feat(tradein): estimator computes additive expected_sold price (#648 S3)
Estimator ADDITIVELY derives expected_sold from asking-median × per-rooms asking_to_sold_ratio (table from #648 S2 / migration 080). Headline asking median, ranges, confidence and actual_deals are UNCHANGED. Graceful: missing/ empty ratio table → expected_sold fields None, estimate still returns 200 (ratio lookup rolls back the shared session on error so the subsequent INSERT isn't poisoned — mirrors sibling cache helpers). - estimator: _get_asking_sold_ratio(db, rooms) cached lookup (per-rooms → global -1 fallback → None, try/except+rollback), applied after repair-coef. - schema: 6 optional expected_sold_* / ratio fields on AggregatedEstimate. - api: rehydrate the new columns in GET /estimate/{id} + /pdf reopen SELECTs and both constructors (the documented reopen-path bug). - migration 081: ADD COLUMN IF NOT EXISTS for the persisted subset. - tests: 10 new (lookup/apply/graceful) + fix pre-existing test_estimator_ source_quota 2→3 tuple unpack of _fetch_analogs (was RED on main).
This commit is contained in:
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c7b9565cd6
commit
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8 changed files with 493 additions and 7 deletions
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@ -99,7 +99,10 @@ def get_estimate(
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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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canonical_address, house_cadnum, house_fias_id,
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dadata_qc_geo, dadata_metro
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dadata_qc_geo, dadata_metro,
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expected_sold_price, expected_sold_range_low,
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expected_sold_range_high, expected_sold_per_m2,
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asking_to_sold_ratio, ratio_basis
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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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@ -140,6 +143,16 @@ def get_estimate(
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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,
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# #648 Stage 3 — sold-correction columns rehydrated for shared-link reopen.
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# (numeric ratio → float for the Pydantic field.)
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expected_sold_price_rub=row.expected_sold_price,
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expected_sold_range_low_rub=row.expected_sold_range_low,
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expected_sold_range_high_rub=row.expected_sold_range_high,
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expected_sold_per_m2=row.expected_sold_per_m2,
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asking_to_sold_ratio=(
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float(row.asking_to_sold_ratio) if row.asking_to_sold_ratio is not None else None
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),
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ratio_basis=row.ratio_basis,
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area_m2=row.area_m2,
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rooms=row.rooms,
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floor=row.floor,
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@ -178,7 +191,10 @@ def estimate_pdf(
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address, lat, lon, area_m2, rooms, floor, total_floors,
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year_built, house_type, repair_state, has_balcony,
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canonical_address, house_cadnum, house_fias_id,
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dadata_qc_geo, dadata_metro
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dadata_qc_geo, dadata_metro,
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expected_sold_price, expected_sold_range_low,
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expected_sold_range_high, expected_sold_per_m2,
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asking_to_sold_ratio, ratio_basis
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FROM trade_in_estimates
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WHERE id = CAST(:id AS uuid)
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"""
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@ -215,6 +231,15 @@ def estimate_pdf(
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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,
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# #648 Stage 3 — sold-correction columns rehydrated so the PDF carries them.
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expected_sold_price_rub=row.expected_sold_price,
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expected_sold_range_low_rub=row.expected_sold_range_low,
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expected_sold_range_high_rub=row.expected_sold_range_high,
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expected_sold_per_m2=row.expected_sold_per_m2,
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asking_to_sold_ratio=(
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float(row.asking_to_sold_ratio) if row.asking_to_sold_ratio is not None else None
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),
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ratio_basis=row.ratio_basis,
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canonical_address=row.canonical_address,
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house_cadnum=row.house_cadnum,
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house_fias_id=row.house_fias_id,
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@ -94,6 +94,18 @@ class AggregatedEstimate(BaseModel):
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data_freshness_minutes: int | None = None # сколько минут назад был самый свежий парсинг
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est_days_on_market: int | None = None # прогноз срока продажи (медиана по аналогам)
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cian_valuation: CianValuationSummary | None = None
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# ── Asking→sold correction (#648 Stage 3) — PURELY ADDITIVE ──
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# Headline median_price_rub/range_*/median_price_per_m2 остаются ASKING (активные
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# объявления). Эти параллельные expected_sold_* = asking × per-rooms ratio
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# (asking_to_sold_ratios, migration 080) — релевантная для выкупа цена сделки.
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# Backtest (#648 Stage 1) показал, что коррекция убирает bias asking-медианы
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# +20% → −4% на held-out ДКП. None если ratio-таблицы нет / бакет пуст (graceful).
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expected_sold_price_rub: int | None = None
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expected_sold_range_low_rub: int | None = None
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expected_sold_range_high_rub: int | None = None
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expected_sold_per_m2: int | None = None
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asking_to_sold_ratio: float | None = None # =sold/asking, ~0.72–0.93
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ratio_basis: str | None = None # 'per_rooms' | 'global_fallback'
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# ── DaData enrichment (PR Q1) — on-demand для target адреса ──
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# canonical_address — DaData-нормализованная форма (с улицей в short form).
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# house_cadnum — кадастровый номер ДОМА (для будущего matching Росреестра).
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@ -24,6 +24,7 @@ import json
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import logging
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import math
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import re
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import time
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from datetime import UTC, datetime, timedelta
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from typing import Any
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from uuid import uuid4
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@ -158,6 +159,81 @@ def _repair_coefficient(repair_state: str | None) -> float:
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return _REPAIR_COEF.get(repair_state, 1.0)
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# ── Asking→sold correction ratio lookup (#648 Stage 3) ──────────────────────
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# Таблица asking_to_sold_ratios (migration 080) хранит per-rooms коэффициент
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# ratio = median(SOLD ppm²) / median(ASKING ppm²) (~0.72–0.93). Estimator
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# домножает ASKING-медиану на этот ratio, получая параллельную expected_sold
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# цену (релевантную для выкупа). Headline asking-медиана НЕ меняется.
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#
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# Кэш: tiny in-process dict {bucket: (ratio, basis, fetched_monotonic)} с TTL.
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# Ratio дрейфует медленно (refresh-задача раз в сутки, Stage 4), поэтому 300с
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# TTL более чем достаточно и снимает по SELECT'у с каждой оценки. Single-worker
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# uvicorn/scheduler — GIL делает dict-доступ atomic enough (без явного lock).
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_ASKING_SOLD_RATIO_CACHE_TTL_S = 300.0
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_asking_sold_ratio_cache: dict[int, tuple[float | None, str | None, float]] = {}
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def _get_asking_sold_ratio(db: Session, rooms: int | None) -> tuple[float | None, str | None]:
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"""Возвращает (ratio, basis) asking→sold для бакета комнат.
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bucket = min(max(rooms or 0, 0), 4). Сначала ищем per-rooms строку
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(district=''), при отсутствии — global fallback (rooms_bucket=-1). Если
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таблицы нет / пуста / любая ошибка → (None, None), НЕ raise (graceful:
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estimator продолжает без sold-коррекции, headline asking-медиана отдаётся).
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Кэшируется на бакет с TTL _ASKING_SOLD_RATIO_CACHE_TTL_S.
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"""
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bucket = min(max(rooms or 0, 0), 4)
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cached = _asking_sold_ratio_cache.get(bucket)
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if cached is not None:
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ratio, basis, fetched = cached
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if (time.monotonic() - fetched) < _ASKING_SOLD_RATIO_CACHE_TTL_S:
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return ratio, basis
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ratio: float | None = None
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basis: str | None = None
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try:
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row = db.execute(
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text(
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"""
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SELECT ratio, basis FROM asking_to_sold_ratios
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WHERE rooms_bucket = CAST(:b AS int) AND district = ''
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"""
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),
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{"b": bucket},
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).fetchone()
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if row is None:
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# Бакет тонкий (n<30 при seed'е) или отсутствует → global fallback (-1).
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row = db.execute(
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text(
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"""
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SELECT ratio, basis FROM asking_to_sold_ratios
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WHERE rooms_bucket = -1 AND district = ''
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"""
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),
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).fetchone()
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if row is not None and row.ratio is not None:
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ratio = float(row.ratio)
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basis = row.basis
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except Exception as exc:
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# Таблицы может не быть на свежей/старой БД (миграция 080 не применена),
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# либо транзакция в сбойном состоянии — graceful: без sold-коррекции.
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# ОБЯЗАТЕЛЬНО rollback (как в sibling-helper'ах _get_or_fetch_*): неудачный
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# SELECT помечает транзакцию InFailedSqlTransaction, и без отката следующий
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# statement (_fetch_deals) упал бы → 500. Откат держит shared session чистой
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# для последующего INSERT. rollback тоже guard'им (соединение могло умереть).
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logger.debug("asking_to_sold_ratio lookup skipped (graceful): %s", exc)
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try:
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db.rollback()
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except Exception:
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pass
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ratio, basis = None, None
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_asking_sold_ratio_cache[bucket] = (ratio, basis, time.monotonic())
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return ratio, basis
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# ── Avito IMV cache lookup (Stage 3) ────────────────────────────────────────
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IMV_CACHE_TTL_HOURS = 24
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@ -775,6 +851,28 @@ async def estimate_quality(payload: TradeInEstimateInput, db: Session) -> Aggreg
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f"({_REPAIR_LABEL.get(payload.repair_state, '')} {pct:+d}%)."
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)
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# 4c. Asking→sold коррекция (#648 Stage 3) — PURELY ADDITIVE. Headline
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# median_price/range_*/median_ppm2 (ASKING активных объявлений) НЕ трогаем;
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# вычисляем ПАРАЛЛЕЛЬНУЮ expected_sold цену = asking × per-rooms ratio
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# (asking_to_sold_ratios, migration 080). Это релевантная для выкупа цена
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# сделки (backtest #648 S1: bias asking-медианы +20% → −4% на held-out ДКП).
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# NOTE: actual_deals (#564) остаётся ИНФОРМАЦИОННЫМ и НЕ подмешивается в
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# headline — sold-коррекция здесь единственный sold-сигнал (без double-count).
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asking_to_sold_ratio, ratio_basis = _get_asking_sold_ratio(db, payload.rooms)
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if asking_to_sold_ratio is not None and listings_clean:
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expected_sold_per_m2: int | None = round(median_ppm2 * asking_to_sold_ratio)
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expected_sold_price: int | None = round(median_price * asking_to_sold_ratio)
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expected_sold_range_low: int | None = round(range_low * asking_to_sold_ratio)
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expected_sold_range_high: int | None = round(range_high * asking_to_sold_ratio)
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else:
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expected_sold_per_m2 = None
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expected_sold_price = None
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expected_sold_range_low = None
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expected_sold_range_high = None
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# Не было ratio (нет таблицы/бакета) — не вводим в заблуждение пустым basis.
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if asking_to_sold_ratio is None:
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ratio_basis = None
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confidence, explanation = _compute_confidence(
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n_analogs,
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median_ppm2,
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@ -924,6 +1022,9 @@ async def estimate_quality(payload: TradeInEstimateInput, db: Session) -> Aggreg
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sources_used, data_freshness_minutes,
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canonical_address, house_cadnum, house_fias_id,
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dadata_qc_geo, dadata_qc_house, dadata_metro,
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expected_sold_price, expected_sold_range_low,
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expected_sold_range_high, expected_sold_per_m2,
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asking_to_sold_ratio, ratio_basis,
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expires_at
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) VALUES (
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CAST(:id AS uuid),
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@ -940,6 +1041,9 @@ async def estimate_quality(payload: TradeInEstimateInput, db: Session) -> Aggreg
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:canonical_address, :house_cadnum, :house_fias_id,
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:dadata_qc_geo, :dadata_qc_house,
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CAST(:dadata_metro_json AS jsonb),
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:expected_sold_price, :expected_sold_range_low,
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:expected_sold_range_high, :expected_sold_per_m2,
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:asking_to_sold_ratio, :ratio_basis,
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:expires_at
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)
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"""
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@ -982,6 +1086,12 @@ async def estimate_quality(payload: TradeInEstimateInput, db: Session) -> Aggreg
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"dadata_qc_geo": dadata.qc_geo if dadata else None,
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"dadata_qc_house": dadata.qc_house if dadata else None,
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"dadata_metro_json": dadata_metro_json,
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"expected_sold_price": expected_sold_price,
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"expected_sold_range_low": expected_sold_range_low,
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"expected_sold_range_high": expected_sold_range_high,
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"expected_sold_per_m2": expected_sold_per_m2,
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"asking_to_sold_ratio": asking_to_sold_ratio,
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"ratio_basis": ratio_basis,
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"expires_at": expires_at,
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},
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)
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@ -1068,6 +1178,12 @@ async def estimate_quality(payload: TradeInEstimateInput, db: Session) -> Aggreg
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if cian_val is not None
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else None
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),
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expected_sold_price_rub=expected_sold_price,
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expected_sold_range_low_rub=expected_sold_range_low,
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expected_sold_range_high_rub=expected_sold_range_high,
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expected_sold_per_m2=expected_sold_per_m2,
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asking_to_sold_ratio=asking_to_sold_ratio,
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ratio_basis=ratio_basis,
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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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@ -0,0 +1,52 @@
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-- 081_trade_in_estimates_expected_sold.sql
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-- #648 Stage 3 — persist the asking→sold corrected price on each estimate.
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--
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-- ПРОБЛЕМА (#648). Estimator (estimator.py) отдаёт headline-медиану по АКТИВНЫМ
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-- asking-объявлениям. Backtest (#648 Stage 1) показал систематический bias
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-- asking-медианы +20% над реальной ДКП-ценой. Stage 2 (migration 080) сохранил
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-- per-rooms коэффициент asking_to_sold_ratios (ratio = sold/asking, ~0.72–0.93).
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-- Stage 3 (estimator) ДОПОЛНИТЕЛЬНО (purely additive — headline НЕ меняется)
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-- вычисляет expected_sold = asking × ratio. Эту параллельную цену надо
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-- ПЕРСИСТИТЬ на trade_in_estimates, чтобы shared-link reopen (GET /estimate/{id})
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-- и PDF (GET /estimate/{id}/pdf) её отдавали (re-SELECT строит AggregatedEstimate
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-- из явных колонок — без персиста значения терялись бы при reopen).
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--
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-- ДОБАВЛЯЕТ (все nullable — backward-safe; старые строки = NULL = «нет коррекции»):
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-- expected_sold_price bigint — asking median_price × ratio
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-- expected_sold_range_low bigint — asking range_low × ratio
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-- expected_sold_range_high bigint — asking range_high × ratio
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-- expected_sold_per_m2 int — asking median ₽/м² × ratio
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-- asking_to_sold_ratio numeric — применённый ratio (=sold/asking), диагностика
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-- ratio_basis text — 'per_rooms' | 'global_fallback'
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--
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-- GRACEFUL: если asking_to_sold_ratios пуста / бакета нет — estimator пишет NULL
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-- в эти колонки (sold-коррекция недоступна), оценка возвращается штатно.
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--
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-- ЗАВИСИМОСТИ: trade_in_estimates (existing), asking_to_sold_ratios (080).
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-- Idempotent (ADD COLUMN IF NOT EXISTS) — безопасно ре-apply / dry-run.
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-- Apply after: 080_asking_to_sold_ratios.sql
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BEGIN;
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ALTER TABLE trade_in_estimates
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ADD COLUMN IF NOT EXISTS expected_sold_price bigint,
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ADD COLUMN IF NOT EXISTS expected_sold_range_low bigint,
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ADD COLUMN IF NOT EXISTS expected_sold_range_high bigint,
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ADD COLUMN IF NOT EXISTS expected_sold_per_m2 int,
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ADD COLUMN IF NOT EXISTS asking_to_sold_ratio numeric,
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ADD COLUMN IF NOT EXISTS ratio_basis text;
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COMMENT ON COLUMN trade_in_estimates.expected_sold_price IS
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'#648 S3: asking median_price × per-rooms sold/asking ratio. NULL = коррекция недоступна.';
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COMMENT ON COLUMN trade_in_estimates.expected_sold_range_low IS
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'#648 S3: asking range_low × ratio.';
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COMMENT ON COLUMN trade_in_estimates.expected_sold_range_high IS
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'#648 S3: asking range_high × ratio.';
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COMMENT ON COLUMN trade_in_estimates.expected_sold_per_m2 IS
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'#648 S3: asking median ₽/м² × ratio.';
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COMMENT ON COLUMN trade_in_estimates.asking_to_sold_ratio IS
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'#648 S3: применённый ratio (=sold/asking, ~0.72–0.93) из asking_to_sold_ratios (080).';
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COMMENT ON COLUMN trade_in_estimates.ratio_basis IS
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'#648 S3: источник ratio — ''per_rooms'' (свой бакет) | ''global_fallback'' (rooms_bucket=-1).';
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COMMIT;
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@ -116,6 +116,11 @@ def _common_patches(cian_mock):
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"app.services.estimator.estimate_via_cian_valuation",
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new=cian_mock,
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),
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# #648 S3: stub asking→sold lookup off (isolates cian-source assertions).
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patch(
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"app.services.estimator._get_asking_sold_ratio",
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return_value=(None, None),
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),
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]
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@ -142,6 +147,8 @@ def test_estimator_includes_cian_valuation_when_available() -> None:
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new=AsyncMock(return_value=None)),
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patch("app.services.estimator.estimate_via_cian_valuation",
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new=cian_mock),
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patch("app.services.estimator._get_asking_sold_ratio",
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return_value=(None, None)),
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):
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result = await estimate_quality(payload, db)
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|
|
@ -172,6 +179,8 @@ def test_estimator_graceful_when_cian_returns_none() -> None:
|
|||
new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator.estimate_via_cian_valuation",
|
||||
new=cian_mock),
|
||||
patch("app.services.estimator._get_asking_sold_ratio",
|
||||
return_value=(None, None)),
|
||||
):
|
||||
result = await estimate_quality(payload, db)
|
||||
|
||||
|
|
@ -203,6 +212,8 @@ def test_estimator_graceful_when_cian_raises() -> None:
|
|||
new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator.estimate_via_cian_valuation",
|
||||
new=cian_mock),
|
||||
patch("app.services.estimator._get_asking_sold_ratio",
|
||||
return_value=(None, None)),
|
||||
):
|
||||
result = await estimate_quality(payload, db)
|
||||
|
||||
|
|
@ -236,6 +247,8 @@ def test_estimator_cian_result_no_sale_price_not_added() -> None:
|
|||
new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator.estimate_via_cian_valuation",
|
||||
new=cian_mock),
|
||||
patch("app.services.estimator._get_asking_sold_ratio",
|
||||
return_value=(None, None)),
|
||||
):
|
||||
result = await estimate_quality(payload, db)
|
||||
|
||||
|
|
|
|||
264
tradein-mvp/backend/tests/test_estimator_expected_sold.py
Normal file
264
tradein-mvp/backend/tests/test_estimator_expected_sold.py
Normal file
|
|
@ -0,0 +1,264 @@
|
|||
"""Tests for the asking→sold correction (#648 Stage 3).
|
||||
|
||||
Two layers:
|
||||
|
||||
1. `_get_asking_sold_ratio` lookup helper (DB mocked):
|
||||
- bucket = min(max(rooms or 0, 0), 4) — clamping + None handling
|
||||
- per-rooms row hit returns (ratio, basis)
|
||||
- per-rooms miss falls back to the global rooms_bucket=-1 row
|
||||
- empty / missing table → (None, None), never raises (graceful)
|
||||
- the in-process TTL cache memoises per bucket
|
||||
|
||||
2. The apply-logic in `estimate_quality` (every I/O stubbed, no DB, no network —
|
||||
same isolation harness as test_estimator_repair_coef.py):
|
||||
- when a ratio exists: expected_sold_price_rub ≈ round(median_price_rub * ratio)
|
||||
and expected_sold_per_m2 ≈ round(median_price_per_m2 * ratio)
|
||||
- the headline median_price_rub / ranges / per_m2 stay UNCHANGED (additive)
|
||||
- graceful path: lookup returns (None, None) → all expected_sold_* are None,
|
||||
no crash, headline still returned
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
from datetime import UTC, datetime
|
||||
from typing import Any
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import anyio
|
||||
|
||||
# Settings requires DATABASE_URL at init time. Set dummy DSN before any app import.
|
||||
os.environ.setdefault("DATABASE_URL", "postgresql+psycopg://test:test@localhost/test_db")
|
||||
|
||||
|
||||
# ── Layer 1: _get_asking_sold_ratio lookup helper ───────────────────────────
|
||||
|
||||
|
||||
class _FakeRow:
|
||||
"""Stand-in for a SQLAlchemy Row (attribute access .ratio / .basis)."""
|
||||
|
||||
def __init__(self, ratio: float | None, basis: str | None) -> None:
|
||||
self.ratio = ratio
|
||||
self.basis = basis
|
||||
|
||||
|
||||
def _clear_ratio_cache() -> None:
|
||||
from app.services import estimator
|
||||
|
||||
estimator._asking_sold_ratio_cache.clear()
|
||||
|
||||
|
||||
def _db_returning(rows: list[_FakeRow | None]) -> MagicMock:
|
||||
"""MagicMock db whose successive .execute(...).fetchone() yield `rows`."""
|
||||
db = MagicMock()
|
||||
db.execute.return_value.fetchone.side_effect = rows
|
||||
return db
|
||||
|
||||
|
||||
def test_bucket_clamping() -> None:
|
||||
"""rooms None→0, negative→0, >4→4; 0..4 pass through."""
|
||||
from app.services.estimator import _get_asking_sold_ratio
|
||||
|
||||
cases = {None: 0, -3: 0, 0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 4, 99: 4}
|
||||
for rooms, expected_bucket in cases.items():
|
||||
_clear_ratio_cache()
|
||||
db = _db_returning([_FakeRow(0.8, "per_rooms")])
|
||||
_get_asking_sold_ratio(db, rooms)
|
||||
# First positional bind param is {"b": bucket}.
|
||||
bind = db.execute.call_args_list[0].args[1]
|
||||
assert bind["b"] == expected_bucket, (
|
||||
f"rooms={rooms} → bucket {bind['b']} != {expected_bucket}"
|
||||
)
|
||||
|
||||
|
||||
def test_per_rooms_hit_returns_ratio_basis() -> None:
|
||||
"""Per-rooms row present → returned directly, no fallback query."""
|
||||
from app.services.estimator import _get_asking_sold_ratio
|
||||
|
||||
_clear_ratio_cache()
|
||||
db = _db_returning([_FakeRow(0.74, "per_rooms")])
|
||||
ratio, basis = _get_asking_sold_ratio(db, 1)
|
||||
assert ratio == 0.74
|
||||
assert basis == "per_rooms"
|
||||
assert db.execute.call_count == 1 # no global fallback needed
|
||||
|
||||
|
||||
def test_global_fallback_when_per_rooms_missing() -> None:
|
||||
"""Per-rooms miss (None) → second query for rooms_bucket=-1 global row."""
|
||||
from app.services.estimator import _get_asking_sold_ratio
|
||||
|
||||
_clear_ratio_cache()
|
||||
db = _db_returning([None, _FakeRow(0.79, "global_fallback")])
|
||||
ratio, basis = _get_asking_sold_ratio(db, 3)
|
||||
assert ratio == 0.79
|
||||
assert basis == "global_fallback"
|
||||
assert db.execute.call_count == 2
|
||||
|
||||
|
||||
def test_empty_table_returns_none_none() -> None:
|
||||
"""Both queries miss (empty table) → (None, None), no raise."""
|
||||
from app.services.estimator import _get_asking_sold_ratio
|
||||
|
||||
_clear_ratio_cache()
|
||||
db = _db_returning([None, None])
|
||||
assert _get_asking_sold_ratio(db, 2) == (None, None)
|
||||
|
||||
|
||||
def test_missing_table_is_graceful() -> None:
|
||||
"""db.execute raises (relation does not exist) → (None, None), swallowed."""
|
||||
from app.services.estimator import _get_asking_sold_ratio
|
||||
|
||||
_clear_ratio_cache()
|
||||
db = MagicMock()
|
||||
db.execute.side_effect = RuntimeError("relation asking_to_sold_ratios does not exist")
|
||||
assert _get_asking_sold_ratio(db, 1) == (None, None)
|
||||
|
||||
|
||||
def test_cache_memoises_per_bucket() -> None:
|
||||
"""Second call for same bucket within TTL → no extra DB query."""
|
||||
from app.services.estimator import _get_asking_sold_ratio
|
||||
|
||||
_clear_ratio_cache()
|
||||
db = _db_returning([_FakeRow(0.8, "per_rooms")])
|
||||
first = _get_asking_sold_ratio(db, 2)
|
||||
second = _get_asking_sold_ratio(db, 2)
|
||||
assert first == second == (0.8, "per_rooms")
|
||||
assert db.execute.call_count == 1 # second served from cache
|
||||
|
||||
|
||||
# ── Layer 2: apply-logic inside estimate_quality (all I/O stubbed) ──────────
|
||||
|
||||
|
||||
def _make_listing(*, price_per_m2: float, area_m2: float = 40.0) -> dict[str, Any]:
|
||||
price_rub = price_per_m2 * area_m2
|
||||
return {
|
||||
"source": "cian",
|
||||
"source_url": "https://cian.ru/offer/1",
|
||||
"address": "ЕКБ, ул. Учителей, 18",
|
||||
"lat": 56.838,
|
||||
"lon": 60.595,
|
||||
"rooms": 1,
|
||||
"area_m2": area_m2,
|
||||
"floor": 4,
|
||||
"total_floors": 16,
|
||||
"price_rub": price_rub,
|
||||
"price_per_m2": price_per_m2,
|
||||
"listing_date": datetime(2026, 5, 1),
|
||||
"days_on_market": 10,
|
||||
"photo_urls": [],
|
||||
"scraped_at": datetime(2026, 5, 20, tzinfo=UTC),
|
||||
"distance_m": 100.0,
|
||||
"relevance_score": 0.1,
|
||||
}
|
||||
|
||||
|
||||
# Three fixed analogs → deterministic median ppm2 = 150_000 (< 5 ⇒ no outlier drop).
|
||||
_ANALOGS: list[dict[str, Any]] = [
|
||||
_make_listing(price_per_m2=140_000.0),
|
||||
_make_listing(price_per_m2=150_000.0),
|
||||
_make_listing(price_per_m2=160_000.0),
|
||||
]
|
||||
|
||||
|
||||
def _make_fake_geo():
|
||||
from app.services.geocoder import GeocodeResult
|
||||
|
||||
return GeocodeResult(
|
||||
lat=56.838,
|
||||
lon=60.595,
|
||||
full_address="Свердловская обл., Екатеринбург, ул. Учителей, 18",
|
||||
provider="nominatim",
|
||||
)
|
||||
|
||||
|
||||
def _make_payload():
|
||||
from app.schemas.trade_in import TradeInEstimateInput
|
||||
|
||||
return TradeInEstimateInput(
|
||||
address="ЕКБ, ул. Учителей, 18",
|
||||
area_m2=40.0,
|
||||
rooms=1,
|
||||
floor=4,
|
||||
total_floors=16,
|
||||
)
|
||||
|
||||
|
||||
def _run_estimate(ratio_tuple: tuple[float | None, str | None]):
|
||||
"""estimate_quality with all deps stubbed; _get_asking_sold_ratio forced."""
|
||||
from app.services.estimator import estimate_quality
|
||||
|
||||
db = MagicMock()
|
||||
payload = _make_payload()
|
||||
|
||||
async def _run():
|
||||
with (
|
||||
patch("app.services.estimator.geocode", new=AsyncMock(return_value=_make_fake_geo())),
|
||||
patch("app.services.estimator.dadata_clean_address",
|
||||
new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator.match_house_readonly", return_value=None),
|
||||
patch("app.services.estimator.get_house_metadata", new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator._fetch_analogs",
|
||||
return_value=(list(_ANALOGS), False, "S")),
|
||||
patch("app.services.estimator._fetch_deals", return_value=[]),
|
||||
patch("app.services.estimator._get_or_fetch_imv_cached",
|
||||
new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator._get_or_fetch_yandex_valuation_cached",
|
||||
new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator.estimate_via_cian_valuation",
|
||||
new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator._get_asking_sold_ratio", return_value=ratio_tuple),
|
||||
):
|
||||
return await estimate_quality(payload, db)
|
||||
|
||||
return anyio.run(_run)
|
||||
|
||||
|
||||
def test_expected_sold_applied_when_ratio_present() -> None:
|
||||
"""ratio present → expected_sold_* ≈ asking × ratio; headline UNCHANGED."""
|
||||
ratio = 0.74
|
||||
est = _run_estimate((ratio, "per_rooms"))
|
||||
|
||||
# Headline asking-median is the unadjusted market median (additive invariant).
|
||||
expected_headline = int(150_000.0 * 40.0) # 6_000_000
|
||||
assert est.median_price_rub == expected_headline
|
||||
assert est.median_price_per_m2 == 150_000
|
||||
|
||||
# Parallel expected_sold = asking × ratio (round()).
|
||||
assert est.expected_sold_price_rub == round(est.median_price_rub * ratio)
|
||||
assert est.expected_sold_per_m2 == round(est.median_price_per_m2 * ratio)
|
||||
assert est.expected_sold_range_low_rub == round(est.range_low_rub * ratio)
|
||||
assert est.expected_sold_range_high_rub == round(est.range_high_rub * ratio)
|
||||
assert est.asking_to_sold_ratio == ratio
|
||||
assert est.ratio_basis == "per_rooms"
|
||||
|
||||
|
||||
def test_headline_unchanged_vs_no_ratio() -> None:
|
||||
"""median_price_rub / ranges / per_m2 identical with and without a ratio."""
|
||||
with_ratio = _run_estimate((0.8, "global_fallback"))
|
||||
without_ratio = _run_estimate((None, None))
|
||||
|
||||
assert with_ratio.median_price_rub == without_ratio.median_price_rub
|
||||
assert with_ratio.range_low_rub == without_ratio.range_low_rub
|
||||
assert with_ratio.range_high_rub == without_ratio.range_high_rub
|
||||
assert with_ratio.median_price_per_m2 == without_ratio.median_price_per_m2
|
||||
|
||||
|
||||
def test_graceful_when_ratio_none() -> None:
|
||||
"""Lookup returns (None, None) → all expected_sold_* None, no crash."""
|
||||
est = _run_estimate((None, None))
|
||||
|
||||
assert est.expected_sold_price_rub is None
|
||||
assert est.expected_sold_range_low_rub is None
|
||||
assert est.expected_sold_range_high_rub is None
|
||||
assert est.expected_sold_per_m2 is None
|
||||
assert est.asking_to_sold_ratio is None
|
||||
assert est.ratio_basis is None
|
||||
# Headline still produced normally.
|
||||
assert est.median_price_rub == int(150_000.0 * 40.0)
|
||||
|
||||
|
||||
def test_global_fallback_basis_carried_through() -> None:
|
||||
"""basis='global_fallback' propagates to the returned estimate."""
|
||||
est = _run_estimate((0.79, "global_fallback"))
|
||||
assert est.ratio_basis == "global_fallback"
|
||||
assert est.asking_to_sold_ratio == 0.79
|
||||
|
|
@ -109,6 +109,10 @@ def _run_estimate(repair_state: str | None):
|
|||
new=AsyncMock(return_value=None)),
|
||||
patch("app.services.estimator.estimate_via_cian_valuation",
|
||||
new=AsyncMock(return_value=None)),
|
||||
# #648 S3: stub asking→sold lookup off so this test isolates the
|
||||
# repair coefficient (no sold-correction, no DB).
|
||||
patch("app.services.estimator._get_asking_sold_ratio",
|
||||
return_value=(None, None)),
|
||||
):
|
||||
return await estimate_quality(payload, db)
|
||||
|
||||
|
|
|
|||
|
|
@ -77,7 +77,7 @@ def test_address_cap_limits_per_address_listings() -> None:
|
|||
]
|
||||
db = _make_db_mock(sql_rows)
|
||||
|
||||
result, fallback_used = _fetch_analogs(
|
||||
result, fallback_used, _tier = _fetch_analogs(
|
||||
db, lat=56.838, lon=60.595, rooms=1, area=38.0, radius_m=1000
|
||||
)
|
||||
|
||||
|
|
@ -116,7 +116,7 @@ def test_source_quota_prevents_cian_starvation() -> None:
|
|||
sql_rows = avito_rows + cian_rows
|
||||
db = _make_db_mock(sql_rows)
|
||||
|
||||
result, _ = _fetch_analogs(
|
||||
result, _, _ = _fetch_analogs(
|
||||
db, lat=56.838, lon=60.595, rooms=1, area=38.0, radius_m=1000
|
||||
)
|
||||
|
||||
|
|
@ -150,7 +150,7 @@ def test_source_quota_includes_all_when_supply_below_min() -> None:
|
|||
sql_rows = avito_rows + cian_rows
|
||||
db = _make_db_mock(sql_rows)
|
||||
|
||||
result, _ = _fetch_analogs(
|
||||
result, _, _ = _fetch_analogs(
|
||||
db, lat=56.838, lon=60.595, rooms=1, area=38.0, radius_m=1000
|
||||
)
|
||||
|
||||
|
|
@ -177,13 +177,13 @@ def test_fallback_signal_reflects_radius() -> None:
|
|||
]
|
||||
|
||||
db_default = _make_db_mock(rows)
|
||||
_, fallback_default = _fetch_analogs(
|
||||
_, fallback_default, _ = _fetch_analogs(
|
||||
db_default, lat=56.838, lon=60.595, rooms=1, area=38.0, radius_m=DEFAULT_RADIUS_M
|
||||
)
|
||||
assert fallback_default is False, "radius == DEFAULT should produce fallback_used=False"
|
||||
|
||||
db_fallback = _make_db_mock(rows)
|
||||
_, fallback_wide = _fetch_analogs(
|
||||
_, fallback_wide, _ = _fetch_analogs(
|
||||
db_fallback, lat=56.838, lon=60.595, rooms=1, area=38.0, radius_m=FALLBACK_RADIUS_M
|
||||
)
|
||||
assert fallback_wide is True, "radius == FALLBACK should produce fallback_used=True"
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue