import nominatim.api.results as nres
from nominatim.api.logging import log
from nominatim.api.types import AnyPoint, DataLayer, ReverseDetails, GeometryFormat, Bbox
+from nominatim.db.sqlalchemy_types import Geometry
# In SQLAlchemy expression which compare with NULL need to be expressed with
# the equal sign.
RowFunc = Callable[[Optional[SaRow], Type[nres.ReverseResult]], Optional[nres.ReverseResult]]
-def _select_from_placex(t: SaFromClause, wkt: Optional[str] = None) -> SaSelect:
+WKT_PARAM = sa.bindparam('wkt', type_=Geometry)
+MAX_RANK_PARAM = sa.bindparam('max_rank')
+
+def _select_from_placex(t: SaFromClause, use_wkt: bool = True) -> SaSelect:
""" Create a select statement with the columns relevant for reverse
results.
"""
- if wkt is None:
+ if not use_wkt:
distance = t.c.distance
centroid = t.c.centroid
else:
- distance = t.c.geometry.ST_Distance(wkt)
- centroid = sa.case((t.c.geometry.is_line_like(), t.c.geometry.ST_ClosestPoint(wkt)),
+ distance = t.c.geometry.ST_Distance(WKT_PARAM)
+ centroid = sa.case((t.c.geometry.is_line_like(), t.c.geometry.ST_ClosestPoint(WKT_PARAM)),
else_=t.c.centroid).label('centroid')
else_=table.c.linegeo.ST_LineInterpolatePoint(rounded_pos)).label('centroid')
-def _locate_interpolation(table: SaFromClause, wkt: str) -> SaLabel:
+def _locate_interpolation(table: SaFromClause) -> SaLabel:
""" Given a position, locate the closest point on the line.
"""
- return sa.case((table.c.linegeo.is_line_like(), table.c.linegeo.ST_LineLocatePoint(wkt)),
+ return sa.case((table.c.linegeo.is_line_like(),
+ table.c.linegeo.ST_LineLocatePoint(WKT_PARAM)),
else_=0).label('position')
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)
+
class ReverseGeocoder:
""" Class implementing the logic for looking up a place from a
coordinate.
self.conn = conn
self.params = params
+ self.bind_params = {'max_rank': params.max_rank}
+
@property
def max_rank(self) -> int:
"""
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
return table.c.class_.in_(tuple(include))
- async def _find_closest_street_or_poi(self, wkt: str,
- distance: float) -> Optional[SaRow]:
+ async def _find_closest_street_or_poi(self, distance: float) -> Optional[SaRow]:
""" Look up the closest rank 26+ place in the database, which
is closer than the given distance.
"""
t = self.conn.t.placex
- sql = _select_from_placex(t, wkt)\
- .where(t.c.geometry.ST_DWithin(wkt, distance))\
+ 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)\
.where(sa.or_(sa.not_(t.c.geometry.is_area()),
- t.c.centroid.ST_Distance(wkt) < distance))\
+ t.c.centroid.ST_Distance(WKT_PARAM) < distance))\
.order_by('distance')\
.limit(1)
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, self.max_rank),
+ restrict.append(sa.and_(t.c.rank_search.between(26, MAX_RANK_PARAM),
t.c.rank_address == 0,
self._filter_by_layer(t)))
if not restrict:
return None
- return (await self.conn.execute(sql.where(sa.or_(*restrict)))).one_or_none()
+ sql = sql.where(sa.or_(*restrict))
+
+ return (await self.conn.execute(sql, self.bind_params)).one_or_none()
- async def _find_housenumber_for_street(self, parent_place_id: int,
- wkt: str) -> Optional[SaRow]:
+ async def _find_housenumber_for_street(self, parent_place_id: int) -> Optional[SaRow]:
t = self.conn.t.placex
- sql = _select_from_placex(t, wkt)\
- .where(t.c.geometry.ST_DWithin(wkt, 0.001))\
+ 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)\
sql = self._add_geometry_columns(sql, t.c.geometry)
- return (await self.conn.execute(sql)).one_or_none()
+ return (await self.conn.execute(sql, self.bind_params)).one_or_none()
async def _find_interpolation_for_street(self, parent_place_id: Optional[int],
- wkt: str,
distance: float) -> Optional[SaRow]:
t = self.conn.t.osmline
sql = sa.select(t,
- t.c.linegeo.ST_Distance(wkt).label('distance'),
- _locate_interpolation(t, wkt))\
- .where(t.c.linegeo.ST_DWithin(wkt, distance))\
+ 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)
sub = sql.subquery('geom')
sql = self._add_geometry_columns(sa.select(sub), sub.c.centroid)
- return (await self.conn.execute(sql)).one_or_none()
+ 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,
- wkt: str) -> Optional[SaRow]:
+ parent_type: str,
+ parent_id: int) -> Optional[SaRow]:
t = self.conn.t.tiger
inner = sa.select(t,
- t.c.linegeo.ST_Distance(wkt).label('distance'),
- _locate_interpolation(t, wkt))\
- .where(t.c.linegeo.ST_DWithin(wkt, 0.001))\
+ 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)\
sub = sql.subquery('geom')
sql = self._add_geometry_columns(sa.select(sub), sub.c.centroid)
- return (await self.conn.execute(sql)).one_or_none()
+ return (await self.conn.execute(sql, self.bind_params)).one_or_none()
- async def lookup_street_poi(self,
- wkt: str) -> Tuple[Optional[SaRow], RowFunc]:
+ async def lookup_street_poi(self) -> Tuple[Optional[SaRow], RowFunc]:
""" Find a street or POI/address for the given WKT point.
"""
log().section('Reverse lookup on street/address level')
distance = 0.006
parent_place_id = None
- row = await self._find_closest_street_or_poi(wkt, distance)
+ row = await self._find_closest_street_or_poi(distance)
row_func: RowFunc = nres.create_from_placex_row
log().var_dump('Result (street/building)', row)
distance = 0.001
parent_place_id = row.place_id
log().comment('Find housenumber for street')
- addr_row = await self._find_housenumber_for_street(parent_place_id, wkt)
+ addr_row = await self._find_housenumber_for_street(parent_place_id)
log().var_dump('Result (street housenumber)', addr_row)
if addr_row 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,
- wkt)
+ row.osm_id)
log().var_dump('Result (street Tiger housenumber)', addr_row)
if addr_row is not None:
if self.max_rank > 27 and self.layer_enabled(DataLayer.ADDRESS):
log().comment('Find interpolation for street')
addr_row = await self._find_interpolation_for_street(parent_place_id,
- wkt, distance)
+ distance)
log().var_dump('Result (street interpolation)', addr_row)
if addr_row is not None:
row = addr_row
return row, row_func
- async def _lookup_area_address(self, wkt: str) -> Optional[SaRow]:
+ async def _lookup_area_address(self) -> Optional[SaRow]:
""" Lookup large addressable areas for the given WKT point.
"""
log().comment('Reverse lookup by larger address area features')
# 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, self.max_rank))\
+ .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))\
+ .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)\
.limit(50)\
.subquery('area')
- sql = _select_from_placex(inner)\
- .where(inner.c.geometry.ST_Contains(wkt))\
+ sql = _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)
- address_row = (await self.conn.execute(sql)).one_or_none()
+ 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,
- t.c.geometry.ST_Distance(wkt).label('distance'))\
+ 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 <= self.max_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.type != 'postcode')\
.where(t.c.geometry
.ST_Buffer(sa.func.reverse_place_diameter(t.c.rank_search))
- .intersects(wkt))\
+ .intersects(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)\
+ 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))\
sql = self._add_geometry_columns(sql, inner.c.geometry)
- place_address_row = (await self.conn.execute(sql)).one_or_none()
+ place_address_row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
log().var_dump('Result (place node)', place_address_row)
if place_address_row is not None:
return address_row
- async def _lookup_area_others(self, wkt: str) -> Optional[SaRow]:
+ async def _lookup_area_others(self) -> Optional[SaRow]:
t = self.conn.t.placex
- inner = sa.select(t, t.c.geometry.ST_Distance(wkt).label('distance'))\
+ inner = sa.select(t, t.c.geometry.ST_Distance(WKT_PARAM).label('distance'))\
.where(t.c.rank_address == 0)\
- .where(t.c.rank_search.between(5, self.max_rank))\
+ .where(t.c.rank_search.between(5, MAX_RANK_PARAM))\
.where(t.c.name != None)\
.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))\
+ .intersects(WKT_PARAM))\
.order_by(sa.desc(t.c.rank_search))\
.limit(50)\
.subquery()
- sql = _select_from_placex(inner)\
- .where(sa.or_(not inner.c.geometry.is_area(),
- inner.c.geometry.ST_Contains(wkt)))\
+ sql = _select_from_placex(inner, False)\
+ .where(sa.or_(sa.not_(inner.c.geometry.is_area()),
+ inner.c.geometry.ST_Contains(WKT_PARAM)))\
.order_by(sa.desc(inner.c.rank_search), inner.c.distance)\
.limit(1)
sql = self._add_geometry_columns(sql, inner.c.geometry)
- row = (await self.conn.execute(sql)).one_or_none()
+ row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
log().var_dump('Result (non-address feature)', row)
return row
- async def lookup_area(self, wkt: str) -> Optional[SaRow]:
- """ Lookup large areas for the given WKT point.
+ async def lookup_area(self) -> Optional[SaRow]:
+ """ Lookup large areas for the current search.
"""
log().section('Reverse lookup by larger area features')
if self.layer_enabled(DataLayer.ADDRESS):
- address_row = await self._lookup_area_address(wkt)
+ address_row = await self._lookup_area_address()
else:
address_row = None
if self.has_feature_layers():
- other_row = await self._lookup_area_others(wkt)
+ other_row = await self._lookup_area_others()
else:
other_row = None
return _get_closest(address_row, other_row)
- async def lookup_country(self, wkt: str) -> Optional[SaRow]:
- """ Lookup the country for the given WKT point.
+ async def lookup_country(self) -> Optional[SaRow]:
+ """ Lookup the country for the current search.
"""
log().section('Reverse lookup by country code')
t = self.conn.t.country_grid
sql = sa.select(t.c.country_code).distinct()\
- .where(t.c.geometry.ST_Contains(wkt))
+ .where(t.c.geometry.ST_Contains(WKT_PARAM))
- ccodes = tuple((r[0] for r in await self.conn.execute(sql)))
+ ccodes = tuple((r[0] for r in await self.conn.execute(sql, self.bind_params)))
log().var_dump('Country codes', ccodes)
if not ccodes:
log().comment('Search for place nodes in country')
inner = sa.select(t,
- t.c.geometry.ST_Distance(wkt).label('distance'))\
+ 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 <= self.max_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.country_code.in_(ccodes))\
.where(t.c.geometry
.ST_Buffer(sa.func.reverse_place_diameter(t.c.rank_search))
- .intersects(wkt))\
+ .intersects(WKT_PARAM))\
.order_by(sa.desc(t.c.rank_search))\
.limit(50)\
.subquery()
- sql = _select_from_placex(inner)\
+ 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)
sql = self._add_geometry_columns(sql, inner.c.geometry)
- address_row = (await self.conn.execute(sql)).one_or_none()
+ address_row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
log().var_dump('Result (addressable place node)', address_row)
else:
address_row = None
if address_row is None:
# Still nothing, then return a country with the appropriate country code.
- sql = _select_from_placex(t, wkt)\
+ sql = _select_from_placex(t)\
.where(t.c.country_code.in_(ccodes))\
.where(t.c.rank_address == 4)\
.where(t.c.rank_search == 4)\
sql = self._add_geometry_columns(sql, t.c.geometry)
- address_row = (await self.conn.execute(sql)).one_or_none()
+ address_row = (await self.conn.execute(sql, self.bind_params)).one_or_none()
return address_row
log().function('reverse_lookup', coord=coord, params=self.params)
- wkt = f'POINT({coord[0]} {coord[1]})'
+ self.bind_params['wkt'] = f'SRID=4326;POINT({coord[0]} {coord[1]})'
row: Optional[SaRow] = None
row_func: RowFunc = nres.create_from_placex_row
if self.max_rank >= 26:
- row, tmp_row_func = await self.lookup_street_poi(wkt)
+ 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(wkt)
+ row = await self.lookup_area()
if row is None and self.layer_enabled(DataLayer.ADDRESS):
- row = await self.lookup_country(wkt)
+ row = await self.lookup_country()
result = row_func(row, nres.ReverseResult)
if result is not None:
assert row is not None
result.distance = row.distance
if hasattr(row, 'bbox'):
- result.bbox = Bbox.from_wkb(row.bbox.data)
+ result.bbox = Bbox.from_wkb(row.bbox)
await nres.add_result_details(self.conn, [result], self.params)
return result
projects / nominatim.git / blobdiff