"""
Implementation of reverse geocoding.
"""
-from typing import Optional, List, Callable, Type, Tuple, Dict, Any
+from typing import Optional, List, Callable, Type, Tuple, Dict, Any, cast, Union
+import functools
import sqlalchemy as sa
-from nominatim.typing import SaColumn, SaSelect, SaFromClause, SaLabel, SaRow, SaBind
+from nominatim.typing import SaColumn, SaSelect, SaFromClause, SaLabel, SaRow,\
+ SaBind, SaLambdaSelect
from nominatim.api.connection import SearchConnection
import nominatim.api.results as nres
from nominatim.api.logging import log
return self.layer_enabled(DataLayer.RAILWAY, DataLayer.MANMADE, DataLayer.NATURAL)
- def _add_geometry_columns(self, sql: SaSelect, col: SaColumn) -> SaSelect:
- if not self.has_geometries():
- return sql
-
+ def _add_geometry_columns(self, sql: SaLambdaSelect, col: SaColumn) -> SaSelect:
out = []
if self.params.geometry_simplification > 0.0:
# PostgreSQL must not get the distance as a parameter because
# there is a danger it won't be able to proberly estimate index use
# when used with prepared statements
- dist_param = sa.text(f"{distance}")
+ diststr = sa.text(f"{distance}")
- sql = _select_from_placex(t)\
- .where(t.c.geometry.ST_DWithin(WKT_PARAM, dist_param))\
- .where(t.c.indexed_status == 0)\
- .where(t.c.linked_place_id == None)\
+ sql: SaLambdaSelect = sa.lambda_stmt(lambda: _select_from_placex(t)
+ .where(t.c.geometry.ST_DWithin(WKT_PARAM, diststr))
+ .where(t.c.indexed_status == 0)
+ .where(t.c.linked_place_id == None)
.where(sa.or_(sa.not_(t.c.geometry.is_area()),
- t.c.centroid.ST_Distance(WKT_PARAM) < dist_param))\
- .order_by('distance')\
- .limit(1)
+ t.c.centroid.ST_Distance(WKT_PARAM) < diststr))
+ .order_by('distance')
+ .limit(1))
- sql = self._add_geometry_columns(sql, t.c.geometry)
+ if self.has_geometries():
+ sql = self._add_geometry_columns(sql, t.c.geometry)
- restrict: List[SaColumn] = []
+ restrict: List[Union[SaColumn, Callable[[], SaColumn]]] = []
if self.layer_enabled(DataLayer.ADDRESS):
- restrict.append(no_index(t.c.rank_address).between(26, min(29, self.max_rank)))
+ max_rank = min(29, self.max_rank)
+ restrict.append(lambda: no_index(t.c.rank_address).between(26, max_rank))
if self.max_rank == 30:
- restrict.append(_is_address_point(t))
+ restrict.append(lambda: _is_address_point(t))
if self.layer_enabled(DataLayer.POI) and self.max_rank == 30:
- restrict.append(sa.and_(no_index(t.c.rank_search) == 30,
- t.c.class_.not_in(('place', 'building')),
- sa.not_(t.c.geometry.is_line_like())))
+ restrict.append(lambda: sa.and_(no_index(t.c.rank_search) == 30,
+ t.c.class_.not_in(('place', 'building')),
+ sa.not_(t.c.geometry.is_line_like())))
if self.has_feature_layers():
restrict.append(sa.and_(no_index(t.c.rank_search).between(26, MAX_RANK_PARAM),
no_index(t.c.rank_address) == 0,
async def _find_housenumber_for_street(self, parent_place_id: int) -> Optional[SaRow]:
t = self.conn.t.placex
- sql = _select_from_placex(t)\
- .where(t.c.geometry.ST_DWithin(WKT_PARAM, 0.001))\
- .where(t.c.parent_place_id == parent_place_id)\
- .where(_is_address_point(t))\
- .where(t.c.indexed_status == 0)\
- .where(t.c.linked_place_id == None)\
- .order_by('distance')\
- .limit(1)
+ sql: SaLambdaSelect = sa.lambda_stmt(lambda: _select_from_placex(t)
+ .where(t.c.geometry.ST_DWithin(WKT_PARAM, 0.001))
+ .where(t.c.parent_place_id == parent_place_id)
+ .where(_is_address_point(t))
+ .where(t.c.indexed_status == 0)
+ .where(t.c.linked_place_id == None)
+ .order_by('distance')
+ .limit(1))
- sql = self._add_geometry_columns(sql, t.c.geometry)
+ if self.has_geometries():
+ sql = self._add_geometry_columns(sql, t.c.geometry)
return (await self.conn.execute(sql, self.bind_params)).one_or_none()
distance: float) -> Optional[SaRow]:
t = self.conn.t.osmline
- sql = sa.select(t,
- t.c.linegeo.ST_Distance(WKT_PARAM).label('distance'),
- _locate_interpolation(t))\
- .where(t.c.linegeo.ST_DWithin(WKT_PARAM, distance))\
- .where(t.c.startnumber != None)\
- .order_by('distance')\
- .limit(1)
+ sql: Any = sa.lambda_stmt(lambda:
+ sa.select(t,
+ t.c.linegeo.ST_Distance(WKT_PARAM).label('distance'),
+ _locate_interpolation(t))
+ .where(t.c.linegeo.ST_DWithin(WKT_PARAM, distance))
+ .where(t.c.startnumber != None)
+ .order_by('distance')
+ .limit(1))
if parent_place_id is not None:
- sql = sql.where(t.c.parent_place_id == parent_place_id)
+ sql += lambda s: s.where(t.c.parent_place_id == parent_place_id)
- inner = sql.subquery('ipol')
+ def _wrap_query(base_sql: SaLambdaSelect) -> SaSelect:
+ inner = base_sql.subquery('ipol')
- sql = sa.select(inner.c.place_id, inner.c.osm_id,
- inner.c.parent_place_id, inner.c.address,
- _interpolated_housenumber(inner),
- _interpolated_position(inner),
- inner.c.postcode, inner.c.country_code,
- inner.c.distance)
+ return sa.select(inner.c.place_id, inner.c.osm_id,
+ inner.c.parent_place_id, inner.c.address,
+ _interpolated_housenumber(inner),
+ _interpolated_position(inner),
+ inner.c.postcode, inner.c.country_code,
+ inner.c.distance)
+
+ sql += _wrap_query
if self.has_geometries():
sub = sql.subquery('geom')
return (await self.conn.execute(sql, self.bind_params)).one_or_none()
- async def _find_tiger_number_for_street(self, parent_place_id: int,
- parent_type: str,
- parent_id: int) -> Optional[SaRow]:
+ async def _find_tiger_number_for_street(self, parent_place_id: int) -> Optional[SaRow]:
t = self.conn.t.tiger
- inner = sa.select(t,
- t.c.linegeo.ST_Distance(WKT_PARAM).label('distance'),
- _locate_interpolation(t))\
- .where(t.c.linegeo.ST_DWithin(WKT_PARAM, 0.001))\
- .where(t.c.parent_place_id == parent_place_id)\
- .order_by('distance')\
- .limit(1)\
- .subquery('tiger')
-
- sql = sa.select(inner.c.place_id,
- inner.c.parent_place_id,
- sa.literal(parent_type).label('osm_type'),
- sa.literal(parent_id).label('osm_id'),
- _interpolated_housenumber(inner),
- _interpolated_position(inner),
- inner.c.postcode,
- inner.c.distance)
+ def _base_query() -> SaSelect:
+ inner = sa.select(t,
+ t.c.linegeo.ST_Distance(WKT_PARAM).label('distance'),
+ _locate_interpolation(t))\
+ .where(t.c.linegeo.ST_DWithin(WKT_PARAM, 0.001))\
+ .where(t.c.parent_place_id == parent_place_id)\
+ .order_by('distance')\
+ .limit(1)\
+ .subquery('tiger')
+
+ return sa.select(inner.c.place_id,
+ inner.c.parent_place_id,
+ _interpolated_housenumber(inner),
+ _interpolated_position(inner),
+ inner.c.postcode,
+ inner.c.distance)
+
+ sql: SaLambdaSelect = sa.lambda_stmt(_base_query)
if self.has_geometries():
sub = sql.subquery('geom')
distance = addr_row.distance
elif row.country_code == 'us' and parent_place_id is not None:
log().comment('Find TIGER housenumber for street')
- addr_row = await self._find_tiger_number_for_street(parent_place_id,
- row.osm_type,
- row.osm_id)
+ addr_row = await self._find_tiger_number_for_street(parent_place_id)
log().var_dump('Result (street Tiger housenumber)', addr_row)
if addr_row is not None:
+ row_func = cast(RowFunc,
+ functools.partial(nres.create_from_tiger_row,
+ osm_type=row.osm_type,
+ osm_id=row.osm_id))
row = addr_row
- row_func = nres.create_from_tiger_row
else:
distance = row.distance
log().comment('Reverse lookup by larger address area features')
t = self.conn.t.placex
- # The inner SQL brings results in the right order, so that
- # later only a minimum of results needs to be checked with ST_Contains.
- inner = sa.select(t, sa.literal(0.0).label('distance'))\
- .where(t.c.rank_search.between(5, MAX_RANK_PARAM))\
- .where(t.c.geometry.intersects(WKT_PARAM))\
- .where(snfn.select_index_placex_geometry_reverse_lookuppolygon('placex'))\
- .order_by(sa.desc(t.c.rank_search))\
- .limit(50)\
- .subquery('area')
+ def _base_query() -> SaSelect:
+ # The inner SQL brings results in the right order, so that
+ # later only a minimum of results needs to be checked with ST_Contains.
+ inner = sa.select(t, sa.literal(0.0).label('distance'))\
+ .where(t.c.rank_search.between(5, MAX_RANK_PARAM))\
+ .where(t.c.geometry.intersects(WKT_PARAM))\
+ .where(snfn.select_index_placex_geometry_reverse_lookuppolygon('placex'))\
+ .order_by(sa.desc(t.c.rank_search))\
+ .limit(50)\
+ .subquery('area')
- sql = _select_from_placex(inner, False)\
- .where(inner.c.geometry.ST_Contains(WKT_PARAM))\
- .order_by(sa.desc(inner.c.rank_search))\
- .limit(1)
+ return _select_from_placex(inner, False)\
+ .where(inner.c.geometry.ST_Contains(WKT_PARAM))\
+ .order_by(sa.desc(inner.c.rank_search))\
+ .limit(1)
- sql = self._add_geometry_columns(sql, inner.c.geometry)
+ sql: SaLambdaSelect = sa.lambda_stmt(_base_query)
+ if self.has_geometries():
+ sql = self._add_geometry_columns(sql, sa.literal_column('area.geometry'))
address_row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
log().var_dump('Result (area)', address_row)
if address_row is not None and address_row.rank_search < self.max_rank:
log().comment('Search for better matching place nodes inside the area')
- inner = sa.select(t,
+
+ address_rank = address_row.rank_search
+ address_id = address_row.place_id
+
+ def _place_inside_area_query() -> SaSelect:
+ inner = \
+ sa.select(t,
t.c.geometry.ST_Distance(WKT_PARAM).label('distance'))\
- .where(t.c.rank_search > address_row.rank_search)\
+ .where(t.c.rank_search > address_rank)\
.where(t.c.rank_search <= MAX_RANK_PARAM)\
.where(t.c.indexed_status == 0)\
.where(snfn.select_index_placex_geometry_reverse_lookupplacenode('placex'))\
.limit(50)\
.subquery('places')
- touter = self.conn.t.placex.alias('outer')
- sql = _select_from_placex(inner, False)\
- .join(touter, touter.c.geometry.ST_Contains(inner.c.geometry))\
- .where(touter.c.place_id == address_row.place_id)\
- .where(inner.c.distance < sa.func.reverse_place_diameter(inner.c.rank_search))\
- .order_by(sa.desc(inner.c.rank_search), inner.c.distance)\
- .limit(1)
+ touter = t.alias('outer')
+ return _select_from_placex(inner, False)\
+ .join(touter, touter.c.geometry.ST_Contains(inner.c.geometry))\
+ .where(touter.c.place_id == address_id)\
+ .where(inner.c.distance < sa.func.reverse_place_diameter(inner.c.rank_search))\
+ .order_by(sa.desc(inner.c.rank_search), inner.c.distance)\
+ .limit(1)
- sql = self._add_geometry_columns(sql, inner.c.geometry)
+ sql = sa.lambda_stmt(_place_inside_area_query)
+ if self.has_geometries():
+ sql = self._add_geometry_columns(sql, sa.literal_column('places.geometry'))
place_address_row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
log().var_dump('Result (place node)', place_address_row)
.order_by(sa.desc(inner.c.rank_search), inner.c.distance)\
.limit(1)
- sql = self._add_geometry_columns(sql, inner.c.geometry)
+ if self.has_geometries():
+ sql = self._add_geometry_columns(sql, inner.c.geometry)
row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
log().var_dump('Result (non-address feature)', row)
"""
log().section('Reverse lookup by country code')
t = self.conn.t.country_grid
- sql = sa.select(t.c.country_code).distinct()\
+ sql: SaLambdaSelect = sa.select(t.c.country_code).distinct()\
.where(t.c.geometry.ST_Contains(WKT_PARAM))
ccodes = tuple((r[0] for r in await self.conn.execute(sql, self.bind_params)))
if self.max_rank > 4:
log().comment('Search for place nodes in country')
- inner = sa.select(t,
+ def _base_query() -> SaSelect:
+ inner = \
+ sa.select(t,
t.c.geometry.ST_Distance(WKT_PARAM).label('distance'))\
.where(t.c.rank_search > 4)\
.where(t.c.rank_search <= MAX_RANK_PARAM)\
.intersects(WKT_PARAM))\
.order_by(sa.desc(t.c.rank_search))\
.limit(50)\
- .subquery()
+ .subquery('area')
- sql = _select_from_placex(inner, False)\
- .where(inner.c.distance < sa.func.reverse_place_diameter(inner.c.rank_search))\
- .order_by(sa.desc(inner.c.rank_search), inner.c.distance)\
- .limit(1)
+ return _select_from_placex(inner, False)\
+ .where(inner.c.distance < sa.func.reverse_place_diameter(inner.c.rank_search))\
+ .order_by(sa.desc(inner.c.rank_search), inner.c.distance)\
+ .limit(1)
- sql = self._add_geometry_columns(sql, inner.c.geometry)
+ sql = sa.lambda_stmt(_base_query)
+ if self.has_geometries():
+ sql = self._add_geometry_columns(sql, sa.literal_column('area.geometry'))
address_row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
log().var_dump('Result (addressable place node)', address_row)
if address_row is None:
# Still nothing, then return a country with the appropriate country code.
- sql = _select_from_placex(t)\
+ sql = sa.lambda_stmt(lambda: _select_from_placex(t)\
.where(t.c.country_code.in_(ccodes))\
.where(t.c.rank_address == 4)\
.where(t.c.rank_search == 4)\
.where(t.c.linked_place_id == None)\
.order_by('distance')\
- .limit(1)
+ .limit(1))
- sql = self._add_geometry_columns(sql, t.c.geometry)
+ if self.has_geometries():
+ sql = self._add_geometry_columns(sql, t.c.geometry)
address_row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
"""
Implementation of the acutal database accesses for forward search.
"""
-from typing import List, Tuple, AsyncIterator, Dict, Any
+from typing import List, Tuple, AsyncIterator, Dict, Any, Callable
import abc
import sqlalchemy as sa
from sqlalchemy.dialects.postgresql import ARRAY, array_agg
from nominatim.typing import SaFromClause, SaScalarSelect, SaColumn, \
- SaExpression, SaSelect, SaRow, SaBind
+ SaExpression, SaSelect, SaLambdaSelect, SaRow, SaBind
from nominatim.api.connection import SearchConnection
from nominatim.api.types import SearchDetails, DataLayer, GeometryFormat, Bbox
import nominatim.api.results as nres
VIEWBOX2_PARAM: SaBind = sa.bindparam('viewbox2', type_=Geometry)
NEAR_PARAM: SaBind = sa.bindparam('near', type_=Geometry)
NEAR_RADIUS_PARAM: SaBind = sa.bindparam('near_radius')
-EXCLUDED_PARAM: SaBind = sa.bindparam('excluded')
COUNTRIES_PARAM: SaBind = sa.bindparam('countries')
+def _within_near(t: SaFromClause) -> Callable[[], SaExpression]:
+ return lambda: t.c.geometry.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM)
+
+def _exclude_places(t: SaFromClause) -> Callable[[], SaExpression]:
+ return lambda: t.c.place_id.not_in(sa.bindparam('excluded'))
+
def _select_placex(t: SaFromClause) -> SaSelect:
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.geometry.ST_Expand(0).label('bbox'))
-def _add_geometry_columns(sql: SaSelect, col: SaColumn, details: SearchDetails) -> SaSelect:
- if not details.geometry_output:
- return sql
-
+def _add_geometry_columns(sql: SaLambdaSelect, col: SaColumn, details: SearchDetails) -> SaSelect:
out = []
if details.geometry_simplification > 0.0:
for n in numerals)))
if details.excluded:
- sql = sql.where(table.c.place_id.not_in(EXCLUDED_PARAM))
+ sql = sql.where(_exclude_places(table))
return sql.scalar_subquery()
t = conn.t.placex
sql = _select_placex(t).where(t.c.place_id.in_(place_ids))
- sql = _add_geometry_columns(sql, t.c.geometry, details)
+ if details.geometry_output:
+ sql = _add_geometry_columns(sql, t.c.geometry, details)
for row in await conn.execute(sql):
result = nres.create_from_placex_row(row, nres.SearchResult)
if details.countries:
sql = sql.where(t.c.country_code.in_(COUNTRIES_PARAM))
if details.excluded:
- sql = sql.where(t.c.place_id.not_in(EXCLUDED_PARAM))
+ sql = sql.where(_exclude_places(t))
if details.layers is not None:
sql = sql.where(_filter_by_layer(t, details.layers))
if details.near and details.near_radius is not None and details.near_radius < 0.2:
# simply search in placex table
- sql = _select_placex(t) \
- .where(t.c.linked_place_id == None) \
- .where(t.c.geometry.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM)) \
- .order_by(t.c.centroid.ST_Distance(NEAR_PARAM))
+ def _base_query() -> SaSelect:
+ return _select_placex(t) \
+ .where(t.c.linked_place_id == None) \
+ .where(t.c.geometry.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM)) \
+ .order_by(t.c.centroid.ST_Distance(NEAR_PARAM)) \
+ .limit(LIMIT_PARAM)
+
+ classtype = self.categories.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))
- classtype = self.categories.values
- if len(classtype) == 1:
- sql = sql.where(t.c.class_ == classtype[0][0]) \
- .where(t.c.type == classtype[0][1])
- else:
- sql = sql.where(sa.or_(*(sa.and_(t.c.class_ == cls, t.c.type == typ)
- for cls, typ in classtype)))
-
- sql = sql.limit(LIMIT_PARAM)
rows.extend(await conn.execute(sql, bind_params))
else:
# use the class type tables
"""
t = conn.t.placex
- sql = _select_placex(t)\
- .where(t.c.country_code.in_(self.countries.values))\
- .where(t.c.rank_address == 4)
+ ccodes = self.countries.values
+ sql: SaLambdaSelect = sa.lambda_stmt(lambda: _select_placex(t)\
+ .where(t.c.country_code.in_(ccodes))\
+ .where(t.c.rank_address == 4))
- sql = _add_geometry_columns(sql, t.c.geometry, details)
+ if details.geometry_output:
+ sql = _add_geometry_columns(sql, t.c.geometry, details)
if details.excluded:
- sql = sql.where(t.c.place_id.not_in(EXCLUDED_PARAM))
+ sql = sql.where(_exclude_places(t))
if details.viewbox is not None and details.bounded_viewbox:
- sql = sql.where(t.c.geometry.intersects(VIEWBOX_PARAM))
+ sql = sql.where(lambda: t.c.geometry.intersects(VIEWBOX_PARAM))
if details.near is not None and details.near_radius is not None:
- sql = sql.where(t.c.geometry.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM))
+ sql = sql.where(_within_near(t))
results = nres.SearchResults()
for row in await conn.execute(sql, _details_to_bind_params(details)):
if details.viewbox is not None and details.bounded_viewbox:
sql = sql.where(tgrid.c.geometry.intersects(VIEWBOX_PARAM))
if details.near is not None and details.near_radius is not None:
- sql = sql.where(tgrid.c.geometry.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM))
+ sql = sql.where(_within_near(tgrid))
sub = sql.subquery('grid')
""" 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,
+ sql: SaLambdaSelect = sa.lambda_stmt(lambda:
+ 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_(self.postcodes.values))
+ t.c.geometry.label('centroid'))
+ .where(t.c.postcode.in_(pcs)))
- sql = _add_geometry_columns(sql, t.c.geometry, details)
+ if details.geometry_output:
+ sql = _add_geometry_columns(sql, t.c.geometry, details)
penalty: SaExpression = sa.literal(self.penalty)
if details.near is not None:
if details.near_radius is not None:
- sql = sql.where(t.c.geometry.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM))
+ sql = sql.where(_within_near(t))
sql = sql.order_by(t.c.geometry.ST_Distance(NEAR_PARAM))
if self.countries:
sql = sql.where(t.c.country_code.in_(self.countries.values))
if details.excluded:
- sql = sql.where(t.c.place_id.not_in(EXCLUDED_PARAM))
+ sql = sql.where(_exclude_places(t))
if self.lookups:
assert len(self.lookups) == 1
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
- t = conn.t.placex.alias('p')
- tsearch = conn.t.search_name.alias('s')
+ t = conn.t.placex
+ tsearch = conn.t.search_name
- sql = 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.centroid,
- t.c.geometry.ST_Expand(0).label('bbox'))\
- .where(t.c.place_id == tsearch.c.place_id)
+ sql: SaLambdaSelect = sa.lambda_stmt(lambda:
+ 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.centroid,
+ t.c.geometry.ST_Expand(0).label('bbox'))
+ .where(t.c.place_id == tsearch.c.place_id))
- sql = _add_geometry_columns(sql, t.c.geometry, details)
+ if details.geometry_output:
+ sql = _add_geometry_columns(sql, t.c.geometry, details)
penalty: SaExpression = sa.literal(self.penalty)
for ranking in self.rankings:
# if a postcode is given, don't search for state or country level objects
sql = sql.where(tsearch.c.address_rank > 9)
tpc = conn.t.postcode
+ pcs = self.postcodes.values
if self.expected_count > 1000:
# Many results expected. Restrict by postcode.
- sql = sql.where(sa.select(tpc.c.postcode)
- .where(tpc.c.postcode.in_(self.postcodes.values))
+ sql = sql.where(lambda: sa.select(tpc.c.postcode)
+ .where(tpc.c.postcode.in_(pcs))
.where(tsearch.c.centroid.ST_DWithin(tpc.c.geometry, 0.12))
.exists())
# Less results, only have a preference for close postcodes
pc_near = sa.select(sa.func.min(tpc.c.geometry.ST_Distance(tsearch.c.centroid)))\
- .where(tpc.c.postcode.in_(self.postcodes.values))\
+ .where(tpc.c.postcode.in_(pcs))\
.scalar_subquery()
- penalty += sa.case((t.c.postcode.in_(self.postcodes.values), 0.0),
+ penalty += sa.case((t.c.postcode.in_(pcs), 0.0),
else_=sa.func.coalesce(pc_near, 2.0))
if details.viewbox is not None:
hnr_regexp = f"\\m({'|'.join(self.housenumbers.values)})\\M"
sql = sql.where(tsearch.c.address_rank.between(16, 30))\
.where(sa.or_(tsearch.c.address_rank < 30,
- t.c.housenumber.op('~*')(hnr_regexp)))
+ t.c.housenumber.op('~*')(hnr_regexp)))
# Cross check for housenumbers, need to do that on a rather large
# set. Worst case there are 40.000 main streets in OSM.
.where(thnr.c.indexed_status == 0)
if details.excluded:
- place_sql = place_sql.where(thnr.c.place_id.not_in(EXCLUDED_PARAM))
+ place_sql = place_sql.where(_exclude_places(thnr))
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()]
- interpol_sql: SaExpression
- tiger_sql: SaExpression
+ interpol_sql: SaColumn
+ tiger_sql: SaColumn
if numerals and \
(not self.qualifiers or ('place', 'house') in self.qualifiers.values):
# Housenumbers from interpolations
numerals, details)
), else_=None)
else:
- interpol_sql = sa.literal_column('NULL')
- tiger_sql = sa.literal_column('NULL')
+ interpol_sql = sa.null()
+ tiger_sql = sa.null()
unsort = sa.select(inner, place_sql.scalar_subquery().label('placex_hnr'),
interpol_sql.label('interpol_hnr'),
if self.qualifiers:
sql = sql.where(self.qualifiers.sql_restrict(t))
if details.excluded:
- sql = sql.where(tsearch.c.place_id.not_in(EXCLUDED_PARAM))
+ sql = sql.where(_exclude_places(tsearch))
if details.min_rank > 0:
sql = sql.where(sa.or_(tsearch.c.address_rank >= MIN_RANK_PARAM,
tsearch.c.search_rank >= MIN_RANK_PARAM))
projects / nominatim.git / commitdiff