83 lines
2.5 KiB
Python
83 lines
2.5 KiB
Python
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"""Nearby-place search with iterative radius expansion.
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Sorts candidate places by distance ascending and grows the search radius by
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``step_m`` until at least ``min_results`` places are found (or ``max_radius_m``
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is hit, as a safety cap against runaway loops in sparsely-covered areas).
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Reserved for a future v2 extension: ``speed``/``heading`` inputs to bias
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results toward the user's direction of travel and to pick a shorter content
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``length`` automatically when moving fast through a dense cluster of places.
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Not implemented in this iteration — callers should not pass them yet.
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"""
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from dataclasses import dataclass
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from geoalchemy2 import Geometry
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from sqlalchemy import Row, and_, cast, func, select
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from sqlalchemy.orm import Session
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from app.models.city import City
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from app.models.enums import ContentLanguage, ContentLength
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from app.models.place import Place
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from app.models.place_content import PlaceContent
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@dataclass
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class NearbyResult:
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search_radius_m: int
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rows: list[Row]
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def find_nearby(
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db: Session,
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*,
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lat: float,
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lon: float,
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language: ContentLanguage,
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length: ContentLength,
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city_slug: str | None = None,
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min_results: int = 5,
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initial_radius_m: int = 300,
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step_m: int = 200,
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max_radius_m: int = 5000,
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) -> NearbyResult:
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city_id: int | None = None
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if city_slug is not None:
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city_id = db.scalar(select(City.id).where(City.slug == city_slug))
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origin = func.ST_GeogFromText(f"SRID=4326;POINT({lon} {lat})")
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distance_expr = func.ST_Distance(Place.location, origin)
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base_stmt = (
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select(
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Place,
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PlaceContent,
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distance_expr.label("distance_m"),
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func.ST_X(cast(Place.location, Geometry)).label("lon"),
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func.ST_Y(cast(Place.location, Geometry)).label("lat"),
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)
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.join(
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PlaceContent,
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and_(
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PlaceContent.place_id == Place.id,
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PlaceContent.language == language,
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PlaceContent.length == length,
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),
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)
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.where(Place.is_active.is_(True))
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.order_by(distance_expr)
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)
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if city_id is not None:
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base_stmt = base_stmt.where(Place.city_id == city_id)
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radius = initial_radius_m
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rows: list[Row] = []
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while True:
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stmt = base_stmt.where(func.ST_DWithin(Place.location, origin, radius))
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rows = db.execute(stmt).all()
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if len(rows) >= min_results or radius >= max_radius_m:
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break
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radius += step_m
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return NearbyResult(search_radius_m=radius, rows=rows)
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