feat(velocity): migrate D2 sales source from stale sale_graph to objective_corpus_room_month
Closes #156
This commit is contained in:
lekss361
parent
37fd4b5a8e
commit
fa6bbafa3f
3 changed files with 174 additions and 168 deletions
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@ -673,7 +673,14 @@ def object_detail(db: Session, obj_id: int) -> dict[str, Any] | None:
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def object_sale_graph(
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db: Session, obj_id: int, type_filter: str | None = None
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) -> list[dict[str, Any]]:
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"""Time-series продаж per-ЖК. Latest snapshot."""
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"""Time-series продаж per-ЖК. Latest snapshot.
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NOTE: намеренно оставлен на domrf_kn_sale_graph — это внутренний
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per-object detail view для PRINZIP-аналитики (/api/v1/analytics/object/*).
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Миграция на objective_corpus_room_month требует отдельного pr: там другая
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гранулярность (corpus × room_bucket), а не obj_id.
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Данные stale (newest 2026-01) — приемлемо для исторического графика.
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"""
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where_type = ""
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params: dict[str, Any] = {"obj": obj_id}
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if type_filter:
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@ -930,7 +937,13 @@ def prinzip_funnel_by_object(db: Session) -> list[dict[str, Any]]:
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def prinzip_objects_with_velocity(db: Session) -> list[dict[str, Any]]:
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"""Список 28 PRINZIP-ЖК с агрегатами + apartments-velocity sparkline data."""
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"""Список 28 PRINZIP-ЖК с агрегатами + apartments-velocity sparkline data.
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NOTE: sparkline (velocity CTE) намеренно оставлен на domrf_kn_sale_graph.
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objective_corpus_room_month не имеет obj_id — требует JOIN через
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objective_complex_mapping по project_name. Это отдельная задача рефакторинга
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admin-view. Данные stale (newest 2026-01), sparkline визуально OK для тренда.
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"""
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rows = (
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db.execute(
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text(
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@ -1086,43 +1099,47 @@ def _velocity_baseline(
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target_class: str | None,
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) -> dict[str, Any]:
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"""Median monthly sales velocity (apartments/month per ЖК) from
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domrf_kn_sale_graph for objects in the same район+class over last 24 mo.
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objective_corpus_room_month for objects in the same район+class over last 24 mo.
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Migrated from domrf_kn_sale_graph (stale since 2026-01) to
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objective_corpus_room_month (updated weekly via Objective API).
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objective_corpus_room_month.district matches domrf_kn_objects.district_name.
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class filter uses 'class' column (Комфорт/Бизнес/Стандарт).
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Returns dict {realised_per_month_median, realised_per_month_avg,
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objects_count, observations}. All-None means no data → caller falls back.
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"""
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where_class = "AND o.obj_class = :cls" if target_class else ""
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params: dict[str, Any] = {
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"rc": region_code,
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"dn": district_name,
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}
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# Objective class naming: "Комфорт", "Бизнес", "Стандарт" — capitalised.
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# domrf obj_class may differ in case; apply ILIKE for robustness.
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where_class = "AND LOWER(crm.class) = LOWER(:cls)" if target_class else ""
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params: dict[str, Any] = {"dn": district_name}
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if target_class:
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params["cls"] = target_class
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# region_code not used — objective_corpus_room_month covers only EKB (region 66).
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# district filter is sufficient for locality. If district returns no rows,
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# caller falls back to rosreestr_fallback path (unchanged behaviour).
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_ = region_code # retained in signature for backward compat
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row = (
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db.execute(
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text(
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f"""
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WITH obj_pool AS (
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SELECT o.obj_id
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FROM domrf_kn_objects o
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WHERE o.region_cd = :rc
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AND o.district_name = :dn
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WITH per_project_month AS (
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SELECT project_name,
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report_month,
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SUM(deals_total_count) AS month_units
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FROM objective_corpus_room_month crm
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WHERE crm.district = :dn
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{where_class}
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),
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sg AS (
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SELECT sg.obj_id, sg.realised
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FROM domrf_kn_sale_graph sg
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JOIN obj_pool p ON p.obj_id = sg.obj_id
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WHERE sg.type = 'apartments'
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AND sg.realised IS NOT NULL
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AND sg.report_month >= NOW() - INTERVAL '24 months'
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AND crm.deals_total_count > 0
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AND crm.report_month >= NOW() - INTERVAL '24 months'
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GROUP BY project_name, report_month
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)
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SELECT
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AVG(realised) AS avg_pm,
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PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY realised) AS median_pm,
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COUNT(DISTINCT obj_id) AS objects,
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COUNT(*) AS observations
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FROM sg
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AVG(month_units) AS avg_pm,
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PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY month_units) AS median_pm,
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COUNT(DISTINCT project_name) AS objects,
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COUNT(*) AS observations
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FROM per_project_month
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"""
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),
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params,
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@ -1182,6 +1199,10 @@ def _district_velocity_trend(db: Session, *, district_name: str) -> tuple[float
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"""Ratio realised: recent_6mo / prior_6mo. >1.5 — рынок горит, <0.7 —
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остывает. Считаем за окно 12 мес: H1 2025 vs H2 2025+.
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Мигрировано с domrf_kn_sale_graph (stale 2026-01) на
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objective_corpus_room_month (обновляется еженедельно).
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deals_total_count заменяет realised (DDU + DKP всего по корпусу).
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Возвращает (ratio, recent_units, prior_units). None если данных мало.
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"""
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row = (
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@ -1189,17 +1210,16 @@ def _district_velocity_trend(db: Session, *, district_name: str) -> tuple[float
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text(
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"""
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SELECT
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SUM(sg.realised) FILTER (WHERE sg.report_month >= DATE '2025-07-01')
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SUM(crm.deals_total_count)
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FILTER (WHERE crm.report_month >= DATE '2025-07-01')
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AS recent,
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SUM(sg.realised) FILTER (WHERE sg.report_month BETWEEN DATE '2025-01-01'
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AND DATE '2025-06-30')
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SUM(crm.deals_total_count)
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FILTER (WHERE crm.report_month BETWEEN DATE '2025-01-01'
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AND DATE '2025-06-30')
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AS prior
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FROM domrf_kn_sale_graph sg
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JOIN domrf_kn_objects o
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ON o.obj_id = sg.obj_id
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AND o.snapshot_date = sg.snapshot_date
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WHERE sg.type = 'apartments'
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AND o.district_name = :dn
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FROM objective_corpus_room_month crm
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WHERE crm.district = :dn
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AND crm.deals_total_count > 0
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"""
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),
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{"dn": district_name},
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@ -1450,37 +1470,40 @@ def _elasticity_coef(
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target_class: str | None,
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elasticity_window_months: int = 24,
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) -> dict[str, Any]:
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"""Fit log-log regression LN(realised) ~ LN(price_avg) on sale_graph
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observations for the same район+class. Returns elasticity (slope), R²,
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n. Falls back to FALLBACK_ELASTICITY if data thin or regression weak."""
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where_class = "AND o.obj_class = :cls" if target_class else ""
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"""Fit log-log regression LN(deals_total_count) ~ LN(price_per_m2) on
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objective_corpus_room_month observations for the same район+class.
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Returns elasticity (slope), R², n.
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Falls back to FALLBACK_ELASTICITY if data thin or regression weak.
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Мигрировано с domrf_kn_sale_graph (stale 2026-01) на
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objective_corpus_room_month (обновляется еженедельно).
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Маппинг: realised → deals_total_count,
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price_avg → deals_total_avg_price_thousand_rub_per_m2.
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LN-масштаб цены (тыс.руб/м²) сохраняет slope relative magnitude — slope
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не зависит от единиц (аддитивный сдвиг в LN пространстве).
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"""
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where_class = "AND LOWER(crm.class) = LOWER(:cls)" if target_class else ""
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params: dict[str, Any] = {
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"rc": region_code,
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"dn": district_name,
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"ew": elasticity_window_months,
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}
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if target_class:
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params["cls"] = target_class
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_ = region_code # retained for backward compat; objective data covers EKB only
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row = (
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db.execute(
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text(
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f"""
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WITH obj_pool AS (
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SELECT o.obj_id
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FROM domrf_kn_objects o
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WHERE o.region_cd = :rc
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AND o.district_name = :dn
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WITH pts AS (
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SELECT
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LN(crm.deals_total_count::float8) AS y,
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LN(crm.deals_total_avg_price_thousand_rub_per_m2::float8) AS x
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FROM objective_corpus_room_month crm
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WHERE crm.district = :dn
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{where_class}
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),
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pts AS (
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SELECT LN(sg.realised)::float8 AS y,
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LN(sg.price_avg)::float8 AS x
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FROM domrf_kn_sale_graph sg
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JOIN obj_pool p ON p.obj_id = sg.obj_id
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WHERE sg.type = 'apartments'
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AND sg.realised IS NOT NULL AND sg.realised > 0
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AND sg.price_avg IS NOT NULL AND sg.price_avg > 0
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AND sg.report_month >= NOW() - (:ew || ' months')::interval
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AND crm.deals_total_count > 0
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AND crm.deals_total_avg_price_thousand_rub_per_m2 > 0
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AND crm.report_month >= NOW() - (:ew || ' months')::interval
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)
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SELECT
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regr_slope(y, x) AS slope,
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@ -1521,83 +1544,64 @@ def _elasticity_per_bucket_coef(
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fallback: dict[str, Any],
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elasticity_window_months: int = 24,
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) -> dict[str, dict[str, Any]]:
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"""Per-bucket эластичность (Tier 3): группируем sale_graph-наблюдения по
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«доминирующему bucket» каждого ЖК (mode total_area из domrf_kn_flats),
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регрессия log-log для каждой группы. Студии vs 80+ м² реагируют на цену
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по-разному.
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"""Per-bucket эластичность (Tier 3): группируем objective_corpus_room_month
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по room_bucket — регрессия log-log для каждой группы.
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Студии vs 80+ м² реагируют на цену по-разному.
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Мигрировано с domrf_kn_sale_graph + domrf_kn_flats (stale 2026-01) на
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objective_corpus_room_month (обновляется еженедельно).
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objective_corpus_room_month уже содержит room_bucket напрямую — нет
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необходимости в MODE-агрегации domrf_kn_flats.
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Маппинг room_bucket → _BUCKET_PRETTY ключи:
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'студия' → '1-Студия'
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'1' → '2-1-к'
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'2' → '3-2-к'
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'3' → '4-3-к'
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'4'/'5+' → '5-80+ м²'
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Returns: dict[bucket_pretty → {elasticity, r2, n, source}]. Если в bucket'е
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меньше 30 точек или регрессия слабая (R²<0.05 либо positive slope) — берём
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общую эластичность из `fallback` со source='fallback_global'.
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"""
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where_class = "AND o.obj_class = :cls" if target_class else ""
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where_class = "AND LOWER(crm.class) = LOWER(:cls)" if target_class else ""
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params: dict[str, Any] = {
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"rc": region_code,
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"dn": district_name,
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"ew": elasticity_window_months,
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}
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if target_class:
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params["cls"] = target_class
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_ = region_code # retained for backward compat; objective data covers EKB only
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rows = (
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db.execute(
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text(
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f"""
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WITH obj_pool AS (
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SELECT o.obj_id
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FROM domrf_kn_objects o
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WHERE o.region_cd = :rc
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AND o.district_name = :dn
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WITH pts AS (
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SELECT
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CASE
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WHEN LOWER(crm.room_bucket) IN ('студия', 'studio', '0')
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THEN '1-Студия'
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WHEN crm.room_bucket = '1' THEN '2-1-к'
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WHEN crm.room_bucket = '2' THEN '3-2-к'
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WHEN crm.room_bucket = '3' THEN '4-3-к'
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WHEN crm.room_bucket IN ('4', '5+') THEN '5-80+ м²'
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ELSE NULL
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END AS bucket,
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LN(crm.deals_total_count::float8) AS y,
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LN(crm.deals_total_avg_price_thousand_rub_per_m2::float8) AS x
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FROM objective_corpus_room_month crm
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WHERE crm.district = :dn
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{where_class}
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),
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obj_bucket AS (
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-- Доминирующий bucket каждого ЖК = MODE по семантике
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-- квартиры (is_studio + rooms). Раньше брали медиану
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-- total_area — ЖК с mix studios+3к попадали в bucket
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-- "1-к" как среднее, что искажало эластичность. MODE
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-- по типу квартиры сохраняет семантику: ЖК с mix даёт
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-- bucket = самый массовый тип.
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--
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-- Fallback на total_area для строк с NULL rooms (быват
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-- в kn-API для нестандартных квартир).
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SELECT
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f.obj_id,
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MODE() WITHIN GROUP (ORDER BY (
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CASE
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WHEN f.is_studio = true THEN '1-Студия'
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WHEN f.rooms = 1 THEN '2-1-к'
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WHEN f.rooms = 2 THEN '3-2-к'
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WHEN f.rooms = 3 THEN '4-3-к'
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WHEN f.rooms >= 4 THEN '5-80+ м²'
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WHEN f.total_area < 30 THEN '1-Студия'
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WHEN f.total_area < 45 THEN '2-1-к'
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WHEN f.total_area < 60 THEN '3-2-к'
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WHEN f.total_area < 80 THEN '4-3-к'
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ELSE '5-80+ м²'
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END
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)) AS bucket
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FROM domrf_kn_flats f
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JOIN obj_pool p ON p.obj_id = f.obj_id
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WHERE f.total_area IS NOT NULL
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AND f.total_area BETWEEN 15 AND 200
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GROUP BY f.obj_id
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),
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pts AS (
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SELECT
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ob.bucket,
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LN(sg.realised)::float8 AS y,
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LN(sg.price_avg)::float8 AS x
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FROM domrf_kn_sale_graph sg
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JOIN obj_bucket ob ON ob.obj_id = sg.obj_id
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WHERE sg.type = 'apartments'
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AND sg.realised IS NOT NULL AND sg.realised > 0
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AND sg.price_avg IS NOT NULL AND sg.price_avg > 0
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AND sg.report_month >= NOW() - (:ew || ' months')::interval
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AND crm.deals_total_count > 0
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AND crm.deals_total_avg_price_thousand_rub_per_m2 > 0
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AND crm.report_month >= NOW() - (:ew || ' months')::interval
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)
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SELECT bucket,
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regr_slope(y, x) AS slope,
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regr_r2(y, x) AS r2,
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COUNT(*)::bigint AS n
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FROM pts
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WHERE bucket IS NOT NULL
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GROUP BY bucket
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"""
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),
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@ -2065,7 +2069,9 @@ def recommend_mix(
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target_class=target_class_for_geo,
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)
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sale_graph_vel_pm = vel["realised_per_month_median"] or vel["realised_per_month_avg"]
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velocity_source = "sale_graph" if sale_graph_vel_pm is not None else "rosreestr_fallback"
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# velocity_source label: "objective" when data available, "rosreestr_fallback" otherwise.
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# Value key kept as "sale_graph" in output for frontend backward-compat (no breaking change).
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velocity_source = "objective" if sale_graph_vel_pm is not None else "rosreestr_fallback"
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elast = _elasticity_coef(
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db,
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@ -1,12 +1,20 @@
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"""Velocity-score — темп продаж конкурентов вокруг участка.
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Per #34 D2: утилизация domrf_kn_sale_graph (15876 строк).
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Per #34 D2: утилизация objective_corpus_room_month (еженедельно обновляемые данные).
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Ранее использовался domrf_kn_sale_graph (последнее обновление 2026-01, устарел).
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Главный demand-сигнал «продастся ли» — среднемесячный объём продаж
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конкурирующих ЖК в радиусе radius_km от участка, нормированный к
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ЕКБ-медиане по region_cd=66.
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ЕКБ-медиане по данным Objective.
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Foundation: domrf_kn_objects (lat/lon, comm_name, obj_class, region_cd),
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domrf_kn_sale_graph (obj_id, report_month, area_sq, realised, type).
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objective_complex_mapping (domrf_obj_id ↔ objective_complex_name),
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objective_corpus_room_month (project_name, deals_total_vol_m2,
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deals_total_count, report_month).
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Linkage: domrf_kn_objects.obj_id
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→ objective_complex_mapping.domrf_obj_id
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→ objective_complex_mapping.objective_complex_name
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→ objective_corpus_room_month.project_name
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"""
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from __future__ import annotations
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@ -63,8 +71,9 @@ def compute_velocity(
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Алгоритм:
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1. Найти ЖК-конкуренты в радиусе radius_km (через lat/lon ST_DWithin).
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2. Взять sale_graph за последние months_window месяцев (latest snapshot).
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3. Посчитать суммарный объём (area_sq > 0, иначе realised * avg_area).
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2. Взять objective_corpus_room_month за последние months_window месяцев
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через objective_complex_mapping (domrf_obj_id → project_name).
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3. Посчитать суммарный объём deals_total_vol_m2.
|
||||
4. Нормировать на ЕКБ-медиану → score 0..1.
|
||||
|
||||
Возвращает None если parcel_geom_wkt невалиден или конкурентов нет.
|
||||
|
|
@ -149,38 +158,36 @@ def compute_velocity(
|
|||
for r in comp_rows
|
||||
}
|
||||
|
||||
# ── Step 2: sale_graph за последние N месяцев (latest snapshot per obj) ──
|
||||
# area_sq = м² за месяц (primary). Если NULL — realised * 45 м² heuristic.
|
||||
# type = 'apartments' — только жильё.
|
||||
# ── Step 2: objective_corpus_room_month за последние N месяцев ───────────
|
||||
# Linkage: domrf_obj_id → objective_complex_mapping → project_name →
|
||||
# objective_corpus_room_month.
|
||||
# deals_total_vol_m2 = DDU + DKP м² за месяц (primary signal).
|
||||
# deals_total_count > 0 — фильтрует месяцы без сделок.
|
||||
# GROUP BY domrf_obj_id чтобы сохранить совместимость с caller (obj_id key).
|
||||
try:
|
||||
with db.begin_nested():
|
||||
sales_rows = (
|
||||
db.execute(
|
||||
text(
|
||||
"""
|
||||
WITH latest_sg AS (
|
||||
SELECT DISTINCT ON (obj_id, report_month)
|
||||
obj_id,
|
||||
report_month,
|
||||
area_sq,
|
||||
realised
|
||||
FROM domrf_kn_sale_graph
|
||||
WHERE obj_id = ANY(:obj_ids)
|
||||
AND type = 'apartments'
|
||||
AND report_month >= (CURRENT_DATE - :window_interval::interval)
|
||||
ORDER BY obj_id, report_month, snapshot_date DESC NULLS LAST
|
||||
WITH mapped AS (
|
||||
SELECT cm.domrf_obj_id AS obj_id,
|
||||
cm.objective_complex_name
|
||||
FROM objective_complex_mapping cm
|
||||
WHERE cm.domrf_obj_id = ANY(:obj_ids)
|
||||
)
|
||||
SELECT
|
||||
obj_id,
|
||||
SUM(
|
||||
COALESCE(area_sq, realised * 45.0)
|
||||
) AS total_sqm,
|
||||
COUNT(DISTINCT report_month) AS months_with_data,
|
||||
MIN(report_month) AS period_start,
|
||||
MAX(report_month) AS period_end
|
||||
FROM latest_sg
|
||||
WHERE area_sq > 0 OR realised > 0
|
||||
GROUP BY obj_id
|
||||
m.obj_id,
|
||||
SUM(crm.deals_total_vol_m2) AS total_sqm,
|
||||
COUNT(DISTINCT crm.report_month) AS months_with_data,
|
||||
MIN(crm.report_month) AS period_start,
|
||||
MAX(crm.report_month) AS period_end
|
||||
FROM objective_corpus_room_month crm
|
||||
JOIN mapped m
|
||||
ON m.objective_complex_name = crm.project_name
|
||||
WHERE crm.report_month >= (CURRENT_DATE - :window_interval::interval)
|
||||
AND crm.deals_total_count > 0
|
||||
GROUP BY m.obj_id
|
||||
"""
|
||||
),
|
||||
{
|
||||
|
|
@ -192,7 +199,7 @@ def compute_velocity(
|
|||
.all()
|
||||
)
|
||||
except Exception:
|
||||
logger.exception("velocity: sale_graph query failed for obj_ids=%s", obj_ids[:5])
|
||||
logger.exception("velocity: objective sales query failed for obj_ids=%s", obj_ids[:5])
|
||||
# SAVEPOINT auto-rollback'нут — outer tx clean
|
||||
return None
|
||||
|
||||
|
|
@ -270,6 +277,11 @@ def compute_velocity(
|
|||
def _get_ekb_median(db: Session, months_window: int = 6) -> float | None:
|
||||
"""ЕКБ-wide медиана monthly velocity (м²/мес) per ЖК — benchmark.
|
||||
|
||||
Источник: objective_corpus_room_month (актуальные данные, обновляется еженедельно).
|
||||
Ранее использовался domrf_kn_sale_graph с фильтром region_cd=66.
|
||||
objective_corpus_room_month не имеет region_cd — данные Objective'а
|
||||
покрывают primarily ЕКБ, что для baseline допустимо.
|
||||
|
||||
Учитываются только ЖК с ≥3 месяцами данных за окно (стабильный сигнал).
|
||||
Fallback к _EKB_MEDIAN_FALLBACK_SQM_PER_MONTH если нет данных в БД.
|
||||
"""
|
||||
|
|
@ -279,38 +291,23 @@ def _get_ekb_median(db: Session, months_window: int = 6) -> float | None:
|
|||
db.execute(
|
||||
text(
|
||||
"""
|
||||
WITH latest_sg AS (
|
||||
SELECT DISTINCT ON (obj_id, report_month)
|
||||
obj_id,
|
||||
area_sq,
|
||||
realised,
|
||||
report_month
|
||||
FROM domrf_kn_sale_graph sg
|
||||
WHERE sg.type = 'apartments'
|
||||
AND sg.report_month >= (CURRENT_DATE - :window_interval::interval)
|
||||
AND EXISTS (
|
||||
SELECT 1 FROM domrf_kn_objects o
|
||||
WHERE o.obj_id = sg.obj_id
|
||||
AND o.region_cd = 66
|
||||
)
|
||||
ORDER BY obj_id, report_month, snapshot_date DESC NULLS LAST
|
||||
),
|
||||
per_obj AS (
|
||||
WITH per_project AS (
|
||||
SELECT
|
||||
obj_id,
|
||||
SUM(COALESCE(area_sq, realised * 45.0)) AS total_sqm,
|
||||
COUNT(DISTINCT report_month) AS months_data
|
||||
FROM latest_sg
|
||||
WHERE area_sq > 0 OR realised > 0
|
||||
GROUP BY obj_id
|
||||
project_name,
|
||||
SUM(deals_total_vol_m2) AS total_sqm,
|
||||
COUNT(DISTINCT report_month) AS months_data
|
||||
FROM objective_corpus_room_month
|
||||
WHERE report_month >= (CURRENT_DATE - :window_interval::interval)
|
||||
AND deals_total_count > 0
|
||||
GROUP BY project_name
|
||||
HAVING COUNT(DISTINCT report_month) >= 3
|
||||
),
|
||||
per_obj_velocity AS (
|
||||
per_project_velocity AS (
|
||||
SELECT total_sqm / months_data AS velocity
|
||||
FROM per_obj
|
||||
FROM per_project
|
||||
)
|
||||
SELECT PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY velocity) AS median
|
||||
FROM per_obj_velocity
|
||||
FROM per_project_velocity
|
||||
"""
|
||||
),
|
||||
{"window_interval": f"{months_window} months"},
|
||||
|
|
|
|||
|
|
@ -1,6 +1,9 @@
|
|||
"""Tests for velocity-score service (#34 D2).
|
||||
|
||||
Mock-based — не требуют живой БД.
|
||||
Источник данных — objective_corpus_room_month (мигрировано с domrf_kn_sale_graph).
|
||||
Mock shape совместим: sales query возвращает те же aliases (obj_id, total_sqm,
|
||||
months_with_data, period_start, period_end) через GROUP BY domrf_obj_id.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
|
@ -79,7 +82,7 @@ def test_no_competitors_returns_none():
|
|||
|
||||
|
||||
def test_no_sales_data_returns_none():
|
||||
"""ЖК есть, но нет данных sale_graph → None."""
|
||||
"""ЖК есть, но нет данных objective_corpus_room_month → None."""
|
||||
comp_rows = [_comp_row(1), _comp_row(2)]
|
||||
db = _make_db(comp_rows=comp_rows, sales_rows=[])
|
||||
result = compute_velocity(db, parcel_geom_wkt=_PARCEL_WKT)
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue