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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 re
import shutil
import unittest
import json
import gzip
from random import randint
from pyserini.util import download_url, download_prebuilt_index
class TestSearchIntegration(unittest.TestCase):
def setUp(self):
curdir = os.getcwd()
if curdir.endswith('clprf'):
self.pyserini_root = '../..'
else:
self.pyserini_root = '.'
self.tmp = f'{self.pyserini_root}/integrations/tmp{randint(0, 10000)}'
# In the rare event there's a collision
if os.path.exists(self.tmp):
shutil.rmtree(self.tmp)
os.mkdir(self.tmp)
os.mkdir(f'{self.tmp}/runs')
self.round5_runs = {
'https://ir.nist.gov/covidSubmit/archive/round5/covidex.r5.d2q.1s.gz':
'2181ae5b7fe8bafbd3b41700f3ccde02',
'https://ir.nist.gov/covidSubmit/archive/round5/covidex.r5.d2q.2s.gz':
'e61f9b6de5ffbe1b5b82d35216968154',
'https://ir.nist.gov/covidSubmit/archive/round5/covidex.r5.2s.gz':
'6e517a5e044d8b7ce983f7e165cf4aeb',
'https://ir.nist.gov/covidSubmit/archive/round5/covidex.r5.1s.gz':
'dc9b4b45494294a8448cf0693f07f7fd'
}
for url in self.round5_runs:
print(f'Verifying stored run at {url}...')
filename = url.split('/')[-1]
filename = re.sub('\\?dl=1$', '', filename) # Remove the Dropbox 'force download' parameter
gzip_filename = '.'.join(filename.split('.')[:-1])
download_url(url, f'{self.tmp}/runs/', md5=self.round5_runs[url], force=True)
self.assertTrue(os.path.exists(os.path.join(f'{self.tmp}/runs/', filename)))
with gzip.open(f'{self.tmp}/runs/{filename}', 'rb') as f_in:
with open(f'{self.tmp}/runs/{gzip_filename}', 'wb') as f_out:
shutil.copyfileobj(f_in, f_out)
def test_round5(self):
tmp_folder_name = self.tmp.split('/')[-1]
prebuilt_index_path = download_prebuilt_index('trec-covid-r5-abstract')
os.system(f'python {self.pyserini_root}/scripts/classifier_prf/rank_trec_covid.py \
-alpha 0.6 \
-clf lr \
-vectorizer tfidf \
-new_qrels {self.pyserini_root}/tools/topics-and-qrels/qrels.covid-round5.txt \
-base {self.tmp}/runs/covidex.r5.d2q.1s \
-tmp_base {tmp_folder_name} \
-qrels {self.pyserini_root}/tools/topics-and-qrels/qrels.covid-round4-cumulative.txt \
-index {prebuilt_index_path} \
-tag covidex.r5.d2q.1s \
-output {self.tmp}/output.json')
with open(f'{self.tmp}/output.json') as json_file:
data = json.load(json_file)
self.assertEqual("0.3859", data['map'])
self.assertEqual("0.8221", data['ndcg'])
os.system(f'python {self.pyserini_root}/scripts/classifier_prf/rank_trec_covid.py \
-alpha 0.6 \
-clf lr \
-vectorizer tfidf \
-new_qrels {self.pyserini_root}/tools/topics-and-qrels/qrels.covid-round5.txt \
-base {self.tmp}/runs/covidex.r5.d2q.2s \
-tmp_base {tmp_folder_name} \
-qrels {self.pyserini_root}/tools/topics-and-qrels/qrels.covid-round4-cumulative.txt \
-index {prebuilt_index_path} \
-tag covidex.r5.d2q.2s \
-output {self.tmp}/output.json')
with open(f'{self.tmp}/output.json') as json_file:
data = json.load(json_file)
self.assertEqual("0.3875", data['map'])
self.assertEqual("0.8304", data['ndcg'])
os.system(f'python {self.pyserini_root}/scripts/classifier_prf/rank_trec_covid.py \
-alpha 0.6 \
-clf lr \
-vectorizer tfidf \
-new_qrels {self.pyserini_root}/tools/topics-and-qrels/qrels.covid-round5.txt \
-base {self.tmp}/runs/covidex.r5.1s \
-tmp_base {tmp_folder_name} \
-qrels {self.pyserini_root}/tools/topics-and-qrels/qrels.covid-round4-cumulative.txt \
-index {prebuilt_index_path} \
-tag covidex.r5.1s \
-output {self.tmp}/output.json')
with open(f'{self.tmp}/output.json') as json_file:
data = json.load(json_file)
self.assertEqual("0.3885", data['map'])
self.assertEqual("0.8135", data['ndcg'])
os.system(f'python {self.pyserini_root}/scripts/classifier_prf/rank_trec_covid.py \
-alpha 0.6 \
-clf lr \
-vectorizer tfidf \
-new_qrels {self.pyserini_root}/tools/topics-and-qrels/qrels.covid-round5.txt \
-base {self.tmp}/runs/covidex.r5.2s \
-tmp_base {tmp_folder_name} \
-qrels {self.pyserini_root}/tools/topics-and-qrels/qrels.covid-round4-cumulative.txt \
-index {prebuilt_index_path} \
-tag covidex.r5.2s \
-output {self.tmp}/output.json')
with open(f'{self.tmp}/output.json') as json_file:
data = json.load(json_file)
self.assertEqual("0.3922", data['map'])
self.assertEqual("0.8311", data['ndcg'])
def tearDown(self):
shutil.rmtree(self.tmp)
if __name__ == '__main__':
unittest.main()
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