The function creates circular dependencies.
-import psycopg2.extras
-
class PlaceInfo:
""" Data class containing all information the tokenizer gets about a
place it should process the names for.
class PlaceInfo:
""" Data class containing all information the tokenizer gets about a
place it should process the names for.
- def analyze(self, analyzer):
- """ Process this place with the given tokenizer and return the
- result in psycopg2-compatible Json.
- """
- return psycopg2.extras.Json(analyzer.process_place(self))
-
-
@property
def name(self):
""" A dictionary with the names of the place or None if the place
@property
def name(self):
""" A dictionary with the names of the place or None if the place
import functools
from psycopg2 import sql as pysql
import functools
from psycopg2 import sql as pysql
from nominatim.data.place_info import PlaceInfo
from nominatim.data.place_info import PlaceInfo
def _mk_valuelist(template, num):
return pysql.SQL(',').join([pysql.SQL(template)] * num)
def _mk_valuelist(template, num):
return pysql.SQL(',').join([pysql.SQL(template)] * num)
+def _analyze_place(place, analyzer):
+ return psycopg2.extras.Json(analyzer.process_place(PlaceInfo(place)))
class AbstractPlacexRunner:
""" Returns SQL commands for indexing of the placex table.
class AbstractPlacexRunner:
""" Returns SQL commands for indexing of the placex table.
for place in places:
for field in ('place_id', 'name', 'address', 'linked_place_id'):
values.append(place[field])
for place in places:
for field in ('place_id', 'name', 'address', 'linked_place_id'):
values.append(place[field])
- values.append(PlaceInfo(place).analyze(self.analyzer))
+ values.append(_analyze_place(place, self.analyzer))
worker.perform(self._index_sql(len(places)), values)
worker.perform(self._index_sql(len(places)), values)
values = []
for place in places:
values.extend((place[x] for x in ('place_id', 'address')))
values = []
for place in places:
values.extend((place[x] for x in ('place_id', 'address')))
- values.append(PlaceInfo(place).analyze(self.analyzer))
+ values.append(_analyze_place(place, self.analyzer))
worker.perform(self._index_sql(len(places)), values)
worker.perform(self._index_sql(len(places)), values)
+from psycopg2.extras import Json
+
from nominatim.db.connection import connect
from nominatim.db.async_connection import WorkerPool
from nominatim.db.sql_preprocessor import SQLPreprocessor
from nominatim.db.connection import connect
from nominatim.db.async_connection import WorkerPool
from nominatim.db.sql_preprocessor import SQLPreprocessor
address = dict(street=row['street'], postcode=row['postcode'])
args = ('SRID=4326;' + row['geometry'],
int(row['from']), int(row['to']), row['interpolation'],
address = dict(street=row['street'], postcode=row['postcode'])
args = ('SRID=4326;' + row['geometry'],
int(row['from']), int(row['to']), row['interpolation'],
- PlaceInfo({'address': address}).analyze(analyzer),
+ Json(analyzer.process_place(PlaceInfo({'address': address}))),
analyzer.normalize_postcode(row['postcode']))
except ValueError:
continue
analyzer.normalize_postcode(row['postcode']))
except ValueError:
continue