"""
Implementation of the acutal database accesses for forward search.
"""
-from typing import List, Tuple, AsyncIterator
+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
+ 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
from nominatim.api.search.db_search_fields import SearchData, WeightedCategories
+from nominatim.db.sqlalchemy_types import Geometry
#pylint: disable=singleton-comparison,not-callable
#pylint: disable=too-many-branches,too-many-arguments,too-many-locals,too-many-statements
+def _details_to_bind_params(details: SearchDetails) -> Dict[str, Any]:
+ """ Create a dictionary from search parameters that can be used
+ as bind parameter for SQL execute.
+ """
+ return {'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}
+
+
+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 _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:
- col = col.ST_SimplifyPreserveTopology(details.geometry_simplification)
+ col = sa.func.ST_SimplifyPreserveTopology(col, details.geometry_simplification)
if details.geometry_output & GeometryFormat.GEOJSON:
- out.append(col.ST_AsGeoJSON().label('geometry_geojson'))
+ out.append(sa.func.ST_AsGeoJSON(col).label('geometry_geojson'))
if details.geometry_output & GeometryFormat.TEXT:
- out.append(col.ST_AsText().label('geometry_text'))
+ out.append(sa.func.ST_AsText(col).label('geometry_text'))
if details.geometry_output & GeometryFormat.KML:
- out.append(col.ST_AsKML().label('geometry_kml'))
+ out.append(sa.func.ST_AsKML(col).label('geometry_kml'))
if details.geometry_output & GeometryFormat.SVG:
- out.append(col.ST_AsSVG().label('geometry_svg'))
+ out.append(sa.func.ST_AsSVG(col).label('geometry_svg'))
return sql.add_columns(*out)
for n in numerals)))
if details.excluded:
- sql = sql.where(table.c.place_id.not_in(details.excluded))
+ 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)
assert result
- result.bbox = Bbox.from_wkb(row.bbox.data)
+ result.bbox = Bbox.from_wkb(row.bbox)
yield result
sql = sql.join(table, t.c.place_id == table.c.place_id)\
.join(tgeom,
sa.case((sa.and_(tgeom.c.rank_address < 9,
- tgeom.c.geometry.ST_GeometryType().in_(
- ('ST_Polygon', 'ST_MultiPolygon'))),
+ tgeom.c.geometry.is_area()),
tgeom.c.geometry.ST_Contains(table.c.centroid)),
else_ = tgeom.c.centroid.ST_DWithin(table.c.centroid, 0.05)))\
.order_by(tgeom.c.centroid.ST_Distance(table.c.centroid))
+ sql = sql.where(t.c.rank_address.between(MIN_RANK_PARAM, MAX_RANK_PARAM))
if details.countries:
- sql = sql.where(t.c.country_code.in_(details.countries))
- if details.min_rank > 0:
- sql = sql.where(t.c.rank_address >= details.min_rank)
- if details.max_rank < 30:
- sql = sql.where(t.c.rank_address <= details.max_rank)
+ sql = sql.where(t.c.country_code.in_(COUNTRIES_PARAM))
if details.excluded:
- sql = sql.where(t.c.place_id.not_in(details.excluded))
+ sql = sql.where(_exclude_places(t))
if details.layers is not None:
sql = sql.where(_filter_by_layer(t, details.layers))
- for row in await conn.execute(sql.limit(details.max_results)):
+ sql = sql.limit(LIMIT_PARAM)
+ for row in await conn.execute(sql, _details_to_bind_params(details)):
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
result.accuracy = self.penalty + penalty
- result.bbox = Bbox.from_wkb(row.bbox.data)
+ result.bbox = Bbox.from_wkb(row.bbox)
results.append(result)
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
+ bind_params = _details_to_bind_params(details)
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
- sql = _select_placex(t) \
- .where(t.c.linked_place_id == None) \
- .where(t.c.geometry.ST_DWithin(details.near.sql_value(),
- details.near_radius)) \
- .order_by(t.c.centroid.ST_Distance(details.near.sql_value()))
+ 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(details.viewbox.sql_value()))
+ 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)))
-
- rows.extend(await conn.execute(sql.limit(details.max_results)))
+ rows.extend(await conn.execute(sql, bind_params))
else:
# use the class type tables
for category in self.categories.values:
.where(t.c.type == category[1])
if details.viewbox is not None and details.bounded_viewbox:
- sql = sql.where(table.c.centroid.intersects(details.viewbox.sql_value()))
+ sql = sql.where(table.c.centroid.intersects(VIEWBOX_PARAM))
- if details.near:
- sql = sql.order_by(table.c.centroid.ST_Distance(details.near.sql_value()))\
- .where(table.c.centroid.ST_DWithin(details.near.sql_value(),
- details.near_radius or 0.5))
+ 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.ST_DWithin(NEAR_PARAM,
+ NEAR_RADIUS_PARAM))
if self.countries:
sql = sql.where(t.c.country_code.in_(self.countries.values))
- rows.extend(await conn.execute(sql.limit(details.max_results)))
+ 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.categories.get_penalty((row.class_, row.type))
- result.bbox = Bbox.from_wkb(row.bbox.data)
+ result.bbox = Bbox.from_wkb(row.bbox)
results.append(result)
return results
"""
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(details.excluded))
+ sql = sql.where(_exclude_places(t))
if details.viewbox is not None and details.bounded_viewbox:
- sql = sql.where(t.c.geometry.intersects(details.viewbox.sql_value()))
+ 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(details.near.sql_value(),
- details.near_radius))
+ sql = sql.where(_within_near(t))
results = nres.SearchResults()
- for row in await conn.execute(sql):
+ for row in await conn.execute(sql, _details_to_bind_params(details)):
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
.group_by(tgrid.c.country_code)
if details.viewbox is not None and details.bounded_viewbox:
- sql = sql.where(tgrid.c.geometry.intersects(details.viewbox.sql_value()))
+ 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(details.near.sql_value(),
- details.near_radius))
+ sql = sql.where(_within_near(tgrid))
sub = sql.subquery('grid')
.join(sub, t.c.country_code == sub.c.country_code)
results = nres.SearchResults()
- for row in await conn.execute(sql):
+ for row in await conn.execute(sql, _details_to_bind_params(details)):
result = nres.create_from_country_row(row, nres.SearchResult)
assert result
result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
""" 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.viewbox is not None:
if details.bounded_viewbox:
- sql = sql.where(t.c.geometry.intersects(details.viewbox.sql_value()))
+ sql = sql.where(t.c.geometry.intersects(VIEWBOX_PARAM))
else:
- penalty += sa.case((t.c.geometry.intersects(details.viewbox.sql_value()), 0.0),
- (t.c.geometry.intersects(details.viewbox_x2.sql_value()), 1.0),
+ penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM), 0.0),
+ (t.c.geometry.intersects(VIEWBOX2_PARAM), 1.0),
else_=2.0)
if details.near is not None:
if details.near_radius is not None:
- sql = sql.where(t.c.geometry.ST_DWithin(details.near.sql_value(),
- details.near_radius))
- sql = sql.order_by(t.c.geometry.ST_Distance(details.near.sql_value()))
+ 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(details.excluded))
+ sql = sql.where(_exclude_places(t))
if self.lookups:
assert len(self.lookups) == 1
sql = sql.add_columns(penalty.label('accuracy'))
- sql = sql.order_by('accuracy')
+ sql = sql.order_by('accuracy').limit(LIMIT_PARAM)
results = nres.SearchResults()
- for row in await conn.execute(sql.limit(details.max_results)):
+ for row in await conn.execute(sql, _details_to_bind_params(details)):
result = nres.create_from_postcode_row(row, nres.SearchResult)
assert result
result.accuracy = row.accuracy
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')
- limit = details.max_results
+ 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:
if details.bounded_viewbox:
- sql = sql.where(tsearch.c.centroid.intersects(details.viewbox.sql_value()))
+ sql = sql.where(tsearch.c.centroid.intersects(VIEWBOX_PARAM))
else:
- penalty += sa.case((t.c.geometry.intersects(details.viewbox.sql_value()), 0.0),
- (t.c.geometry.intersects(details.viewbox_x2.sql_value()), 1.0),
+ penalty += sa.case((t.c.geometry.intersects(VIEWBOX_PARAM), 0.0),
+ (t.c.geometry.intersects(VIEWBOX2_PARAM), 1.0),
else_=2.0)
if details.near is not None:
if details.near_radius is not None:
- sql = sql.where(tsearch.c.centroid.ST_DWithin(details.near.sql_value(),
- details.near_radius))
- sql = sql.add_columns(-tsearch.c.centroid.ST_Distance(details.near.sql_value())
+ sql = sql.where(tsearch.c.centroid.ST_DWithin(NEAR_PARAM, NEAR_RADIUS_PARAM))
+ sql = sql.add_columns(-tsearch.c.centroid.ST_Distance(NEAR_PARAM)
.label('importance'))
sql = sql.order_by(sa.desc(sa.text('importance')))
else:
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.regexp_match(hnr_regexp, flags='i')))
+ 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.
pid_list = array_agg(thnr.c.place_id) # type: ignore[no-untyped-call]
place_sql = sa.select(pid_list)\
.where(thnr.c.parent_place_id == inner.c.place_id)\
- .where(thnr.c.housenumber.regexp_match(hnr_regexp, flags='i'))\
+ .where(thnr.c.housenumber.op('~*')(hnr_regexp))\
.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(details.excluded))
+ 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(details.excluded))
+ sql = sql.where(_exclude_places(tsearch))
if details.min_rank > 0:
- sql = sql.where(sa.or_(tsearch.c.address_rank >= details.min_rank,
- tsearch.c.search_rank >= details.min_rank))
+ sql = sql.where(sa.or_(tsearch.c.address_rank >= MIN_RANK_PARAM,
+ tsearch.c.search_rank >= MIN_RANK_PARAM))
if details.max_rank < 30:
- sql = sql.where(sa.or_(tsearch.c.address_rank <= details.max_rank,
- tsearch.c.search_rank <= details.max_rank))
+ sql = sql.where(sa.or_(tsearch.c.address_rank <= MAX_RANK_PARAM,
+ tsearch.c.search_rank <= MAX_RANK_PARAM))
if details.layers is not None:
sql = sql.where(_filter_by_layer(t, details.layers))
+ sql = sql.limit(LIMIT_PARAM)
results = nres.SearchResults()
- for row in await conn.execute(sql.limit(limit)):
+ for row in await conn.execute(sql, _details_to_bind_params(details)):
result = nres.create_from_placex_row(row, nres.SearchResult)
assert result
- result.bbox = Bbox.from_wkb(row.bbox.data)
+ result.bbox = Bbox.from_wkb(row.bbox)
result.accuracy = row.accuracy
if not details.excluded or not result.place_id in details.excluded:
results.append(result)
projects / nominatim.git / blobdiff