"""
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
WKT_PARAM: SaBind = sa.bindparam('wkt', type_=Geometry)
MAX_RANK_PARAM: SaBind = sa.bindparam('max_rank')
+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) # pylint: disable=not-callable
+
+
def _select_from_placex(t: SaFromClause, use_wkt: bool = True) -> SaSelect:
""" Create a select statement with the columns relevant for reverse
results.
t.c.importance, t.c.wikipedia,
t.c.parent_place_id, t.c.rank_address, t.c.rank_search,
centroid,
+ t.c.linked_place_id, t.c.admin_level,
distance.label('distance'),
t.c.geometry.ST_Expand(0).label('bbox'))
else_=0).label('position')
-def _is_address_point(table: SaFromClause) -> SaColumn:
- return sa.and_(table.c.rank_address == 30,
- sa.or_(table.c.housenumber != None,
- table.c.name.has_key('housename')))
-
-
def _get_closest(*rows: Optional[SaRow]) -> Optional[SaRow]:
return min(rows, key=lambda row: 1000 if row is None else row.distance)
coordinate.
"""
- def __init__(self, conn: SearchConnection, params: ReverseDetails) -> None:
+ def __init__(self, conn: SearchConnection, params: ReverseDetails,
+ restrict_to_country_areas: bool = False) -> None:
self.conn = conn
self.params = params
+ self.restrict_to_country_areas = restrict_to_country_areas
self.bind_params: Dict[str, Any] = {'max_rank': params.max_rank}
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:
col = sa.func.ST_SimplifyPreserveTopology(col, self.params.geometry_simplification)
if self.params.geometry_output & GeometryFormat.GEOJSON:
- out.append(sa.func.ST_AsGeoJSON(col).label('geometry_geojson'))
+ out.append(sa.func.ST_AsGeoJSON(col, 7).label('geometry_geojson'))
if self.params.geometry_output & GeometryFormat.TEXT:
out.append(sa.func.ST_AsText(col).label('geometry_text'))
if self.params.geometry_output & GeometryFormat.KML:
- out.append(sa.func.ST_AsKML(col).label('geometry_kml'))
+ out.append(sa.func.ST_AsKML(col, 7).label('geometry_kml'))
if self.params.geometry_output & GeometryFormat.SVG:
- out.append(sa.func.ST_AsSVG(col).label('geometry_svg'))
+ out.append(sa.func.ST_AsSVG(col, 0, 7).label('geometry_svg'))
return sql.add_columns(*out)
"""
t = self.conn.t.placex
- sql = _select_from_placex(t)\
- .where(t.c.geometry.ST_DWithin(WKT_PARAM, distance))\
- .where(t.c.indexed_status == 0)\
- .where(t.c.linked_place_id == None)\
+ # 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
+ diststr = sa.text(f"{distance}")
+
+ 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) < distance))\
- .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(sa.and_(t.c.rank_address >= 26,
- t.c.rank_address <= 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: sa.func.IsAddressPoint(t))
if self.layer_enabled(DataLayer.POI) and self.max_rank == 30:
- restrict.append(sa.and_(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_(t.c.rank_search.between(26, MAX_RANK_PARAM),
- t.c.rank_address == 0,
+ restrict.append(sa.and_(no_index(t.c.rank_search).between(26, MAX_RANK_PARAM),
+ no_index(t.c.rank_address) == 0,
self._filter_by_layer(t)))
if not restrict:
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(sa.func.IsAddressPoint(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.rank_address.between(5, 25))\
- .where(t.c.geometry.is_area())\
- .where(t.c.geometry.intersects(WKT_PARAM))\
- .where(t.c.name != None)\
- .where(t.c.indexed_status == 0)\
- .where(t.c.linked_place_id == None)\
- .where(t.c.type != 'postcode')\
- .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(sa.func.PlacexGeometryReverseLookuppolygon())\
+ .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.osm_type == 'N')\
- .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.rank_address.between(5, 25))\
- .where(t.c.name != None)\
.where(t.c.indexed_status == 0)\
- .where(t.c.linked_place_id == None)\
- .where(t.c.type != 'postcode')\
- .where(t.c.geometry
- .ST_Buffer(sa.func.reverse_place_diameter(t.c.rank_search))
- .intersects(WKT_PARAM))\
+ .where(sa.func.IntersectsReverseDistance(t, WKT_PARAM))\
.order_by(sa.desc(t.c.rank_search))\
.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(sa.func.IsBelowReverseDistance(inner.c.distance, 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)
.where(t.c.indexed_status == 0)\
.where(t.c.linked_place_id == None)\
.where(self._filter_by_layer(t))\
- .where(t.c.geometry
- .ST_Buffer(sa.func.reverse_place_diameter(t.c.rank_search))
- .intersects(WKT_PARAM))\
+ .where(t.c.geometry.intersects(sa.func.ST_Expand(WKT_PARAM, 0.007)))\
.order_by(sa.desc(t.c.rank_search))\
+ .order_by('distance')\
.limit(50)\
.subquery()
.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)
return _get_closest(address_row, other_row)
- async def lookup_country(self) -> Optional[SaRow]:
+ async def lookup_country_codes(self) -> List[str]:
""" Lookup the country for the current search.
"""
log().section('Reverse lookup by country code')
sql = 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)))
+ ccodes = [cast(str, r[0]) for r in await self.conn.execute(sql, self.bind_params)]
log().var_dump('Country codes', ccodes)
+ return ccodes
+
+
+ async def lookup_country(self, ccodes: List[str]) -> Optional[SaRow]:
+ """ Lookup the country for the current search.
+ """
+ if not ccodes:
+ ccodes = await self.lookup_country_codes()
if not ccodes:
return None
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.osm_type == 'N')\
.where(t.c.rank_search > 4)\
.where(t.c.rank_search <= MAX_RANK_PARAM)\
- .where(t.c.rank_address.between(5, 25))\
- .where(t.c.name != None)\
.where(t.c.indexed_status == 0)\
- .where(t.c.linked_place_id == None)\
- .where(t.c.type != 'postcode')\
.where(t.c.country_code.in_(ccodes))\
- .where(t.c.geometry
- .ST_Buffer(sa.func.reverse_place_diameter(t.c.rank_search))
- .intersects(WKT_PARAM))\
+ .where(sa.func.IntersectsReverseDistance(t, 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(sa.func.IsBelowReverseDistance(inner.c.distance, 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: 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 (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()
row, tmp_row_func = await self.lookup_street_poi()
if row is not None:
row_func = tmp_row_func
- if row is None and self.max_rank > 4:
- row = await self.lookup_area()
- if row is None and self.layer_enabled(DataLayer.ADDRESS):
- row = await self.lookup_country()
+
+ if row is None:
+ if self.restrict_to_country_areas:
+ ccodes = await self.lookup_country_codes()
+ if not ccodes:
+ return None
+ else:
+ ccodes = []
+
+ if self.max_rank > 4:
+ row = await self.lookup_area()
+ if row is None and self.layer_enabled(DataLayer.ADDRESS):
+ row = await self.lookup_country(ccodes)
result = row_func(row, nres.ReverseResult)
if result is not None:
projects / nominatim.git / blobdiff