class AggregationTestCase(unittest.TestCase):
def setUp(self):
search_term = 'q'
parameters = {'h': 1000}
self.dblp = PublApi(top_k=1000,
delay=5,
search_term=search_term,
**parameters)
localdata_file = os.path.abspath(
os.path.dirname(__file__) + os.path.sep +
"../../") + '/csv_example/dblp_sample.csv'
localdata = LocalData(localdata_file, 'csv', "key", ["title"],
["title"])
localdata_ids, localdata_query, localdata_er = localdata.getlocalData()
initQueries = utils.queryGene(localdata_query, 2)
self.initQueries = initQueries
def test_stra_stratified_estimator(self):
aggregation.stratified_estimator(query_pool=self.initQueries,
api=self.dblp,
match_term=["info.title"],
candidate_rate=0.2,
query_num=100)
assert True
def test_sota_estimator(self):
aggregation.sota_estimator(query_pool=self.initQueries,
api=self.dblp,
match_term=["info.title"],
uniqueid="info.key",
query_num=1)
self.dblp.getSession().close()
assert True
class DblpPublapiTestCase(unittest.TestCase):
def setUp(self):
search_term = 'q'
parameters = {'h': 1000}
self.dblp = PublApi(top_k=1000, delay=5, search_term=search_term, **parameters)
def tearDown(self):
self.dblp = None
def test_callApi(self):
query = ['set', 'cover']
params = self.dblp.getKwargs()
params[self.dblp.getSearchTerm()] = '+'.join(query)
hitList = self.dblp.callAPI(params=params)
assert len(hitList) >= 900
def test_callMulApi(self):
queries = [['set', 'cover'], ['approximate', 'query']]
hitList = self.dblp.callMulAPI(queries)
self.dblp.getSession().close()
assert len(hitList) >= 1200
from deeperlib.api.dblp.publapi import PublApi
from deeperlib.core import utils
from deeperlib.data_processing.local_data import LocalData
from deeperlib.estimator import aggregation
# ==== Sota-Estimator Dblp ====
search_term = 'q'
parameters = {'h': 1000}
dblp = PublApi(delay=5, search_term=search_term, **parameters)
localdata_file = 'dblp_10000'
localdata = LocalData(localdata_file, 'pkl', "row['key']", ["row['title']"],
["row['title']"])
localdata_ids, localdata_query, localdata_er = localdata.getlocalData()
initQueries = utils.queryGene(localdata_query, 2)
aggregation.sota_estimator(query_pool=initQueries,
api=dblp,
match_term=["row['info']['title']"],
uniqueid="row['info']['key']",
query_num=1)
# ==== Stratified-Estimator Dblp ====
dblp = PublApi(delay=5, search_term=search_term, **parameters)
aggregation.stratified_estimator(query_pool=initQueries,
api=dblp,
match_term=["row['info']['title']"],
candidate_rate=0.2,
query_num=100)
dblp.getSession().close()