from pathlib import Path
import pytest
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
class APITester:
def __init__(self):
- self.api = napi.NominatimAPI(Path('/invalid'), {})
+ self.api = napi.NominatimAPI(Path('/invalid'))
self.async_to_sync(self.api._async_api.setup_database())
self.async_to_sync(self.exec_async(sql, data))
+ def add_placex(self, **kw):
+ name = kw.get('name')
+ if isinstance(name, str):
+ name = {'name': name}
+
+ centroid = kw.get('centroid', (23.0, 34.0))
+ geometry = kw.get('geometry', 'POINT(%f %f)' % centroid)
+
+ self.add_data('placex',
+ {'place_id': kw.get('place_id', 1000),
+ 'osm_type': kw.get('osm_type', 'W'),
+ 'osm_id': kw.get('osm_id', 4),
+ 'class_': kw.get('class_', 'highway'),
+ 'type': kw.get('type', 'residential'),
+ 'name': name,
+ 'address': kw.get('address'),
+ 'extratags': kw.get('extratags'),
+ 'parent_place_id': kw.get('parent_place_id'),
+ 'linked_place_id': kw.get('linked_place_id'),
+ 'admin_level': kw.get('admin_level', 15),
+ 'country_code': kw.get('country_code'),
+ 'housenumber': kw.get('housenumber'),
+ 'postcode': kw.get('postcode'),
+ 'wikipedia': kw.get('wikipedia'),
+ 'rank_search': kw.get('rank_search', 30),
+ 'rank_address': kw.get('rank_address', 30),
+ 'importance': kw.get('importance'),
+ 'centroid': 'POINT(%f %f)' % centroid,
+ 'indexed_status': kw.get('indexed_status', 0),
+ 'indexed_date': kw.get('indexed_date',
+ dt.datetime(2022, 12, 7, 14, 14, 46, 0)),
+ 'geometry': geometry})
+
+
+ def add_address_placex(self, object_id, **kw):
+ self.add_placex(**kw)
+ self.add_data('addressline',
+ {'place_id': object_id,
+ 'address_place_id': kw.get('place_id', 1000),
+ 'distance': kw.get('distance', 0.0),
+ 'cached_rank_address': kw.get('rank_address', 30),
+ 'fromarea': kw.get('fromarea', False),
+ 'isaddress': kw.get('isaddress', True)})
+
+
+ def add_osmline(self, **kw):
+ self.add_data('osmline',
+ {'place_id': kw.get('place_id', 10000),
+ 'osm_id': kw.get('osm_id', 4004),
+ 'parent_place_id': kw.get('parent_place_id'),
+ 'indexed_date': kw.get('indexed_date',
+ dt.datetime(2022, 12, 7, 14, 14, 46, 0)),
+ 'startnumber': kw.get('startnumber', 2),
+ 'endnumber': kw.get('endnumber', 6),
+ 'step': kw.get('step', 2),
+ 'address': kw.get('address'),
+ 'postcode': kw.get('postcode'),
+ 'country_code': kw.get('country_code'),
+ 'linegeo': kw.get('geometry', 'LINESTRING(1.1 -0.2, 1.09 -0.22)')})
+
+
+ def add_tiger(self, **kw):
+ self.add_data('tiger',
+ {'place_id': kw.get('place_id', 30000),
+ 'parent_place_id': kw.get('parent_place_id'),
+ 'startnumber': kw.get('startnumber', 2),
+ 'endnumber': kw.get('endnumber', 6),
+ 'step': kw.get('step', 2),
+ 'postcode': kw.get('postcode'),
+ 'linegeo': kw.get('geometry', 'LINESTRING(1.1 -0.2, 1.09 -0.22)')})
+
+
+ def add_postcode(self, **kw):
+ self.add_data('postcode',
+ {'place_id': kw.get('place_id', 1000),
+ 'parent_place_id': kw.get('parent_place_id'),
+ 'country_code': kw.get('country_code'),
+ 'postcode': kw.get('postcode'),
+ 'rank_search': kw.get('rank_search', 20),
+ 'rank_address': kw.get('rank_address', 22),
+ 'indexed_date': kw.get('indexed_date',
+ dt.datetime(2022, 12, 7, 14, 14, 46, 0)),
+ 'geometry': kw.get('geometry', 'POINT(23 34)')})
+
+
+ def add_country(self, country_code, geometry):
+ self.add_data('country_grid',
+ {'country_code': country_code,
+ 'area': 0.1,
+ 'geometry': 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': '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)
@pytest.fixture
-def apiobj(temp_db_with_extensions):
+def apiobj(temp_db_with_extensions, temp_db_conn, monkeypatch):
""" Create an asynchronous SQLAlchemy engine for the test DB.
"""
+ monkeypatch.setenv('NOMINATIM_USE_US_TIGER_DATA', 'yes')
testapi = APITester()
testapi.async_to_sync(testapi.create_tables())
+
+ proc = SQLPreprocessor(temp_db_conn, testapi.api.config)
+ proc.run_sql_file(temp_db_conn, 'functions/address_lookup.sql')
+ proc.run_sql_file(temp_db_conn, 'functions/ranking.sql')
+
+ loglib.set_log_output('text')
yield testapi
+ print(loglib.get_and_disable())
+
testapi.api.close()
projects / nominatim.git / blobdiff