chore(tradein): remove dead mock-fallback code from trade_in.py (#521)
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This commit is contained in:
lekss361 2026-05-24 13:11:13 +00:00
parent 7cc7fafeeb
commit d9c6b1bd01

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@ -1,18 +1,14 @@
"""Trade-In Estimator — endpoints (TI-1 mock + TI-2 PDF).
"""Trade-In Estimator — endpoints (TI-2 PDF, photos, history).
MOCK implementation: returns realistic ЕКБ price bands by rooms/floor/repair.
TODO TI-1b: заменить _mock_estimate() на реальный SQL aggregation из
objective_lots + rosreestr_deals после OBJ-1/2 merge.
Реальная оценка делается через app.services.estimator.estimate_quality().
"""
from __future__ import annotations
import json
import logging
import random
from datetime import UTC, datetime, timedelta
from datetime import UTC, datetime
from typing import Annotated
from uuid import UUID, uuid4
from uuid import UUID
from fastapi import APIRouter, Depends, File, HTTPException, Response, UploadFile
from sqlalchemy import text
@ -34,176 +30,6 @@ logger = logging.getLogger(__name__)
router = APIRouter()
# ЕКБ-адреса для фейковых аналогов (реальные улицы центра)
_EKB_STREETS = [
"ул. Малышева",
"ул. Куйбышева",
"ул. 8 Марта",
"ул. Белинского",
"пр. Ленина",
"ул. Толмачёва",
"ул. Радищева",
"ул. Мамина-Сибиряка",
"ул. Луначарского",
"ул. Первомайская",
]
# Базовые ценовые диапазоны по комнатности (ЕКБ, 2026)
_PRICE_BANDS: dict[int, dict[str, int | float | str]] = {
0: { # студия ~25 м²
"median": 6_500_000,
"low": 5_800_000,
"high": 7_500_000,
"ppm2": 260_000,
"ref_area": 25.0,
},
1: { # 1к ~40 м²
"median": 9_000_000,
"low": 8_000_000,
"high": 10_500_000,
"ppm2": 225_000,
"ref_area": 40.0,
},
2: { # 2к ~60 м²
"median": 12_500_000,
"low": 11_000_000,
"high": 14_000_000,
"ppm2": 208_000,
"ref_area": 60.0,
},
3: { # 3к ~80 м²
"median": 17_000_000,
"low": 15_000_000,
"high": 19_000_000,
"ppm2": 213_000,
"ref_area": 80.0,
},
}
def _floor_factor(floor: int, total_floors: int) -> float:
"""±5% поправка за этаж: 1й и последний этаж снижают цену."""
if floor == 1:
return 0.95
if floor == total_floors:
return 0.97
return 1.0
def _repair_factor(repair_state: str | None) -> float:
"""±10% поправка за состояние отделки."""
factors = {
"needs_repair": 0.90,
"standard": 1.00,
"good": 1.05,
"excellent": 1.10,
}
return factors.get(repair_state or "standard", 1.0)
def _confidence(rooms: int) -> str:
if 1 <= rooms <= 3:
return "high"
return "medium"
def _gen_analogs(
rooms: int,
area_m2: float,
base_ppm2: int,
n: int,
*,
is_listing: bool,
) -> list[AnalogLot]:
"""Генерирует список фейковых аналогов (объявления или сделки)."""
rng = random.Random(42 + rooms + n)
result: list[AnalogLot] = []
today = datetime.now(tz=UTC).date()
for i in range(n):
street = _EKB_STREETS[i % len(_EKB_STREETS)]
building_no = rng.randint(1, 120)
apt_no = rng.randint(1, 300)
addr = f"г. Екатеринбург, {street}, {building_no}, кв. {apt_no}"
area_jitter = area_m2 * rng.uniform(0.85, 1.15)
ppm2_jitter = int(base_ppm2 * rng.uniform(0.90, 1.10))
price = int(area_jitter * ppm2_jitter)
floor_val = rng.randint(2, 16)
total_fl = rng.randint(floor_val, 20)
if is_listing:
dom = rng.randint(5, 120)
listing_dt = today - timedelta(days=dom)
else:
dom = rng.randint(10, 60)
listing_dt = today - timedelta(days=rng.randint(30, 365))
result.append(
AnalogLot(
address=addr,
area_m2=round(area_jitter, 1),
rooms=rooms if rooms > 0 else 0,
floor=floor_val,
total_floors=total_fl,
price_rub=price,
price_per_m2=ppm2_jitter,
listing_date=listing_dt,
days_on_market=dom,
photo_url=None,
)
)
return result
def _mock_estimate(payload: TradeInEstimateInput) -> AggregatedEstimate:
"""Возвращает mock-оценку на основе диапазонов ЕКБ 2026.
Логика:
- Берём базовый band по rooms (0-3+).
- Масштабируем на фактическую площадь относительно референсной.
- Применяем поправку за этаж (±5%) и отделку (±10%).
- Генерируем 7-10 аналогов (листинги) и 3-5 actual_deals.
"""
rooms_key = min(payload.rooms, 3) # 4к+ → диапазон 3к
band = _PRICE_BANDS[rooms_key]
# Масштаб по площади
ref_area: float = band["ref_area"] # type: ignore[assignment]
area_scale = payload.area_m2 / ref_area
ff = _floor_factor(payload.floor, payload.total_floors)
rf = _repair_factor(payload.repair_state)
combined = area_scale * ff * rf
median = int(band["median"] * combined) # type: ignore[operator]
low = int(band["low"] * combined) # type: ignore[operator]
high = int(band["high"] * combined) # type: ignore[operator]
ppm2 = int(band["ppm2"] * ff * rf) # type: ignore[operator]
n_analogs = random.randint(7, 10)
n_deals = random.randint(3, 5)
analogs = _gen_analogs(rooms_key, payload.area_m2, ppm2, n_analogs, is_listing=True)
actual_deals = _gen_analogs(
rooms_key, payload.area_m2, int(ppm2 * 0.93), n_deals, is_listing=False
)
now = datetime.now(tz=UTC)
return AggregatedEstimate(
estimate_id=uuid4(),
median_price_rub=median,
range_low_rub=low,
range_high_rub=high,
median_price_per_m2=ppm2,
confidence=_confidence(payload.rooms),
n_analogs=n_analogs + n_deals,
period_months=24,
analogs=analogs,
actual_deals=actual_deals,
expires_at=now + timedelta(hours=24),
)
@router.post("/estimate", response_model=AggregatedEstimate)
async def estimate(
@ -221,77 +47,6 @@ async def estimate(
return await estimate_quality(payload, db)
# OLD MOCK PATH — оставлен как fallback для отладки; не вызывается из router.
def _estimate_legacy_mock(
payload: TradeInEstimateInput,
db: Annotated[Session, Depends(get_db)],
) -> AggregatedEstimate:
"""Старая mock-реализация. НЕ используется в роутере, удалить когда стабилизируем новый estimator."""
result = _mock_estimate(payload)
analogs_json = json.dumps(
[a.model_dump(mode="json") for a in result.analogs],
ensure_ascii=False,
)
deals_json = json.dumps(
[a.model_dump(mode="json") for a in result.actual_deals],
ensure_ascii=False,
)
db.execute(
text(
"""
INSERT INTO trade_in_estimates (
id, address, area_m2, rooms, floor, total_floors,
year_built, house_type, repair_state, has_balcony,
median_price, range_low, range_high, median_price_per_m2,
confidence, n_analogs, analogs, actual_deals, expires_at
) VALUES (
CAST(:id AS uuid),
:address, :area_m2, :rooms, :floor, :total_floors,
:year_built, :house_type, :repair_state, :has_balcony,
:median_price, :range_low, :range_high, :median_price_per_m2,
:confidence, :n_analogs,
CAST(:analogs AS jsonb),
CAST(:actual_deals AS jsonb),
:expires_at
)
"""
),
{
"id": str(result.estimate_id),
"address": payload.address,
"area_m2": payload.area_m2,
"rooms": payload.rooms,
"floor": payload.floor,
"total_floors": payload.total_floors,
"year_built": payload.year_built,
"house_type": payload.house_type,
"repair_state": payload.repair_state,
"has_balcony": payload.has_balcony,
"median_price": result.median_price_rub,
"range_low": result.range_low_rub,
"range_high": result.range_high_rub,
"median_price_per_m2": result.median_price_per_m2,
"confidence": result.confidence,
"n_analogs": result.n_analogs,
"analogs": analogs_json,
"actual_deals": deals_json,
"expires_at": result.expires_at,
},
)
db.commit()
logger.info(
"trade_in estimate saved id=%s rooms=%d area=%.1f confidence=%s",
result.estimate_id,
payload.rooms,
payload.area_m2,
result.confidence,
)
return result
@router.get("/estimate/{estimate_id}", response_model=AggregatedEstimate)
def get_estimate(
estimate_id: UUID,