# typed Python is enabled. See also https://github.com/PyCQA/pylint/issues/5273
disable=too-few-public-methods,duplicate-code,too-many-ancestors,bad-option-value,no-self-use,not-context-manager,use-dict-literal,chained-comparison,attribute-defined-outside-init
-good-names=i,j,x,y,m,t,fd,db,cc,x1,x2,y1,y2,pt,k,v
+good-names=i,j,x,y,m,t,fd,db,cc,x1,x2,y1,y2,pt,k,v,nr
"""
Extended SQLAlchemy connection class that also includes access to the schema.
"""
-from typing import Any, Mapping, Sequence, Union, Dict, cast
+from typing import cast, Any, Mapping, Sequence, Union, Dict, Optional, Set
import sqlalchemy as sa
+from geoalchemy2 import Geometry
from sqlalchemy.ext.asyncio import AsyncConnection
+from nominatim.typing import SaFromClause
from nominatim.db.sqlalchemy_schema import SearchTables
from nominatim.api.logging import log
self.connection = conn
self.t = tables # pylint: disable=invalid-name
self._property_cache = properties
+ self._classtables: Optional[Set[str]] = None
async def scalar(self, sql: sa.sql.base.Executable,
raise ValueError(f"DB setting '{name}' not found in database.")
return self._property_cache['DB:server_version']
+
+
+ async def get_class_table(self, cls: str, typ: str) -> Optional[SaFromClause]:
+ """ Lookup up if there is a classtype table for the given category
+ and return a SQLAlchemy table for it, if it exists.
+ """
+ if self._classtables is None:
+ res = await self.execute(sa.text("""SELECT tablename FROM pg_tables
+ WHERE tablename LIKE 'place_classtype_%'
+ """))
+ self._classtables = {r[0] for r in res}
+
+ tablename = f"place_classtype_{cls}_{typ}"
+
+ if tablename not in self._classtables:
+ return None
+
+ if tablename in self.t.meta.tables:
+ return self.t.meta.tables[tablename]
+
+ return sa.Table(tablename, self.t.meta,
+ sa.Column('place_id', sa.BigInteger),
+ sa.Column('centroid', Geometry(srid=4326, spatial_index=False)))
""" A search result for forward geocoding.
"""
bbox: Optional[Bbox] = None
+ accuracy: float = 0.0
+
+
+ @property
+ def ranking(self) -> float:
+ """ Return the ranking, a combined measure of accuracy and importance.
+ """
+ return (self.accuracy if self.accuracy is not None else 1) \
+ - self.calculated_importance()
class SearchResults(List[SearchResult]):
geometry=_filter_geometries(row))
+def create_from_country_row(row: Optional[SaRow],
+ class_type: Type[BaseResultT]) -> Optional[BaseResultT]:
+ """ Construct a new result and add the data from the result row
+ from the fallback country tables. 'class_type' defines
+ the type of result to return. Returns None if the row is None.
+ """
+ if row is None:
+ return None
+
+ return class_type(source_table=SourceTable.COUNTRY,
+ category=('place', 'country'),
+ centroid=Point.from_wkb(row.centroid.data),
+ names=row.name,
+ rank_address=4, rank_search=4,
+ country_code=row.country_code)
+
+
async def add_result_details(conn: SearchConnection, result: BaseResult,
details: LookupDetails) -> None:
""" Retrieve more details from the database according to the
"""
Data structures for more complex fields in abstract search descriptions.
"""
-from typing import List, Tuple, cast
+from typing import List, Tuple, Iterator, cast
import dataclasses
import sqlalchemy as sa
from sqlalchemy.dialects.postgresql import ARRAY
-from nominatim.typing import SaFromClause, SaColumn
+from nominatim.typing import SaFromClause, SaColumn, SaExpression
from nominatim.api.search.query import Token
@dataclasses.dataclass
return bool(self.values)
+ def __iter__(self) -> Iterator[Tuple[str, float]]:
+ return iter(zip(self.values, self.penalties))
+
+
+ def get_penalty(self, value: str, default: float = 1000.0) -> float:
+ """ Get the penalty for the given value. Returns the given default
+ if the value does not exist.
+ """
+ try:
+ return self.penalties[self.values.index(value)]
+ except ValueError:
+ pass
+ return default
+
+
@dataclasses.dataclass
class WeightedCategories:
""" A list of class/type tuples together with a penalty.
return bool(self.values)
+ def __iter__(self) -> Iterator[Tuple[Tuple[str, str], float]]:
+ return iter(zip(self.values, self.penalties))
+
+
+ def get_penalty(self, value: Tuple[str, str], default: float = 1000.0) -> float:
+ """ Get the penalty for the given value. Returns the given default
+ if the value does not exist.
+ """
+ try:
+ return self.penalties[self.values.index(value)]
+ except ValueError:
+ pass
+ return default
+
+
+ def sql_restrict(self, table: SaFromClause) -> SaExpression:
+ """ Return an SQLAlcheny expression that restricts the
+ class and type columns of the given table to the values
+ in the list.
+ Must not be used with an empty list.
+ """
+ assert self.values
+ if len(self.values) == 1:
+ return sa.and_(table.c.class_ == self.values[0][0],
+ table.c.type == self.values[0][1])
+
+ return sa.or_(*(sa.and_(table.c.class_ == c, table.c.type == t)
+ for c, t in self.values))
+
+
@dataclasses.dataclass(order=True)
class RankedTokens:
""" List of tokens together with the penalty of using it.
"""
Implementation of the acutal database accesses for forward search.
"""
+from typing import List, Tuple, AsyncIterator
import abc
+import sqlalchemy as sa
+from sqlalchemy.dialects.postgresql import ARRAY, array_agg
+
+from nominatim.typing import SaFromClause, SaScalarSelect, SaColumn, \
+ SaExpression, SaSelect, SaRow
from nominatim.api.connection import SearchConnection
-from nominatim.api.types import SearchDetails
+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
+#pylint: disable=singleton-comparison
+#pylint: disable=too-many-branches,too-many-arguments,too-many-locals,too-many-statements
+
+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.address, t.c.extratags,
+ t.c.housenumber, t.c.postcode, t.c.country_code,
+ t.c.importance, 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'))
+
+
+def _add_geometry_columns(sql: SaSelect, col: SaColumn, details: SearchDetails) -> SaSelect:
+ if not details.geometry_output:
+ return sql
+
+ out = []
+
+ if details.geometry_simplification > 0.0:
+ col = col.ST_SimplifyPreserveTopology(details.geometry_simplification)
+
+ if details.geometry_output & GeometryFormat.GEOJSON:
+ out.append(col.ST_AsGeoJSON().label('geometry_geojson'))
+ if details.geometry_output & GeometryFormat.TEXT:
+ out.append(col.ST_AsText().label('geometry_text'))
+ if details.geometry_output & GeometryFormat.KML:
+ out.append(col.ST_AsKML().label('geometry_kml'))
+ if details.geometry_output & GeometryFormat.SVG:
+ out.append(col.ST_AsSVG().label('geometry_svg'))
+
+ return sql.add_columns(*out)
+
+
+def _make_interpolation_subquery(table: SaFromClause, inner: SaFromClause,
+ numerals: List[int], details: SearchDetails) -> SaScalarSelect:
+ all_ids = array_agg(table.c.place_id) # type: ignore[no-untyped-call]
+ 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(table.c.place_id.not_in(details.excluded))
+
+ return sql.scalar_subquery()
+
+
+def _filter_by_layer(table: SaFromClause, layers: DataLayer) -> SaColumn:
+ orexpr: List[SaExpression] = []
+ if layers & DataLayer.ADDRESS and layers & DataLayer.POI:
+ orexpr.append(table.c.rank_address.between(1, 30))
+ elif layers & DataLayer.ADDRESS:
+ orexpr.append(table.c.rank_address.between(1, 29))
+ orexpr.append(sa.and_(table.c.rank_address == 30,
+ sa.or_(table.c.housenumber != None,
+ table.c.address.has_key('housename'))))
+ elif layers & DataLayer.POI:
+ orexpr.append(sa.and_(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)),
+ 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)),
+ table.c.rank_address == 0))
+
+ if len(orexpr) == 1:
+ return orexpr[0]
+
+ return sa.or_(*orexpr)
+
+
+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')
+
+
+async def _get_placex_housenumbers(conn: SearchConnection,
+ place_ids: List[int],
+ details: SearchDetails) -> AsyncIterator[nres.SearchResult]:
+ 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)
+
+ 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)
+ 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 = sa.values(sa.Column('nr', sa.Integer()), name='housenumber')\
+ .data([(n,) for n in 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 = _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 = sa.values(sa.Column('nr', sa.Integer()), name='housenumber')\
+ .data([(n,) for n in 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 = _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 AbstractSearch(abc.ABC):
""" Encapuslation of a single lookup in the database.
"""
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
- return nres.SearchResults([])
+ 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
+ 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)
+
+ 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)
+
+ t = conn.t.placex.alias('p')
+ tgeom = conn.t.placex.alias('pgeom')
+
+ sql = _select_placex(t).where(tgeom.c.place_id.in_(ids))\
+ .where(t.c.class_ == category[0])\
+ .where(t.c.type == category[1])
+
+ if table is None:
+ # No classtype table available, do a simplified lookup in placex.
+ sql = sql.join(tgeom, t.c.geometry.ST_DWithin(tgeom.c.centroid, 0.01))\
+ .order_by(tgeom.c.centroid.ST_Distance(t.c.centroid))
+ else:
+ # Use classtype table. We can afford to use a larger
+ # radius for the lookup.
+ 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.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))
+
+ 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)
+ if details.excluded:
+ sql = sql.where(t.c.place_id.not_in(details.excluded))
+ 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)):
+ result = nres.create_from_placex_row(row, nres.SearchResult)
+ assert result
+ result.accuracy = self.penalty + penalty
+ result.bbox = Bbox.from_wkb(row.bbox.data)
+ results.append(result)
+
class PoiSearch(AbstractSearch):
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
- return nres.SearchResults([])
+ 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()))
+
+ 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()))
+
+ 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)))
+ else:
+ # use the class type tables
+ for category in self.categories.values:
+ table = await conn.get_class_table(*category)
+ if table is not None:
+ sql = _select_placex(t)\
+ .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(details.viewbox.sql_value()))
+
+ 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 self.countries:
+ sql = sql.where(t.c.country_code.in_(self.countries.values))
+
+ rows.extend(await conn.execute(sql.limit(details.max_results)))
+
+ 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)
+ results.append(result)
+
+ return results
class CountrySearch(AbstractSearch):
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
- return nres.SearchResults([])
+ t = conn.t.placex
+
+ sql = _select_placex(t)\
+ .where(t.c.country_code.in_(self.countries.values))\
+ .where(t.c.rank_address == 4)
+
+ sql = _add_geometry_columns(sql, t.c.geometry, details)
+
+ if details.excluded:
+ sql = sql.where(t.c.place_id.not_in(details.excluded))
+
+ if details.viewbox is not None and details.bounded_viewbox:
+ sql = sql.where(t.c.geometry.intersects(details.viewbox.sql_value()))
+
+ 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))
+
+ results = nres.SearchResults()
+ for row in await conn.execute(sql):
+ result = nres.create_from_placex_row(row, nres.SearchResult)
+ assert result
+ result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
+ results.append(result)
+
+ return results or await self.lookup_in_country_table(conn, details)
+
+
+ async def lookup_in_country_table(self, conn: SearchConnection,
+ details: SearchDetails) -> nres.SearchResults:
+ """ Look up the country in the fallback country tables.
+ """
+ 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'))\
+ .where(tgrid.c.country_code.in_(self.countries.values))\
+ .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()))
+ 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))
+
+ sub = sql.subquery('grid')
+
+ sql = sa.select(t.c.country_code,
+ (t.c.name
+ + sa.func.coalesce(t.c.derived_name,
+ sa.cast('', type_=conn.t.types.Composite))
+ ).label('name'),
+ sub.c.centroid)\
+ .join(sub, t.c.country_code == sub.c.country_code)
+
+ results = nres.SearchResults()
+ for row in await conn.execute(sql):
+ result = nres.create_from_country_row(row, nres.SearchResult)
+ assert result
+ result.accuracy = self.penalty + self.countries.get_penalty(row.country_code, 5.0)
+ results.append(result)
+
+ return results
+
class PostcodeSearch(AbstractSearch):
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
- return nres.SearchResults([])
+ t = conn.t.postcode
+
+ 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_(self.postcodes.values))
+
+ 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()))
+ 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),
+ 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()))
+
+ 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))
+
+ if self.lookups:
+ assert len(self.lookups) == 1
+ assert self.lookups[0].lookup_type == 'restrict'
+ tsearch = conn.t.search_name
+ sql = sql.where(tsearch.c.place_id == t.c.parent_place_id)\
+ .where(sa.func.array_cat(tsearch.c.name_vector,
+ tsearch.c.nameaddress_vector,
+ type_=ARRAY(sa.Integer))
+ .contains(self.lookups[0].tokens))
+
+ for ranking in self.rankings:
+ penalty += ranking.sql_penalty(conn.t.search_name)
+ 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')
+
+ results = nres.SearchResults()
+ for row in await conn.execute(sql.limit(details.max_results)):
+ result = nres.create_from_postcode_row(row, nres.SearchResult)
+ assert result
+ result.accuracy = row.accuracy
+ results.append(result)
+
+ return results
+
class PlaceSearch(AbstractSearch):
details: SearchDetails) -> nres.SearchResults:
""" Find results for the search in the database.
"""
- return nres.SearchResults([])
+ t = conn.t.placex.alias('p')
+ tsearch = conn.t.search_name.alias('s')
+ limit = details.max_results
+
+ 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 = _add_geometry_columns(sql, t.c.geometry, details)
+
+ penalty: SaExpression = sa.literal(self.penalty)
+ for ranking in self.rankings:
+ penalty += ranking.sql_penalty(tsearch)
+
+ for lookup in self.lookups:
+ sql = sql.where(lookup.sql_condition(tsearch))
+
+ if self.countries:
+ sql = sql.where(tsearch.c.country_code.in_(self.countries.values))
+
+ if self.postcodes:
+ tpc = conn.t.postcode
+ 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))
+ .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))\
+ .scalar_subquery()
+ penalty += sa.case((t.c.postcode.in_(self.postcodes.values), 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()))
+ 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),
+ 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())
+ .label('importance'))
+ sql = sql.order_by(sa.desc(sa.text('importance')))
+ else:
+ sql = sql.order_by(penalty - sa.case((tsearch.c.importance > 0, tsearch.c.importance),
+ else_=0.75001-(sa.cast(tsearch.c.search_rank, sa.Float())/40)))
+ sql = sql.add_columns(t.c.importance)
+
+
+ sql = sql.add_columns(penalty.label('accuracy'))\
+ .order_by(sa.text('accuracy'))
+
+ if self.housenumbers:
+ 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')))
+
+ # Cross check for housenumbers, need to do that on a rather large
+ # set. Worst case there are 40.000 main streets in OSM.
+ inner = sql.limit(10000).subquery()
+
+ # Housenumbers from placex
+ thnr = conn.t.placex.alias('hnr')
+ 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.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))
+ 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
+ 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.literal(None)
+ tiger_sql = sa.literal(None)
+
+ 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.excluded:
+ sql = sql.where(tsearch.c.place_id.not_in(details.excluded))
+ if details.min_rank > 0:
+ sql = sql.where(sa.or_(tsearch.c.address_rank >= details.min_rank,
+ tsearch.c.search_rank >= details.min_rank))
+ if details.max_rank < 30:
+ sql = sql.where(sa.or_(tsearch.c.address_rank <= details.max_rank,
+ tsearch.c.search_rank <= details.max_rank))
+ if details.layers is not None:
+ sql = sql.where(_filter_by_layer(t, details.layers))
+
+
+ results = nres.SearchResults()
+ for row in await conn.execute(sql.limit(limit)):
+ result = nres.create_from_placex_row(row, nres.SearchResult)
+ assert result
+ result.bbox = Bbox.from_wkb(row.bbox.data)
+ result.accuracy = row.accuracy
+ if not details.excluded or not result.place_id in details.excluded:
+ results.append(result)
+
+ 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)
+
+ result.accuracy += 1.0 # penalty for missing housenumber
+
+ return results
import math
from struct import unpack
+from geoalchemy2 import WKTElement
+import geoalchemy2.functions
+
from nominatim.errors import UsageError
# pylint: disable=no-member,too-many-boolean-expressions,too-many-instance-attributes
return Point(x, y)
+ def sql_value(self) -> WKTElement:
+ """ Create an SQL expression for the point.
+ """
+ return WKTElement(f'POINT({self.x} {self.y})', srid=4326)
+
+
AnyPoint = Union[Point, Tuple[float, float]]
return self.coords[2]
+ @property
+ def area(self) -> float:
+ """ Return the area of the box in WGS84.
+ """
+ return (self.coords[2] - self.coords[0]) * (self.coords[3] - self.coords[1])
+
+
+ def sql_value(self) -> Any:
+ """ Create an SQL expression for the box.
+ """
+ return geoalchemy2.functions.ST_MakeEnvelope(*self.coords, 4326)
+
+
def contains(self, pt: Point) -> bool:
""" Check if the point is inside or on the boundary of the box.
"""
return self.coords[0] <= pt[0] and self.coords[1] <= pt[1]\
and self.coords[2] >= pt[0] and self.coords[3] >= pt[1]
+
@staticmethod
def from_wkb(wkb: Optional[bytes]) -> 'Optional[Bbox]':
""" Create a Bbox from a bounding box polygon as returned by
if self.viewbox is not None:
xext = (self.viewbox.maxlon - self.viewbox.minlon)/2
yext = (self.viewbox.maxlat - self.viewbox.minlat)/2
- self.viewbox_x2 = Bbox(self.viewbox.minlon - xext, self.viewbox.maxlon - yext,
+ self.viewbox_x2 = Bbox(self.viewbox.minlon - xext, self.viewbox.minlat - yext,
self.viewbox.maxlon + xext, self.viewbox.maxlat + yext)
TypeAlias = str
SaSelect: TypeAlias = 'sa.Select[Any]'
+SaScalarSelect: TypeAlias = 'sa.ScalarSelect[Any]'
SaRow: TypeAlias = 'sa.Row[Any]'
SaColumn: TypeAlias = 'sa.ColumnElement[Any]'
+SaExpression: TypeAlias = 'sa.ColumnElement[bool]'
SaLabel: TypeAlias = 'sa.Label[Any]'
SaFromClause: TypeAlias = 'sa.FromClause'
SaSelectable: TypeAlias = 'sa.Selectable'
import time
import datetime as dt
+import sqlalchemy as sa
+
import nominatim.api as napi
from nominatim.db.sql_preprocessor import SQLPreprocessor
import nominatim.api.logging as loglib
'geometry': 'SRID=4326;' + geometry})
+ def add_country_name(self, country_code, names, partition=0):
+ self.add_data('country_name',
+ {'country_code': country_code,
+ 'name': names,
+ 'partition': partition})
+
+
+ def add_search_name(self, place_id, **kw):
+ centroid = kw.get('centroid', (23.0, 34.0))
+ self.add_data('search_name',
+ {'place_id': place_id,
+ 'importance': kw.get('importance', 0.00001),
+ 'search_rank': kw.get('search_rank', 30),
+ 'address_rank': kw.get('address_rank', 30),
+ 'name_vector': kw.get('names', []),
+ 'nameaddress_vector': kw.get('address', []),
+ 'country_code': kw.get('country_code', 'xx'),
+ 'centroid': 'SRID=4326;POINT(%f %f)' % centroid})
+
+
+ def add_class_type_table(self, cls, typ):
+ self.async_to_sync(
+ self.exec_async(sa.text(f"""CREATE TABLE place_classtype_{cls}_{typ}
+ AS (SELECT place_id, centroid FROM placex
+ WHERE class = '{cls}' AND type = '{typ}')
+ """)))
+
+
async def exec_async(self, sql, *args, **kwargs):
async with self.api._async_api.begin() as conn:
return await conn.execute(sql, *args, **kwargs)
--- /dev/null
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+# This file is part of Nominatim. (https://nominatim.org)
+#
+# Copyright (C) 2023 by the Nominatim developer community.
+# For a full list of authors see the git log.
+"""
+Tests for running the country searcher.
+"""
+import pytest
+
+import nominatim.api as napi
+from nominatim.api.types import SearchDetails
+from nominatim.api.search.db_searches import CountrySearch
+from nominatim.api.search.db_search_fields import WeightedStrings
+
+
+def run_search(apiobj, global_penalty, ccodes,
+ country_penalties=None, details=SearchDetails()):
+ if country_penalties is None:
+ country_penalties = [0.0] * len(ccodes)
+
+ class MySearchData:
+ penalty = global_penalty
+ countries = WeightedStrings(ccodes, country_penalties)
+
+ search = CountrySearch(MySearchData())
+
+ async def run():
+ async with apiobj.api._async_api.begin() as conn:
+ return await search.lookup(conn, details)
+
+ return apiobj.async_to_sync(run())
+
+
+def test_find_from_placex(apiobj):
+ apiobj.add_placex(place_id=55, class_='boundary', type='administrative',
+ rank_search=4, rank_address=4,
+ name={'name': 'Lolaland'},
+ country_code='yw',
+ centroid=(10, 10),
+ geometry='POLYGON((9.5 9.5, 9.5 10.5, 10.5 10.5, 10.5 9.5, 9.5 9.5))')
+
+ results = run_search(apiobj, 0.5, ['de', 'yw'], [0.0, 0.3])
+
+ assert len(results) == 1
+ assert results[0].place_id == 55
+ assert results[0].accuracy == 0.8
+
+def test_find_from_fallback_countries(apiobj):
+ apiobj.add_country('ro', 'POLYGON((0 0, 0 1, 1 1, 1 0, 0 0))')
+ apiobj.add_country_name('ro', {'name': 'România'})
+
+ results = run_search(apiobj, 0.0, ['ro'])
+
+ assert len(results) == 1
+ assert results[0].names == {'name': 'România'}
+
+
+def test_find_none(apiobj):
+ assert len(run_search(apiobj, 0.0, ['xx'])) == 0
--- /dev/null
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+# This file is part of Nominatim. (https://nominatim.org)
+#
+# Copyright (C) 2023 by the Nominatim developer community.
+# For a full list of authors see the git log.
+"""
+Tests for running the near searcher.
+"""
+import pytest
+
+import nominatim.api as napi
+from nominatim.api.types import SearchDetails
+from nominatim.api.search.db_searches import NearSearch, PlaceSearch
+from nominatim.api.search.db_search_fields import WeightedStrings, WeightedCategories,\
+ FieldLookup, FieldRanking, RankedTokens
+
+
+def run_search(apiobj, global_penalty, cat, cat_penalty=None,
+ details=SearchDetails()):
+
+ class PlaceSearchData:
+ penalty = 0.0
+ postcodes = WeightedStrings([], [])
+ countries = WeightedStrings([], [])
+ housenumbers = WeightedStrings([], [])
+ qualifiers = WeightedStrings([], [])
+ lookups = [FieldLookup('name_vector', [56], 'lookup_all')]
+ rankings = []
+
+ place_search = PlaceSearch(0.0, PlaceSearchData(), 2)
+
+ if cat_penalty is None:
+ cat_penalty = [0.0] * len(cat)
+
+ near_search = NearSearch(0.1, WeightedCategories(cat, cat_penalty), place_search)
+
+ async def run():
+ async with apiobj.api._async_api.begin() as conn:
+ return await near_search.lookup(conn, details)
+
+ results = apiobj.async_to_sync(run())
+ results.sort(key=lambda r: r.accuracy)
+
+ return results
+
+
+def test_no_results_inner_query(apiobj):
+ assert not run_search(apiobj, 0.4, [('this', 'that')])
+
+
+class TestNearSearch:
+
+ @pytest.fixture(autouse=True)
+ def fill_database(self, apiobj):
+ apiobj.add_placex(place_id=100, country_code='us',
+ centroid=(5.6, 4.3))
+ apiobj.add_search_name(100, names=[56], country_code='us',
+ centroid=(5.6, 4.3))
+ apiobj.add_placex(place_id=101, country_code='mx',
+ centroid=(-10.3, 56.9))
+ apiobj.add_search_name(101, names=[56], country_code='mx',
+ centroid=(-10.3, 56.9))
+
+
+ def test_near_in_placex(self, apiobj):
+ apiobj.add_placex(place_id=22, class_='amenity', type='bank',
+ centroid=(5.6001, 4.2994))
+ apiobj.add_placex(place_id=23, class_='amenity', type='bench',
+ centroid=(5.6001, 4.2994))
+
+ results = run_search(apiobj, 0.1, [('amenity', 'bank')])
+
+ assert [r.place_id for r in results] == [22]
+
+
+ def test_multiple_types_near_in_placex(self, apiobj):
+ apiobj.add_placex(place_id=22, class_='amenity', type='bank',
+ importance=0.002,
+ centroid=(5.6001, 4.2994))
+ apiobj.add_placex(place_id=23, class_='amenity', type='bench',
+ importance=0.001,
+ centroid=(5.6001, 4.2994))
+
+ results = run_search(apiobj, 0.1, [('amenity', 'bank'),
+ ('amenity', 'bench')])
+
+ assert [r.place_id for r in results] == [22, 23]
+
+
+ def test_near_in_classtype(self, apiobj):
+ apiobj.add_placex(place_id=22, class_='amenity', type='bank',
+ centroid=(5.6, 4.34))
+ apiobj.add_placex(place_id=23, class_='amenity', type='bench',
+ centroid=(5.6, 4.34))
+ apiobj.add_class_type_table('amenity', 'bank')
+ apiobj.add_class_type_table('amenity', 'bench')
+
+ results = run_search(apiobj, 0.1, [('amenity', 'bank')])
+
+ assert [r.place_id for r in results] == [22]
+
--- /dev/null
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+# This file is part of Nominatim. (https://nominatim.org)
+#
+# Copyright (C) 2023 by the Nominatim developer community.
+# For a full list of authors see the git log.
+"""
+Tests for running the generic place searcher.
+"""
+import pytest
+
+import nominatim.api as napi
+from nominatim.api.types import SearchDetails
+from nominatim.api.search.db_searches import PlaceSearch
+from nominatim.api.search.db_search_fields import WeightedStrings, WeightedCategories,\
+ FieldLookup, FieldRanking, RankedTokens
+
+def run_search(apiobj, global_penalty, lookup, ranking, count=2,
+ hnrs=[], pcs=[], ccodes=[], quals=[],
+ details=SearchDetails()):
+ class MySearchData:
+ penalty = global_penalty
+ postcodes = WeightedStrings(pcs, [0.0] * len(pcs))
+ countries = WeightedStrings(ccodes, [0.0] * len(ccodes))
+ housenumbers = WeightedStrings(hnrs, [0.0] * len(hnrs))
+ qualifiers = WeightedCategories(quals, [0.0] * len(quals))
+ lookups = lookup
+ rankings = ranking
+
+ search = PlaceSearch(0.0, MySearchData(), count)
+
+ async def run():
+ async with apiobj.api._async_api.begin() as conn:
+ return await search.lookup(conn, details)
+
+ results = apiobj.async_to_sync(run())
+ results.sort(key=lambda r: r.accuracy)
+
+ return results
+
+
+class TestNameOnlySearches:
+
+ @pytest.fixture(autouse=True)
+ def fill_database(self, apiobj):
+ apiobj.add_placex(place_id=100, country_code='us',
+ centroid=(5.6, 4.3))
+ apiobj.add_search_name(100, names=[1,2,10,11], country_code='us',
+ centroid=(5.6, 4.3))
+ apiobj.add_placex(place_id=101, country_code='mx',
+ centroid=(-10.3, 56.9))
+ apiobj.add_search_name(101, names=[1,2,20,21], country_code='mx',
+ centroid=(-10.3, 56.9))
+
+
+ @pytest.mark.parametrize('lookup_type', ['lookup_all', 'restrict'])
+ @pytest.mark.parametrize('rank,res', [([10], [100, 101]),
+ ([20], [101, 100])])
+ def test_lookup_all_match(self, apiobj, lookup_type, rank, res):
+ lookup = FieldLookup('name_vector', [1,2], lookup_type)
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, rank)])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking])
+
+ assert [r.place_id for r in results] == res
+
+
+ @pytest.mark.parametrize('lookup_type', ['lookup_all', 'restrict'])
+ def test_lookup_all_partial_match(self, apiobj, lookup_type):
+ lookup = FieldLookup('name_vector', [1,20], lookup_type)
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, [21])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking])
+
+ assert len(results) == 1
+ assert results[0].place_id == 101
+
+ @pytest.mark.parametrize('rank,res', [([10], [100, 101]),
+ ([20], [101, 100])])
+ def test_lookup_any_match(self, apiobj, rank, res):
+ lookup = FieldLookup('name_vector', [11,21], 'lookup_any')
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, rank)])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking])
+
+ assert [r.place_id for r in results] == res
+
+
+ def test_lookup_any_partial_match(self, apiobj):
+ lookup = FieldLookup('name_vector', [20], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, [21])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking])
+
+ assert len(results) == 1
+ assert results[0].place_id == 101
+
+
+ @pytest.mark.parametrize('cc,res', [('us', 100), ('mx', 101)])
+ def test_lookup_restrict_country(self, apiobj, cc, res):
+ lookup = FieldLookup('name_vector', [1,2], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, [10])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking], ccodes=[cc])
+
+ assert [r.place_id for r in results] == [res]
+
+
+ def test_lookup_restrict_placeid(self, apiobj):
+ lookup = FieldLookup('name_vector', [1,2], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, [10])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking],
+ details=SearchDetails(excluded=[101]))
+
+ assert [r.place_id for r in results] == [100]
+
+
+ @pytest.mark.parametrize('geom', [napi.GeometryFormat.GEOJSON,
+ napi.GeometryFormat.KML,
+ napi.GeometryFormat.SVG,
+ napi.GeometryFormat.TEXT])
+ def test_return_geometries(self, apiobj, geom):
+ lookup = FieldLookup('name_vector', [20], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, [21])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking],
+ details=SearchDetails(geometry_output=geom))
+
+ assert geom.name.lower() in results[0].geometry
+
+
+ @pytest.mark.parametrize('viewbox', ['5.0,4.0,6.0,5.0', '5.7,4.0,6.0,5.0'])
+ def test_prefer_viewbox(self, apiobj, viewbox):
+ lookup = FieldLookup('name_vector', [1, 2], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, [21])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking])
+ assert [r.place_id for r in results] == [101, 100]
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking],
+ details=SearchDetails.from_kwargs({'viewbox': viewbox}))
+ assert [r.place_id for r in results] == [100, 101]
+
+
+ def test_force_viewbox(self, apiobj):
+ lookup = FieldLookup('name_vector', [1, 2], 'lookup_all')
+
+ details=SearchDetails.from_kwargs({'viewbox': '5.0,4.0,6.0,5.0',
+ 'bounded_viewbox': True})
+
+ results = run_search(apiobj, 0.1, [lookup], [], details=details)
+ assert [r.place_id for r in results] == [100]
+
+
+ def test_prefer_near(self, apiobj):
+ lookup = FieldLookup('name_vector', [1, 2], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.9, [RankedTokens(0.0, [21])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking])
+ assert [r.place_id for r in results] == [101, 100]
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking],
+ details=SearchDetails.from_kwargs({'near': '5.6,4.3'}))
+ results.sort(key=lambda r: -r.importance)
+ assert [r.place_id for r in results] == [100, 101]
+
+
+ def test_force_near(self, apiobj):
+ lookup = FieldLookup('name_vector', [1, 2], 'lookup_all')
+
+ details=SearchDetails.from_kwargs({'near': '5.6,4.3',
+ 'near_radius': 0.11})
+
+ results = run_search(apiobj, 0.1, [lookup], [], details=details)
+
+ assert [r.place_id for r in results] == [100]
+
+
+class TestStreetWithHousenumber:
+
+ @pytest.fixture(autouse=True)
+ def fill_database(self, apiobj):
+ apiobj.add_placex(place_id=1, class_='place', type='house',
+ parent_place_id=1000,
+ housenumber='20 a', country_code='es')
+ apiobj.add_placex(place_id=2, class_='place', type='house',
+ parent_place_id=1000,
+ housenumber='21;22', country_code='es')
+ apiobj.add_placex(place_id=1000, class_='highway', type='residential',
+ rank_search=26, rank_address=26,
+ country_code='es')
+ apiobj.add_search_name(1000, names=[1,2,10,11],
+ search_rank=26, address_rank=26,
+ country_code='es')
+ apiobj.add_placex(place_id=91, class_='place', type='house',
+ parent_place_id=2000,
+ housenumber='20', country_code='pt')
+ apiobj.add_placex(place_id=92, class_='place', type='house',
+ parent_place_id=2000,
+ housenumber='22', country_code='pt')
+ apiobj.add_placex(place_id=93, class_='place', type='house',
+ parent_place_id=2000,
+ housenumber='24', country_code='pt')
+ apiobj.add_placex(place_id=2000, class_='highway', type='residential',
+ rank_search=26, rank_address=26,
+ country_code='pt')
+ apiobj.add_search_name(2000, names=[1,2,20,21],
+ search_rank=26, address_rank=26,
+ country_code='pt')
+
+
+ @pytest.mark.parametrize('hnr,res', [('20', [91, 1]), ('20 a', [1]),
+ ('21', [2]), ('22', [2, 92]),
+ ('24', [93]), ('25', [])])
+ def test_lookup_by_single_housenumber(self, apiobj, hnr, res):
+ lookup = FieldLookup('name_vector', [1,2], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.3, [RankedTokens(0.0, [10])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking], hnrs=[hnr])
+
+ assert [r.place_id for r in results] == res + [1000, 2000]
+
+
+ @pytest.mark.parametrize('cc,res', [('es', [2, 1000]), ('pt', [92, 2000])])
+ def test_lookup_with_country_restriction(self, apiobj, cc, res):
+ lookup = FieldLookup('name_vector', [1,2], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.3, [RankedTokens(0.0, [10])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking], hnrs=['22'],
+ ccodes=[cc])
+
+ assert [r.place_id for r in results] == res
+
+
+ def test_lookup_exclude_housenumber_placeid(self, apiobj):
+ lookup = FieldLookup('name_vector', [1,2], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.3, [RankedTokens(0.0, [10])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking], hnrs=['22'],
+ details=SearchDetails(excluded=[92]))
+
+ assert [r.place_id for r in results] == [2, 1000, 2000]
+
+
+ def test_lookup_exclude_street_placeid(self, apiobj):
+ lookup = FieldLookup('name_vector', [1,2], 'lookup_all')
+ ranking = FieldRanking('name_vector', 0.3, [RankedTokens(0.0, [10])])
+
+ results = run_search(apiobj, 0.1, [lookup], [ranking], hnrs=['22'],
+ details=SearchDetails(excluded=[1000]))
+
+ assert [r.place_id for r in results] == [2, 92, 2000]
+
+
+ @pytest.mark.parametrize('geom', [napi.GeometryFormat.GEOJSON,
+ napi.GeometryFormat.KML,
+ napi.GeometryFormat.SVG,
+ napi.GeometryFormat.TEXT])
+ def test_return_geometries(self, apiobj, geom):
+ lookup = FieldLookup('name_vector', [1, 2], 'lookup_all')
+
+ results = run_search(apiobj, 0.1, [lookup], [], hnrs=['20', '21', '22'],
+ details=SearchDetails(geometry_output=geom))
+
+ assert results
+ assert all(geom.name.lower() in r.geometry for r in results)
+
+
+class TestInterpolations:
+
+ @pytest.fixture(autouse=True)
+ def fill_database(self, apiobj):
+ apiobj.add_placex(place_id=990, class_='highway', type='service',
+ rank_search=27, rank_address=27,
+ centroid=(10.0, 10.0),
+ geometry='LINESTRING(9.995 10, 10.005 10)')
+ apiobj.add_search_name(990, names=[111],
+ search_rank=27, address_rank=27)
+ apiobj.add_placex(place_id=991, class_='place', type='house',
+ parent_place_id=990,
+ rank_search=30, rank_address=30,
+ housenumber='23',
+ centroid=(10.0, 10.00002))
+ apiobj.add_osmline(place_id=992,
+ parent_place_id=990,
+ startnumber=21, endnumber=29, step=2,
+ centroid=(10.0, 10.00001),
+ geometry='LINESTRING(9.995 10.00001, 10.005 10.00001)')
+
+
+ @pytest.mark.parametrize('hnr,res', [('21', [992]), ('22', []), ('23', [991])])
+ def test_lookup_housenumber(self, apiobj, hnr, res):
+ lookup = FieldLookup('name_vector', [111], 'lookup_all')
+
+ results = run_search(apiobj, 0.1, [lookup], [], hnrs=[hnr])
+
+ assert [r.place_id for r in results] == res + [990]
+
+
+class TestTiger:
+
+ @pytest.fixture(autouse=True)
+ def fill_database(self, apiobj):
+ apiobj.add_placex(place_id=990, class_='highway', type='service',
+ rank_search=27, rank_address=27,
+ country_code='us',
+ centroid=(10.0, 10.0),
+ geometry='LINESTRING(9.995 10, 10.005 10)')
+ apiobj.add_search_name(990, names=[111], country_code='us',
+ search_rank=27, address_rank=27)
+ apiobj.add_placex(place_id=991, class_='place', type='house',
+ parent_place_id=990,
+ rank_search=30, rank_address=30,
+ housenumber='23',
+ country_code='us',
+ centroid=(10.0, 10.00002))
+ apiobj.add_tiger(place_id=992,
+ parent_place_id=990,
+ startnumber=21, endnumber=29, step=2,
+ centroid=(10.0, 10.00001),
+ geometry='LINESTRING(9.995 10.00001, 10.005 10.00001)')
+
+
+ @pytest.mark.parametrize('hnr,res', [('21', [992]), ('22', []), ('23', [991])])
+ def test_lookup_housenumber(self, apiobj, hnr, res):
+ lookup = FieldLookup('name_vector', [111], 'lookup_all')
+
+ results = run_search(apiobj, 0.1, [lookup], [], hnrs=[hnr])
+
+ assert [r.place_id for r in results] == res + [990]
+
+
+class TestLayersRank30:
+
+ @pytest.fixture(autouse=True)
+ def fill_database(self, apiobj):
+ apiobj.add_placex(place_id=223, class_='place', type='house',
+ housenumber='1',
+ rank_address=30,
+ rank_search=30)
+ apiobj.add_search_name(223, names=[34],
+ importance=0.0009,
+ address_rank=30, search_rank=30)
+ apiobj.add_placex(place_id=224, class_='amenity', type='toilet',
+ rank_address=30,
+ rank_search=30)
+ apiobj.add_search_name(224, names=[34],
+ importance=0.0008,
+ address_rank=30, search_rank=30)
+ apiobj.add_placex(place_id=225, class_='man_made', type='tower',
+ rank_address=0,
+ rank_search=30)
+ apiobj.add_search_name(225, names=[34],
+ importance=0.0007,
+ address_rank=0, search_rank=30)
+ apiobj.add_placex(place_id=226, class_='railway', type='station',
+ rank_address=0,
+ rank_search=30)
+ apiobj.add_search_name(226, names=[34],
+ importance=0.0006,
+ address_rank=0, search_rank=30)
+ apiobj.add_placex(place_id=227, class_='natural', type='cave',
+ rank_address=0,
+ rank_search=30)
+ apiobj.add_search_name(227, names=[34],
+ importance=0.0005,
+ address_rank=0, search_rank=30)
+
+
+ @pytest.mark.parametrize('layer,res', [(napi.DataLayer.ADDRESS, [223]),
+ (napi.DataLayer.POI, [224]),
+ (napi.DataLayer.ADDRESS | napi.DataLayer.POI, [223, 224]),
+ (napi.DataLayer.MANMADE, [225]),
+ (napi.DataLayer.RAILWAY, [226]),
+ (napi.DataLayer.NATURAL, [227]),
+ (napi.DataLayer.MANMADE | napi.DataLayer.NATURAL, [225, 227]),
+ (napi.DataLayer.MANMADE | napi.DataLayer.RAILWAY, [225, 226])])
+ def test_layers_rank30(self, apiobj, layer, res):
+ lookup = FieldLookup('name_vector', [34], 'lookup_any')
+
+ results = run_search(apiobj, 0.1, [lookup], [],
+ details=SearchDetails(layers=layer))
+
+ assert [r.place_id for r in results] == res
--- /dev/null
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+# This file is part of Nominatim. (https://nominatim.org)
+#
+# Copyright (C) 2023 by the Nominatim developer community.
+# For a full list of authors see the git log.
+"""
+Tests for running the POI searcher.
+"""
+import pytest
+
+import nominatim.api as napi
+from nominatim.api.types import SearchDetails
+from nominatim.api.search.db_searches import PoiSearch
+from nominatim.api.search.db_search_fields import WeightedStrings, WeightedCategories
+
+
+def run_search(apiobj, global_penalty, poitypes, poi_penalties=None,
+ ccodes=[], details=SearchDetails()):
+ if poi_penalties is None:
+ poi_penalties = [0.0] * len(poitypes)
+
+ class MySearchData:
+ penalty = global_penalty
+ qualifiers = WeightedCategories(poitypes, poi_penalties)
+ countries = WeightedStrings(ccodes, [0.0] * len(ccodes))
+
+ search = PoiSearch(MySearchData())
+
+ async def run():
+ async with apiobj.api._async_api.begin() as conn:
+ return await search.lookup(conn, details)
+
+ return apiobj.async_to_sync(run())
+
+
+@pytest.mark.parametrize('coord,pid', [('34.3, 56.100021', 2),
+ ('5.0, 4.59933', 1)])
+def test_simple_near_search_in_placex(apiobj, coord, pid):
+ apiobj.add_placex(place_id=1, class_='highway', type='bus_stop',
+ centroid=(5.0, 4.6))
+ apiobj.add_placex(place_id=2, class_='highway', type='bus_stop',
+ centroid=(34.3, 56.1))
+
+ details = SearchDetails.from_kwargs({'near': coord, 'near_radius': 0.001})
+
+ results = run_search(apiobj, 0.1, [('highway', 'bus_stop')], [0.5], details=details)
+
+ assert [r.place_id for r in results] == [pid]
+
+
+@pytest.mark.parametrize('coord,pid', [('34.3, 56.100021', 2),
+ ('34.3, 56.4', 2),
+ ('5.0, 4.59933', 1)])
+def test_simple_near_search_in_classtype(apiobj, coord, pid):
+ apiobj.add_placex(place_id=1, class_='highway', type='bus_stop',
+ centroid=(5.0, 4.6))
+ apiobj.add_placex(place_id=2, class_='highway', type='bus_stop',
+ centroid=(34.3, 56.1))
+ apiobj.add_class_type_table('highway', 'bus_stop')
+
+ details = SearchDetails.from_kwargs({'near': coord, 'near_radius': 0.5})
+
+ results = run_search(apiobj, 0.1, [('highway', 'bus_stop')], [0.5], details=details)
+
+ assert [r.place_id for r in results] == [pid]
+
+
+class TestPoiSearchWithRestrictions:
+
+ @pytest.fixture(autouse=True, params=["placex", "classtype"])
+ def fill_database(self, apiobj, request):
+ apiobj.add_placex(place_id=1, class_='highway', type='bus_stop',
+ country_code='au',
+ centroid=(34.3, 56.10003))
+ apiobj.add_placex(place_id=2, class_='highway', type='bus_stop',
+ country_code='nz',
+ centroid=(34.3, 56.1))
+ if request.param == 'classtype':
+ apiobj.add_class_type_table('highway', 'bus_stop')
+ self.args = {'near': '34.3, 56.4', 'near_radius': 0.5}
+ else:
+ self.args = {'near': '34.3, 56.100021', 'near_radius': 0.001}
+
+
+ def test_unrestricted(self, apiobj):
+ results = run_search(apiobj, 0.1, [('highway', 'bus_stop')], [0.5],
+ details=SearchDetails.from_kwargs(self.args))
+
+ assert [r.place_id for r in results] == [1, 2]
+
+
+ def test_restict_country(self, apiobj):
+ results = run_search(apiobj, 0.1, [('highway', 'bus_stop')], [0.5],
+ ccodes=['de', 'nz'],
+ details=SearchDetails.from_kwargs(self.args))
+
+ assert [r.place_id for r in results] == [2]
+
+
+ def test_restrict_by_viewbox(self, apiobj):
+ args = {'bounded_viewbox': True, 'viewbox': '34.299,56.0,34.3001,56.10001'}
+ args.update(self.args)
+ results = run_search(apiobj, 0.1, [('highway', 'bus_stop')], [0.5],
+ ccodes=['de', 'nz'],
+ details=SearchDetails.from_kwargs(args))
+
+ assert [r.place_id for r in results] == [2]
--- /dev/null
+# SPDX-License-Identifier: GPL-3.0-or-later
+#
+# This file is part of Nominatim. (https://nominatim.org)
+#
+# Copyright (C) 2023 by the Nominatim developer community.
+# For a full list of authors see the git log.
+"""
+Tests for running the postcode searcher.
+"""
+import pytest
+
+import nominatim.api as napi
+from nominatim.api.types import SearchDetails
+from nominatim.api.search.db_searches import PostcodeSearch
+from nominatim.api.search.db_search_fields import WeightedStrings, FieldLookup, \
+ FieldRanking, RankedTokens
+
+def run_search(apiobj, global_penalty, pcs, pc_penalties=None,
+ ccodes=[], lookup=[], ranking=[], details=SearchDetails()):
+ if pc_penalties is None:
+ pc_penalties = [0.0] * len(pcs)
+
+ class MySearchData:
+ penalty = global_penalty
+ postcodes = WeightedStrings(pcs, pc_penalties)
+ countries = WeightedStrings(ccodes, [0.0] * len(ccodes))
+ lookups = lookup
+ rankings = ranking
+
+ search = PostcodeSearch(0.0, MySearchData())
+
+ async def run():
+ async with apiobj.api._async_api.begin() as conn:
+ return await search.lookup(conn, details)
+
+ return apiobj.async_to_sync(run())
+
+
+def test_postcode_only_search(apiobj):
+ apiobj.add_postcode(place_id=100, country_code='ch', postcode='12345')
+ apiobj.add_postcode(place_id=101, country_code='pl', postcode='12 345')
+
+ results = run_search(apiobj, 0.3, ['12345', '12 345'], [0.0, 0.1])
+
+ assert len(results) == 2
+ assert [r.place_id for r in results] == [100, 101]
+
+
+def test_postcode_with_country(apiobj):
+ apiobj.add_postcode(place_id=100, country_code='ch', postcode='12345')
+ apiobj.add_postcode(place_id=101, country_code='pl', postcode='12 345')
+
+ results = run_search(apiobj, 0.3, ['12345', '12 345'], [0.0, 0.1],
+ ccodes=['de', 'pl'])
+
+ assert len(results) == 1
+ assert results[0].place_id == 101
+
+
+class TestPostcodeSearchWithAddress:
+
+ @pytest.fixture(autouse=True)
+ def fill_database(self, apiobj):
+ apiobj.add_postcode(place_id=100, country_code='ch',
+ parent_place_id=1000, postcode='12345')
+ apiobj.add_postcode(place_id=101, country_code='pl',
+ parent_place_id=2000, postcode='12345')
+ apiobj.add_placex(place_id=1000, class_='place', type='village',
+ rank_search=22, rank_address=22,
+ country_code='ch')
+ apiobj.add_search_name(1000, names=[1,2,10,11],
+ search_rank=22, address_rank=22,
+ country_code='ch')
+ apiobj.add_placex(place_id=2000, class_='place', type='village',
+ rank_search=22, rank_address=22,
+ country_code='pl')
+ apiobj.add_search_name(2000, names=[1,2,20,21],
+ search_rank=22, address_rank=22,
+ country_code='pl')
+
+
+ def test_lookup_both(self, apiobj):
+ lookup = FieldLookup('name_vector', [1,2], 'restrict')
+ ranking = FieldRanking('name_vector', 0.3, [RankedTokens(0.0, [10])])
+
+ results = run_search(apiobj, 0.1, ['12345'], lookup=[lookup], ranking=[ranking])
+
+ assert [r.place_id for r in results] == [100, 101]
+
+
+ def test_restrict_by_name(self, apiobj):
+ lookup = FieldLookup('name_vector', [10], 'restrict')
+
+ results = run_search(apiobj, 0.1, ['12345'], lookup=[lookup])
+
+ assert [r.place_id for r in results] == [100]
+
projects / nominatim.git / commitdiff