair_factor(payload.repair_state)
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combined = area_scale * ff * rf
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median = int(band["median"] * combined) # type: ignore[operator]
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low = int(band["low"] * combined) # type: ignore[operator]
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high = int(band["high"] * combined) # type: ignore[operator]
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ppm2 = int(band["ppm2"] * ff * rf) # type: ignore[operator]
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n_analogs = random.randint(7, 10)
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n_deals = random.randint(3, 5)
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analogs = _gen_analogs(rooms_key, payload.area_m2, ppm2, n_analogs, is_listing=True)
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actual_deals = _gen_analogs(
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rooms_key, payload.area_m2, int(ppm2 * 0.93), n_deals, is_listing=False
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)
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now = datetime.now(tz=UTC)
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return AggregatedEstimate(
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estimate_id=uuid4(),
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median_price_rub=median,
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range_low_rub=low,
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range_high_rub=high,
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median_price_per_m2=ppm2,
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confidence=_confidence(payload.rooms),
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n_analogs=n_analogs + n_deals,
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period_months=24,
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analogs=analogs,
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actual_deals=actual_deals,
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expires_at=now + timedelta(hours=24),
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)
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@router.post("/estimate", response_model=AggregatedEstimate)
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async def estimate(
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payload: TradeInEstimateInput,
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db: Annotated[Session, Depends(get_db)],
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) -> AggregatedEstimate:
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"""Реальная оценка через SQL aggregation поверх listings + deals.
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1. Geocode address → lat/lon
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2. PostGIS ST_DWithin радиус 800м (или 2км fallback)
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3. Tukey IQR outlier filter
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4. Median + Q1 + Q3 + confidence с explanation
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"""
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from app.services.estimator import estimate_quality
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return await estimate_quality(payload, db)
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# OLD MOCK PATH — оставлен как fallback для отладки; не вызывается из router.
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def _estimate_legacy_mock(
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payload: TradeInEstimateInput,
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db: Annotated[Session, Depends(get_db)],
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) -> AggregatedEstimate:
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"""Старая mock-реализация. НЕ используется в роутере, удалить когда стабилизируем новый estimator."""
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result = _mock_estimate(payload)
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analogs_json = json.dumps(
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[a.model_dump(mode="json") for a in result.analogs],
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ensure_ascii=False,
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)
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deals_json = json.dumps(
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[a.model_dump(mode="json") for a in result.actual_deals],
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ensure_ascii=False,
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)
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db.execute(
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text(
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"""
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INSERT INTO trade_in_estimates (
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id, address, area_m2, rooms, floor, total_floors,
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year_built, house_type, repair_state, has_balcony,
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median_price, range_low, range_high, median_price_per_m2,
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confidence, n_analogs, analogs, actual_deals, expires_at
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) VALUES (
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CAST(:id AS uuid),
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:address, :area_m2, :rooms, :floor, :total_floors,
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:year_built, :house_type, :repair_state, :has_balcony,
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:median_price, :range_low, :range_high, :median_price_per_m2,
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:confidence, :n_analogs,
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CAST(:analogs AS jsonb),
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CAST(:actual_deals AS jsonb),
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:expires_at
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)
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"""
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),
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{
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"id": str(result.estimate_id),
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"address": payload.address,
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"area_m2": payload.area_m2,
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"rooms": payload.rooms,
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"floor": payload.floor,
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"total_floors": payload.total_floors,
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"year_built": payload.year_built,
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"house_type": payload.house_type,
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"repair_state": payload.repair_state,
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"has_balcony": payload.has_balcony,
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"median_price": result.median_price_rub,
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"range_low": result.range_low_rub,
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"range_high": result.range_high_rub,
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"median_price_per_m2": result.median_price_per_m2,
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"confidence": result.confidence,
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"n_analogs": result.n_analogs,
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"analogs": analogs_json,
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"actual_deals": deals_json,
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"expires_at": result.expires_at,
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},
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)
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db.commit()
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logger.info(
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"trade_in estimate saved id=%s rooms=%d area=%.1f confidence=%s",
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result.estimate_id,
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payload.rooms,
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payload.area_m2,
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result.confidence,
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)
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return result
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@router.get("/estimate/{estimate_id}", response_model=AggregatedEstimate)
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def get_estimate(
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estimate_id: UUID,
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db: Annotated[Session, Depends(get_db)],
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) -> AggregatedEstimate:
|
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"""Получить сохранённую оценку по UUID (для генерации PDF).
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Возвращает 404 если оценка не найдена или TTL истёк.
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"""
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row = db.execute(
|
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text(
|
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"""
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SELECT id, median_price, range_low, range_high, median_price_per_m2,
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confidence, confidence_explanation, n_analogs,
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analogs, actual_deals, sources_used, data_freshness_minutes,
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expires_at, address, lat, lon,
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area_m2, rooms, floor, total_floors,
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year_built, house_type, repair_state, has_balcony
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FROM trade_in_estimates
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WHERE id = CAST(:id AS uuid)
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AND expires_at > NOW()
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"""
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),
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{"id": str(estimate_id)},
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).fetchone()
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if row is None:
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raise HTTPException(status_code=404, detail="estimate not found or expired")
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analogs = [AnalogLot(**a) for a in (row.analogs or [])]
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actual_deals = [AnalogLot(**a) for a in (row.actual_deals or [])]
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# ВАЖНО: возвращаем ПОЛНЫЙ набор полей. Раньше эндпоинт отдавал огрызок
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# без sources_used / confidence_explanation / координат — и при открытии
|
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# оценки по ссылке (?id=) карточка источников пустела до «0/7».
|
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return AggregatedEstimate(
|
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estimate_id=row.id,
|
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median_price_rub=row.median_price,
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range_low_rub=row.range_low,
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||
range_high_rub=row.range_high,
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median_price_per_m2=row.median_price_per_m2,
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confidence=row.confidence,
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confidence_explanation=row.confidence_explanation,
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n_analogs=row.n_analogs,
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period_months=12,
|
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analogs=analogs,
|
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actual_deals=actual_deals,
|
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expires_at=row.expires_at,
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target_address=row.address,
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target_lat=row.lat,
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target_lon=row.lon,
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sources_used=row.sources_used or [],
|
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data_freshness_minutes=row.data_freshness_minutes,
|
||
area_m2=row.area_m2,
|
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rooms=row.rooms,
|
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floor=row.floor,
|
||
total_floors=row.total_floors,
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||
year_built=row.year_built,
|
||
house_type=row.house_type,
|
||
repair_state=row.repair_state,
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||
has_balcony=row.has_balcony,
|
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)
|
||
|
||
|
||
@router.get("/estimate/{estimate_id}/pdf")
|
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def estimate_pdf(
|
||
estimate_id: UUID,
|
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db: Annotated[Session, Depends(get_db)],
|
||
brand: str | None = None,
|
||
) -> Response:
|
||
"""Скачать 4-страничный PDF-отчёт для оценки trade-in.
|
||
|
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Возвращает application/pdf attachment.
|
||
404 — оценка не найдена.
|
||
410 — оценка просрочена (TTL 24ч).
|
||
"""
|
||
row = db.execute(
|
||
text(
|
||
"""
|
||
SELECT id, median_price, range_low, range_high, median_price_per_m2,
|
||
confidence, confidence_explanation, n_analogs,
|
||
analogs, actual_deals, sources_used, data_freshness_minutes,
|
||
expires_at,
|
||
address, lat, lon, area_m2, rooms, floor, total_floors,
|
||
year_built, house_type, repair_state, has_balcony
|
||
FROM trade_in_estimates
|
||
WHERE id = CAST(:id AS uuid)
|
||
"""
|
||
),
|
||
{"id": str(estimate_id)},
|
||
).fetchone()
|
||
|
||
if row is None:
|
||
raise HTTPException(status_code=404, detail="estimate not found")
|
||
|
||
if row.expires_at.replace(tzinfo=UTC) < datetime.now(tz=UTC):
|
||
raise HTTPException(status_code=410, detail="estimate expired (24h TTL)")
|
||
|
||
analogs = [AnalogLot(**a) for a in (row.analogs or [])]
|
||
actual_deals = [AnalogLot(**a) for a in (row.actual_deals or [])]
|
||
|
||
estimate = AggregatedEstimate(
|
||
estimate_id=row.id,
|
||
median_price_rub=row.median_price,
|
||
range_low_rub=row.range_low,
|
||
range_high_rub=row.range_high,
|
||
median_price_per_m2=row.median_price_per_m2,
|
||
confidence=row.confidence,
|
||
confidence_explanation=row.confidence_explanation,
|
||
n_analogs=row.n_analogs,
|
||
period_months=24,
|
||
analogs=analogs,
|
||
actual_deals=actual_deals,
|
||
expires_at=row.expires_at,
|
||
target_address=row.address,
|
||
target_lat=row.lat,
|
||
target_lon=row.lon,
|
||
sources_used=row.sources_used or [],
|
||
data_freshness_minutes=row.data_freshness_minutes,
|
||
)
|
||
input_snapshot = {
|
||
"address": row.address,
|
||
"area_m2": row.area_m2,
|
||
"rooms": row.rooms,
|
||
"floor": row.floor,
|
||
"total_floors": row.total_floors,
|
||
"year_built": row.year_built,
|
||
"house_type": row.house_type,
|
||
"repair_state": row.repair_state,
|
||
"has_balcony": row.has_balcony,
|
||
}
|
||
|
||
from app.services.brand import get_brand as _resolve_brand
|
||
brand_obj = _resolve_brand(brand, db)
|
||
pdf_bytes = generate_trade_in_pdf(estimate, input_snapshot, brand=brand_obj)
|
||
filename = f"trade-in-{brand_obj.slug}-{estimate_id}.pdf"
|
||
logger.info(
|
||
"PDF generated estimate_id=%s brand=%s size=%d",
|
||
estimate_id, brand_obj.slug, len(pdf_bytes),
|
||
)
|
||
return Response(
|
||
content=pdf_bytes,
|
||
media_type="application/pdf",
|
||
headers={"Content-Disposition": f'attachment; filename="{filename}"'},
|
||
)
|
||
|
||
|
||
# ── Фото квартиры (#394) ─────────────────────────────────────────────────────
|
||
_MAX_PHOTO_BYTES = 10 * 1024 * 1024 # 10 МБ на фото
|
||
_MAX_PHOTOS_PER_ESTIMATE = 12
|
||
_ALLOWED_IMAGE_TYPES = {"image/jpeg", "image/png", "image/webp", "image/heic"}
|
||
|
||
|
||
@router.post("/estimate/{estimate_id}/photos", response_model=PhotoMeta)
|
||
async def upload_photo(
|
||
estimate_id: UUID,
|
||
db: Annotated[Session, Depends(get_db)],
|
||
file: Annotated[UploadFile, File()],
|
||
) -> PhotoMeta:
|
||
"""Загрузить фото квартиры к оценке (#394). Хранение в estimate_photos (bytea)."""
|
||
estimate = db.execute(
|
||
text("SELECT 1 FROM trade_in_estimates WHERE id = CAST(:id AS uuid)"),
|
||
{"id": str(estimate_id)},
|
||
).fetchone()
|
||
if estimate is None:
|
||
raise HTTPException(status_code=404, detail="estimate not found")
|
||
|
||
ctype = (file.content_type or "").lower()
|
||
if ctype not in _ALLOWED_IMAGE_TYPES:
|
||
raise HTTPException(
|
||
status_code=415, detail=f"unsupported content-type: {ctype or 'unknown'}"
|
||
)
|
||
|
||
count = db.execute(
|
||
text("SELECT count(*) FROM estimate_photos WHERE estimate_id = CAST(:id AS uuid)"),
|
||
{"id": str(estimate_id)},
|
||
).scalar_one()
|
||
if count >= _MAX_PHOTOS_PER_ESTIMATE:
|
||
raise HTTPException(
|
||
status_code=409, detail=f"photo limit reached ({_MAX_PHOTOS_PER_ESTIMATE})"
|
||
)
|
||
|
||
content = await file.read()
|
||
if not content:
|
||
raise HTTPException(status_code=400, detail="empty file")
|
||
if len(content) > _MAX_PHOTO_BYTES:
|
||
raise HTTPException(status_code=413, detail="file too large (max 10 MB)")
|
||
|
||
row = db.execute(
|
||
text(
|
||
"""
|
||
INSERT INTO estimate_photos
|
||
(estimate_id, filename, content_type, content, size_bytes)
|
||
VALUES (CAST(:eid AS uuid), :fn, :ct, :content, :sz)
|
||
RETURNING id, filename, content_type, size_bytes, uploaded_at
|
||
"""
|
||
),
|
||
{
|
||
"eid": str(estimate_id),
|
||
"fn": file.filename,
|
||
"ct": ctype,
|
||
"content": content,
|
||
"sz": len(content),
|
||
},
|
||
).mappings().fetchone()
|
||
db.commit()
|
||
logger.info(
|
||
"photo uploaded: estimate=%s photo=%s size=%d", estimate_id, row["id"], len(content)
|
||
)
|
||
return PhotoMeta(**row)
|
||
|
||
|
||
@router.get("/estimate/{estimate_id}/photos", response_model=list[PhotoMeta])
|
||
def list_photos(
|
||
estimate_id: UUID,
|
||
db: Annotated[Session, Depends(get_db)],
|
||
) -> list[PhotoMeta]:
|
||
"""Список фото оценки — метаданные, без содержимого (#394)."""
|
||
rows = db.execute(
|
||
text(
|
||
"""
|
||
SELECT id, filename, content_type, size_bytes, uploaded_at
|
||
FROM estimate_photos
|
||
WHERE estimate_id = CAST(:id AS uuid)
|
||
ORDER BY uploaded_at
|
||
"""
|
||
),
|
||
{"id": str(estimate_id)},
|
||
).mappings().all()
|
||
return [PhotoMeta(**r) for r in rows]
|
||
|
||
|
||
@router.get("/estimate/{estimate_id}/photos/{photo_id}")
|
||
def get_photo(
|
||
estimate_id: UUID,
|
||
photo_id: UUID,
|
||
db: Annotated[Session, Depends(get_db)],
|
||
) -> Response:
|
||
"""Отдать содержимое фото — image bytes (#394)."""
|
||
row = db.execute(
|
||
text(
|
||
"""
|
||
SELECT content, content_type
|
||
FROM estimate_photos
|
||
WHERE id = CAST(:pid AS uuid) AND estimate_id = CAST(:eid AS uuid)
|
||
"""
|
||
),
|
||
{"pid": str(photo_id), "eid": str(estimate_id)},
|
||
).fetchone()
|
||
if row is None:
|
||
raise HTTPException(status_code=404, detail="photo not found")
|
||
return Response(
|
||
content=bytes(row.content),
|
||
media_type=row.content_type,
|
||
headers={"Cache-Control": "private, max-age=3600"},
|
||
)
|
||
|
||
|
||
# ── История и кэш (#399) ─────────────────────────────────────────────────────
|
||
@router.get("/history")
|
||
def estimate_history(
|
||
db: Annotated[Session, Depends(get_db)],
|
||
limit: int = 50,
|
||
) -> list[dict[str, object]]:
|
||
"""История оценок (#399) — последние N записей trade_in_estimates."""
|
||
rows = db.execute(
|
||
text(
|
||
"""
|
||
SELECT id, address, rooms, area_m2, median_price,
|
||
confidence, n_analogs, created_at
|
||
FROM trade_in_estimates
|
||
ORDER BY created_at DESC
|
||
LIMIT :limit
|
||
"""
|
||
),
|
||
{"limit": min(max(limit, 1), 200)},
|
||
).mappings().all()
|
||
return [dict(r) for r in rows]
|
||
|
||
|
||
@router.get("/cache-stats")
|
||
def cache_stats(db: Annotated[Session, Depends(get_db)]) -> dict[str, object]:
|
||
"""Состояние данных и кэшей (#399) — для страницы «Кэш»."""
|
||
row = db.execute(
|
||
text(
|
||
"""
|
||
SELECT
|
||
(SELECT count(*) FROM geocode_cache) AS geocode_cache,
|
||
(SELECT count(*) FROM geocode_cache WHERE expires_at > NOW())
|
||
AS geocode_cache_fresh,
|
||
(SELECT count(*) FROM listings WHERE is_active) AS listings_active,
|
||
(SELECT max(scraped_at) FROM listings) AS listings_last_scraped,
|
||
(SELECT count(*) FROM deals) AS deals,
|
||
(SELECT count(*) FROM gendesign_cad_buildings) AS cad_buildings,
|
||
(SELECT count(*) FROM house_metadata) AS house_metadata,
|
||
(SELECT count(*) FROM trade_in_estimates) AS estimates_total
|
||
"""
|
||
)
|
||
).mappings().fetchone()
|
||
return dict(row) if row else {}
|
||
|
||
|
||
# ── Stage 4a: house info + IMV benchmark для UI ───────────────────────────────
|
||
|
||
|
||
@router.get("/estimate/{estimate_id}/houses", response_model=list[HouseInfoForEstimate])
|
||
def get_estimate_houses(
|
||
estimate_id: UUID,
|
||
db: Annotated[Session, Depends(get_db)],
|
||
) -> list[HouseInfoForEstimate]:
|
||
"""House(s) информация для estimate.
|
||
|
||
Логика: estimate сохранён с target_address + lat/lon. Ищем houses которые:
|
||
- либо лежат в радиусе 500м от target (PostGIS)
|
||
- либо linked через listings.house_id_fk у аналогов оценки
|
||
|
||
Возвращаем top-5 ближайших домов с их characteristics из houses table.
|
||
Пустой список если нет matches.
|
||
"""
|
||
# Сначала достанем target_lat/lon из estimate
|
||
target = db.execute(
|
||
text(
|
||
"""
|
||
SELECT lat, lon FROM trade_in_estimates
|
||
WHERE id = CAST(:id AS uuid)
|
||
"""
|
||
),
|
||
{"id": str(estimate_id)},
|
||
).fetchone()
|
||
if target is None:
|
||
raise HTTPException(status_code=404, detail="estimate not found")
|
||
if target.lat is None or target.lon is None:
|
||
return [] # нет координат → не можем искать дома
|
||
|
||
rows = db.execute(
|
||
text(
|
||
"""
|
||
SELECT
|
||
id AS house_id, ext_house_id, address, short_address,
|
||
lat, lon, year_built, total_floors, house_type,
|
||
passenger_elevators, cargo_elevators,
|
||
has_concierge, closed_yard, has_playground, parking_type,
|
||
developer_name, rating, reviews_count,
|
||
COALESCE(raw_characteristics, '[]'::jsonb) AS raw_characteristics,
|
||
ST_Distance(geom::geography, ST_MakePoint(:lon, :lat)::geography) AS distance_m
|
||
FROM houses
|
||
WHERE source = 'avito'
|
||
AND geom IS NOT NULL
|
||
AND ST_DWithin(geom::geography, ST_MakePoint(:lon, :lat)::geography, 500)
|
||
ORDER BY distance_m
|
||
LIMIT 5
|
||
"""
|
||
),
|
||
{"lat": target.lat, "lon": target.lon},
|
||
).mappings().all()
|
||
|
||
return [
|
||
HouseInfoForEstimate(**{k: v for k, v in row.items() if k != "distance_m"})
|
||
for row in rows
|
||
]
|
||
|
||
|
||
@router.get("/estimate/{estimate_id}/imv-benchmark", response_model=IMVBenchmarkResponse)
|
||
def get_estimate_imv_benchmark(
|
||
estimate_id: UUID,
|
||
db: Annotated[Session, Depends(get_db)],
|
||
) -> IMVBenchmarkResponse:
|
||
"""Avito IMV benchmark для estimate (для UI badge «наша 6.4М · Avito 6.29М»).
|
||
|
||
Источники lookup:
|
||
1. avito_imv_evaluations WHERE estimate_id = :id (если linked в estimator)
|
||
2. Если не linked — fallback: most recent IMV для same address (TTL 24h)
|
||
"""
|
||
# Сначала пытаемся найти directly linked
|
||
row = db.execute(
|
||
text(
|
||
"""
|
||
SELECT cache_key, recommended_price, lower_price, higher_price,
|
||
market_count, fetched_at
|
||
FROM avito_imv_evaluations
|
||
WHERE estimate_id = CAST(:id AS uuid)
|
||
ORDER BY fetched_at DESC
|
||
LIMIT 1
|
||
"""
|
||
),
|
||
{"id": str(estimate_id)},
|
||
).fetchone()
|
||
|
||
if row is None:
|
||
# Fallback: same address за 24h (на случай если link не успел)
|
||
est = db.execute(
|
||
text(
|
||
"""
|
||
SELECT address FROM trade_in_estimates
|
||
WHERE id = CAST(:id AS uuid)
|
||
"""
|
||
),
|
||
{"id": str(estimate_id)},
|
||
).fetchone()
|
||
if est is None:
|
||
raise HTTPException(status_code=404, detail="estimate not found")
|
||
if est.address:
|
||
row = db.execute(
|
||
text(
|
||
"""
|
||
SELECT cache_key, recommended_price, lower_price, higher_price,
|
||
market_count, fetched_at
|
||
FROM avito_imv_evaluations
|
||
WHERE address = :address
|
||
AND fetched_at > NOW() - INTERVAL '24 hours'
|
||
ORDER BY fetched_at DESC
|
||
LIMIT 1
|
||
"""
|
||
),
|
||
{"address": est.address},
|
||
).fetchone()
|
||
|
||
if row is None:
|
||
return IMVBenchmarkResponse(available=False)
|
||
|
||
# Get our_median_price для compare
|
||
our = db.execute(
|
||
text(
|
||
"""
|
||
SELECT median_price FROM trade_in_estimates
|
||
WHERE id = CAST(:id AS uuid)
|
||
"""
|
||
),
|
||
{"id": str(estimate_id)},
|
||
).fetchone()
|
||
our_median = our.median_price if our else None
|
||
diff_pct = None
|
||
if our_median and row.recommended_price:
|
||
diff_pct = round((our_median - row.recommended_price) / row.recommended_price * 100, 1)
|
||
|
||
return IMVBenchmarkResponse(
|
||
available=True,
|
||
cache_key=row.cache_key,
|
||
recommended_price=row.recommended_price,
|
||
lower_price=row.lower_price,
|
||
higher_price=row.higher_price,
|
||
market_count=row.market_count,
|
||
fetched_at=row.fetched_at,
|
||
our_median_price=our_median,
|
||
diff_pct=diff_pct,
|
||
)
|