lekss361
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114 lines
4.5 KiB
Python
114 lines
4.5 KiB
Python
"""Buildings — страница «доля квартир дома в продаже» (мигр. 143).
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Дома вторичного рынка, где active_secondary / flat_count_effective >= threshold%.
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Данные берём из готового view v_building_sale_share (логику доли не пересчитываем).
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Endpoints:
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- GET /api/v1/buildings/sale-share — список домов
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- GET /api/v1/buildings/{house_id}/listings — активные вторичные объявления дома
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- GET /api/v1/buildings/sale-share/summary — сводка для слайдера % + coverage
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"""
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from __future__ import annotations
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import logging
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from typing import Annotated
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from fastapi import APIRouter, Depends, Path, Query
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from sqlalchemy import text
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from sqlalchemy.orm import Session
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from app.core.db import get_db
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from app.schemas.buildings import (
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BuildingListing,
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BuildingSaleShare,
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HistogramBucket,
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SaleShareSummary,
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)
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from app.services.buildings_query import (
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HISTOGRAM_BUCKETS,
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build_listings_query,
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build_sale_share_query,
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build_summary_histogram_query,
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build_summary_scalars_query,
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)
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logger = logging.getLogger(__name__)
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router = APIRouter()
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@router.get("/sale-share", response_model=list[BuildingSaleShare])
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async def list_sale_share(
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db: Annotated[Session, Depends(get_db)],
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min_pct: Annotated[float, Query(ge=0, le=1000)] = 5.0,
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max_pct: Annotated[float | None, Query(ge=0, le=1000)] = None,
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city: Annotated[str | None, Query(max_length=120)] = None,
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price_min: Annotated[int | None, Query(ge=0)] = None,
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price_max: Annotated[int | None, Query(ge=0)] = None,
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year_min: Annotated[int | None, Query(ge=1800, le=2100)] = None,
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year_max: Annotated[int | None, Query(ge=1800, le=2100)] = None,
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house_type: Annotated[str | None, Query(max_length=40)] = None,
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sort: Annotated[
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str,
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Query(
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pattern="^(share_desc|share_45d_desc|active_desc|count_45d_desc"
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"|exposure_desc|price_asc|price_desc)$"
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),
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] = "share_desc",
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limit: Annotated[int, Query(ge=1, le=1000)] = 200,
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) -> list[BuildingSaleShare]:
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"""Дома вторички, где ЛЮБОЙ из двух % (now / 45д) >= min_pct (+ фильтры)."""
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sql, args = build_sale_share_query(
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min_pct=min_pct,
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max_pct=max_pct,
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city=city,
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price_min=price_min,
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price_max=price_max,
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year_min=year_min,
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year_max=year_max,
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house_type=house_type,
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sort=sort,
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limit=limit,
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)
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rows = db.execute(text(sql), args).mappings().all()
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return [BuildingSaleShare.model_validate(r) for r in rows]
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@router.get("/{house_id}/listings", response_model=list[BuildingListing])
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async def list_building_listings(
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db: Annotated[Session, Depends(get_db)],
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house_id: Annotated[int, Path(ge=1)],
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) -> list[BuildingListing]:
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"""Активные вторичные объявления в одном доме (для drawer), ORDER BY price."""
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sql, args = build_listings_query(house_id)
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rows = db.execute(text(sql), args).mappings().all()
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return [BuildingListing.model_validate(r) for r in rows]
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@router.get("/sale-share/summary", response_model=SaleShareSummary)
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async def sale_share_summary(
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db: Annotated[Session, Depends(get_db)],
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) -> SaleShareSummary:
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"""Сводка распределения обоих % (now + 45д): coverage, max, p95, две гистограммы."""
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scalars = db.execute(text(build_summary_scalars_query())).mappings().one()
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def _histogram(column: str) -> list[HistogramBucket]:
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rows = db.execute(text(build_summary_histogram_query(column))).mappings().all()
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counts = {str(r["bucket"]): int(r["count"]) for r in rows}
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return [HistogramBucket(bucket=b, count=counts.get(b, 0)) for b in HISTOGRAM_BUCKETS]
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def _opt_float(key: str) -> float | None:
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return float(scalars[key]) if scalars[key] is not None else None
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return SaleShareSummary(
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total_secondary_buildings=int(scalars["total_secondary_buildings"]),
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buildings_with_denominator=int(scalars["buildings_with_denominator"]),
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coverage_pct=float(scalars["coverage_pct"]),
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max_pct=_opt_float("max_pct"),
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p95_pct=_opt_float("p95_pct"),
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max_pct_45d=_opt_float("max_pct_45d"),
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p95_pct_45d=_opt_float("p95_pct_45d"),
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histogram=_histogram("sale_share_pct"),
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histogram_45d=_histogram("sale_share_pct_45d"),
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)
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