f3d85f4d7a
Active competitor analysis для site-finder. Радиус 0.1-1.5km, time_window month/quarter/year, фильтр obj_class, exclude_obj_ids. Schema correctness (review fixed 4 critical): - snapshot_date (not snapshot_at) - flat_count (not flats_total/flats_sold) — flats_sold/sold_pct null - Velocity migrated domrf_kn_sale_graph -> objective_corpus_room_month - domrf_kn_flats.status (not deal_status) 9 mock tests pass. Closes part of #112 backend.
93 lines
2.3 KiB
Python
93 lines
2.3 KiB
Python
from typing import Any, Literal
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from pydantic import BaseModel, Field
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class ParcelFilter(BaseModel):
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vri: list[str] | None = None
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area_min_sqm: float | None = None
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area_max_sqm: float | None = None
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region: str | None = None
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polygon_geojson: dict[str, Any] | None = None
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text_search: str | None = None
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class ScoringWeights(BaseModel):
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distance_to_center: float = 0.4
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poi_density: float = 0.3
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neighborhood_price: float = 0.3
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class ParcelSearchRequest(BaseModel):
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filters: ParcelFilter = Field(default_factory=ParcelFilter)
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weights: ScoringWeights = Field(default_factory=ScoringWeights)
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limit: int = 50
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class ScoreBreakdown(BaseModel):
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total: float
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distance_to_center: float
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poi_density: float
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neighborhood_price: float
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class ParcelSummary(BaseModel):
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id: str
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cadastral_number: str
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area_sqm: float
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vri: str
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address: str | None
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score: ScoreBreakdown
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class ParcelSearchResponse(BaseModel):
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items: list[ParcelSummary]
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total: int
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class ParcelDetail(ParcelSummary):
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geometry_geojson: dict[str, Any]
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enrichment: dict[str, Any]
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# ── Competitors endpoint schemas ──────────────────────────────────────────────
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TimeWindow = Literal["last_month", "last_quarter", "last_year"]
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ObjClassFilter = Literal["economy", "comfort", "business"]
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class CompetitorsRequest(BaseModel):
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radius_km: float = Field(default=1.0, ge=0.1, le=1.5)
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time_window: TimeWindow = "last_quarter"
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obj_class_filter: ObjClassFilter | None = None
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exclude_obj_ids: list[int] = Field(default_factory=list)
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class Competitor(BaseModel):
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obj_id: int
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comm_name: str | None
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dev_name: str | None
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obj_class: str | None
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distance_m: float
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lat: float
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lng: float
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stage: str | None
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flats_total: int | None
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flats_sold: int | None
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sold_pct: float | None
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velocity_per_month: float
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avg_price_per_m2: float | None
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is_active: bool
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class CompetitorsSummary(BaseModel):
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total_competitors: int
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active_count: int
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weighted_avg_velocity: float
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radius_km: float
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time_window: str
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class CompetitorsResponse(BaseModel):
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competitors: list[Competitor]
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summary: CompetitorsSummary
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