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# | |
# Pyserini: Reproducible IR research with sparse and dense representations | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# | |
import os | |
import shutil | |
import tarfile | |
import unittest | |
from random import randint | |
from urllib.request import urlretrieve | |
from pyserini.analysis import get_lucene_analyzer | |
from pyserini.search.lucene import LuceneSearcher, querybuilder | |
class TestQueryBuilding(unittest.TestCase): | |
def setUp(self): | |
# Download pre-built CACM index built using Lucene 9; append a random value to avoid filename clashes. | |
r = randint(0, 10000000) | |
self.collection_url = 'https://github.com/castorini/anserini-data/raw/master/CACM/lucene9-index.cacm.tar.gz' | |
self.tarball_name = 'lucene-index.cacm-{}.tar.gz'.format(r) | |
self.index_dir = 'index{}/'.format(r) | |
filename, headers = urlretrieve(self.collection_url, self.tarball_name) | |
tarball = tarfile.open(self.tarball_name) | |
tarball.extractall(self.index_dir) | |
tarball.close() | |
self.searcher = LuceneSearcher(f'{self.index_dir}lucene9-index.cacm') | |
def testBuildBoostedQuery(self): | |
term_query1 = querybuilder.get_term_query('information') | |
term_query2 = querybuilder.get_term_query('retrieval') | |
boost1 = querybuilder.get_boost_query(term_query1, 2.) | |
boost2 = querybuilder.get_boost_query(term_query2, 2.) | |
should = querybuilder.JBooleanClauseOccur['should'].value | |
boolean_query = querybuilder.get_boolean_query_builder() | |
boolean_query.add(boost1, should) | |
boolean_query.add(boost2, should) | |
bq = boolean_query.build() | |
hits1 = self.searcher.search(bq) | |
boolean_query2 = querybuilder.get_boolean_query_builder() | |
boolean_query2.add(term_query1, should) | |
boolean_query2.add(term_query2, should) | |
bq2 = boolean_query2.build() | |
hits2 = self.searcher.search(bq2) | |
for h1, h2 in zip(hits1, hits2): | |
self.assertEqual(h1.docid, h2.docid) | |
self.assertAlmostEqual(h1.score, h2.score*2, delta=0.001) | |
boost3 = querybuilder.get_boost_query(term_query1, 2.) | |
boost4 = querybuilder.get_boost_query(term_query2, 3.) | |
boolean_query = querybuilder.get_boolean_query_builder() | |
boolean_query.add(boost3, should) | |
boolean_query.add(boost4, should) | |
bq3 = boolean_query.build() | |
hits3 = self.searcher.search(bq3) | |
for h1, h3 in zip(hits1, hits3): | |
self.assertNotEqual(h1.score, h3.score) | |
def testTermQuery(self): | |
should = querybuilder.JBooleanClauseOccur['should'].value | |
query_builder = querybuilder.get_boolean_query_builder() | |
query_builder.add(querybuilder.get_term_query('information'), should) | |
query_builder.add(querybuilder.get_term_query('retrieval'), should) | |
query = query_builder.build() | |
hits1 = self.searcher.search(query) | |
hits2 = self.searcher.search('information retrieval') | |
for h1, h2 in zip(hits1, hits2): | |
self.assertEqual(h1.docid, h2.docid) | |
self.assertEqual(h1.score, h2.score) | |
def testIncompatabilityWithRM3(self): | |
should = querybuilder.JBooleanClauseOccur['should'].value | |
query_builder = querybuilder.get_boolean_query_builder() | |
query_builder.add(querybuilder.get_term_query('information'), should) | |
query_builder.add(querybuilder.get_term_query('retrieval'), should) | |
query = query_builder.build() | |
hits = self.searcher.search(query) | |
self.assertEqual(10, len(hits)) | |
self.searcher.set_rm3() | |
self.assertTrue(self.searcher.is_using_rm3()) | |
with self.assertRaises(NotImplementedError): | |
self.searcher.search(query) | |
def testTermQuery2(self): | |
term_query1 = querybuilder.get_term_query('inform', analyzer=get_lucene_analyzer(stemming=False)) | |
term_query2 = querybuilder.get_term_query('retriev', analyzer=get_lucene_analyzer(stemming=False)) | |
should = querybuilder.JBooleanClauseOccur['should'].value | |
boolean_query1 = querybuilder.get_boolean_query_builder() | |
boolean_query1.add(term_query1, should) | |
boolean_query1.add(term_query2, should) | |
bq1 = boolean_query1.build() | |
hits1 = self.searcher.search(bq1) | |
hits2 = self.searcher.search('information retrieval') | |
for h1, h2 in zip(hits1, hits2): | |
self.assertEqual(h1.docid, h2.docid) | |
self.assertEqual(h1.score, h2.score) | |
def tearDown(self): | |
self.searcher.close() | |
os.remove(self.tarball_name) | |
shutil.rmtree(self.index_dir) | |
if __name__ == '__main__': | |
unittest.main() | |