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64 lines
2.4 KiB
Python
64 lines
2.4 KiB
Python
# SPDX-License-Identifier: GPL-2.0-only
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#
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# This file is part of Nominatim. (https://nominatim.org)
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#
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# Copyright (C) 2022 by the Nominatim developer community.
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# For a full list of authors see the git log.
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"""
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Tests for correctly assigning wikipedia pages to places.
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"""
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import gzip
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import csv
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import pytest
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from nominatim_db.tools.refresh import import_wikipedia_articles, recompute_importance, create_functions
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@pytest.fixture
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def wiki_csv(tmp_path, sql_preprocessor):
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def _import(data):
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with gzip.open(tmp_path / 'wikimedia-importance.csv.gz', mode='wt') as fd:
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writer = csv.DictWriter(fd, fieldnames=['language', 'type', 'title',
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'importance', 'wikidata_id'],
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delimiter='\t', quotechar='|')
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writer.writeheader()
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for lang, title, importance, wd in data:
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writer.writerow({'language': lang, 'type': 'a',
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'title': title, 'importance': str(importance),
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'wikidata_id' : wd})
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return tmp_path
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return _import
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@pytest.mark.parametrize('extra', [{'wikipedia:en': 'Test'},
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{'wikipedia': 'en:Test'},
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{'wikidata': 'Q123'}])
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def test_wikipedia(dsn, temp_db_conn, temp_db_cursor, def_config, wiki_csv, placex_table, extra):
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import_wikipedia_articles(dsn, wiki_csv([('en', 'Test', 0.3, 'Q123')]))
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create_functions(temp_db_conn, def_config)
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content = temp_db_cursor.row_set(
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'SELECT language, title, importance, wikidata FROM wikimedia_importance')
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assert content == set([('en', 'Test', 0.3, 'Q123')])
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placex_table.add(osm_id=12, extratags=extra)
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recompute_importance(temp_db_conn)
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content = temp_db_cursor.row_set('SELECT wikipedia, importance FROM placex')
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assert content == set([('en:Test', 0.3)])
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def test_wikipedia_no_match(dsn, temp_db_conn, temp_db_cursor, def_config, wiki_csv,
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placex_table):
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import_wikipedia_articles(dsn, wiki_csv([('de', 'Test', 0.3, 'Q123')]))
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create_functions(temp_db_conn, def_config)
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placex_table.add(osm_id=12, extratags={'wikipedia': 'en:Test'}, rank_search=10)
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recompute_importance(temp_db_conn)
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content = temp_db_cursor.row_set('SELECT wikipedia, importance FROM placex')
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assert list(content) == [(None, pytest.approx(0.26667666))]
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