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Nominatim/src/nominatim_api/search/db_searches/near_search.py
2025-07-01 22:57:04 +02:00

137 lines
5.5 KiB
Python

# SPDX-License-Identifier: GPL-3.0-or-later
#
# This file is part of Nominatim. (https://nominatim.org)
#
# Copyright (C) 2025 by the Nominatim developer community.
# For a full list of authors see the git log.
"""
Implementation of a category search around a place.
"""
from typing import List, Tuple
import sqlalchemy as sa
from . import base
from ...typing import SaBind
from ...types import SearchDetails, Bbox
from ...connection import SearchConnection
from ... import results as nres
from ..db_search_fields import WeightedCategories
LIMIT_PARAM: SaBind = sa.bindparam('limit')
MIN_RANK_PARAM: SaBind = sa.bindparam('min_rank')
MAX_RANK_PARAM: SaBind = sa.bindparam('max_rank')
COUNTRIES_PARAM: SaBind = sa.bindparam('countries')
class NearSearch(base.AbstractSearch):
""" Category search of a place type near the result of another search.
"""
def __init__(self, penalty: float, categories: WeightedCategories,
search: base.AbstractSearch) -> None:
super().__init__(penalty)
self.search = search
self.categories = categories
async def lookup(self, conn: SearchConnection,
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
results = nres.SearchResults()
base = await self.search.lookup(conn, details)
if not base:
return results
base.sort(key=lambda r: (r.accuracy, r.rank_search))
max_accuracy = base[0].accuracy + 0.5
if base[0].rank_address == 0:
min_rank = 0
max_rank = 0
elif base[0].rank_address < 26:
min_rank = 1
max_rank = min(25, base[0].rank_address + 4)
else:
min_rank = 26
max_rank = 30
base = nres.SearchResults(r for r in base
if (r.source_table == nres.SourceTable.PLACEX
and r.accuracy <= max_accuracy
and r.bbox and r.bbox.area < 20
and r.rank_address >= min_rank
and r.rank_address <= max_rank))
if base:
baseids = [b.place_id for b in base[:5] if b.place_id]
for category, penalty in self.categories:
await self.lookup_category(results, conn, baseids, category, penalty, details)
if len(results) >= details.max_results:
break
return results
async def lookup_category(self, results: nres.SearchResults,
conn: SearchConnection, ids: List[int],
category: Tuple[str, str], penalty: float,
details: SearchDetails) -> None:
""" Find places of the given category near the list of
place ids and add the results to 'results'.
"""
table = await conn.get_class_table(*category)
tgeom = conn.t.placex.alias('pgeom')
if table is None:
# No classtype table available, do a simplified lookup in placex.
table = conn.t.placex
sql = sa.select(table.c.place_id,
sa.func.min(tgeom.c.centroid.ST_Distance(table.c.centroid))
.label('dist'))\
.join(tgeom, table.c.geometry.intersects(tgeom.c.centroid.ST_Expand(0.01)))\
.where(table.c.class_ == category[0])\
.where(table.c.type == category[1])
else:
# Use classtype table. We can afford to use a larger
# radius for the lookup.
sql = sa.select(table.c.place_id,
sa.func.min(tgeom.c.centroid.ST_Distance(table.c.centroid))
.label('dist'))\
.join(tgeom,
table.c.centroid.ST_CoveredBy(
sa.case((sa.and_(tgeom.c.rank_address > 9,
tgeom.c.geometry.is_area()),
tgeom.c.geometry),
else_=tgeom.c.centroid.ST_Expand(0.05))))
inner = sql.where(tgeom.c.place_id.in_(ids))\
.group_by(table.c.place_id).subquery()
t = conn.t.placex
sql = base.select_placex(t).add_columns((-inner.c.dist).label('importance'))\
.join(inner, inner.c.place_id == t.c.place_id)\
.order_by(inner.c.dist)
sql = sql.where(base.no_index(t.c.rank_address).between(MIN_RANK_PARAM, MAX_RANK_PARAM))
if details.countries:
sql = sql.where(t.c.country_code.in_(COUNTRIES_PARAM))
if details.excluded:
sql = sql.where(base.exclude_places(t))
if details.layers is not None:
sql = sql.where(base.filter_by_layer(t, details.layers))
sql = sql.limit(LIMIT_PARAM)
bind_params = {'limit': details.max_results,
'min_rank': details.min_rank,
'max_rank': details.max_rank,
'excluded': details.excluded,
'countries': details.countries}
for row in await conn.execute(sql, bind_params):
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
result.accuracy = self.penalty + penalty
result.bbox = Bbox.from_wkb(row.bbox)
results.append(result)