5a4408e0ab
Раньше _VELOCITY_DIVISORS делил агрегаты mv_layout_velocity (24 мес) на 4/12 для quarter/year, не меняя реальное окно данных. Теперь inline SQL из objective_corpus_room_month с CAST(:window_interval AS interval). velocity_per_month = deals_window / months_in_window (1.0/3.0/12.0). Разные time_window → разные строки из БД → разный mix/velocity/jk_count. Closes (epic part) #271 item 1
337 lines
12 KiB
Python
337 lines
12 KiB
Python
"""Unit-тесты для get_best_layouts (Fix SF-01: honest time_window velocity).
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Проверяет, что разные time_window → разные deals_window → разный velocity_per_month.
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Mock-стратегия: патчим db.execute с side_effect, повторяя порядок вызовов
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в get_best_layouts:
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1. _PARCEL_CENTROID_SQL → .mappings().first()
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2. _COMPETITORS_IN_RADIUS_SQL → .mappings().all()
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3. _INLINE_VELOCITY_SQL → .mappings().all()
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4. db.scalar() → MAX(snapshot_date) — через .return_value
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5. _SUPPLY_BATCH_SQL → .mappings().all()
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Ключевые asserts:
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- last_month (1 мес) → velocity = deals_window / 1.0
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- last_quarter (3 мес) → velocity = deals_window / 3.0
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- last_year (12 мес) → velocity = deals_window / 12.0
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- Разный deals_window при разных time_window → разный mix.
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"""
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from __future__ import annotations
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import datetime as dt
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from unittest.mock import MagicMock
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import pytest
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from app.schemas.parcel import BestLayoutsRequest
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from app.services.site_finder.best_layouts import _TIME_WINDOW_PARAMS, get_best_layouts
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_TODAY = dt.date.today()
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CAD_NUM = "66:41:0303161:123"
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# ── Фабрики mock-строк ────────────────────────────────────────────────────────
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def _coord_row(lon: float = 60.6, lat: float = 56.85) -> MagicMock:
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r = MagicMock()
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r.__getitem__ = lambda self, k: {"center_lon": lon, "center_lat": lat}[k]
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return r
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def _obj_id_row(obj_id: int) -> MagicMock:
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r = MagicMock()
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r.__getitem__ = lambda self, k: {"obj_id": obj_id}[k]
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return r
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def _vel_row(
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room_bucket: str = "2",
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deals_window: float = 48.0,
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avg_area: float = 55.0,
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avg_price_rub: float | None = 120000.0,
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obj_ids: list[int] | None = None,
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window_start: dt.date | None = None,
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window_end: dt.date | None = None,
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) -> MagicMock:
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"""Строка из _INLINE_VELOCITY_SQL.
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deals_window — реальные сделки за честное окно (не 24 мес).
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"""
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oids = obj_ids if obj_ids is not None else [1]
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ws = window_start or _TODAY - dt.timedelta(days=90)
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we = window_end or _TODAY
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r = MagicMock()
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r.__getitem__ = lambda self, k: {
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"room_bucket": room_bucket,
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"deals_window": deals_window,
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"avg_area_m2": avg_area,
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"avg_price_per_m2_rub": avg_price_rub,
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"competitor_obj_ids": oids,
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"competitor_count": len(oids),
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"window_start": ws,
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"window_end": we,
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}[k]
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return r
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def _supply_row(rb: str, ab: str, units: int) -> MagicMock:
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r = MagicMock()
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r.__getitem__ = lambda self, k: {"rb": rb, "ab": ab, "units": units}[k]
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return r
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def _make_db(
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coord: MagicMock | None = None,
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id_rows: list[MagicMock] | None = None,
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vel_rows: list[MagicMock] | None = None,
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supply_rows: list[MagicMock] | None = None,
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latest_snap: dt.date | None = None,
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) -> MagicMock:
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"""Сконструировать mock Session.
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Порядок db.execute():
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1. centroid → .mappings().first()
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2. competitors → .mappings().all()
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3. velocity → .mappings().all()
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4. supply → .mappings().all() (только если latest_snap is not None)
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db.scalar() → latest_snap (MAX snapshot_date).
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"""
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db = MagicMock()
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db.scalar.return_value = latest_snap if latest_snap is not None else _TODAY
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r0 = MagicMock()
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r0.mappings.return_value.first.return_value = coord
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r1 = MagicMock()
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r1.mappings.return_value.all.return_value = id_rows or []
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r2 = MagicMock()
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r2.mappings.return_value.all.return_value = vel_rows or []
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r3 = MagicMock()
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r3.mappings.return_value.all.return_value = supply_rows or []
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db.execute.side_effect = [r0, r1, r2, r3]
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return db
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def _request(**kwargs) -> BestLayoutsRequest:
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defaults: dict = {
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"radius_km": 1.0,
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"time_window": "last_quarter",
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"min_velocity_per_month": 0.0,
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}
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defaults.update(kwargs)
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return BestLayoutsRequest(**defaults)
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# ── Тесты TIME_WINDOW_PARAMS ──────────────────────────────────────────────────
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def test_time_window_params_keys() -> None:
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"""Все три time_window определены, months_in_window > 0."""
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for key in ("last_month", "last_quarter", "last_year"):
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assert key in _TIME_WINDOW_PARAMS
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interval_str, months = _TIME_WINDOW_PARAMS[key]
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assert isinstance(interval_str, str) and len(interval_str) > 0
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assert months > 0
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# ── Тест SF-01: разный deals_window → разный velocity ────────────────────────
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def test_last_month_velocity_divisor_1() -> None:
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"""time_window=last_month: velocity = deals_window / 1.0."""
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deals = 30.0
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db = _make_db(
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coord=_coord_row(),
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id_rows=[_obj_id_row(1)],
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vel_rows=[_vel_row("1", deals_window=deals, obj_ids=[1])],
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)
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req = _request(time_window="last_month")
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resp = get_best_layouts(db, CAD_NUM, req)
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assert len(resp.top_layouts) == 1
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assert resp.top_layouts[0].velocity_per_month == pytest.approx(30.0, rel=1e-3)
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def test_last_quarter_velocity_divisor_3() -> None:
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"""time_window=last_quarter: velocity = deals_window / 3.0."""
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deals = 30.0
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db = _make_db(
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coord=_coord_row(),
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id_rows=[_obj_id_row(1)],
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vel_rows=[_vel_row("1", deals_window=deals, obj_ids=[1])],
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)
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req = _request(time_window="last_quarter")
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resp = get_best_layouts(db, CAD_NUM, req)
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assert len(resp.top_layouts) == 1
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assert resp.top_layouts[0].velocity_per_month == pytest.approx(10.0, rel=1e-3)
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def test_last_year_velocity_divisor_12() -> None:
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"""time_window=last_year: velocity = deals_window / 12.0."""
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deals = 60.0
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db = _make_db(
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coord=_coord_row(),
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id_rows=[_obj_id_row(1)],
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vel_rows=[_vel_row("1", deals_window=deals, obj_ids=[1])],
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)
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req = _request(time_window="last_year")
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resp = get_best_layouts(db, CAD_NUM, req)
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assert len(resp.top_layouts) == 1
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assert resp.top_layouts[0].velocity_per_month == pytest.approx(5.0, rel=1e-3)
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def test_different_time_windows_produce_different_velocity() -> None:
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"""Одни и те же deals_window → разная velocity_per_month для разных time_window.
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Главный acceptance-тест SF-01: time_window влияет на velocity, не только на масштаб.
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При одном и том же deals_window=30:
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last_month → 30.0
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last_quarter → 10.0
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last_year → 2.5
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"""
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deals = 30.0
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velocities: dict[str, float] = {}
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for tw in ("last_month", "last_quarter", "last_year"):
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db = _make_db(
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coord=_coord_row(),
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id_rows=[_obj_id_row(1)],
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vel_rows=[_vel_row("2", deals_window=deals, obj_ids=[1])],
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)
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req = _request(time_window=tw)
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resp = get_best_layouts(db, CAD_NUM, req)
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assert len(resp.top_layouts) == 1, f"No layouts for {tw}"
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velocities[tw] = resp.top_layouts[0].velocity_per_month
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# Все три значения различаются
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vals = list(velocities.values())
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assert vals[0] != vals[1] != vals[2], f"Velocities must differ: {velocities}"
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# last_month > last_quarter > last_year (одинаковые deals, разный знаменатель)
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assert velocities["last_month"] > velocities["last_quarter"] > velocities["last_year"]
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# ── Тест: ranking по velocity и sum pct = 100 ────────────────────────────────
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def test_ranking_and_pct_sum_100() -> None:
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"""3 room_buckets → ranking по velocity, sum pct = 100."""
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id_rows = [_obj_id_row(1), _obj_id_row(2), _obj_id_row(3)]
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vel_rows = [
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_vel_row("studio", deals_window=9.0, avg_area=26.0, obj_ids=[1]), # 9/3=3.0
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_vel_row("1", deals_window=24.0, avg_area=40.0, obj_ids=[2]), # 24/3=8.0
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_vel_row("2", deals_window=48.0, avg_area=55.0, obj_ids=[3]), # 48/3=16.0
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]
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supply_rows = [
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_supply_row("studio", "<25", 20),
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_supply_row("1", "40-60", 60),
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_supply_row("2", "40-60", 80),
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]
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db = _make_db(coord=_coord_row(), id_rows=id_rows, vel_rows=vel_rows, supply_rows=supply_rows)
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req = _request(time_window="last_quarter")
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resp = get_best_layouts(db, CAD_NUM, req)
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top = resp.top_layouts
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assert len(top) == 3
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# rank 1 = "2" (наибольший velocity 16.0)
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assert top[0].room_bucket == "2"
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assert top[0].rank == 1
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assert top[0].velocity_per_month == pytest.approx(16.0, rel=1e-3)
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# rank 2 = "1" (8.0)
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assert top[1].room_bucket == "1"
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assert top[1].velocity_per_month == pytest.approx(8.0, rel=1e-3)
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# ранги уникальны
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assert sorted(t.rank for t in top) == [1, 2, 3]
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# sum pct = 100
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mix = resp.recommendation_for_tz.mix
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assert sum(m.pct for m in mix) == 100
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# ── Тест: пустые конкуренты ───────────────────────────────────────────────────
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def test_no_competitors_returns_empty_response() -> None:
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"""Нет конкурентов в радиусе → пустые top_layouts + confidence=low."""
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db = _make_db(coord=_coord_row(), id_rows=[], vel_rows=[])
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req = _request()
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resp = get_best_layouts(db, CAD_NUM, req)
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assert resp.top_layouts == []
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assert resp.data_quality.confidence == "low"
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assert resp.recommendation_for_tz.based_on_obj_count == 0
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# ── Тест: centroid не найден ──────────────────────────────────────────────────
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def test_centroid_not_found_raises_value_error() -> None:
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"""Геометрия участка не найдена → ValueError."""
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db = _make_db(coord=None)
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req = _request()
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with pytest.raises(ValueError, match="не найдена"):
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get_best_layouts(db, "99:99:9999999:999", req)
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# ── Тест: min_velocity фильтрует строки ──────────────────────────────────────
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def test_min_velocity_filters_low_rows() -> None:
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"""min_velocity_per_month=5 → строки с velocity<5 не попадают в top_layouts.
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last_quarter (3 мес):
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studio: 9 / 3 = 3.0 < 5.0 → отфильтрован
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1: 24 / 3 = 8.0 > 5.0 → остаётся
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"""
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id_rows = [_obj_id_row(1), _obj_id_row(2)]
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vel_rows = [
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_vel_row("studio", deals_window=9.0, obj_ids=[1]),
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_vel_row("1", deals_window=24.0, obj_ids=[2]),
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]
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db = _make_db(coord=_coord_row(), id_rows=id_rows, vel_rows=vel_rows)
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req = _request(time_window="last_quarter", min_velocity_per_month=5.0)
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resp = get_best_layouts(db, CAD_NUM, req)
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top = resp.top_layouts
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assert len(top) == 1
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assert top[0].room_bucket == "1"
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assert top[0].velocity_per_month == pytest.approx(8.0, rel=1e-3)
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# ── Тест: exclude_competitor_obj_ids ─────────────────────────────────────────
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def test_exclude_competitor_obj_ids() -> None:
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"""exclude_competitor_obj_ids=[20] при единственном конкуренте → пустой ответ."""
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id_rows = [_obj_id_row(20)]
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db = _make_db(coord=_coord_row(), id_rows=id_rows, vel_rows=[])
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req = _request(exclude_competitor_obj_ids=[20])
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resp = get_best_layouts(db, CAD_NUM, req)
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assert resp.top_layouts == []
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assert resp.data_quality.objects_total_in_radius == 1
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# ── Тест: total_sold_in_window совпадает с deals_window ──────────────────────
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def test_total_sold_in_window_matches_deals_window() -> None:
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"""total_sold_in_window в TopLayoutRow = deals_window (целое)."""
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deals = 37.0
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db = _make_db(
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coord=_coord_row(),
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id_rows=[_obj_id_row(5)],
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vel_rows=[_vel_row("3", deals_window=deals, obj_ids=[5])],
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)
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req = _request(time_window="last_quarter")
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resp = get_best_layouts(db, CAD_NUM, req)
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assert len(resp.top_layouts) == 1
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assert resp.top_layouts[0].total_sold_in_window == int(deals)
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