def test_updates_optimization_tables(self, cursor):
self.override_recent_date()
# Call the command line script.
args = ['--log-format', 'plain', testing.config_uri(),
TEST_VARNISH_LOG]
from cnxarchive.scripts.hits_counter import main
main(args)
# Check the optimization tables for content.
cursor.execute("SELECT count(*) from recent_hit_ranks;")
recent_count = cursor.fetchone()[0]
cursor.execute("SELECT count(*) from overall_hit_ranks;")
overall_count = cursor.fetchone()[0]
self.assertTrue(recent_count > 0)
self.assertTrue(overall_count > 0)
def test_updates_optimization_tables(self, cursor):
self.override_recent_date()
# Call the command line script.
args = [
'--log-format', 'plain',
testing.config_uri(), TEST_VARNISH_LOG
]
from cnxarchive.scripts.hits_counter import main
main(args)
# Check the optimization tables for content.
cursor.execute("SELECT count(*) from recent_hit_ranks;")
recent_count = cursor.fetchone()[0]
cursor.execute("SELECT count(*) from overall_hit_ranks;")
overall_count = cursor.fetchone()[0]
self.assertTrue(recent_count > 0)
self.assertTrue(overall_count > 0)
def test_insertion(self, cursor):
# Call the command line script.
args = ['--log-format', 'plain', testing.config_uri(),
TEST_VARNISH_LOG]
from cnxarchive.scripts.hits_counter import main
return_code = main(args)
self.assertEqual(return_code, 0)
expectations = [[1, 3], [2, 1], [3, 4], [4, 1]]
# Check for the insertion of data.
cursor.execute("SELECT documentid, hits "
" FROM document_hits;")
hits = cursor.fetchall()
hits = sorted(hits)
self.assertEqual(hits, expectations)
def test_insertion(self, cursor):
# Call the command line script.
args = [
'--log-format', 'plain',
testing.config_uri(), TEST_VARNISH_LOG
]
from cnxarchive.scripts.hits_counter import main
return_code = main(args)
self.assertEqual(return_code, 0)
expectations = [(1, 3), (2, 1), (3, 4), (4, 1)]
# Check for the insertion of data.
cursor.execute("SELECT documentid, hits " " FROM document_hits;")
hits = cursor.fetchall()
hits = sorted(hits)
self.assertEqual(hits, expectations)