split db_searches moving each class in its own file

This commit is contained in:
Sarah Hoffmann
2025-07-01 22:57:04 +02:00
parent a7797f8b37
commit 11d624e92a
8 changed files with 1043 additions and 867 deletions

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# 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.
"""
Module implementing the actual database accesses for forward search.
"""
from .base import AbstractSearch as AbstractSearch
from .near_search import NearSearch as NearSearch
from .poi_search import PoiSearch as PoiSearch
from .country_search import CountrySearch as CountrySearch
from .postcode_search import PostcodeSearch as PostcodeSearch
from .place_search import PlaceSearch as PlaceSearch

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# 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.
"""
Interface for classes implementing a database search.
"""
from typing import Callable, List
import abc
import sqlalchemy as sa
from ...typing import SaFromClause, SaSelect, SaColumn, SaExpression, SaLambdaSelect
from ...sql.sqlalchemy_types import Geometry
from ...connection import SearchConnection
from ...types import SearchDetails, DataLayer, GeometryFormat
from ...results import SearchResults
class AbstractSearch(abc.ABC):
""" Encapuslation of a single lookup in the database.
"""
SEARCH_PRIO: int = 2
def __init__(self, penalty: float) -> None:
self.penalty = penalty
@abc.abstractmethod
async def lookup(self, conn: SearchConnection, details: SearchDetails) -> SearchResults:
""" Find results for the search in the database.
"""
def select_placex(t: SaFromClause) -> SaSelect:
""" Return the basic select query for placex which returns all
fields necessary to fill a Nominatim result. 't' must either be
the placex table or a subquery returning appropriate fields from
a placex-related query.
"""
return sa.select(t.c.place_id, t.c.osm_type, t.c.osm_id, t.c.name,
t.c.class_, t.c.type,
t.c.address, t.c.extratags,
t.c.housenumber, t.c.postcode, t.c.country_code,
t.c.wikipedia,
t.c.parent_place_id, t.c.rank_address, t.c.rank_search,
t.c.linked_place_id, t.c.admin_level,
t.c.centroid,
t.c.geometry.ST_Expand(0).label('bbox'))
def exclude_places(t: SaFromClause) -> Callable[[], SaExpression]:
""" Return an expression to exclude place IDs from the list in the
SearchDetails.
Requires the excluded IDs to be supplied as a bind parameter in SQL.
"""
return lambda: t.c.place_id.not_in(sa.bindparam('excluded'))
def filter_by_layer(table: SaFromClause, layers: DataLayer) -> SaColumn:
""" Return an expression that filters the given table by layers.
"""
orexpr: List[SaExpression] = []
if layers & DataLayer.ADDRESS and layers & DataLayer.POI:
orexpr.append(no_index(table.c.rank_address).between(1, 30))
elif layers & DataLayer.ADDRESS:
orexpr.append(no_index(table.c.rank_address).between(1, 29))
orexpr.append(sa.func.IsAddressPoint(table))
elif layers & DataLayer.POI:
orexpr.append(sa.and_(no_index(table.c.rank_address) == 30,
table.c.class_.not_in(('place', 'building'))))
if layers & DataLayer.MANMADE:
exclude = []
if not layers & DataLayer.RAILWAY:
exclude.append('railway')
if not layers & DataLayer.NATURAL:
exclude.extend(('natural', 'water', 'waterway'))
orexpr.append(sa.and_(table.c.class_.not_in(tuple(exclude)),
no_index(table.c.rank_address) == 0))
else:
include = []
if layers & DataLayer.RAILWAY:
include.append('railway')
if layers & DataLayer.NATURAL:
include.extend(('natural', 'water', 'waterway'))
orexpr.append(sa.and_(table.c.class_.in_(tuple(include)),
no_index(table.c.rank_address) == 0))
if len(orexpr) == 1:
return orexpr[0]
return sa.or_(*orexpr)
def no_index(expr: SaColumn) -> SaColumn:
""" Wrap the given expression, so that the query planner will
refrain from using the expression for index lookup.
"""
return sa.func.coalesce(sa.null(), expr)
def filter_by_area(sql: SaSelect, t: SaFromClause,
details: SearchDetails, avoid_index: bool = False) -> SaSelect:
""" Apply SQL statements for filtering by viewbox and near point,
if applicable.
"""
if details.near is not None and details.near_radius is not None:
if details.near_radius < 0.1 and not avoid_index:
sql = sql.where(
t.c.geometry.within_distance(sa.bindparam('near', type_=Geometry),
sa.bindparam('near_radius')))
else:
sql = sql.where(
t.c.geometry.ST_Distance(
sa.bindparam('near', type_=Geometry)) <= sa.bindparam('near_radius'))
if details.viewbox is not None and details.bounded_viewbox:
sql = sql.where(t.c.geometry.intersects(sa.bindparam('viewbox', type_=Geometry),
use_index=not avoid_index and
details.viewbox.area < 0.2))
return sql
def add_geometry_columns(sql: SaLambdaSelect, col: SaColumn, details: SearchDetails) -> SaSelect:
""" Add columns for requested geometry formats and return the new query.
"""
out = []
if details.geometry_simplification > 0.0:
col = sa.func.ST_SimplifyPreserveTopology(col, details.geometry_simplification)
if details.geometry_output & GeometryFormat.GEOJSON:
out.append(sa.func.ST_AsGeoJSON(col, 7).label('geometry_geojson'))
if details.geometry_output & GeometryFormat.TEXT:
out.append(sa.func.ST_AsText(col).label('geometry_text'))
if details.geometry_output & GeometryFormat.KML:
out.append(sa.func.ST_AsKML(col, 7).label('geometry_kml'))
if details.geometry_output & GeometryFormat.SVG:
out.append(sa.func.ST_AsSVG(col, 0, 7).label('geometry_svg'))
return sql.add_columns(*out)

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# 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 searches for a country.
"""
import sqlalchemy as sa
from . import base
from ..db_search_fields import SearchData
from ... import results as nres
from ...connection import SearchConnection
from ...types import SearchDetails, Bbox
class CountrySearch(base.AbstractSearch):
""" Search for a country name or country code.
"""
SEARCH_PRIO = 0
def __init__(self, sdata: SearchData) -> None:
super().__init__(sdata.penalty)
self.countries = sdata.countries
async def lookup(self, conn: SearchConnection,
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
t = conn.t.placex
ccodes = self.countries.values
sql = base.select_placex(t)\
.add_columns(t.c.importance)\
.where(t.c.country_code.in_(ccodes))\
.where(t.c.rank_address == 4)
if details.geometry_output:
sql = base.add_geometry_columns(sql, t.c.geometry, details)
if details.excluded:
sql = sql.where(base.exclude_places(t))
sql = base.filter_by_area(sql, t, details)
bind_params = {
'excluded': details.excluded,
'viewbox': details.viewbox,
'near': details.near,
'near_radius': details.near_radius
}
results = nres.SearchResults()
for row in await conn.execute(sql, bind_params):
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
result.bbox = Bbox.from_wkb(row.bbox)
results.append(result)
if not results:
results = await self.lookup_in_country_table(conn, details)
if results:
details.min_rank = min(5, details.max_rank)
details.max_rank = min(25, details.max_rank)
return results
async def lookup_in_country_table(self, conn: SearchConnection,
details: SearchDetails) -> nres.SearchResults:
""" Look up the country in the fallback country tables.
"""
# Avoid the fallback search when this is a more search. Country results
# usually are in the first batch of results and it is not possible
# to exclude these fallbacks.
if details.excluded:
return nres.SearchResults()
t = conn.t.country_name
tgrid = conn.t.country_grid
sql = sa.select(tgrid.c.country_code,
tgrid.c.geometry.ST_Centroid().ST_Collect().ST_Centroid()
.label('centroid'),
tgrid.c.geometry.ST_Collect().ST_Expand(0).label('bbox'))\
.where(tgrid.c.country_code.in_(self.countries.values))\
.group_by(tgrid.c.country_code)
sql = base.filter_by_area(sql, tgrid, details, avoid_index=True)
sub = sql.subquery('grid')
sql = sa.select(t.c.country_code,
t.c.name.merge(t.c.derived_name).label('name'),
sub.c.centroid, sub.c.bbox)\
.join(sub, t.c.country_code == sub.c.country_code)
if details.geometry_output:
sql = base.add_geometry_columns(sql, sub.c.centroid, details)
bind_params = {
'viewbox': details.viewbox,
'near': details.near,
'near_radius': details.near_radius
}
results = nres.SearchResults()
for row in await conn.execute(sql, bind_params):
result = nres.create_from_country_row(row, nres.SearchResult)
assert result
result.bbox = Bbox.from_wkb(row.bbox)
result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
results.append(result)
return results

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# 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)

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# 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 search for a named place.
"""
from typing import cast, List, AsyncIterator
import sqlalchemy as sa
from . import base
from ...typing import SaBind, SaExpression, SaColumn, SaFromClause, SaScalarSelect
from ...types import SearchDetails, Bbox
from ...sql.sqlalchemy_types import Geometry
from ...connection import SearchConnection
from ... import results as nres
from ..db_search_fields import SearchData
LIMIT_PARAM: SaBind = sa.bindparam('limit')
MIN_RANK_PARAM: SaBind = sa.bindparam('min_rank')
MAX_RANK_PARAM: SaBind = sa.bindparam('max_rank')
VIEWBOX_PARAM: SaBind = sa.bindparam('viewbox', type_=Geometry)
VIEWBOX2_PARAM: SaBind = sa.bindparam('viewbox2', type_=Geometry)
NEAR_PARAM: SaBind = sa.bindparam('near', type_=Geometry)
NEAR_RADIUS_PARAM: SaBind = sa.bindparam('near_radius')
COUNTRIES_PARAM: SaBind = sa.bindparam('countries')
def _int_list_to_subquery(inp: List[int]) -> 'sa.Subquery':
""" Create a subselect that returns the given list of integers
as rows in the column 'nr'.
"""
vtab = sa.func.JsonArrayEach(sa.type_coerce(inp, sa.JSON))\
.table_valued(sa.column('value', type_=sa.JSON))
return sa.select(sa.cast(sa.cast(vtab.c.value, sa.Text), sa.Integer).label('nr')).subquery()
def _interpolated_position(table: SaFromClause, nr: SaColumn) -> SaColumn:
pos = sa.cast(nr - table.c.startnumber, sa.Float) / (table.c.endnumber - table.c.startnumber)
return sa.case(
(table.c.endnumber == table.c.startnumber, table.c.linegeo.ST_Centroid()),
else_=table.c.linegeo.ST_LineInterpolatePoint(pos)).label('centroid')
def _make_interpolation_subquery(table: SaFromClause, inner: SaFromClause,
numerals: List[int], details: SearchDetails) -> SaScalarSelect:
all_ids = sa.func.ArrayAgg(table.c.place_id)
sql = sa.select(all_ids).where(table.c.parent_place_id == inner.c.place_id)
if len(numerals) == 1:
sql = sql.where(sa.between(numerals[0], table.c.startnumber, table.c.endnumber))\
.where((numerals[0] - table.c.startnumber) % table.c.step == 0)
else:
sql = sql.where(sa.or_(
*(sa.and_(sa.between(n, table.c.startnumber, table.c.endnumber),
(n - table.c.startnumber) % table.c.step == 0)
for n in numerals)))
if details.excluded:
sql = sql.where(base.exclude_places(table))
return sql.scalar_subquery()
async def _get_placex_housenumbers(conn: SearchConnection,
place_ids: List[int],
details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
t = conn.t.placex
sql = base.select_placex(t).add_columns(t.c.importance)\
.where(t.c.place_id.in_(place_ids))
if details.geometry_output:
sql = base.add_geometry_columns(sql, t.c.geometry, details)
for row in await conn.execute(sql):
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
result.bbox = Bbox.from_wkb(row.bbox)
yield result
async def _get_osmline(conn: SearchConnection, place_ids: List[int],
numerals: List[int],
details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
t = conn.t.osmline
values = _int_list_to_subquery(numerals)
sql = sa.select(t.c.place_id, t.c.osm_id,
t.c.parent_place_id, t.c.address,
values.c.nr.label('housenumber'),
_interpolated_position(t, values.c.nr),
t.c.postcode, t.c.country_code)\
.where(t.c.place_id.in_(place_ids))\
.join(values, values.c.nr.between(t.c.startnumber, t.c.endnumber))
if details.geometry_output:
sub = sql.subquery()
sql = base.add_geometry_columns(sa.select(sub), sub.c.centroid, details)
for row in await conn.execute(sql):
result = nres.create_from_osmline_row(row, nres.SearchResult)
assert result
yield result
async def _get_tiger(conn: SearchConnection, place_ids: List[int],
numerals: List[int], osm_id: int,
details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
t = conn.t.tiger
values = _int_list_to_subquery(numerals)
sql = sa.select(t.c.place_id, t.c.parent_place_id,
sa.literal('W').label('osm_type'),
sa.literal(osm_id).label('osm_id'),
values.c.nr.label('housenumber'),
_interpolated_position(t, values.c.nr),
t.c.postcode)\
.where(t.c.place_id.in_(place_ids))\
.join(values, values.c.nr.between(t.c.startnumber, t.c.endnumber))
if details.geometry_output:
sub = sql.subquery()
sql = base.add_geometry_columns(sa.select(sub), sub.c.centroid, details)
for row in await conn.execute(sql):
result = nres.create_from_tiger_row(row, nres.SearchResult)
assert result
yield result
class PlaceSearch(base.AbstractSearch):
""" Generic search for an address or named place.
"""
SEARCH_PRIO = 1
def __init__(self, extra_penalty: float, sdata: SearchData, expected_count: int) -> None:
super().__init__(sdata.penalty + extra_penalty)
self.countries = sdata.countries
self.postcodes = sdata.postcodes
self.housenumbers = sdata.housenumbers
self.qualifiers = sdata.qualifiers
self.lookups = sdata.lookups
self.rankings = sdata.rankings
self.expected_count = expected_count
def _inner_search_name_cte(self, conn: SearchConnection,
details: SearchDetails) -> 'sa.CTE':
""" Create a subquery that preselects the rows in the search_name
table.
"""
t = conn.t.search_name
penalty: SaExpression = sa.literal(self.penalty)
for ranking in self.rankings:
penalty += ranking.sql_penalty(t)
sql = sa.select(t.c.place_id, t.c.search_rank, t.c.address_rank,
t.c.country_code, t.c.centroid,
t.c.name_vector, t.c.nameaddress_vector,
sa.case((t.c.importance > 0, t.c.importance),
else_=0.40001-(sa.cast(t.c.search_rank, sa.Float())/75))
.label('importance'),
penalty.label('penalty'))
for lookup in self.lookups:
sql = sql.where(lookup.sql_condition(t))
if self.countries:
sql = sql.where(t.c.country_code.in_(self.countries.values))
if self.postcodes:
# if a postcode is given, don't search for state or country level objects
sql = sql.where(t.c.address_rank > 9)
if self.expected_count > 10000:
# Many results expected. Restrict by postcode.
tpc = conn.t.postcode
sql = sql.where(sa.select(tpc.c.postcode)
.where(tpc.c.postcode.in_(self.postcodes.values))
.where(t.c.centroid.within_distance(tpc.c.geometry, 0.4))
.exists())
if details.viewbox is not None:
if details.bounded_viewbox:
sql = sql.where(t.c.centroid
.intersects(VIEWBOX_PARAM,
use_index=details.viewbox.area < 0.2))
elif not self.postcodes and not self.housenumbers and self.expected_count >= 10000:
sql = sql.where(t.c.centroid
.intersects(VIEWBOX2_PARAM,
use_index=details.viewbox.area < 0.5))
if details.near is not None and details.near_radius is not None:
if details.near_radius < 0.1:
sql = sql.where(t.c.centroid.within_distance(NEAR_PARAM,
NEAR_RADIUS_PARAM))
else:
sql = sql.where(t.c.centroid
.ST_Distance(NEAR_PARAM) < NEAR_RADIUS_PARAM)
if self.housenumbers:
sql = sql.where(t.c.address_rank.between(16, 30))
else:
if details.excluded:
sql = sql.where(base.exclude_places(t))
if details.min_rank > 0:
sql = sql.where(sa.or_(t.c.address_rank >= MIN_RANK_PARAM,
t.c.search_rank >= MIN_RANK_PARAM))
if details.max_rank < 30:
sql = sql.where(sa.or_(t.c.address_rank <= MAX_RANK_PARAM,
t.c.search_rank <= MAX_RANK_PARAM))
inner = sql.limit(10000).order_by(sa.desc(sa.text('importance'))).subquery()
sql = sa.select(inner.c.place_id, inner.c.search_rank, inner.c.address_rank,
inner.c.country_code, inner.c.centroid, inner.c.importance,
inner.c.penalty)
# If the query is not an address search or has a geographic preference,
# preselect most important items to restrict the number of places
# that need to be looked up in placex.
if not self.housenumbers\
and (details.viewbox is None or details.bounded_viewbox)\
and (details.near is None or details.near_radius is not None)\
and not self.qualifiers:
sql = sql.add_columns(sa.func.first_value(inner.c.penalty - inner.c.importance)
.over(order_by=inner.c.penalty - inner.c.importance)
.label('min_penalty'))
inner = sql.subquery()
sql = sa.select(inner.c.place_id, inner.c.search_rank, inner.c.address_rank,
inner.c.country_code, inner.c.centroid, inner.c.importance,
inner.c.penalty)\
.where(inner.c.penalty - inner.c.importance < inner.c.min_penalty + 0.5)
return sql.cte('searches')
async def lookup(self, conn: SearchConnection,
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
t = conn.t.placex
tsearch = self._inner_search_name_cte(conn, details)
sql = base.select_placex(t).join(tsearch, t.c.place_id == tsearch.c.place_id)
if details.geometry_output:
sql = base.add_geometry_columns(sql, t.c.geometry, details)
penalty: SaExpression = tsearch.c.penalty
if self.postcodes:
tpc = conn.t.postcode
pcs = self.postcodes.values
pc_near = sa.select(sa.func.min(tpc.c.geometry.ST_Distance(t.c.centroid)))\
.where(tpc.c.postcode.in_(pcs))\
.scalar_subquery()
penalty += sa.case((t.c.postcode.in_(pcs), 0.0),
else_=sa.func.coalesce(pc_near, cast(SaColumn, 2.0)))
if details.viewbox is not None and not details.bounded_viewbox:
penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM, use_index=False), 0.0),
(t.c.geometry.intersects(VIEWBOX2_PARAM, use_index=False), 0.5),
else_=1.0)
if details.near is not None:
sql = sql.add_columns((-tsearch.c.centroid.ST_Distance(NEAR_PARAM))
.label('importance'))
sql = sql.order_by(sa.desc(sa.text('importance')))
else:
sql = sql.order_by(penalty - tsearch.c.importance)
sql = sql.add_columns(tsearch.c.importance)
sql = sql.add_columns(penalty.label('accuracy'))\
.order_by(sa.text('accuracy'))
if self.housenumbers:
hnr_list = '|'.join(self.housenumbers.values)
inner = sql.where(sa.or_(tsearch.c.address_rank < 30,
sa.func.RegexpWord(hnr_list, t.c.housenumber)))\
.subquery()
# Housenumbers from placex
thnr = conn.t.placex.alias('hnr')
pid_list = sa.func.ArrayAgg(thnr.c.place_id)
place_sql = sa.select(pid_list)\
.where(thnr.c.parent_place_id == inner.c.place_id)\
.where(sa.func.RegexpWord(hnr_list, thnr.c.housenumber))\
.where(thnr.c.linked_place_id == None)\
.where(thnr.c.indexed_status == 0)
if details.excluded:
place_sql = place_sql.where(thnr.c.place_id.not_in(sa.bindparam('excluded')))
if self.qualifiers:
place_sql = place_sql.where(self.qualifiers.sql_restrict(thnr))
numerals = [int(n) for n in self.housenumbers.values
if n.isdigit() and len(n) < 8]
interpol_sql: SaColumn
tiger_sql: SaColumn
if numerals and \
(not self.qualifiers or ('place', 'house') in self.qualifiers.values):
# Housenumbers from interpolations
interpol_sql = _make_interpolation_subquery(conn.t.osmline, inner,
numerals, details)
# Housenumbers from Tiger
tiger_sql = sa.case((inner.c.country_code == 'us',
_make_interpolation_subquery(conn.t.tiger, inner,
numerals, details)
), else_=None)
else:
interpol_sql = sa.null()
tiger_sql = sa.null()
unsort = sa.select(inner, place_sql.scalar_subquery().label('placex_hnr'),
interpol_sql.label('interpol_hnr'),
tiger_sql.label('tiger_hnr')).subquery('unsort')
sql = sa.select(unsort)\
.order_by(sa.case((unsort.c.placex_hnr != None, 1),
(unsort.c.interpol_hnr != None, 2),
(unsort.c.tiger_hnr != None, 3),
else_=4),
unsort.c.accuracy)
else:
sql = sql.where(t.c.linked_place_id == None)\
.where(t.c.indexed_status == 0)
if self.qualifiers:
sql = sql.where(self.qualifiers.sql_restrict(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,
'viewbox': details.viewbox,
'viewbox2': details.viewbox_x2,
'near': details.near,
'near_radius': details.near_radius,
'excluded': details.excluded,
'countries': details.countries
}
results = nres.SearchResults()
for row in await conn.execute(sql, bind_params):
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
result.bbox = Bbox.from_wkb(row.bbox)
result.accuracy = row.accuracy
if self.housenumbers and row.rank_address < 30:
if row.placex_hnr:
subs = _get_placex_housenumbers(conn, row.placex_hnr, details)
elif row.interpol_hnr:
subs = _get_osmline(conn, row.interpol_hnr, numerals, details)
elif row.tiger_hnr:
subs = _get_tiger(conn, row.tiger_hnr, numerals, row.osm_id, details)
else:
subs = None
if subs is not None:
async for sub in subs:
assert sub.housenumber
sub.accuracy = result.accuracy
if not any(nr in self.housenumbers.values
for nr in sub.housenumber.split(';')):
sub.accuracy += 0.6
results.append(sub)
# Only add the street as a result, if it meets all other
# filter conditions.
if (not details.excluded or result.place_id not in details.excluded)\
and (not self.qualifiers or result.category in self.qualifiers.values)\
and result.rank_address >= details.min_rank:
result.accuracy += 1.0 # penalty for missing housenumber
results.append(result)
else:
results.append(result)
return results

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# 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 category search.
"""
from typing import List
import sqlalchemy as sa
from . import base
from ..db_search_fields import SearchData
from ... import results as nres
from ...typing import SaBind, SaRow, SaSelect, SaLambdaSelect
from ...sql.sqlalchemy_types import Geometry
from ...connection import SearchConnection
from ...types import SearchDetails, Bbox
LIMIT_PARAM: SaBind = sa.bindparam('limit')
VIEWBOX_PARAM: SaBind = sa.bindparam('viewbox', type_=Geometry)
NEAR_PARAM: SaBind = sa.bindparam('near', type_=Geometry)
NEAR_RADIUS_PARAM: SaBind = sa.bindparam('near_radius')
class PoiSearch(base.AbstractSearch):
""" Category search in a geographic area.
"""
def __init__(self, sdata: SearchData) -> None:
super().__init__(sdata.penalty)
self.qualifiers = sdata.qualifiers
self.countries = sdata.countries
async def lookup(self, conn: SearchConnection,
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
bind_params = {
'limit': details.max_results,
'viewbox': details.viewbox,
'near': details.near,
'near_radius': details.near_radius,
'excluded': details.excluded
}
t = conn.t.placex
rows: List[SaRow] = []
if details.near and details.near_radius is not None and details.near_radius < 0.2:
# simply search in placex table
def _base_query() -> SaSelect:
return base.select_placex(t) \
.add_columns((-t.c.centroid.ST_Distance(NEAR_PARAM))
.label('importance'))\
.where(t.c.linked_place_id == None) \
.where(t.c.geometry.within_distance(NEAR_PARAM, NEAR_RADIUS_PARAM)) \
.order_by(t.c.centroid.ST_Distance(NEAR_PARAM)) \
.limit(LIMIT_PARAM)
classtype = self.qualifiers.values
if len(classtype) == 1:
cclass, ctype = classtype[0]
sql: SaLambdaSelect = sa.lambda_stmt(
lambda: _base_query().where(t.c.class_ == cclass)
.where(t.c.type == ctype))
else:
sql = _base_query().where(sa.or_(*(sa.and_(t.c.class_ == cls, t.c.type == typ)
for cls, typ in classtype)))
if self.countries:
sql = sql.where(t.c.country_code.in_(self.countries.values))
if details.viewbox is not None and details.bounded_viewbox:
sql = sql.where(t.c.geometry.intersects(VIEWBOX_PARAM))
rows.extend(await conn.execute(sql, bind_params))
else:
# use the class type tables
for category in self.qualifiers.values:
table = await conn.get_class_table(*category)
if table is not None:
sql = base.select_placex(t)\
.add_columns(t.c.importance)\
.join(table, t.c.place_id == table.c.place_id)\
.where(t.c.class_ == category[0])\
.where(t.c.type == category[1])
if details.viewbox is not None and details.bounded_viewbox:
sql = sql.where(table.c.centroid.intersects(VIEWBOX_PARAM))
if details.near and details.near_radius is not None:
sql = sql.order_by(table.c.centroid.ST_Distance(NEAR_PARAM))\
.where(table.c.centroid.within_distance(NEAR_PARAM,
NEAR_RADIUS_PARAM))
if self.countries:
sql = sql.where(t.c.country_code.in_(self.countries.values))
sql = sql.limit(LIMIT_PARAM)
rows.extend(await conn.execute(sql, bind_params))
results = nres.SearchResults()
for row in rows:
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
result.accuracy = self.penalty + self.qualifiers.get_penalty((row.class_, row.type))
result.bbox = Bbox.from_wkb(row.bbox)
results.append(result)
return results

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# 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 search for a postcode.
"""
import sqlalchemy as sa
from . import base
from ...typing import SaBind, SaExpression
from ...sql.sqlalchemy_types import Geometry, IntArray
from ...connection import SearchConnection
from ...types import SearchDetails, Bbox
from ... import results as nres
from ..db_search_fields import SearchData
LIMIT_PARAM: SaBind = sa.bindparam('limit')
VIEWBOX_PARAM: SaBind = sa.bindparam('viewbox', type_=Geometry)
VIEWBOX2_PARAM: SaBind = sa.bindparam('viewbox2', type_=Geometry)
NEAR_PARAM: SaBind = sa.bindparam('near', type_=Geometry)
class PostcodeSearch(base.AbstractSearch):
""" Search for a postcode.
"""
def __init__(self, extra_penalty: float, sdata: SearchData) -> None:
super().__init__(sdata.penalty + extra_penalty)
self.countries = sdata.countries
self.postcodes = sdata.postcodes
self.lookups = sdata.lookups
self.rankings = sdata.rankings
async def lookup(self, conn: SearchConnection,
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
t = conn.t.postcode
pcs = self.postcodes.values
sql = sa.select(t.c.place_id, t.c.parent_place_id,
t.c.rank_search, t.c.rank_address,
t.c.postcode, t.c.country_code,
t.c.geometry.label('centroid'))\
.where(t.c.postcode.in_(pcs))
if details.geometry_output:
sql = base.add_geometry_columns(sql, t.c.geometry, details)
penalty: SaExpression = sa.literal(self.penalty)
if details.viewbox is not None and not details.bounded_viewbox:
penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM), 0.0),
(t.c.geometry.intersects(VIEWBOX2_PARAM), 0.5),
else_=1.0)
if details.near is not None:
sql = sql.order_by(t.c.geometry.ST_Distance(NEAR_PARAM))
sql = base.filter_by_area(sql, t, details)
if self.countries:
sql = sql.where(t.c.country_code.in_(self.countries.values))
if details.excluded:
sql = sql.where(base.exclude_places(t))
if self.lookups:
assert len(self.lookups) == 1
tsearch = conn.t.search_name
sql = sql.where(tsearch.c.place_id == t.c.parent_place_id)\
.where((tsearch.c.name_vector + tsearch.c.nameaddress_vector)
.contains(sa.type_coerce(self.lookups[0].tokens,
IntArray)))
# Do NOT add rerank penalties based on the address terms.
# The standard rerank penalty only checks the address vector
# while terms may appear in name and address vector. This would
# lead to overly high penalties.
# We assume that a postcode is precise enough to not require
# additional full name matches.
penalty += sa.case(*((t.c.postcode == v, p) for v, p in self.postcodes),
else_=1.0)
sql = sql.add_columns(penalty.label('accuracy'))
sql = sql.order_by('accuracy').limit(LIMIT_PARAM)
bind_params = {
'limit': details.max_results,
'viewbox': details.viewbox,
'viewbox2': details.viewbox_x2,
'near': details.near,
'near_radius': details.near_radius,
'excluded': details.excluded
}
results = nres.SearchResults()
for row in await conn.execute(sql, bind_params):
p = conn.t.placex
placex_sql = base.select_placex(p)\
.add_columns(p.c.importance)\
.where(sa.text("""class = 'boundary'
AND type = 'postal_code'
AND osm_type = 'R'"""))\
.where(p.c.country_code == row.country_code)\
.where(p.c.postcode == row.postcode)\
.limit(1)
if details.geometry_output:
placex_sql = base.add_geometry_columns(placex_sql, p.c.geometry, details)
for prow in await conn.execute(placex_sql, bind_params):
result = nres.create_from_placex_row(prow, nres.SearchResult)
if result is not None:
result.bbox = Bbox.from_wkb(prow.bbox)
break
else:
result = nres.create_from_postcode_row(row, nres.SearchResult)
assert result
if result.place_id not in details.excluded:
result.accuracy = row.accuracy
results.append(result)
return results